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“Giving something back”: A systematic review and ethical enquiry into public views on the use of patient data for research in the United Kingdom and the Republic of Ireland

“Giving something back”: A systematic review and ethical enquiry into public views on the use of...   Invited Referees Background: Use of patients’ medical data for secondary purposes such as 1 2 health research, audit, and service planning is well established in the UK. However, the governance environment, as well as public understanding about    this work, have lagged behind. We aimed to systematically review the literature report report version 2 on UK and Irish public views of patient data used in research, critically published analysing such views though an established biomedical ethics framework, to 17 Jan 2019 draw out potential strategies for future good practice guidance and inform ethical and privacy debates. version 1 Methods: We searched three databases using terms such as patient, public, published report report 16 Jan 2018 opinion, and electronic health records. Empirical studies were eligible for inclusion if they surveyed healthcare users, patients or the public in UK and Ireland and examined attitudes, opinions or beliefs about the use of patient data Sarah Cunningham-Burley , for medical research. Results were synthesised into broad themes using a University of Edinburgh, UK framework analysis. Results: Out of 13,492 papers and reports screened, 20 papers or reports Chrysanthi Papoutsi, University of were eligible. While there was a widespread willingness to share patient data Oxford, UK for research for the common good, this very rarely led to unqualified support. The public expressed two generalised concerns about the potential risks to Any reports and responses or comments on their privacy. The first of these concerns related to a party’s competence in the article can be found at the end of the keeping data secure, while the second was associated with the motivation a article. party might have to use the data. Conclusions: The public evaluates trustworthiness of research organisations by assessing their competence in data-handling and motivation for accessing the data. Public attitudes around data-sharing exemplified several principles which are also widely accepted in biomedical ethics. This provides a framework for understanding public attitudes, which should be considered in the development in any guidance for regulators and data custodians. We propose four salient questions which decision makers should address when evaluating proposals for the secondary use of data Page 1 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 Keywords Privacy, Patient Data, Electronic Health Records, Governance, Public, Engagement, Ethics Corresponding author: Elizabeth Ford (e.m.ford@bsms.ac.uk) Author roles: Stockdale J: Conceptualization, Data Curation, Formal Analysis, Writing – Original Draft Preparation, Writing – Review & Editing;  Cassell J: Conceptualization, Writing – Review & Editing; Ford E: Conceptualization, Formal Analysis, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing Competing interests: No competing interests were disclosed. Grant information: This work was supported by the Wellcome Trust [202133]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Copyright: © 2019 Stockdale J et al. This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. How to cite this article: Stockdale J, Cassell J and Ford E. “Giving something back”: A systematic review and ethical enquiry into public views on the use of patient data for research in the United Kingdom and the Republic of Ireland [version 2; referees: 2 approved] Wellcome Open Research 2019, 3:6 (https://doi.org/10.12688/wellcomeopenres.13531.2) First published: 16 Jan 2018, 3:6 (https://doi.org/10.12688/wellcomeopenres.13531.1)  Page 2 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 concern with the impact that its aim to collect and share data on   REVISED           Amendments from  Version 1 a large scale might have on patient privacy. The case of Care. data indicates a reluctance on behalf of the public to share their We would like to thank the reviewers and the editor for their very helpful comments, which have enabled us to substantially patient data, and it is still not wholly clear whether the public improve the paper. We spent a lot of time discussing the are willing to accept future attempts at extracting and linking reviewers’ insightful comments in order to best make large datasets of medical information. The picture of mixed improvements to the manuscript. Our key revisions include: opinion makes taking an evidence-based position, drawing on • Gr eater justification of the use of core ethics principles to social consensus, difficult for legislators, regulators, and data understand patient views, and the weaving of these long- custodians who may respond to personal or media generated standing principles together with the new theory of social perceptions of public views. However, despite differing results licence, within the domain of patient data research. This of studies canvassing public views, we hypothesise that there includes a full re-write of the future directions section of the discussion. may be underlying ethical principles that could be extracted from the literature on public views, which may provide guidance • Better explanation of our methods of paper selection, quality screening and results synthesis, including reference to to policy-makers for future data-sharing. established methodologies. • An up to date section on GDPR as it r elates to re-use of Governance and legal framework of data use patient data for research, and further exploration of the Since 2018, the General Data Protection Regulation (GDPR) has meaning of privacy in this context. governed the use of patients’ medical data in the EU and UK, • Better consistency in use of ter ms such as patient data and superseding the Data Protection Act in the UK (1998). GDPR public views. covers personal, or patient identifiable data in the UK, and • The title has been edited and Supplementary File 2 has been defines pseudonymised data, which can be traced back to the updated. individual using a study or database specific ID code, as personal data. Patient data can be used for direct care or audit and health- See referee reports care quality improvement projects without consent as these are seen as primary use of data. Research, however, is a secondary use of such data, as it is a use different from the originally Introduction declared purpose of data collection. Research organisations The use of patients’ medical data for secondary purposes such as thus need a “legal basis” for processing the data even when health research, audit, and service planning is well established identifiers are stripped, if individuals are still potentially re- in the UK, and technological innovation in analytical methods identifiable by a pseudonymisation code . One such legal basis is for new discoveries using these data resources is developing individual consent for use of the data in this way, and a second quickly. Data scientists have developed, and are improving, many is “a task in the public interest”. For research, such processing ways to extract and process information in medical records. may be justified in terms of research for the public good, as long This continues to lead to an exciting range of health related as appropriate safeguards are in place to reduce potential harms discoveries, improving population health and saving lives. to the data subject and ensure respect for the principle of data Nevertheless, as the development of analytic technologies minimisation. accelerates, the decision-making and governance environment as well as public views and understanding about this work, has Reducing potential harms to the data subject involves taking a been lagging behind . range of precautions to reduce the risk that an individual patient could be re-identified. Removing the pseudonymisation code Public opinion and data use and aggregating the data to a level at which re-identification is A range of small studies canvassing patient views, mainly in the not possible is the surest way of reducing such harm, but USA, have found an overall positive orientation to the use of often renders the data less usable for research purposes and 2–7 patient data for societal benefit . However, recent case studies, destroys the ability to link the data to other sources of health like NHS England’s ill-fated Care.data scheme, indicate that information. Research teams usually robustly protect patient certain schemes for secondary data use can prove unpopular in data with computing security systems, which do not allow the the UK. Launched in 2013, Care.data aimed to extract and upload data to be downloaded, or unapproved datasets to be uploaded and the whole population’s general practice patient records to a linked to the sensitive data. They also ensure only trusted and central database for prevalence studies and service planning . trained users are permitted access to the data. If data are to be Despite the stated intention of Care.data to “make major released to the public, this is usually done only after data have advances in quality and patient safety” , this programme was met been aggregated so that they have become truly anonymous. with a widely reported public outcry leading to its suspension and eventual closure in 2016. Several factors may have been involved Striking a balance in this failure, from the poor public communication about the While it is clearly important to make sure patient privacy is project, lack of social licence , or as pressure group Med- protected, it is also argued that the societal benefit of medical Confidential suggests, dislike of selling data to profit-making research using patient data, should be given ethical weight. This companies . However, beyond these specific explanations for is argued on the basis that harms to patients may occur where the project’s failure, what ignited public controversy was a these rich data sources are not used to improve our understanding Page 3 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 of health conditions and treatments . While individual privacy sharing”) AND (Research). We restricted our search to pub- and societal benefit are often portrayed as being in opposition, lications from 2006–2016 inclusive. We also searched the for the future of health data research, a way to achieve both to the grey literature using the search string: “public attitudes” AND satisfaction of patients, clinicians, legislators and researchers “sharing” AND “health data” on Google (in June 2017). The first must be found. Recent work has sought to identify the key issues 20 results were selected and screened. The following inclusion of patient views on data-sharing . However, few syntheses of criteria were then applied: patient views have additionally aimed to identify the implicit 1. Empirical studies using any methods reported as a full reasoning on which patients rely to justify the responses they length peer review manuscript or published report. give. Identifying a framework which describes the core moral or ethical values underlying public views may help us to predict 2. Healthcare users, patients or the wider public as the reaction of the public to new data sharing challenges in the participants future. Since the tension between data sharing and privacy is an ethical tension (to the extent that it involves what states of affairs 3. Examining views, attitudes, opinions, perspectives, ought to obtain, morally speaking), we are interested in the thoughts, awareness or acceptance about the topic of use ethical dimensions of such patient reasoning. To this end, we of patient data for medical research. propose to draw on core principles of biomedical ethics. First 3a. Patient data for medical research includes suggested in 1978 and 1979 in two forms, by Beauchamp and electronic hospital records, electronic general prac- Childress for ethical conduct within medicine , and in the tice records, and data extracted from these records, Belmont report for ethical conduct in healthcare research. for example cancer registries and national disease Core principles include the concepts of respect for autonomy, databases (summarised as patient data or EHRs). beneficence, non-maleficence, and justice. A similar set of principles were applied to information technology research in 4. Studies using a UK or Irish sample, written in English. science and technology by Menlo in a 2012 report . We aimed We chose to keep our review to these two countries to use these widely accepted principles as a tool to identify because of similarities in their socialised healthcare underlying themes expressed in patient views, and as a lens systems, and because of the well-established use of to discuss the findings. We also aimed to bring together these patient data within these jurisdictions. core principles with the newly adopted social licence theory for patient data research . This theory suggests that by volun- Studies were excluded if they were: tarily adhering to social codes of trustworthy and responsible 1. Focused more broadly on digital technologies in health behaviour that go beyond legal or regulatory frameworks, and care where the focus was on use of digital methods or by honouring additional safeguards, organisations can engender records rather than public attitudes trust from the public for schemes which may initially be controversial. 2. Focused on patient and practitioner attitudes to analogous areas such as biorepositories, genetic testing In this study, we therefore aimed to systematically review and and genomic research or personal data not exclusively thematically analyse UK and Irish studies exploring patient related to health. and public views on patients’ medical data being used for the secondary purpose of research, and aimed to understand and 3. Non-empirical reviews of legislation, policy, ethical map these views onto established biomedical ethical principles. challenges etc. We aimed to make suggestions for consideration by ethics committees and regulators to ensure that such research operates Using these criteria, the articles extracted from the literature in a transparent and trustworthy way, with the aim of maximis- search were screened based on their title, then abstract (by author ing the potential for the public to grant a social licence for such JS), then finally the choice of full text papers for the review was research to operate. undertaken by two authors (JS and EF). Methods Quality Assessment We followed the PRISMA guidelines for the conduct and report- Study quality was assessed using the Mixed Methods Appraisal ing of this review . Tool (MMAT) . This tool was designed for the appraisal of studies in mixed methods systematic reviews and attempts to Search strategy appraise the quality of methodology, rather than the quality of We searched PubMed, Web of Science, and Scopus between reporting. All studies meeting the inclusion criteria above were 03/10/16 and 11/10/16 using the following search string: assessed using six criteria. The first two criteria are the same for (Public OR Patient OR People) AND (Attitudes OR Knowledge all studies: is there a clear research question or objective, and OR Opinions OR Views OR Perceptions) AND (“Care.data” OR does the data collected address the research question or objective. “Electronic Health Record” OR “Electronic Health Data” OR A further four questions were specific to the study type. Studies “Electronic Medical Record” OR “Electronic Medical Data” OR were given a score out of six depending on how many of the six “Personal Health Information” OR “Personal Health Record” OR criteria they met, and were rejected if they did not meet at least “Electronic Patient Information” OR “Electronic Patient Data” the first two criteria. Two papers were excluded on the basis of OR “Electronic Patient Record” OR “Data linkage” OR “Data scoring zero on all criteria. Page 4 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 While quantitative papers are generally seen as of higher and Clarke’s guidance on qualitative thematic analysis , an quality, we believed that the in-depth exploration of human approach recommended for meta-synthesis by Dixon-Woods 21 22 reasoning for participant perspectives and decisions, illustrated et al. and Thomas and Harden . By taking an interpretive in the qualitative studies, could offer a greater understanding to approach to the synthesis of the data, we examined “the underpin our moral and ethical interpretation. Thus we treated underlying ideas, assumptions, and conceptualisation – and quantitative and qualitative studies as having equal value in the ideologies – that are theorized as shaping or informing the analysis if they met quality criteria. semantic content of the data” (p.84) . This was shaped and directed by Beauchamp and Childress’ four principles of bioethics , which enabled us to gain a better understanding of Data extraction the emerging moral meaning, and moral values conveyed by the We extracted author names, dates, location, type of study (quali- study participants in these themes. As far as the authors are tative or quantitative), methods used, number of participants, aware, there are no pre-existing applications of this framework their backgrounds or roles, ages, genders, and the study findings to study patient attitudes. However, this general approach which fitted into the themes relating to research questions has been taken before using The Belmont Report to identify reported below. stakeholder views on technology-enabled research . While the 25,26 four principles have drawn criticism elsewhere they continue Synthesis of results to be extremely influential in evaluations of ethical dilemmas The full text of eligible articles was read iteratively by two in health care, and a useful framework with which to identify authors (JS and EF) with the aim of extracting coherent themes. In moral values in participant decision-making. the first iteration of reading and coding the results of the papers, nine questions arose, which formed the basic direction of the Results inquiry. A total of 13,472 peer-reviewed papers were found through 1. Are patients/public aware of electronic health records the systematic search, as well as 20 reports found through the (EHRs) and their secondary uses? grey literature search. Of these, 20 UK and Ireland based papers 4,27–45 met the inclusion criteria and were included in the review 2. Are patients/public concerned about the privacy and (Supplementary File 2). Studies which reported time periods security of their medical data? indicated that data was collected from 2004 to 2016, although 3. Are patients/public willing to share their medical data for seven studies published between 2011 and 2016 did not report research, policy and planning? the data collection period. Research participants included patients, service-users, lay persons, those living with chronic 4. What consent model do patients/public prefer? conditions, and the general public ranging from 16 years of 5. How does data being identifiable or anonymised affect age to over 75. Five of the studies included the views of health patient/public preferences? researchers, health professionals, industry experts, NHS managers and other key stakeholders. Seven of the papers were quanti- 6. Which organisations are most and least trusted with tative, using surveys or structured questionnaires. Ten of the patients’/public data? studies were qualitative, using focus groups and one-to-one 7. What are the reported perceptions of risks and benefits of interviews, and there were three mixed methods studies. Details of sharing medical data for research? studies are reported in Table 1. 8. Are there any other ways in which willingness to share Quality assessment could be increased? Studies’ quality scores ranged from 3 to 6 out of a possible 6, 9. Is there any differences between demographic groups scores of individual studies are shown in Table 1. Two studies concerned with the sharing of EHRs? which otherwise met inclusion criteria were rejected on the basis 46,47 of quality and do not appear further in the results . A framework was created with a column for each of the nine questions and data was extracted from each study where it fitted Themes elicited from the studies into these categories. Following this data extraction, the two The seven themes identified in and elicited from the studies were: authors (EF and JS) discussed refining and combining extracted Knowledge and Awareness of Electronic Records; Willingness to data into as smaller number of themes. In a second iteration of Share; Privacy; Trust; De-identification and Consent Preferences; data extraction, authors re-read articles and extracted data into Routes to Securing Trust; and Demographic Differences. The seven themes. For interpretation and synthesis, a data driven contribution of each study to each theme is shown in Table 2. approach was taken, trying to make meaning from first order data reported in the papers (i.e. statistics or participant quotes). Knowledge and awareness of electronic records Where themes were populated mainly by summary of quantitative Generally, knowledge of the content and electronic collection data, a straightforward report of papers’ findings is given. of GP records among respondents was high. One quantitative study reported that a moderately high proportion of respondents Where contributing papers were mainly qualitative e.g. in the at 59% had prior awareness of EHRs . Another quantitative study Trust theme, we undertook a deeper analysis directed by Braun reported that levels of understanding of the information recorded Page 5 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 Page 6 of 25 Table1. Includedstudycharacteristics. Study Reference Method Setting DataCollection Sample Quality no. Period Score 27 Audrey, S., et al., BMC Medical Qualitative: focus groups Bristol, England Not stated Total n=55, 56.4% female 43.6% male Ages: 17–19. 5 Research Methodology, 2016. 16: with participants from p. 34 ALSPAC. 28 Baird, W., et al., Journal of Medical Qualitative: focus groups England and February and July Total n=68 Focus groups: Patients with MS and 5 Ethics, 2009. 35(2): p. 92–96. and interviews. Northern Ireland 2006 stakeholders (n=55) Interviews: Health and social care professionals an academics (n=13) 29 Barrett, G., et al., British Medical Quantitative: survey run England, Wales March and April Total n=2872 46% male 54% female Ages: 16–44 6 Journal, 2006. 332(7549): p. 1068–1070. by the Office of national and Scotland 2005 46%; 45–64 35%; 65+ 20% statistics 30 Buckley, B.S., A.W. Murphy, and A.E. Quantitative: postal Republic of Not stated Total n=1575 27.6% male 71.6% female Ages: 4 MacFarlane, Journal of Medical Ethics, electoral roll-based Ireland 18–75+ 2011. 37(1): p. 50–55. questionnaire survey. 31 Campbell, B., et al., Quality and Safety Quantitative: postal South-West October to Total n=166 patients recently discharged from 5 in Health Care, 2007. 16(6): p. 404–408. questionnaire England December 2004 the care of 78 bed-holding consultants across all specialties at the Royal Devon and Exeter Hospital. 32 CM Insight and Wellcome Trust, Qualitative: focus groups London, 29 April to 12 May Total n=50, Ages: 18–70 Focus group 3 Summary report of qualitative research and one-to-one telephone Midlands and 2013 respondents were recruited as owners of store into public attitudes to personal data interviews. Norfolk, England loyalty cards, smart phones and social media and linking personal data. 2013. users. Telephone interviewees were recruited as especially pro-privacy or cautious about sharing personal data. 4 Clerkin, P., et al., Family Practice, 2013. Qualitative: focus groups. West Republic of Not stated Total n=35, female (n=18) male (n=17) Ages: 6 30(1): p. 105–112. Ireland 18–35(n=2); 36–55(n=14); 56–70 (n=19). 33 Grant, A., et al., BMC Health Services Qualitative: focus groups Tayside and Between February Total n=64, Focus Groups: Patients (n=37), Health 5 Research, 2013. 13: p. 422. and semi-structured Lothian, Scotland and June 2011 services researchers (n=10) Interviews: GPs and interviews. Practice managers (n=17) 34 Haddow, G., et al., Journal of Qualitative: focus groups. North East May and June 2009 Total n=19, female (n=12), male (n=6), Unstated 5 Evaluation in Clinical Practice, 2011. Scotland (n=1) Ages: <60 (n=1); 60–74 (n=15); +75 (n=3). 17(6): p. 1140–1146. 35 Hays, R. and G. Daker-White, BMC Qualitative: using tweets. Twitter Over 18 days 3537 tweets containing the hashtag #caredata; 6 Public Health, 2015. 15: p. 838. during February 904 contributors and March 2014 36 Hill, E.M., et al., BMC Medical Research Qualitative: focus groups. England, Wales, Not stated Total n=19, 100% male Ages: 54–69; mean age 61. 4 Methodology, 2013. 13: p. 72. Scotland and Northern Ireland 37 Ipsos Mori, Medical Research Council, Mixed methods study. England, Wales, Quant: 14–18 Sept Quant: 2106 people aged 15+; Qual: Total n=69 3 The use of personal health information Qualitative: workshops Scotland and 2006; Qual 29/7- Workshops: General public (n=63) Interviews: in medical research general public and interviews Northern Ireland 5/8 2006 disabled people, and people with chronic consultation. 2007. Quantitative: face-to-face illnesses/or their carers (n=6) survey Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 Page 7 of 25 Study Reference Method Setting DataCollection Sample Quality no. Period Score 38 Ipsos Mori, Macmillan Cancer Support, Quantitative: online England 13 June to 4 July Total n=2,033 Adults who have, or have had 5 Cancer Research UK, Perceptions survey. 2016 cancer (PLWC) (n=1,033) Adults from the general of the Cancer Registry: Attitudes public (n=1,000). All 18+ towards and awareness of cancer data collection. 2016. 39 Ipsos Mori, Wellcome Trust, The Mixed methods study. England, Wales, September to Quant: n = 2017, age 16+; Qual n= 247; 3 one-way mirror: Public attitudes to Quantitative: Scotland and December 2015 Members of the general public, patients, and commercial access to health data. face-to-face survey Northern Ireland ALSPAC cohort members (n=212) GPs and 2016. Qualitative workshops hospital doctors (n=35) 40 Ipsos Mori, Wellcome Trust, Wellcome Quantitative: England, Wales, 2 June to 1 Total n=1,524 Ages: 18+ 5 Trust monitor report wave 3: Tracking questionnaire Scotland and November 2015 public views on science and using face-to-face Northern Ireland biomedical research. 2016. Computer-Assisted Personal Interviewing (CAPI). 41 Luchenski, S.A., et al., Journal of Quantitative: cross West London, Six weeks from 1 Total n=2857, 59.5% female, 40.5% male Ages: 5 Medical Internet Research, 2013. 15(8). sectional, self-completed England August 2011 18–75+ questionnaire survey. 42 Papoutsi, C., et al. BMC Medical Mixed methods study. West London, Between August Quant: n=2761, 59.1% female; Qual: n=160, 4 Informatics and Decision Making, 2015. Quantitative: England 2011 and April Patients (n=114). Health professionals and 15(1): p. 124. questionnaire 2013 researcher total not stated Interviews: Patients survey Qualitative: focus who did not wish to join group discussions (n=6). groups and interviews. 43 Riordan, F., et al., International Journal Quantitative: West London, Six weeks from 1 Total n=3157, 60.4% female, 39.6% male 5 of Medical Informatics, 2015. 84(4): Crosssectional, England August 2011 p. 237–247. self-completed questionnaire survey. 44 Spencer, K., et al., Journal of Medical Qualitative: focus groups Salford, England Not stated Total n=40, 58% female, 43% male, Ages: 23–88 4 Internet Research, 2016. 18(4): p. e66. and interviews. 45 Stevenson, F., et al., Family Practice, Qualitative: focus groups Not stated Not stated Total n=57, Patients (n=50), Staff members (n=7). 4 2013. 30(2): p. 227–232. and interviews Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 Table 2.   Contribution of Studies to  Themes. Study Knowledge and  Willingness to  Privacy Trust De-identification  Routes to  Demographic  Awareness of  Share Data and Consent Securing  Differences Electronic  Trust Records Audrey et al. 2016 X X X Baird et al. 2009 X X X X Barrett et al. 2006 X X X X Buckley et al. 2011 X X X X Campbell et al. 2007 X CM Insight and X X X X X Wellcome Trust 2013 Clerkin et al. 2013 X X X Grant et al. 2013 X X X X Haddow et al. 2011 X X X X Hays & Daker-White X X X X X X Hill et al. 2013 X X X X X X Ipsos Mori, MRC 2007 X X X X X X X Ipsos Mori, MacMillan, X X X X CRUK 2016 Ipsos Mori, Wellcome X X X X X Trust 2016 One Way Mirror Ipsos Mori, Wellcome X Trust 2016 Monitor Report 3 Luchenski et al. 2013 X X Papoutsi et al. 2015 X X X X X Riordan et al. 2015 X X X Spencer et al. 2016 X X X Stevenson et al. 2013 X X X X by GPs were high without giving exact numbers . One quali- Willingness to share tative study reported that across groups, participants had a good In many of the studies, participants expressed willingness to awareness of the kind of information that usually held in general share their EHRs for secondary purposes like research, policy practice records . Nevertheless, participant awareness of specific and planning, despite the range of concerns discussed below. uses of routinely collected patient data was low. For instance, Among the quantitative studies, support for sharing patient data 29 39 30 40 42 two quantitative studies reported that 82% and 80% of the with researchers was reported at 68.7% , 77% , 81.4% , and general public had not heard of the National Cancer Registry, while 83% . In the qualitative studies, participants identified will - another study reported that patients were not only inadequately ingness to share their EHRs for secondary purposes with the 4,27,28,32,37 informed about their right to opt-out of Care.data, but were also “common”, “greater” or “public good” ; “social 44,45 28 unaware of the project . Two studies indicated that understand- responsibility” ; “altruistic attitudes” ; and “giving some- 32,37 33 4,28,34–36,44 ing of medical research using patient data was low , while thing back” to “other people” or “future generations” . another suggested that participants were unaware of how their For example, in one study it was stated: data was currently used . Another demonstrated limited public I’m saying yes because I think there is a greater good. grasp of a range of concepts related to patient information use, (Participant 1, Group 2, ) such as de-identification, data science, the benefits of aggregate data, and the role of private companies in the healthcare system. People with lower understanding of these issues were more likely Such reasoning was largely predicated on the understanding that to have concerns about commercial access to health data . medical research using EHRs could lead to benefits such as the Page 8 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 4,27,28,32,39,42,44 improvement of healthcare services, or innovations in the diagnosis privacy . Privacy was generally conceptualised and treatment of disease. For example: by participants as a process of control: Seemingly radical idea: let PATIENTS control who can access I think if you are going to do something, eczema, allergies, their personal medical data! #caredata. (Twitter user, ) something that affects one in five people you need the huge samples in order to do it. (Patient Interview L2, ) Participants frequently identified two key elements that could be determined in relation to their information. The first was And: whether information is revealed to, or accessed by another party: . . . because you never know where research is going to go. My concern is exactly that: who has access to my files and You don’t know where some brilliant young scientist’s mind how can we make sure that only those I want to have access linking up different things, you know. And you cannot put a would have access? (Focus Group 12, ) halt on that, a break on that. (Di, Focus Group 1, ) A second element concerned how this information should be Moreover, it was also understood that using EHRs might be a used, or analysed after it being revealed to another party: better way of doing and facilitating research: At the end of the day, it’s not who has access to it all, it’s . . . I mean it’s a better system than it is at present, because how they use it, I think is the main concern for us, for you are going to get 100% response that way or near everybody. . . how they use it. (Person with MS, Focus enough and the present system is that the GPs put out things Group 7, ) on spec to people that may want to join this thing and they may get a very low return. (Male, Patient Focus Group 3, ) These two factors were necessary components in identifying what was and was not acceptable when it came to unlocking the From these studies, the “common good” appeared to consist potential of patient data. of the collective public health benefits brought about by the improvement of the services, practices and methods of healthcare Trust through secondary uses of data. Willingness to share appears Views on storing and using patient data were linked to the kind connected to idea of an individual having a personal respon- of trust or distrust the public had in an organisation or individual sibility, obligation or duty to help bring about this common using or accessing the data. good: You have to trust people. (Fiona, Focus Group 2, ) Once you have been in receipt of the excellent kind of care and treatment that I’ve had, I think you have a social Where participants distrusted organisations who would handle responsibility that if you can help the next generation by their data, this generally occurred along two lines: having your information provided to the researchers to [do] 1. Distrust of a party’s ability, or competence, to ensure some good. (Focus Group 3, ) data security. Privacy 2. Distrust of a party’s motivations. Despite the general willingness to share EHRs for second- ary purposes, many qualifying concerns were raised by In terms of a party’s competence, participants were likely to 27,28,32–39,42,44,45 participants . This suggests that although the shar- agree that a particular party could store and use their data in ing of EHRs is largely seen as being for the overall common principle, but were concerned that they are not able to guaran- good, participants believe that it also has the potential to create tee the level of security required by such personal data due to new risks, and increase existing ones. The various perceived risks 36,42 institutional incompetence. One such party was “the NHS” . involved in sharing EHRs were well described by participants. For example, in one study a majority of respondents (71.3%) 35,42 These included routes to harm like hacking , unintentional data voiced doubts about the ability of the NHS to guarantee the 35 42 leakage or loss , unauthorised access , access without explicit security of EHRs, yet 53.5% of those respondents would 27 42 34 consent , errors in medical records , re-identification , 42 nevertheless support the development of a national EHR . On aggregating data to a group’s disadvantage , and access, use the incompetence and inefficiency of the NHS, participants and governance of data by the government . Participants also stated the following things: listed perceived harms as a result of adversaries gaining access I just have very little faith in the way that the NHS handles to data, these included: identity theft , unnecessary stigmatis- databases. I don’t think it’s got a very good record. . . (Focus ing judgements in clinical settings , consequences for employ- Group 3, ) ment, pension eligibility, or insurance costs , social discomfort and community embarrassment , and the use of EHRs for Always thought that [the NHS] would mess it up (Focus financial gain . The breadth of this list demonstrates the structural Group 11, ) complexities of the particular, concrete situations which study #NHSPatientdata scheme handling a ‘masterclass in incompe- participants imagine may arise from the misuse of their data. tence’ #CareData #NHS [link] [link]. (Twitter user, ) Several studies connected these risks and the concept of Page 9 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 However, in some qualitative studies, participants expressed a This dimension was further discussed in the grey literature generalised trust towards the NHS, especially when concerning which revealed a more nuanced picture regarding public opinion GPs: towards the commercial uses of data. Support for commercial access to patient data raised from 54% to 61% when taking I mean I can trust the doctors and all . . . but other people, into account the possibility of new treatments being discovered , no. Once it leaves the NHS, I’d be wondering where it’s and participants were indifferent to who conducts research so going and who’s looking at it. (Participant 19, ) long as the objective is to increase knowledge around the causes and cures of ill health . This suggests that participants recog- . . . once it goes out of the NHS, the NHS have no control nise that not all commercial uses of data are done from purely over it whatsoever. (Di, Focus Group 1, ) privately interested motivations, but that at least in part can involve public motivations too. In explaining the apparent reluctance Nevertheless, and perhaps surprisingly, participants tended to of the public to accept certain private interests so as to ensure say that the data would be safer in the hands of the NHS or a public benefits, one study identified that participants did not public sector organisation, and that private companies were less currently feel that they could evaluate the motivations of com- likely to be as diligent in their handling of it . mercial organisations who would use the data, which created an unclear conception of what the public could stand to gain When it came to an organisation’s motivation, there was a strong through these uses of data. As a result, participants tended to sense that any access and use of the data must be for the good of fall back into wider assumptions, personal beliefs and prejudices the individual patient or the common good of the public. Many regarding private companies . studies indicated that any kind of data handing for private 32–36,42,45 interests would be unacceptable . In terms of the possi- ble consequences, a recurring theme was that if a party had the De-identification and consent preferences wrong competences or motivations, this could lead to substan- In the quantitative studies, 67.5% of respondents in 2011 and tial harm on both an individual or collective societal level. For 91% of respondents in 2015 were clear that although it was instance, as the following quote illustrates, it was identified fine for researchers to access their EHRs, they still expected to that the private profit motivations of insurance and marketing be asked for consent when their identifiable data was accessed companies could lead to harms on an individual level: for secondary purposes. However, there was less consensus 30 31 43 over de-identified data, with 83.7% , 51% , and 49.3% of One of my fears was if it somehow goes astray from there respondents reporting willingness to share or agreement that and somebody, for instance, like insurance companies, get a de-identified patient data could be extracted without consent. hold of it they could use it to their advantage and the patient’s Reasons for concern around de-identification also emerged in disadvantage. (P2, Focus Group, ) the qualitative studies where participants questioned what would qualify as identifying information , whether de-identification However, direct harm to individuals is not a necessary factor in 37,42 could be achieved effectively , whether it was sufficient determining the wrongness of certain motivations. It was also 27,36 for the elimination of consent and highlighted the risks of indicated that even if no particular individual is disadvantaged, 32,35 re-identifying individuals . allowing those with private interests to access public data can constitute a collective harm. This is because there is a strong Several studies also indicated substantial concerns about the sense that data should only be used to benefit either individuals: opt-out rather than opt-in model of consent which was pro- 35,45 posed in schemes such as Care.data , while others noted that Financial gain comes into it then so why should you then let participants generally thought about consent along opt-in lines them look at your records? They are going to gain out of it when asked for their opinions . Participants expressed worries and you’re not. . . (Participant 2, Group 2, ) about whether people would really understand the concept of opting-out . They also criticised opt-out on the basis that it Or, the public at large: was unethical and illegal . However, in one quantitative study If there was a large commercial company. . . [that] had free 52% of the general public supported the opt-out method of and easy access to people’s medical records I don’t think collection for the National Cancer Registry , while a minority of that would be right. It would further their research into the participants in another study acknowledged that opt-out might be particular drug or treatment, but it’d also further their prof- a better option given the impracticalities of opting-in . its that would be wrong. But if it was for medical research for everybody then that would be different. (Participant 6, The problem of selection bias and its connection with Group 3, ) 27,36,42 consent arrangements was explored in three studies . In two studies, some participants identified the potential for bias Despite this firm belief, several of the studies indicated a tension if the information which was gained was neither accurate nor in the status of pharmaceutical companies whose products are 27,42 balanced : indispensable to medicine and the health of populations, but 28,33,36,37,42 which ultimately operate in a profit driven capacity . As  If they’ve got mental health illness then. . . that might affect Grant et al. write, this leads some participants to see the involve- their willingness, so it might be hard to. . . gather enough ment of pharmaceutical companies as a “necessary evil”. information. I think that might be biased. . . (Male ID47, ) Page 10 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 Participants also recognised that larger, more representative more acceptable than any other . However, in the same study, samples could be gained by an opt-out process: participants were significantly less likely to endorse sharing data without any safeguards (49% agreed) compared to with You are going to get 100% response that way, or near enough safeguards (56–64% agreed, depending on the safeguard). This and the present system is that the GPs put out things on suggests that the precise nature of the safeguard may be less spec to people that may want to join this thing and they important to improving willingness to share than knowing that may get a very low return. (Male, Patient focus group 3, ) there are safeguards in place. This prompted discussion in one study about the importance Demographic differences of mitigating the requirement of consent by de-identifying We aimed to ascertain whether the included studies indicated information: a level of heightened concern, worry or fear among one or more specific social groups and we restricted this analysis to quan - There is certain situations where you might be able to, it titative studies which could enable such contrasts. Although might be acceptable to ask or it might be acceptable just to go participants were asked a variety of different questions across ahead and get it—as long as it wasn’t directly linked back to each survey, we evaluated responses on the basis of whether you as a person, it would be alright. . . (Female, ID6, ) they indicated an overall negative or positive attitude towards the In another study , after receiving presentation about selection sharing of EHRs for secondary purposes such as research. For bias, participants recognised the difficulties faced by researchers. example, in Papoutsi et al. , participants were asked if they Interestingly, when asked if this information had changed their would be more worried about the security of their informa- opinion about using health data without consent, several partici- tion if it were part of a national EHR register, while Buckley pants out of the group who at first indicated reluctance, reported et al. asked if they would allow their EHRs to be provided to that they had indeed changed their minds. A quantitative study researchers without their explicit consent. Despite the differ- showed that a substantial minority of respondents (20%) ing approaches of these questions, we concluded that a response believe that consent may not be needed if it is not practical to indicating more worry about security, and one indicating less obtain. likelihood of granting researchers access without explicit consent, were comparative insofar as they represented a negative attitude towards sharing of EHRs. Routes to Securing Trust Across studies, participants identified several different infra - structure arrangements which could increase willingness to share Within quantitative studies, findings were reported across a whole patient data for secondary purposes and trust in their use for range of demographic differences. Between studies, compari- public benefit. Participants indicated that no single organisation son could only be made between age range, levels of education, should be responsible for deciding who could access and use and ethnicity. We found conflicting findings in all three of these their EHRs, rather a committee of stakeholders was called for, categories. We found evidence that both younger people and older including Caldicott Guardians, research consultants, members people would favour sharing their data, that people with lower of the public, GPs, social services staff, charities, funders, levels of education were both more and less likely to agree to 28,34 and patients. . It was also felt that greater transparency was sharing without consent, and that people of non-white ethnicity needed in regards to safeguarding processes and data sharing were both more and less likely to support EHRs and think of 35,44 arrangements , including stiff penalties or fines for misuses them as secure. For a full break down of the demographic results, 35,39 39 of data ; the publication of results ; clear guidelines and laws see Table 3. to regulate access and use of data ; and, regulators and parties accessing data to be held to high standards . Several studies Discussion also indicated that participants wanted a better understanding We found that knowledge of the content and collection of patient about the nature of EHR initiatives, medical research , the data in EHRs was reasonably high, but knowledge about the 33,37 purposes and benefits of using data , de-identification and secondary uses, such as data sharing for research, was low. aggregation , and also why in some situations consent might not Nevertheless, when asked, participants were generally willing to be practical . More generally, participants wanted the security share their data for the “common good”, subject to safeguards. 33,39 39 of records to be ensured ; for private profit to be capped ; and Willingness was qualified with concerns about privacy which denial of third party access . In several studies, participants participants generally equated with the idea of control. This also indicated their preference to retain granular control over conceptualisation of privacy as control closely corresponds the data in their EHR using an explicit opt-in consent scheme, to the idea that informational privacy is the ability of an the right to withdraw at any time and ability to tailor sharing individual to determine for themselves what happens with certain 28,33,35,44 48,49 preferences . information relating to them . This particular definition has attracted criticism insofar as it difficult to capture what Despite the breadth and diversity of participant suggestions constitutes “certain” information . Within the legal and philo- to increase trust, it might be that no single, or any specific sophical literature it is generally accepted that what constitutes combination of strategies will amount to a gold standard of an individual’s determination is whether or not information is acceptability or social licence. One study found that no particu- communicated to other parties, however, our analysis suggests lar safeguard made sharing data with commercial companies any that the public also believes that their privacy can be violated not Page 11 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 Table 3.   Study findings on Demographic Differences. Group Indicative of Negative Attitude Indicative of Positive Attitude Age Compared to those aged 25–34, respondents between Increase in age by each 10 year increment was the ages of 35–64 were more likely to report they would be significantly associated with an increased likelihood of worried about the security of their records as part of a national reporting that any info can be provided to researchers 42 30 EHR . without asking for consent . Compared to those aged 25–34, respondents over 35 years Older people (55–64, 65+) were more likely to find old were more likely to report less confidence in the ability of a drug company conducting research into the NHS security and were less likely to report that EHRs were unwanted side effects of a drug using deidentified equally or more secure than paper records . data to be more acceptable than younger people (16–24, 25–34, 35–44, 45–54) . Older people were increasingly more likely to report that they Those aged 55–64 tended to agree that research would not be in favour of a national EHR compared with should be conducted by commercial organisations 25–34 year olds . if there is a possibility of new treatments being discovered in comparison to 16–24s and 35–44s . In the general public, support for the opt-out collection method was higher in over 55s (58%) than 18–34 (49%) and 35–54s (49%) . Those over 55 were more likely to say to say that they would allow their data to be used for medical research compared to those aged 16–24 . Education Respondents with lower educational qualifications were more Compared with participants with higher degrees, likely to expect to be asked for explicit consent before their individuals with no academic qualifications were less deidentified records were accessed . likely to say that they would worry about security if their record was part of a national EHR . Compared with completion of third level education, completion of only primary level education was associated with increased likelihood of reporting that any info can be provided to researchers without asking for consent . Socioeconomic Those of a lower socioeconomic status were more likely to be Those in the lower socioeconomic group DE (43%) Status concerned about privacy . were more likely to support companies using health data collected in the NHS to help target health products at different groups of people . Those in socioeconomic groups C2 and DE were less likely than those in AB and C1 to view the use of health data as having a potential benefit to society . Those in the lower socioeconomic group DE were less likely to say they trusted a variety of people with their health data; say that the advantages outweigh the disadvantages of using health data in research; and say that researcher can use data without prior consent than Abs . Those in socioeconomic groups C1 and C2 were less likely than ABs to allow their health data to be used . Those in socioeconomic groups DE (46%) were less likely Those in socioeconomic groups DE (26%) were to support commercial organisations to undertaking health less likely to support commercial organisations to research with health data than AB (62%) . undertaking health research with health data than AB (30%) . Ethnicity Black British respondents were more likely to say they would Compared with White British groups White non-British, not support the development of a national EHR system Asian, British Asian, Black-African, Caribbean, and compared with White British respondents . British Black groups were more likely to say that EHRs are as secure, or more secure that paper records . Respondents identifying as belonging to an ethnic group other than White British were more likely to expect to be asked for explicit consent before their deidentified records were accessed . Those whose ethnicity was not White British were more likely to be concerned about the invasion of privacy . Page 12 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 just in the sharing of their information, but in the subsequent use of data usage, and for expressing the concept of public opinion and that information too (e.g. using personal information for profit). attitudes. We cast a wide net and spent time excluding papers, and believe this review encompasses all available research meeting our criteria up until the search was conducted. Our Participants feared adverse outcomes less when they trusted both findings were deliberately limited to UK and the Republic of the motivation of research organisations to conduct research Ireland to create a manageable, relevant and comparable body of for the common good, and the competence of organisations to literature. This enabled us to look for underlying principles for handle the data safely and without compromise. When evaluat- publics exposed to a particular type of healthcare system, but ing opinions on consent mechanisms, findings suggested that findings are obviously only applicable within these contexts. educational and deliberative research into public opinion may There may also have been differences between UK and Irish provide different answers from snapshot surveys. This is because respondents due to differences in these healthcare systems. Both after weighing up a range of issues involved, participants could systems have a general practice plus hospital system. However, often see the benefit to research quality of opt-out schemes. Results in the UK, all GP and hospital visits are free at the point of use, suggested a range of mechanisms to increase public trust, and whereas in Ireland, around two thirds of the population must the overarching theme here was transparency of motivation, data pay a fee for GP or hospital care. This financial transaction may handling and data flow. influence how patients perceive ownership and use of their medical data, although we found no literature on this. Core Ethical Principles The foundational moral principles which Beauchamp and Synthesis of results was also challenging as there was a wide Childress identify as paramount to governing biomedical range of study types, using different methods. The small, practice, and which Belmont identified as important for medical convenience samples and low response rates in the majority of research can be used as a lens for understanding and interpret- studies is also likely to have introduced bias into the findings, ing these findings. Where we find that public reasoning maps to as it is probable that only members of the public most interested these basic principles, it can be inferred that these core ethical in the issues consented to take part in the research. This means principles are a constituent part of non-specialist thinking that each study likely represents a narrow range of views, and about the ethical practicalities of healthcare and medicine. This views expressed may have been influenced by the means of data in turn identifies these ethical principles as a suitable structure for collection. It is not clear how this might have affected results guiding reasoning on future data sharing challenges. across the whole range of studies, but it is likely that the themes and views represented here are not a complete picture of the For instance, the included studies indicate that there is a wide- public’s opinions. This may have contributed to the inability spread willingness to share EHRs for secondary purposes, in to find systematic differences in views between demographic principle. This willingness was held on the basis that, using and groups. Additionally, certain research questions of particular accessing data in such a way can bring about benefits which interest were not asked of participants and therefore our under- are in the interests of all individuals, or in other words, the standing of public opinion is still limited. One example of this is “common good”. The basis of this belief may be the general whether the use of medical text (in contrast to structured data expectation that if members of the public can contribute to the in medical records) elicits specific privacy concerns for the welfare of each other by sharing data, then they feel a moral public. obligation to do so. We could reinterpret this as the principle of beneficence, which urges us to act, where we can, to promote Our analysis was informed and influenced by our respective good. backgrounds in philosophy, psychology and epidemiology. While attempting to be data-led, we must acknowledge that we Willingness to share data rarely led to unqualified support of may not have been wholly neutral in approach. However, our the schemes designed to enable secondary use. Support was review highlights similar themes to Aitken et al. , suggesting a withheld because, in practice, it was felt that key values would consistency with other syntheses in this area. not, or could not, be ensured, thus bringing with it the risk of individual and collective harm. The public might feel justified Future directions in objecting to irresponsible, or insecure use of data because This review demonstrates and makes explicit the extent to which it is likely to cause individual harm; a direct violation of the public attitudes to sharing health data are based on reasoning principle of non-maleficence. Similarly, the use of data for in line with established bioethics principles. Decision makers, private gain may be said to be in violation of the principle of who evaluate data-sharing proposals can therefore draw on an justice because it is generally unfair to exploit something for explicit framework of ethical principles to address challenges reasons other than what it was intended for. Finally, the use of around the sharing of patient data. It is becoming increasingly patient data without transparency or consent may be seen to accepted that the use of patient data for research or for the violate the principle of respect for autonomy. development of novel healthcare technologies should be sup- ported by a social licence to operate . According to social licence Strengths and limitations theory, the public expect that organisations who are institut- We conducted a wide search and sifted a huge number of papers, ing potentially controversial schemes (such as patient data shar- including grey literature reports. The search was challenging due ing) will go beyond the requirements of formal regulation and to wide range of terms used within the literature for secondary Page 13 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 adhere to voluntary codes of trustworthy behaviour . Where the that the public and patients benefit from the data usage as well public are satisfied that the motivations of the organisation are as the company. Benefits which come from patient data research trustworthy, they confer a “social licence” to operate. It has been should additionally be publicised and communicated, so that hypothesised that previous patient data-sharing initiatives, such these common gains become part of the public consciousness. as Care.data, have failed to secure public support because they Examples of good practice in this sphere can be seen in the UK 9 56 lacked a social licence for their operation . Farr Institute and the Wellcome Trust Initiative “Understanding Patient Data” . Public views are complex, and interpreting them to guide policy 4. Could granting access to the data, or granting a can be difficult. A simple and explicit framework may act as a particular use of the data, lead to individual or collective focussing lens, reducing complexity by pulling out underpinning harm? (Non-maleficence) moral principles in participants’ views. Establishing core values held by the public may facilitate identification of the types of Participants in the studies we reviewed articulated a range of safeguards which could help to secure a social licence for harms that they fear could arise from re-use of patient data. sharing patient data. We make recommendations about how pub- Possible risks may include individual harms, such as re-iden- lic views could fit into the four tenets of the Beauchamp and tification and discrimination from insurance companies or Childress framework, and could be used to guide decision mak- government agencies. However, ethical bodies and regulators ers or regulators. We phrase these suggestions as guiding should also consider the risk of collective harms from pursuing questions, which could be asked of research proposals by ethics certain research agendas. For example, failure to achieve fair- committees and regulators. ness or transparency in data-sharing agreements may result in 1. Do the methods of data collection and usage in the a loss of public trust in the endeavours of research, or in public proposal respect individual patient autonomy? (Respect institutions’ policies on keeping data safe. Such a loss of pub- for Autonomy) lic trust would put at risk any gains made in securing a social licence for sharing patient data. In addition, infrastructure put in place to safeguard patient privacy must be made transparent to Patient autonomy can only be achieved if inclusion of stakehold- stakeholders to increase trustworthiness. These may include ers and transparency of motivation and data flows are assured at high standards for data storage security, restrictions on data all parts of the research process, from study design, through linkage where necessary, evaluation of analytical methods, and ethics approvals, to analysis and interpretation of results . It is consistently applied sanctions for any breaches in data security. also essential that individuals have the possibility to opt-out of any data collecting schemes. Notably, the opt-out is only a meaningful way of ensuring individual autonomy if transpar- Conclusions ency of data usage, and stakeholder inclusion, is guaranteed. This Our interpretation of a range of studies of public views combination (opt-out plus full transparency) is also the pub- suggests that the public generally support the use of patient data 53,54 lic’s preferred approach , and is thus vital for maximising for research purposes. However, the public demand that projects public trust, and securing a social licence, for any initiative. One of this nature are conducted in a secure way to prioritise privacy, example of operationalising a transparent patient opt out was and minimise individual and collective harm; that projects set launched by the NHS in the UK in May 2018. Known as the research objectives (or negotiate agreements with third parties) National Data Opt-Out , it was originally recommended and which are primarily concerned with contributing to the common designed by the UK National Data Guardian’s Office. good; and that they do this in a spirit of transparency and inclu- sivity of stakeholder views. So long as these values are main- 2. Are the objectives and the intended outputs primarily tained, it is likely that the majority of the public will willingly concerned with contributing to the public good? Do they share their patient data for research purposes. have clear scientific value? (Beneficence) 3. Is any agreement between the NHS and organisations We have shown that public thinking about the privacy issues providing analytics (private or public) fair and just? around sharing patient data for research maps onto established (Justice) biomedical ethical principles, and such understanding may help researchers or regulators to identify how the public comes to confer a social licence on patient data research. These core One almost universal finding was that the public generally principles can be developed to frame guidance for data custo- support research using patient data if the research is for the com- dians, regulators and researchers when planning or approving mon or public good. They tend not to support research using research projects using patient data. patient data which enables private companies to increase profits. Thus, to retain a social licence, ethical bodies and regulators must evaluate proposals on the basis of their intended aims and whether they contribute significantly towards the common good. The engagement of industry and private companies to Grant information provide data analytics will be crucial to maximise benefits from This work was supported by the Wellcome Trust [202133]. patient data in the future. Where private companies are involved, there should be clear and transparent communication to all The funders had no role in study design, data collection and stakeholders about how a fair settlement has been negotiated, so analysis, decision to publish, or preparation of the manuscript. Page 14 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 Supplementary material Supplementary File 1: PRISMA checklist. Click here to access the data. Supplementary File 2: PRISMA flowchart, showing the number of records identified, included and excluded. Click here to access the data References 1. Academy of Medical Sciences: Personal data for public good:  using health  pilot Mixed Methods Appraisal  Tool (MMAT) for systematic mixed studies  information in medical research . London, UK: Academy of Medical Sciences; review. Int J Nurs Stud. 2012; 49(1): 47–53. 2006. PubMed Abstract   Publisher Full  Text  Reference Sourc e 19. Smith J, Firth J: Qualitative data analysis:  the framework approach. Nurse Res. 2. Kim KK, Joseph JG, Ohno-Machado L: Comparison of consumers’  views on  2011; 18(2): 52–62. electronic data sharing for healthcare and research. J Am Med Inform Assoc. PubMed Abstract   Publisher Full  Text  2015; 22(4): 821–30. 20. Braun V, Clarke V: Using thematic analysis in psychology. Qual Res Psychol. PubMed Abstract   Publisher Full  Text  Free Full  Text  | | 2006; 3(2): 77–101. 3. Botkin JR, Rothwell E, Anderson R, et al.: Public attitudes regarding the use of  Publisher Full  Text  electronic health information and residual clinical tissues for research. 21. Dixon-Woods M, Cavers D, Agarwal S, et al.: Conducting a critical interpretive  J Community Genet. 2014; 5(3): 205–13. synthesis of the literature on access to healthcare by vulnerable groups. BMC PubMed Abstract   Publisher Full  Text  Free Full  Text  | | Med Res Methodol. 2006; 6: 35. 4. Clerkin P, Buckley BS, Murphy AW, et al.: Patients’ views about the use of  PubMed Abstract   Publisher Full  Text  Free Full  Text  | | their personal information from general practice medical records in health  22. Thomas J, Harden A: Methods  for  the  thematic  synthesis  of  qualitative  research  research: a qualitative study in Ireland. Fam Pract. 2013; 30(1): 105–12. in systematic reviews. BMC Med Res Methodol. 2008; 8: 45. PubMed Abstract   Publisher Full  Text  | PubMed Abstract   Publisher Full  Text  Free Full  Text  | | 5. Grande D, Mitra N, Shah A, et al.: Public preferences about secondary uses  23. Noblit G, Hare R: Meta-ethnography: synthesizing qualitative studies. Thousand of electronic health information. JAMA Intern Med. 2013; 173(19): 1798–806. Oaks, US: Sage Publications; 1988. PubMed Abstract   Publisher Full  Text  Free Full  Text  | | Publisher Full  Text 6. Teschke K, Marino S, Chu R, et al.: Public opinions about participating in health  24. Nebeker C, Harlow J, Espinoza Giacinto R, et al.: Ethical and regulatory  research. Can J Public Health. 2010; 101(2): 159–64. challenges of research using pervasive sensing and other emerging  PubMed Abstract   Publisher Full  Text  | technologies: IRB perspectives. AJOB Empir Bioeth. 2017; 8(4): 266–276. 7. Weitzman ER, Kaci L, Mandl KD: Sharing medical data for health research:  the  PubMed Abstract   Publisher Full  Text  early personal health record experience. J Med Internet Res. 2010; 12(2): e14. 25. Clouser KD, Gert B: A critique of principlism. J Med Philos. 1990; 15(2): 219–36. PubMed Abstract   Publisher Full  Text  Free Full  Text  | | PubMed Abstract   Publisher Full  Text  8. NHS England: NHS England sets out the next steps of public awareness about  26. Huxtable R: For  and  against  the  four  principles  of  biomedical  ethics. Clin Ethics. Care.Data. 2013, [cited 2017 6th September]. 2013; 8(2–3): 39–43. Reference Sourc e Publisher Full  Text  9. Carter P, Laurie GT, Dixon-Woods M: The social licence for research:  why  Care. 27. Audrey S, Brown L, Campbell R, et al.: Young people’s views about consenting  Data ran into trouble. J Med Ethics. 2015; 41(5): 404–9. to data linkage:  findings from the PEARL qualitative study. BMC Med Res PubMed Abstract   Publisher Full  Text  Free Full  Text  | | Methodol. 2016; 16: 34. 10. Ramesh R: £140 could buy private firms data on NHS patients . The Guardian; PubMed Abstract   Publisher Full  Text  Free Full  Text  | | 2013, [cited 2017 26th September]. 28. Baird W, Jackson R, Ford H, et al.: Holding personal information in a disease- Reference Sourc e specific register:  the perspectives of people with multiple sclerosis and  11. GPRD and research - An overview for researchers. UK Research and Innovation. professionals on consent and access. J Med Ethics. 2009; 35(2): 92–6. 2018; [cited 2018 18th November]. PubMed Abstract   Publisher Full  Text  Reference Sourc e 29. Barrett G, Cassell JA, Peacock JL, et al.: National survey of British public’s  12. Jones KH, Laurie G, Stevens L, et al.: The other side of the coin:  Harm due to  views on use of identifiable medical data by the National Cancer Registry. the non-use of health-related data. Int J Med Inform. 2017; 97: 43–51. BMJ. 2006; 332(7549): 1068–72. PubMed Abstract   Publisher Full  Text  PubMed Abstract   Publisher Full  Text  Free Full  Text  | | | 13. Aitken M, de St Jorre J, Pagliari C, et al.: Public responses to the sharing  30. Buckley BS, Murphy AW, MacFarlane AE: Public attitudes to the use in research  and linkage of health data for research purposes:  a systematic review and  of personal health information from general practitioners’  records:  a survey of  thematic synthesis of qualitative studies. BMC Med Ethics. 2016; 17(1): 73. the Irish general public. J Med Ethics. 2011; 37(1): 50–5. PubMed Abstract   Publisher Full  Text  Free Full  Text  PubMed Abstract   Publisher Full  Text  | | | 14. Beauchamp T, Childress J: Principles of biomedical ethics . 6th ed, 2013 ed. New 31. Campbell B, Thomson H, Slater J, et al.: Extracting information from hospital  York, US: Oxford University Press; 1979. records: what patients think about consent. Qual Saf Health Care. 2007; 16(6): Reference Sourc e 404–8. PubMed Abstract   Publisher Full  Text  Free Full  Text  | | 15. The Belmont report . Washington, US: National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research, Department of Health, 32. Summary report of qualitative research into public attitudes to personal data  Education and Welfare (DHEW); 1978. and linking personal data. CM Insight, Wellcome Trust; 2013. Reference Sourc e Reference Sourc e 16. Dittrich D, Kenneally E: The menlo report:  Ethical principles guiding information  33. Grant A, Ure J, Nicolson DJ, et al.: Acceptability and perceived barriers and  and communication technology research . U.S. Department of Homeland facilitators to creating a national research register to enable  ‘direct to patient’   Security; 2012. enrolment into research:  the Scottish Health Research Register (SHARE). BMC Reference Sourc e Health Serv Res. 2013; 13: 422. PubMed Abstract   Publisher Full  Text  Free Full  Text  17. Moher D, Liberati A, Tetzlaff J, et al.: Preferred reporting items for systematic  | | reviews and meta-analyses:   The PRISMA statement. Ann Intern Med. 2009; 34. Haddow G, Bruce A, Sathanandam S, et al.: ‘Nothing is really safe’:  a focus  151(4): 264–9. group study on the processes of anonymizing and sharing of health data for  PubMed Abstract   Publisher Full  Text  research purposes. J Eval Clin Pract. 2011; 17(6): 1140–6. PubMed Abstract   Publisher Full  Text  18. Pace R, Pluye P, Bartlett G, et al.: Testing the reliability and efficiency of the  Page 15 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 35. Hays R, Daker-White G: The Care.data consensus? A qualitative analysis of  45. Stevenson F, Lloyd N, Harrington L, et al.: Use of electronic patient records for  opinions expressed on  Twitter. BMC Public Health. 2015; 15(1): 838. research:  Views of patients and staff in general practice. Fam Pract. 2013; PubMed Abstract   Publisher Full  Text  Free Full  Text  30(2): 227–32. | | PubMed Abstract   Publisher Full  Text  36. Hill EM, Turner EL, Martin RM, et al.: “Let’s get the best quality research we  | can”: public awareness and acceptance of consent to use existing data in  46. Robinson G, Dolk H: Public attitudes to data sharing in Northern Ireland . health research:  a systematic review and qualitative study. BMC Med Res Administrative Data Research Centre, Northern Ireland, 2016. Methodol. 2013; 13(1): 72. Reference Sourc e PubMed Abstract   Publisher Full  Text  Free Full  Text  | | 47. Stevenson F: The use of electronic patient records for medical research:   37. The use of personal health information in medical research general public  conflicts and contradictions. BMC Health Serv Res. 2015; 15(1): 124. consultation. Ipsos Mori, Medical Research Council; 2007. PubMed Abstract   Publisher Full  Text  Free Full  Text  | | Reference Sourc e 48. Westin A: Privacy and freedom . New York, US: Atheneum; 1967. 38. Perceptions of the Cancer Registry:  Attitudes towards and awareness of  Reference Sourc e cancer data collection. Ipsos Mori, Macmillan, Cancer Support Cancer Research 49. Parent WA: Privacy, morality,  and the law. Philosophy & Public Affairs. 1983; UK; 2016. 12(4): 269–88. Reference Sourc e Reference Sourc e 39. The one-way mirror:  public attitudes to commercial access to health data. 50. DeCew J: In pursuit of privacy:  Law,  ethics,  and the rise of technology . Ithaca, Ipsos Mori, Wellcome Trust; 2016. US: Cornell University Press; 1997. Reference Sourc e Reference Sourc e 40. Wellcome  Trust monitor report wave 3:   Tracking public views on science and  51. Gunningham N, Kagan R, Thornton D: Social license and environmental  biomedical research. Ipsos Mori, Wellcome Trust; 2016. protection:  Why businesses go beyond compliance. Law & Soc Inquiry. 2004; Reference Sourc e 29(2): 307–41. 41. Luchenski SA, Reed JE, Marston C, et al.: Patient and public views on electronic  Publisher Full  Text  health records and their uses in the United Kingdom:  cross-sectional survey. 52. Ford E, Boyd A, Bowles J: Our data,  our society,  our health:  A vision for  J Med Internet Res. 2013; 15(8): e160. inclusive and transparent health data science.  A position statement . submitted. PubMed Abstract   Publisher Full  Text  Free Full  Text  | | 53. Tully MP, Bozentko K, Clement S, et al.: Investigating the Extent to  Which  42. Papoutsi C, Reed JE, Marston C, et al.: Patient and public views about the  Patients  Should  Control  Access  to  Patient  Records  for  Research:  A  Deliberative  security and privacy of Electronic Health Records (EHRs) in the UK:  results  Process  Using  Citizens’  Juries. J Med Internet Res. 2018; 20(3): e112. from a mixed methods study. BMC Med Inform Decis Mak. 2015; 15(1): 86. PubMed Abstract   Publisher Full  Text  Free Full  Text  | | PubMed Abstract   Publisher Full  Text  Free Full  Text  | | 54. Ford E, Oswald M, Hassan L: Should free text data in electronic patient records  43. Riordan F, Papoutsi C, Reed JE, et al.: Patient and public attitudes towards  be shared for research? A citizens’  jury study . submitted. informed consent models and levels of awareness of Electronic Health  55. National  data  opt-out  programme: NHS  Digital. 2018; [cited 2018 18th November]. Records in the UK. Int J Med Inform. 2015; 84(4): 237–47. Reference Sourc e PubMed Abstract   Publisher Full  Text  Free Full  Text  | | 56. Annual  report  2016-2017. The Farr Institute of Health Informatics Research. 2017. 44. Spencer K, Sanders C, Whitley EA, et al.: Patient Perspectives on Sharing  Reference Sourc e Anonymized Personal Health Data Using a Digital System for Dynamic  57. Understanding Patient Data launches today. Wellcome Trust. 2017; [cited 2018 Consent and Research Feedback:  A Qualitative Study. J Med Internet Res. 18th November]. 2016; 18(4): e66. Reference Sourc e PubMed Abstract   Publisher Full  Text  Free Full  Text  | | Page 16 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 Open Peer Review Current Referee Status: Version 2 Referee Report 04 March 2019 https://doi.org/10.21956/wellcomeopenres.16368.r34595 Chrysanthi Papoutsi  Department of Primary Care Health Sciences, University of Oxford, Oxford, UK No further comments - the authors have done an excellent job in addressing issues raised previously. Competing Interests: No competing interests were disclosed. I have read this submission. I believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Referee Report 18 February 2019 https://doi.org/10.21956/wellcomeopenres.16368.r34596 Sarah Cunningham-Burley    Usher Institute, Edinburgh Medical School, University of Edinburgh, Edinburgh, UK The authors have made careful revisions.  The paper is clearer and more cogently argued. The review will be useful to all those engaged in research with patient medical data and its governance:  the challenge now is the extension to health-relevant data and to understand and benefit from diverse approaches within the UK devolved administrations, particularly Scotland with its Data Linkage Strategy. Competing Interests: No competing interests were disclosed. Reviewer Expertise: Sociology of health and illness, public engagement in health research and medical technologies I have read this submission. I believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Version 1 Referee Report 12 February 2018 https://doi.org/10.21956/wellcomeopenres.14693.r29910 Page 17 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 Chrysanthi Papoutsi  Department of Primary Care Health Sciences, University of Oxford, Oxford, UK This paper on public opinions about the use of patient data provides a comprehensive overview of relevant studies. The synthesis covers significant ground in drawing together findings from a mix of study designs. Despite long-standing debates in this area, the topic continues to be of importance for policy and practice. Please see some suggestions for improvement below. Perhaps revise some of the full quotes provided in the introduction so that the text flows better. Can you please elaborate on how this review differs from existing systematic reviews on this topic and its contribution to knowledge? The paper follows systematic processes for literature searching and screening. The approach to analysing the data has been methodical. More explanation is needed on whether the paper has followed any established approaches for systematically reviewing mixed methods, secondary data (e.g. see 1 2 Dixon-Woods et al. (2005)  or Thomas and Harden (2008) ) and if not, why not. Could you please provide more details on the following: ‘we undertook a deeper analysis of meaning within findings guided 20 9 by both metasynthesis principles  and established principles of bioethics ’. Please elaborate on the application of the Mixed Methods Appraisal Tool (MMAT) for assessing quality across different study designs. The findings section draws heavily on qualitative data, however, these studies tend to be ranked lower in terms of ‘quality’ – are studies being prioritised based on a hierarchy of evidence or are they judged based on the merit of each study design, and what does this mean for the topic studied here? How has the study using Twitter data been assessed for quality and inclusion (e.g. is it clear whether participants are from the UK or Ireland for example)? Please revise the PRISMA diagram to clarify which studies were only quantitative, which were only qualitative and which were mixed methods (these numbers are provided correctly in the text). It is difficult to interpret syntheses of results presented as a list of percentages e.g. ‘Among the 36 35 quantitative studies, public support for a national EHR system was reported at 62.5% , 62.47% , and 23 32 81% , while support for sharing information in general was reported 73% .’ What do the authors mean by national EHR system, what does ‘public support mean’, what does ‘sharing information’ mean and what do these percentages refer to? Of course these terms are artifacts of the studies reviewed here but it would be helpful to provide more context for the reader who has not seen the original studies, when presenting percentages across the document. There are differences in the healthcare and EHR systems across the UK and Ireland – it would be worth reflecting on this when synthesising results from different studies. Academic literature on privacy may help clarify some of the nuances around control and self-determination (e.g. when it is mentioned that ‘Privacy was widely conceptualised as a process whereby an individual determines for themselves what happens with the information relating to them.’) Further use of background literature and theory could inform the analysis. It would be useful to elaborate on the use of the Beauchamp and Childress framework. Are there any pre-existing applications of this framework to study patient attitudes? How do the nine questions used for data analysis fit with the Beauchamp and Childress framework? Was the framework used as part of the analysis or as a lens to discuss the findings? If the latter, more extensive and critical discussion is needed Page 18 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 analysis or as a lens to discuss the findings? If the latter, more extensive and critical discussion is needed – perhaps reflecting on how normative ethical frameworks can encompass the messiness of everyday reality and practice. The paper mentions contradictions between studies based on demographic characteristics. It would be useful to reflect on why these differences may have occurred and how qualitative data could help explain them. The future directions section needs further development – this links back to the use of the Beauchamp and Childress framework. The authors present 4 questions for policy and practice but may need to further clarify how these would be used, how some of the terms need to be understood (e.g. what constitutes patient autonomy is in itself a challenging topic of philosophical contention) and whether the answer to these 4 questions could ever be straightforward in practice. References 1. Dixon-Woods M, Agarwal S, Jones D, Young B, Sutton A: Synthesising qualitative and quantitative evidence: A review of possible methods. Journal of Health Services Research & Policy. 2005; 10 (1): 45-53 Publisher Full Text  2. Thomas J, Harden A: Methods for the thematic synthesis of qualitative research in systematic reviews. BMC Med Res Methodol. 2008; 8: 45 PubMed Abstract | Publisher Full Text  Are the rationale for, and objectives of, the Systematic Review clearly stated? Yes Are sufficient details of the methods and analysis provided to allow replication by others? Yes Is the statistical analysis and its interpretation appropriate? Not applicable Are the conclusions drawn adequately supported by the results presented in the review? Yes Competing Interests: No competing interests were disclosed. I have read this submission. I believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. Author Response 04 Jan 2019 Elizabeth Ford, Brighton and Sussex Medical School, UK We would like to thank you for these very helpful comments, which have enabled us to substantially improve the paper. We spent a lot of time discussing these insightful comments in order to best make improvements to the manuscript. We detail point by point below how we have addressed each comment. We have highlighted our changes in our revised manuscript in red font. 1) Perhaps revise some of the full quotes provided in the introduction so that the text flows better. Page 19 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 flows better. We have completely updated the paragraph with the quotes, to reflect new changes in the law due to GDPR. No quotes are included in the new paragraph (page 3).  2) Can you please elaborate on how this review differs from existing systematic reviews on this topic and its contribution to knowledge? We have added a new section on this on page 4 in the “Striking a balance” paragraph. We have described how by using a well-recognized ethical framework we can draw underlying themes from the results which may help to organize policy. 3) More explanation is needed on whether the paper has followed any established approaches for systematically reviewing mixed methods, secondary data (e.g. see Dixon-Woods et al. (2005) or Thomas and Harden (2008)) and if not, why not. Could you please provide more details on the following: ‘we undertook a deeper analysis of meaning within findings guided by both metasynthesis principles and established principles of bioethics’. We have included a new section on data synthesis in the methods section page 6, outlining how we used a thematic analysis to interpret the data (a method recommended by both Dixon-Woods et al. and Thomas and Harden). We have extended this section to explain how the Beauchamp and Childress framework informed our analysis. 4) Please elaborate on the application of the Mixed Methods Appraisal Tool (MMAT) for assessing quality across different study designs. The findings section draws heavily on qualitative data, however, these studies tend to be ranked lower in terms of ‘quality’ – are studies being prioritised based on a hierarchy of evidence or are they judged based on the merit of each study design, and what does this mean for the topic studied here? How has the study using Twitter data been assessed for quality and inclusion (e.g. is it clear whether participants are from the UK or Ireland for example)? We treated insights from qualitative and quantitative studies as having different roles but equal value in our enquiry, and therefore if they met MMAT criteria we did not further differentiate between methodologies in terms of a hierarchy. We have explained this on page 6. 5) Please revise the PRISMA diagram to clarify which studies were only quantitative, which were only qualitative and which were mixed methods (these numbers are provided correctly in the text).  We have revised the PRISMA diagram as requested (supplementary file 2) 6) It is difficult to interpret syntheses of results presented as a list of percentages e.g. ‘Among the quantitative studies, public support for a national EHR system was reported at 36 35 23 62.5% , 62.47% , and 81% , while support for sharing information in general was reported 73% .’ We revised the reporting of results in this section, because, when we considered its value within the paper, we found the sentence that the reviewer referred to did not answer any of the outlined research objectives. We now only present evidence on participants’ willingness to share their patient data for research in this section. 7) There are differences in the healthcare and EHR systems across the UK and Ireland – it would be worth reflecting on this when synthesising results from different studies. We have added a paragraph reflecting on the differences in the two systems and how this could influence results. Page 24. Page 20 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 influence results. Page 24. 8) Academic literature on privacy may help clarify some of the nuances around control and self-determination (e.g. when it is mentioned that ‘Privacy was widely conceptualised as a process whereby an individual determines for themselves what happens with the information relating to them.’) Further use of background literature and theory could inform the analysis. We have added a paragraph in the discussion on pages 22-23, to describe further literature on the nuances around the conceptualisation of privacy. 9) It would be useful to elaborate on the use of the Beauchamp and Childress framework. Are there any pre-existing applications of this framework to study patient attitudes? We reference the Beauchamp and Childress framework, but note its similarity to other ethical principles such as Belmont. While we have not found such basic principles applied to study patient attitudes (now explained on page 6), we have found them applied to information technology research (Menlo report, now described and referenced, page 4). We used this simple framework to cast a lens on the findings of our review, as a way of sorting and filtering through the complexity of public opinions. A stable and concise framework might enable policy makers and regulators to more efficiently apply stakeholder views to their decision making, thus facilitating securing a social license for research. 10) How do the nine questions used for data analysis fit with the Beauchamp and Childress framework? The nine questions for the data analysis were driven by the problem of data sharing for health research as it manifested itself, rather than our interpretation of the problem through the Beauchamp and Childress framework. They represent the first iteration of our search for themes within the data. We have made this clearer on page 6. Our assimilation of the results was data-driven, and Beauchamp and Childress only used to add the highest levels of interpretation. 11) Was the framework used as part of the analysis or as a lens to discuss the findings? If the latter, more extensive and critical discussion is needed – perhaps reflecting on how normative ethical frameworks can encompass the messiness of everyday reality and practice. We have provided much more clarity on our use of this framework, on page 4. We say: “We use these widely accepted principles as a tool to identify patient reasoning in the analysis, and additionally as a lens to discuss the findings in terms of the newly adopted social license theory for patient data research. Identifying a framework which describes the core moral or ethical values underlying public views may help us to understand approaches to sharing patient data for research that the public will deem as acceptable, and help us to predict the reaction of the public to new data sharing challenges in the future.” 12) The paper mentions contradictions between studies based on demographic characteristics. It would be useful to reflect on why these differences may have occurred and how qualitative data could help explain them. In our investigation of differences in views by demographic characteristics, we did not find any replicable trends across quantitative studies. This may be because quantitative studies were limited in their ability to rigorously identify differences, or because such difference do not exist. Therefore we cannot speculate on reasons for differences, because we have not got any firm evidence that these differences exist. We have added a sentence on this to the discussion. Page Page 21 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 13) The future directions section needs further development – this links back to the use of the Beauchamp and Childress framework. The authors present 4 questions for policy and practice but may need to further clarify how these would be used, how some of the terms need to be understood (e.g. what constitutes patient autonomy is in itself a challenging topic of philosophical contention) and whether the answer to these 4 questions could ever be straightforward in practice. Many thanks for these suggestions. We have substantially re-written this section.  Competing Interests: No competing interests were disclosed. Referee Report 30 January 2018 https://doi.org/10.21956/wellcomeopenres.14693.r29907 Sarah Cunningham-Burley    Usher Institute, Edinburgh Medical School, University of Edinburgh, Edinburgh, UK On the whole this is a clearly presented systematic review (a copy edit is required as there are a few typos) and it reinforces the findings of a similar systematic review that I am co-author on, as the authors note in their conclusion. However, this review included quantitative studies and focused only on UK and Ireland, so the articles included do not fully overlap - the reviews were different in scope. So this is an additional contribution to the literature on public attitudes to data linkage and sharing for health research.  The process of the systematic review is delineated well and there is sufficient information on each included article for the reader to be able to access these and also to relate the findings of the review to those articles.  The authors also cite some other relevant literature not included in the review. The authors are appropriately cautious in their interpretation of the findings from various studies, as these are often small scale, limited response rates etc.  I have a few concerns about the paper. The authors do not seem to be aware of existing governance structures, carefully developed alongside research on public attidues and legal and ethical analyses. Health is a devolved matter in the UK. They need to read and make reference to the Scottish Government’s Data Linkage Framework (http://www.gov.scot/Topics/Statistics/datalinkageframework), the Guiding Principles for Data Linkage, and the terms of reference for the Public Benefits and Privacy Panel for Health and Social Care. Perhaps also look at the FARR Institute website to see how this major initiative is promoting safe use of health data for research purposes. There are some key reports that have not been identified by their search that are highly relevant: Public Acceptability of Cross-Sectoral Data Linkage (http://www.gov.scot/Publications/2012/08/9455); Public acceptability of data sharing between public, private and third sectors for research purposes (http://www.gov.scot/resource/0043/00435458.pdf ); Aitken et al (2011) . These would all help the authors craft more apposite recommendations.  A few other points – while supportive of an approach that identifies core principles, I’m not sure that Beauchamp and Childress’ four principles for biomedical research translate as easily as they suggest. I think some reference to emergent frameworks that speak to a social licence might be more compelling and the core principles that might underpin such a license. Public health ethics might help here.  Page 22 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 and the core principles that might underpin such a license. Public health ethics might help here.  A more minor point – the authors start by referring the medical data but really they are focussed on health data – a broader term. I also wonder why they use the term public opinion instead of attitudes. It may be that these terms are used differently in quantitative and qualitative research perhaps, but some justification would be helpful. During the presentation of the findings of the review, they also refer to GP records, the Electronic Health Record, Cancer Registries – maybe clarify what type of records the studies they are referring to – or use the overarching term of EHR. The authors touch on the differences in the way in which public’s views are accessed and I think that point bears further elaboration. References 1. Aitken M, Cunningham-Burley S, Pagliari C: Moving from trust to trustworthiness: Experiences of public engagement in the Scottish Health Informatics Programme.Sci Public Policy. 2016; 43 (5): 713-723  PubMed Abstract | Publisher Full Text  Are the rationale for, and objectives of, the Systematic Review clearly stated? Yes Are sufficient details of the methods and analysis provided to allow replication by others? Yes Is the statistical analysis and its interpretation appropriate? Not applicable Are the conclusions drawn adequately supported by the results presented in the review? Yes Competing Interests: No competing interests were disclosed. Reviewer Expertise: Sociology of health and illness, public engagement in health research and medical technologies I have read this submission. I believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. Author Response 04 Jan 2019 Elizabeth Ford, Brighton and Sussex Medical School, UK Many thanks for your helpful comments which have enabled us to substantially improve the paper. We detail point by point below how we have addressed each comment. We have highlighted our changes in the manuscript in red font. 1) Copy edit is required. Thank you, we have thoroughly proofread the paper. 2) The authors do not seem to be aware of existing governance structures, carefully developed alongside research on public attidues and legal and ethical analyses. Health is a devolved matter in the UK. They need to read and make reference to the Scottish Government’s Data Linkage Framework Page 23 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 Government’s Data Linkage Framework (http://www.gov.scot/Topics/Statistics/datalinkageframework), the Guiding Principles for Data Linkage, and the terms of reference for the Public Benefits and Privacy Panel for Health and Social Care. Thank you for pointing out the regional differences and the link to the Scottish framework. We have replaced this section with a general overview of the new EU GDPR legislation (page 3) and its general implications for the sharing of patient data, with no references made to specific countries’ frameworks or data access policies. 3) Perhaps also look at the FARR Institute website to see how this major initiative is promoting safe use of health data for research purposes We have included reference to Farr, and the Wellcome trust initiative Understanding Patient Data as key exemplars of disseminators of public benefits of patient data research, in the discussion page 25 4) There are some key reports that have not been identified by their search that are highly relevant: Public Acceptability of Cross-Sectoral Data Linkage (http://www.gov.scot/Publications/2012/08/9455); Public acceptability of data sharing between public, private and third sectors for research purposes (http://www.gov.scot/resource/0043/00435458.pdf); Aitken et al (2011) . recommendations. Many thanks for suggesting these reports. We scrutinised these reports in detail and found they did not meet our eligibility criterion that studies must be about sharing health data in particular and not personal data in general. 5) A few other points – while supportive of an approach that identifies core principles, I’m not sure that Beauchamp and Childress’ four principles for biomedical research translate as easily as they suggest. I think some reference to emergent frameworks that speak to a social licence might be more compelling and the core principles that might underpin such a license. Public health ethics might help here. Many thanks for these suggestions which mirror recommendations from reviewer 1 and have helped us to strengthen the main messages of the paper. We have substantially rewritten the future directions section and the majority of the discussion. We have given more background information on the use of key ethical principles such as Beauchamp and Childress in the introduction, and have related these principles to social license theory throughout the paper. 6) A more minor point – the authors start by referring the medical data but really they are focussed on health data – a broader term. I also wonder why they use the term public opinion instead of attitudes. It may be that these terms are used differently in quantitative and qualitative research perhaps, but some justification would be helpful. Papers used a variety of different terms denoting that they were capturing the thoughts of patients and the public, including: views, perspectives, attitudes, perceptions, opinions, acceptance, awareness, thoughts. We have decided to use generically the term public “views” because this feels like the most general term, and we have made this consistent throughout. We agree with the reviewers on the need for clarification of the terms medical and health data. We have described the type of data we are focusing on in the methods (page 5), as “electronic hospital records, electronic general practice records, and data extracted from these records, for example cancer registries and national disease databases” and have used the terms patient data or EHRs to represent these data throughout the manuscript. We preferred the term “patient data” to keep our language consistent with public facing initiatives such as the Wellcome Trust “Understanding Page 24 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 our language consistent with public facing initiatives such as the Wellcome Trust “Understanding Patient Data” initiative. 7) During the presentation of the findings of the review, they also refer to GP records, the Electronic Health Record, Cancer Registries – maybe clarify what type of records the studies they are referring to – or use the overarching term of EHR. The authors touch on the differences in the way in which public’s views are accessed and I think that point bears further elaboration. Please see response to the point above regarding terms for patient data. We have added a sentence to the limitations about how the views expressed may have been affected by methods of studies. (Page 24)  Competing Interests: No competing interests were disclosed. Page 25 of 25 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Wellcome Open Research Pubmed Central

“Giving something back”: A systematic review and ethical enquiry into public views on the use of patient data for research in the United Kingdom and the Republic of Ireland

Wellcome Open Research , Volume 3 – Jan 17, 2019

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Pubmed Central
Copyright
Copyright: © 2019 Stockdale J et al.
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2398-502X
eISSN
2398-502X
DOI
10.12688/wellcomeopenres.13531.2
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Abstract

  Invited Referees Background: Use of patients’ medical data for secondary purposes such as 1 2 health research, audit, and service planning is well established in the UK. However, the governance environment, as well as public understanding about    this work, have lagged behind. We aimed to systematically review the literature report report version 2 on UK and Irish public views of patient data used in research, critically published analysing such views though an established biomedical ethics framework, to 17 Jan 2019 draw out potential strategies for future good practice guidance and inform ethical and privacy debates. version 1 Methods: We searched three databases using terms such as patient, public, published report report 16 Jan 2018 opinion, and electronic health records. Empirical studies were eligible for inclusion if they surveyed healthcare users, patients or the public in UK and Ireland and examined attitudes, opinions or beliefs about the use of patient data Sarah Cunningham-Burley , for medical research. Results were synthesised into broad themes using a University of Edinburgh, UK framework analysis. Results: Out of 13,492 papers and reports screened, 20 papers or reports Chrysanthi Papoutsi, University of were eligible. While there was a widespread willingness to share patient data Oxford, UK for research for the common good, this very rarely led to unqualified support. The public expressed two generalised concerns about the potential risks to Any reports and responses or comments on their privacy. The first of these concerns related to a party’s competence in the article can be found at the end of the keeping data secure, while the second was associated with the motivation a article. party might have to use the data. Conclusions: The public evaluates trustworthiness of research organisations by assessing their competence in data-handling and motivation for accessing the data. Public attitudes around data-sharing exemplified several principles which are also widely accepted in biomedical ethics. This provides a framework for understanding public attitudes, which should be considered in the development in any guidance for regulators and data custodians. We propose four salient questions which decision makers should address when evaluating proposals for the secondary use of data Page 1 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 Keywords Privacy, Patient Data, Electronic Health Records, Governance, Public, Engagement, Ethics Corresponding author: Elizabeth Ford (e.m.ford@bsms.ac.uk) Author roles: Stockdale J: Conceptualization, Data Curation, Formal Analysis, Writing – Original Draft Preparation, Writing – Review & Editing;  Cassell J: Conceptualization, Writing – Review & Editing; Ford E: Conceptualization, Formal Analysis, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing Competing interests: No competing interests were disclosed. Grant information: This work was supported by the Wellcome Trust [202133]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Copyright: © 2019 Stockdale J et al. This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. How to cite this article: Stockdale J, Cassell J and Ford E. “Giving something back”: A systematic review and ethical enquiry into public views on the use of patient data for research in the United Kingdom and the Republic of Ireland [version 2; referees: 2 approved] Wellcome Open Research 2019, 3:6 (https://doi.org/10.12688/wellcomeopenres.13531.2) First published: 16 Jan 2018, 3:6 (https://doi.org/10.12688/wellcomeopenres.13531.1)  Page 2 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 concern with the impact that its aim to collect and share data on   REVISED           Amendments from  Version 1 a large scale might have on patient privacy. The case of Care. data indicates a reluctance on behalf of the public to share their We would like to thank the reviewers and the editor for their very helpful comments, which have enabled us to substantially patient data, and it is still not wholly clear whether the public improve the paper. We spent a lot of time discussing the are willing to accept future attempts at extracting and linking reviewers’ insightful comments in order to best make large datasets of medical information. The picture of mixed improvements to the manuscript. Our key revisions include: opinion makes taking an evidence-based position, drawing on • Gr eater justification of the use of core ethics principles to social consensus, difficult for legislators, regulators, and data understand patient views, and the weaving of these long- custodians who may respond to personal or media generated standing principles together with the new theory of social perceptions of public views. However, despite differing results licence, within the domain of patient data research. This of studies canvassing public views, we hypothesise that there includes a full re-write of the future directions section of the discussion. may be underlying ethical principles that could be extracted from the literature on public views, which may provide guidance • Better explanation of our methods of paper selection, quality screening and results synthesis, including reference to to policy-makers for future data-sharing. established methodologies. • An up to date section on GDPR as it r elates to re-use of Governance and legal framework of data use patient data for research, and further exploration of the Since 2018, the General Data Protection Regulation (GDPR) has meaning of privacy in this context. governed the use of patients’ medical data in the EU and UK, • Better consistency in use of ter ms such as patient data and superseding the Data Protection Act in the UK (1998). GDPR public views. covers personal, or patient identifiable data in the UK, and • The title has been edited and Supplementary File 2 has been defines pseudonymised data, which can be traced back to the updated. individual using a study or database specific ID code, as personal data. Patient data can be used for direct care or audit and health- See referee reports care quality improvement projects without consent as these are seen as primary use of data. Research, however, is a secondary use of such data, as it is a use different from the originally Introduction declared purpose of data collection. Research organisations The use of patients’ medical data for secondary purposes such as thus need a “legal basis” for processing the data even when health research, audit, and service planning is well established identifiers are stripped, if individuals are still potentially re- in the UK, and technological innovation in analytical methods identifiable by a pseudonymisation code . One such legal basis is for new discoveries using these data resources is developing individual consent for use of the data in this way, and a second quickly. Data scientists have developed, and are improving, many is “a task in the public interest”. For research, such processing ways to extract and process information in medical records. may be justified in terms of research for the public good, as long This continues to lead to an exciting range of health related as appropriate safeguards are in place to reduce potential harms discoveries, improving population health and saving lives. to the data subject and ensure respect for the principle of data Nevertheless, as the development of analytic technologies minimisation. accelerates, the decision-making and governance environment as well as public views and understanding about this work, has Reducing potential harms to the data subject involves taking a been lagging behind . range of precautions to reduce the risk that an individual patient could be re-identified. Removing the pseudonymisation code Public opinion and data use and aggregating the data to a level at which re-identification is A range of small studies canvassing patient views, mainly in the not possible is the surest way of reducing such harm, but USA, have found an overall positive orientation to the use of often renders the data less usable for research purposes and 2–7 patient data for societal benefit . However, recent case studies, destroys the ability to link the data to other sources of health like NHS England’s ill-fated Care.data scheme, indicate that information. Research teams usually robustly protect patient certain schemes for secondary data use can prove unpopular in data with computing security systems, which do not allow the the UK. Launched in 2013, Care.data aimed to extract and upload data to be downloaded, or unapproved datasets to be uploaded and the whole population’s general practice patient records to a linked to the sensitive data. They also ensure only trusted and central database for prevalence studies and service planning . trained users are permitted access to the data. If data are to be Despite the stated intention of Care.data to “make major released to the public, this is usually done only after data have advances in quality and patient safety” , this programme was met been aggregated so that they have become truly anonymous. with a widely reported public outcry leading to its suspension and eventual closure in 2016. Several factors may have been involved Striking a balance in this failure, from the poor public communication about the While it is clearly important to make sure patient privacy is project, lack of social licence , or as pressure group Med- protected, it is also argued that the societal benefit of medical Confidential suggests, dislike of selling data to profit-making research using patient data, should be given ethical weight. This companies . However, beyond these specific explanations for is argued on the basis that harms to patients may occur where the project’s failure, what ignited public controversy was a these rich data sources are not used to improve our understanding Page 3 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 of health conditions and treatments . While individual privacy sharing”) AND (Research). We restricted our search to pub- and societal benefit are often portrayed as being in opposition, lications from 2006–2016 inclusive. We also searched the for the future of health data research, a way to achieve both to the grey literature using the search string: “public attitudes” AND satisfaction of patients, clinicians, legislators and researchers “sharing” AND “health data” on Google (in June 2017). The first must be found. Recent work has sought to identify the key issues 20 results were selected and screened. The following inclusion of patient views on data-sharing . However, few syntheses of criteria were then applied: patient views have additionally aimed to identify the implicit 1. Empirical studies using any methods reported as a full reasoning on which patients rely to justify the responses they length peer review manuscript or published report. give. Identifying a framework which describes the core moral or ethical values underlying public views may help us to predict 2. Healthcare users, patients or the wider public as the reaction of the public to new data sharing challenges in the participants future. Since the tension between data sharing and privacy is an ethical tension (to the extent that it involves what states of affairs 3. Examining views, attitudes, opinions, perspectives, ought to obtain, morally speaking), we are interested in the thoughts, awareness or acceptance about the topic of use ethical dimensions of such patient reasoning. To this end, we of patient data for medical research. propose to draw on core principles of biomedical ethics. First 3a. Patient data for medical research includes suggested in 1978 and 1979 in two forms, by Beauchamp and electronic hospital records, electronic general prac- Childress for ethical conduct within medicine , and in the tice records, and data extracted from these records, Belmont report for ethical conduct in healthcare research. for example cancer registries and national disease Core principles include the concepts of respect for autonomy, databases (summarised as patient data or EHRs). beneficence, non-maleficence, and justice. A similar set of principles were applied to information technology research in 4. Studies using a UK or Irish sample, written in English. science and technology by Menlo in a 2012 report . We aimed We chose to keep our review to these two countries to use these widely accepted principles as a tool to identify because of similarities in their socialised healthcare underlying themes expressed in patient views, and as a lens systems, and because of the well-established use of to discuss the findings. We also aimed to bring together these patient data within these jurisdictions. core principles with the newly adopted social licence theory for patient data research . This theory suggests that by volun- Studies were excluded if they were: tarily adhering to social codes of trustworthy and responsible 1. Focused more broadly on digital technologies in health behaviour that go beyond legal or regulatory frameworks, and care where the focus was on use of digital methods or by honouring additional safeguards, organisations can engender records rather than public attitudes trust from the public for schemes which may initially be controversial. 2. Focused on patient and practitioner attitudes to analogous areas such as biorepositories, genetic testing In this study, we therefore aimed to systematically review and and genomic research or personal data not exclusively thematically analyse UK and Irish studies exploring patient related to health. and public views on patients’ medical data being used for the secondary purpose of research, and aimed to understand and 3. Non-empirical reviews of legislation, policy, ethical map these views onto established biomedical ethical principles. challenges etc. We aimed to make suggestions for consideration by ethics committees and regulators to ensure that such research operates Using these criteria, the articles extracted from the literature in a transparent and trustworthy way, with the aim of maximis- search were screened based on their title, then abstract (by author ing the potential for the public to grant a social licence for such JS), then finally the choice of full text papers for the review was research to operate. undertaken by two authors (JS and EF). Methods Quality Assessment We followed the PRISMA guidelines for the conduct and report- Study quality was assessed using the Mixed Methods Appraisal ing of this review . Tool (MMAT) . This tool was designed for the appraisal of studies in mixed methods systematic reviews and attempts to Search strategy appraise the quality of methodology, rather than the quality of We searched PubMed, Web of Science, and Scopus between reporting. All studies meeting the inclusion criteria above were 03/10/16 and 11/10/16 using the following search string: assessed using six criteria. The first two criteria are the same for (Public OR Patient OR People) AND (Attitudes OR Knowledge all studies: is there a clear research question or objective, and OR Opinions OR Views OR Perceptions) AND (“Care.data” OR does the data collected address the research question or objective. “Electronic Health Record” OR “Electronic Health Data” OR A further four questions were specific to the study type. Studies “Electronic Medical Record” OR “Electronic Medical Data” OR were given a score out of six depending on how many of the six “Personal Health Information” OR “Personal Health Record” OR criteria they met, and were rejected if they did not meet at least “Electronic Patient Information” OR “Electronic Patient Data” the first two criteria. Two papers were excluded on the basis of OR “Electronic Patient Record” OR “Data linkage” OR “Data scoring zero on all criteria. Page 4 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 While quantitative papers are generally seen as of higher and Clarke’s guidance on qualitative thematic analysis , an quality, we believed that the in-depth exploration of human approach recommended for meta-synthesis by Dixon-Woods 21 22 reasoning for participant perspectives and decisions, illustrated et al. and Thomas and Harden . By taking an interpretive in the qualitative studies, could offer a greater understanding to approach to the synthesis of the data, we examined “the underpin our moral and ethical interpretation. Thus we treated underlying ideas, assumptions, and conceptualisation – and quantitative and qualitative studies as having equal value in the ideologies – that are theorized as shaping or informing the analysis if they met quality criteria. semantic content of the data” (p.84) . This was shaped and directed by Beauchamp and Childress’ four principles of bioethics , which enabled us to gain a better understanding of Data extraction the emerging moral meaning, and moral values conveyed by the We extracted author names, dates, location, type of study (quali- study participants in these themes. As far as the authors are tative or quantitative), methods used, number of participants, aware, there are no pre-existing applications of this framework their backgrounds or roles, ages, genders, and the study findings to study patient attitudes. However, this general approach which fitted into the themes relating to research questions has been taken before using The Belmont Report to identify reported below. stakeholder views on technology-enabled research . While the 25,26 four principles have drawn criticism elsewhere they continue Synthesis of results to be extremely influential in evaluations of ethical dilemmas The full text of eligible articles was read iteratively by two in health care, and a useful framework with which to identify authors (JS and EF) with the aim of extracting coherent themes. In moral values in participant decision-making. the first iteration of reading and coding the results of the papers, nine questions arose, which formed the basic direction of the Results inquiry. A total of 13,472 peer-reviewed papers were found through 1. Are patients/public aware of electronic health records the systematic search, as well as 20 reports found through the (EHRs) and their secondary uses? grey literature search. Of these, 20 UK and Ireland based papers 4,27–45 met the inclusion criteria and were included in the review 2. Are patients/public concerned about the privacy and (Supplementary File 2). Studies which reported time periods security of their medical data? indicated that data was collected from 2004 to 2016, although 3. Are patients/public willing to share their medical data for seven studies published between 2011 and 2016 did not report research, policy and planning? the data collection period. Research participants included patients, service-users, lay persons, those living with chronic 4. What consent model do patients/public prefer? conditions, and the general public ranging from 16 years of 5. How does data being identifiable or anonymised affect age to over 75. Five of the studies included the views of health patient/public preferences? researchers, health professionals, industry experts, NHS managers and other key stakeholders. Seven of the papers were quanti- 6. Which organisations are most and least trusted with tative, using surveys or structured questionnaires. Ten of the patients’/public data? studies were qualitative, using focus groups and one-to-one 7. What are the reported perceptions of risks and benefits of interviews, and there were three mixed methods studies. Details of sharing medical data for research? studies are reported in Table 1. 8. Are there any other ways in which willingness to share Quality assessment could be increased? Studies’ quality scores ranged from 3 to 6 out of a possible 6, 9. Is there any differences between demographic groups scores of individual studies are shown in Table 1. Two studies concerned with the sharing of EHRs? which otherwise met inclusion criteria were rejected on the basis 46,47 of quality and do not appear further in the results . A framework was created with a column for each of the nine questions and data was extracted from each study where it fitted Themes elicited from the studies into these categories. Following this data extraction, the two The seven themes identified in and elicited from the studies were: authors (EF and JS) discussed refining and combining extracted Knowledge and Awareness of Electronic Records; Willingness to data into as smaller number of themes. In a second iteration of Share; Privacy; Trust; De-identification and Consent Preferences; data extraction, authors re-read articles and extracted data into Routes to Securing Trust; and Demographic Differences. The seven themes. For interpretation and synthesis, a data driven contribution of each study to each theme is shown in Table 2. approach was taken, trying to make meaning from first order data reported in the papers (i.e. statistics or participant quotes). Knowledge and awareness of electronic records Where themes were populated mainly by summary of quantitative Generally, knowledge of the content and electronic collection data, a straightforward report of papers’ findings is given. of GP records among respondents was high. One quantitative study reported that a moderately high proportion of respondents Where contributing papers were mainly qualitative e.g. in the at 59% had prior awareness of EHRs . Another quantitative study Trust theme, we undertook a deeper analysis directed by Braun reported that levels of understanding of the information recorded Page 5 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 Page 6 of 25 Table1. Includedstudycharacteristics. Study Reference Method Setting DataCollection Sample Quality no. Period Score 27 Audrey, S., et al., BMC Medical Qualitative: focus groups Bristol, England Not stated Total n=55, 56.4% female 43.6% male Ages: 17–19. 5 Research Methodology, 2016. 16: with participants from p. 34 ALSPAC. 28 Baird, W., et al., Journal of Medical Qualitative: focus groups England and February and July Total n=68 Focus groups: Patients with MS and 5 Ethics, 2009. 35(2): p. 92–96. and interviews. Northern Ireland 2006 stakeholders (n=55) Interviews: Health and social care professionals an academics (n=13) 29 Barrett, G., et al., British Medical Quantitative: survey run England, Wales March and April Total n=2872 46% male 54% female Ages: 16–44 6 Journal, 2006. 332(7549): p. 1068–1070. by the Office of national and Scotland 2005 46%; 45–64 35%; 65+ 20% statistics 30 Buckley, B.S., A.W. Murphy, and A.E. Quantitative: postal Republic of Not stated Total n=1575 27.6% male 71.6% female Ages: 4 MacFarlane, Journal of Medical Ethics, electoral roll-based Ireland 18–75+ 2011. 37(1): p. 50–55. questionnaire survey. 31 Campbell, B., et al., Quality and Safety Quantitative: postal South-West October to Total n=166 patients recently discharged from 5 in Health Care, 2007. 16(6): p. 404–408. questionnaire England December 2004 the care of 78 bed-holding consultants across all specialties at the Royal Devon and Exeter Hospital. 32 CM Insight and Wellcome Trust, Qualitative: focus groups London, 29 April to 12 May Total n=50, Ages: 18–70 Focus group 3 Summary report of qualitative research and one-to-one telephone Midlands and 2013 respondents were recruited as owners of store into public attitudes to personal data interviews. Norfolk, England loyalty cards, smart phones and social media and linking personal data. 2013. users. Telephone interviewees were recruited as especially pro-privacy or cautious about sharing personal data. 4 Clerkin, P., et al., Family Practice, 2013. Qualitative: focus groups. West Republic of Not stated Total n=35, female (n=18) male (n=17) Ages: 6 30(1): p. 105–112. Ireland 18–35(n=2); 36–55(n=14); 56–70 (n=19). 33 Grant, A., et al., BMC Health Services Qualitative: focus groups Tayside and Between February Total n=64, Focus Groups: Patients (n=37), Health 5 Research, 2013. 13: p. 422. and semi-structured Lothian, Scotland and June 2011 services researchers (n=10) Interviews: GPs and interviews. Practice managers (n=17) 34 Haddow, G., et al., Journal of Qualitative: focus groups. North East May and June 2009 Total n=19, female (n=12), male (n=6), Unstated 5 Evaluation in Clinical Practice, 2011. Scotland (n=1) Ages: <60 (n=1); 60–74 (n=15); +75 (n=3). 17(6): p. 1140–1146. 35 Hays, R. and G. Daker-White, BMC Qualitative: using tweets. Twitter Over 18 days 3537 tweets containing the hashtag #caredata; 6 Public Health, 2015. 15: p. 838. during February 904 contributors and March 2014 36 Hill, E.M., et al., BMC Medical Research Qualitative: focus groups. England, Wales, Not stated Total n=19, 100% male Ages: 54–69; mean age 61. 4 Methodology, 2013. 13: p. 72. Scotland and Northern Ireland 37 Ipsos Mori, Medical Research Council, Mixed methods study. England, Wales, Quant: 14–18 Sept Quant: 2106 people aged 15+; Qual: Total n=69 3 The use of personal health information Qualitative: workshops Scotland and 2006; Qual 29/7- Workshops: General public (n=63) Interviews: in medical research general public and interviews Northern Ireland 5/8 2006 disabled people, and people with chronic consultation. 2007. Quantitative: face-to-face illnesses/or their carers (n=6) survey Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 Page 7 of 25 Study Reference Method Setting DataCollection Sample Quality no. Period Score 38 Ipsos Mori, Macmillan Cancer Support, Quantitative: online England 13 June to 4 July Total n=2,033 Adults who have, or have had 5 Cancer Research UK, Perceptions survey. 2016 cancer (PLWC) (n=1,033) Adults from the general of the Cancer Registry: Attitudes public (n=1,000). All 18+ towards and awareness of cancer data collection. 2016. 39 Ipsos Mori, Wellcome Trust, The Mixed methods study. England, Wales, September to Quant: n = 2017, age 16+; Qual n= 247; 3 one-way mirror: Public attitudes to Quantitative: Scotland and December 2015 Members of the general public, patients, and commercial access to health data. face-to-face survey Northern Ireland ALSPAC cohort members (n=212) GPs and 2016. Qualitative workshops hospital doctors (n=35) 40 Ipsos Mori, Wellcome Trust, Wellcome Quantitative: England, Wales, 2 June to 1 Total n=1,524 Ages: 18+ 5 Trust monitor report wave 3: Tracking questionnaire Scotland and November 2015 public views on science and using face-to-face Northern Ireland biomedical research. 2016. Computer-Assisted Personal Interviewing (CAPI). 41 Luchenski, S.A., et al., Journal of Quantitative: cross West London, Six weeks from 1 Total n=2857, 59.5% female, 40.5% male Ages: 5 Medical Internet Research, 2013. 15(8). sectional, self-completed England August 2011 18–75+ questionnaire survey. 42 Papoutsi, C., et al. BMC Medical Mixed methods study. West London, Between August Quant: n=2761, 59.1% female; Qual: n=160, 4 Informatics and Decision Making, 2015. Quantitative: England 2011 and April Patients (n=114). Health professionals and 15(1): p. 124. questionnaire 2013 researcher total not stated Interviews: Patients survey Qualitative: focus who did not wish to join group discussions (n=6). groups and interviews. 43 Riordan, F., et al., International Journal Quantitative: West London, Six weeks from 1 Total n=3157, 60.4% female, 39.6% male 5 of Medical Informatics, 2015. 84(4): Crosssectional, England August 2011 p. 237–247. self-completed questionnaire survey. 44 Spencer, K., et al., Journal of Medical Qualitative: focus groups Salford, England Not stated Total n=40, 58% female, 43% male, Ages: 23–88 4 Internet Research, 2016. 18(4): p. e66. and interviews. 45 Stevenson, F., et al., Family Practice, Qualitative: focus groups Not stated Not stated Total n=57, Patients (n=50), Staff members (n=7). 4 2013. 30(2): p. 227–232. and interviews Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 Table 2.   Contribution of Studies to  Themes. Study Knowledge and  Willingness to  Privacy Trust De-identification  Routes to  Demographic  Awareness of  Share Data and Consent Securing  Differences Electronic  Trust Records Audrey et al. 2016 X X X Baird et al. 2009 X X X X Barrett et al. 2006 X X X X Buckley et al. 2011 X X X X Campbell et al. 2007 X CM Insight and X X X X X Wellcome Trust 2013 Clerkin et al. 2013 X X X Grant et al. 2013 X X X X Haddow et al. 2011 X X X X Hays & Daker-White X X X X X X Hill et al. 2013 X X X X X X Ipsos Mori, MRC 2007 X X X X X X X Ipsos Mori, MacMillan, X X X X CRUK 2016 Ipsos Mori, Wellcome X X X X X Trust 2016 One Way Mirror Ipsos Mori, Wellcome X Trust 2016 Monitor Report 3 Luchenski et al. 2013 X X Papoutsi et al. 2015 X X X X X Riordan et al. 2015 X X X Spencer et al. 2016 X X X Stevenson et al. 2013 X X X X by GPs were high without giving exact numbers . One quali- Willingness to share tative study reported that across groups, participants had a good In many of the studies, participants expressed willingness to awareness of the kind of information that usually held in general share their EHRs for secondary purposes like research, policy practice records . Nevertheless, participant awareness of specific and planning, despite the range of concerns discussed below. uses of routinely collected patient data was low. For instance, Among the quantitative studies, support for sharing patient data 29 39 30 40 42 two quantitative studies reported that 82% and 80% of the with researchers was reported at 68.7% , 77% , 81.4% , and general public had not heard of the National Cancer Registry, while 83% . In the qualitative studies, participants identified will - another study reported that patients were not only inadequately ingness to share their EHRs for secondary purposes with the 4,27,28,32,37 informed about their right to opt-out of Care.data, but were also “common”, “greater” or “public good” ; “social 44,45 28 unaware of the project . Two studies indicated that understand- responsibility” ; “altruistic attitudes” ; and “giving some- 32,37 33 4,28,34–36,44 ing of medical research using patient data was low , while thing back” to “other people” or “future generations” . another suggested that participants were unaware of how their For example, in one study it was stated: data was currently used . Another demonstrated limited public I’m saying yes because I think there is a greater good. grasp of a range of concepts related to patient information use, (Participant 1, Group 2, ) such as de-identification, data science, the benefits of aggregate data, and the role of private companies in the healthcare system. People with lower understanding of these issues were more likely Such reasoning was largely predicated on the understanding that to have concerns about commercial access to health data . medical research using EHRs could lead to benefits such as the Page 8 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 4,27,28,32,39,42,44 improvement of healthcare services, or innovations in the diagnosis privacy . Privacy was generally conceptualised and treatment of disease. For example: by participants as a process of control: Seemingly radical idea: let PATIENTS control who can access I think if you are going to do something, eczema, allergies, their personal medical data! #caredata. (Twitter user, ) something that affects one in five people you need the huge samples in order to do it. (Patient Interview L2, ) Participants frequently identified two key elements that could be determined in relation to their information. The first was And: whether information is revealed to, or accessed by another party: . . . because you never know where research is going to go. My concern is exactly that: who has access to my files and You don’t know where some brilliant young scientist’s mind how can we make sure that only those I want to have access linking up different things, you know. And you cannot put a would have access? (Focus Group 12, ) halt on that, a break on that. (Di, Focus Group 1, ) A second element concerned how this information should be Moreover, it was also understood that using EHRs might be a used, or analysed after it being revealed to another party: better way of doing and facilitating research: At the end of the day, it’s not who has access to it all, it’s . . . I mean it’s a better system than it is at present, because how they use it, I think is the main concern for us, for you are going to get 100% response that way or near everybody. . . how they use it. (Person with MS, Focus enough and the present system is that the GPs put out things Group 7, ) on spec to people that may want to join this thing and they may get a very low return. (Male, Patient Focus Group 3, ) These two factors were necessary components in identifying what was and was not acceptable when it came to unlocking the From these studies, the “common good” appeared to consist potential of patient data. of the collective public health benefits brought about by the improvement of the services, practices and methods of healthcare Trust through secondary uses of data. Willingness to share appears Views on storing and using patient data were linked to the kind connected to idea of an individual having a personal respon- of trust or distrust the public had in an organisation or individual sibility, obligation or duty to help bring about this common using or accessing the data. good: You have to trust people. (Fiona, Focus Group 2, ) Once you have been in receipt of the excellent kind of care and treatment that I’ve had, I think you have a social Where participants distrusted organisations who would handle responsibility that if you can help the next generation by their data, this generally occurred along two lines: having your information provided to the researchers to [do] 1. Distrust of a party’s ability, or competence, to ensure some good. (Focus Group 3, ) data security. Privacy 2. Distrust of a party’s motivations. Despite the general willingness to share EHRs for second- ary purposes, many qualifying concerns were raised by In terms of a party’s competence, participants were likely to 27,28,32–39,42,44,45 participants . This suggests that although the shar- agree that a particular party could store and use their data in ing of EHRs is largely seen as being for the overall common principle, but were concerned that they are not able to guaran- good, participants believe that it also has the potential to create tee the level of security required by such personal data due to new risks, and increase existing ones. The various perceived risks 36,42 institutional incompetence. One such party was “the NHS” . involved in sharing EHRs were well described by participants. For example, in one study a majority of respondents (71.3%) 35,42 These included routes to harm like hacking , unintentional data voiced doubts about the ability of the NHS to guarantee the 35 42 leakage or loss , unauthorised access , access without explicit security of EHRs, yet 53.5% of those respondents would 27 42 34 consent , errors in medical records , re-identification , 42 nevertheless support the development of a national EHR . On aggregating data to a group’s disadvantage , and access, use the incompetence and inefficiency of the NHS, participants and governance of data by the government . Participants also stated the following things: listed perceived harms as a result of adversaries gaining access I just have very little faith in the way that the NHS handles to data, these included: identity theft , unnecessary stigmatis- databases. I don’t think it’s got a very good record. . . (Focus ing judgements in clinical settings , consequences for employ- Group 3, ) ment, pension eligibility, or insurance costs , social discomfort and community embarrassment , and the use of EHRs for Always thought that [the NHS] would mess it up (Focus financial gain . The breadth of this list demonstrates the structural Group 11, ) complexities of the particular, concrete situations which study #NHSPatientdata scheme handling a ‘masterclass in incompe- participants imagine may arise from the misuse of their data. tence’ #CareData #NHS [link] [link]. (Twitter user, ) Several studies connected these risks and the concept of Page 9 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 However, in some qualitative studies, participants expressed a This dimension was further discussed in the grey literature generalised trust towards the NHS, especially when concerning which revealed a more nuanced picture regarding public opinion GPs: towards the commercial uses of data. Support for commercial access to patient data raised from 54% to 61% when taking I mean I can trust the doctors and all . . . but other people, into account the possibility of new treatments being discovered , no. Once it leaves the NHS, I’d be wondering where it’s and participants were indifferent to who conducts research so going and who’s looking at it. (Participant 19, ) long as the objective is to increase knowledge around the causes and cures of ill health . This suggests that participants recog- . . . once it goes out of the NHS, the NHS have no control nise that not all commercial uses of data are done from purely over it whatsoever. (Di, Focus Group 1, ) privately interested motivations, but that at least in part can involve public motivations too. In explaining the apparent reluctance Nevertheless, and perhaps surprisingly, participants tended to of the public to accept certain private interests so as to ensure say that the data would be safer in the hands of the NHS or a public benefits, one study identified that participants did not public sector organisation, and that private companies were less currently feel that they could evaluate the motivations of com- likely to be as diligent in their handling of it . mercial organisations who would use the data, which created an unclear conception of what the public could stand to gain When it came to an organisation’s motivation, there was a strong through these uses of data. As a result, participants tended to sense that any access and use of the data must be for the good of fall back into wider assumptions, personal beliefs and prejudices the individual patient or the common good of the public. Many regarding private companies . studies indicated that any kind of data handing for private 32–36,42,45 interests would be unacceptable . In terms of the possi- ble consequences, a recurring theme was that if a party had the De-identification and consent preferences wrong competences or motivations, this could lead to substan- In the quantitative studies, 67.5% of respondents in 2011 and tial harm on both an individual or collective societal level. For 91% of respondents in 2015 were clear that although it was instance, as the following quote illustrates, it was identified fine for researchers to access their EHRs, they still expected to that the private profit motivations of insurance and marketing be asked for consent when their identifiable data was accessed companies could lead to harms on an individual level: for secondary purposes. However, there was less consensus 30 31 43 over de-identified data, with 83.7% , 51% , and 49.3% of One of my fears was if it somehow goes astray from there respondents reporting willingness to share or agreement that and somebody, for instance, like insurance companies, get a de-identified patient data could be extracted without consent. hold of it they could use it to their advantage and the patient’s Reasons for concern around de-identification also emerged in disadvantage. (P2, Focus Group, ) the qualitative studies where participants questioned what would qualify as identifying information , whether de-identification However, direct harm to individuals is not a necessary factor in 37,42 could be achieved effectively , whether it was sufficient determining the wrongness of certain motivations. It was also 27,36 for the elimination of consent and highlighted the risks of indicated that even if no particular individual is disadvantaged, 32,35 re-identifying individuals . allowing those with private interests to access public data can constitute a collective harm. This is because there is a strong Several studies also indicated substantial concerns about the sense that data should only be used to benefit either individuals: opt-out rather than opt-in model of consent which was pro- 35,45 posed in schemes such as Care.data , while others noted that Financial gain comes into it then so why should you then let participants generally thought about consent along opt-in lines them look at your records? They are going to gain out of it when asked for their opinions . Participants expressed worries and you’re not. . . (Participant 2, Group 2, ) about whether people would really understand the concept of opting-out . They also criticised opt-out on the basis that it Or, the public at large: was unethical and illegal . However, in one quantitative study If there was a large commercial company. . . [that] had free 52% of the general public supported the opt-out method of and easy access to people’s medical records I don’t think collection for the National Cancer Registry , while a minority of that would be right. It would further their research into the participants in another study acknowledged that opt-out might be particular drug or treatment, but it’d also further their prof- a better option given the impracticalities of opting-in . its that would be wrong. But if it was for medical research for everybody then that would be different. (Participant 6, The problem of selection bias and its connection with Group 3, ) 27,36,42 consent arrangements was explored in three studies . In two studies, some participants identified the potential for bias Despite this firm belief, several of the studies indicated a tension if the information which was gained was neither accurate nor in the status of pharmaceutical companies whose products are 27,42 balanced : indispensable to medicine and the health of populations, but 28,33,36,37,42 which ultimately operate in a profit driven capacity . As  If they’ve got mental health illness then. . . that might affect Grant et al. write, this leads some participants to see the involve- their willingness, so it might be hard to. . . gather enough ment of pharmaceutical companies as a “necessary evil”. information. I think that might be biased. . . (Male ID47, ) Page 10 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 Participants also recognised that larger, more representative more acceptable than any other . However, in the same study, samples could be gained by an opt-out process: participants were significantly less likely to endorse sharing data without any safeguards (49% agreed) compared to with You are going to get 100% response that way, or near enough safeguards (56–64% agreed, depending on the safeguard). This and the present system is that the GPs put out things on suggests that the precise nature of the safeguard may be less spec to people that may want to join this thing and they important to improving willingness to share than knowing that may get a very low return. (Male, Patient focus group 3, ) there are safeguards in place. This prompted discussion in one study about the importance Demographic differences of mitigating the requirement of consent by de-identifying We aimed to ascertain whether the included studies indicated information: a level of heightened concern, worry or fear among one or more specific social groups and we restricted this analysis to quan - There is certain situations where you might be able to, it titative studies which could enable such contrasts. Although might be acceptable to ask or it might be acceptable just to go participants were asked a variety of different questions across ahead and get it—as long as it wasn’t directly linked back to each survey, we evaluated responses on the basis of whether you as a person, it would be alright. . . (Female, ID6, ) they indicated an overall negative or positive attitude towards the In another study , after receiving presentation about selection sharing of EHRs for secondary purposes such as research. For bias, participants recognised the difficulties faced by researchers. example, in Papoutsi et al. , participants were asked if they Interestingly, when asked if this information had changed their would be more worried about the security of their informa- opinion about using health data without consent, several partici- tion if it were part of a national EHR register, while Buckley pants out of the group who at first indicated reluctance, reported et al. asked if they would allow their EHRs to be provided to that they had indeed changed their minds. A quantitative study researchers without their explicit consent. Despite the differ- showed that a substantial minority of respondents (20%) ing approaches of these questions, we concluded that a response believe that consent may not be needed if it is not practical to indicating more worry about security, and one indicating less obtain. likelihood of granting researchers access without explicit consent, were comparative insofar as they represented a negative attitude towards sharing of EHRs. Routes to Securing Trust Across studies, participants identified several different infra - structure arrangements which could increase willingness to share Within quantitative studies, findings were reported across a whole patient data for secondary purposes and trust in their use for range of demographic differences. Between studies, compari- public benefit. Participants indicated that no single organisation son could only be made between age range, levels of education, should be responsible for deciding who could access and use and ethnicity. We found conflicting findings in all three of these their EHRs, rather a committee of stakeholders was called for, categories. We found evidence that both younger people and older including Caldicott Guardians, research consultants, members people would favour sharing their data, that people with lower of the public, GPs, social services staff, charities, funders, levels of education were both more and less likely to agree to 28,34 and patients. . It was also felt that greater transparency was sharing without consent, and that people of non-white ethnicity needed in regards to safeguarding processes and data sharing were both more and less likely to support EHRs and think of 35,44 arrangements , including stiff penalties or fines for misuses them as secure. For a full break down of the demographic results, 35,39 39 of data ; the publication of results ; clear guidelines and laws see Table 3. to regulate access and use of data ; and, regulators and parties accessing data to be held to high standards . Several studies Discussion also indicated that participants wanted a better understanding We found that knowledge of the content and collection of patient about the nature of EHR initiatives, medical research , the data in EHRs was reasonably high, but knowledge about the 33,37 purposes and benefits of using data , de-identification and secondary uses, such as data sharing for research, was low. aggregation , and also why in some situations consent might not Nevertheless, when asked, participants were generally willing to be practical . More generally, participants wanted the security share their data for the “common good”, subject to safeguards. 33,39 39 of records to be ensured ; for private profit to be capped ; and Willingness was qualified with concerns about privacy which denial of third party access . In several studies, participants participants generally equated with the idea of control. This also indicated their preference to retain granular control over conceptualisation of privacy as control closely corresponds the data in their EHR using an explicit opt-in consent scheme, to the idea that informational privacy is the ability of an the right to withdraw at any time and ability to tailor sharing individual to determine for themselves what happens with certain 28,33,35,44 48,49 preferences . information relating to them . This particular definition has attracted criticism insofar as it difficult to capture what Despite the breadth and diversity of participant suggestions constitutes “certain” information . Within the legal and philo- to increase trust, it might be that no single, or any specific sophical literature it is generally accepted that what constitutes combination of strategies will amount to a gold standard of an individual’s determination is whether or not information is acceptability or social licence. One study found that no particu- communicated to other parties, however, our analysis suggests lar safeguard made sharing data with commercial companies any that the public also believes that their privacy can be violated not Page 11 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 Table 3.   Study findings on Demographic Differences. Group Indicative of Negative Attitude Indicative of Positive Attitude Age Compared to those aged 25–34, respondents between Increase in age by each 10 year increment was the ages of 35–64 were more likely to report they would be significantly associated with an increased likelihood of worried about the security of their records as part of a national reporting that any info can be provided to researchers 42 30 EHR . without asking for consent . Compared to those aged 25–34, respondents over 35 years Older people (55–64, 65+) were more likely to find old were more likely to report less confidence in the ability of a drug company conducting research into the NHS security and were less likely to report that EHRs were unwanted side effects of a drug using deidentified equally or more secure than paper records . data to be more acceptable than younger people (16–24, 25–34, 35–44, 45–54) . Older people were increasingly more likely to report that they Those aged 55–64 tended to agree that research would not be in favour of a national EHR compared with should be conducted by commercial organisations 25–34 year olds . if there is a possibility of new treatments being discovered in comparison to 16–24s and 35–44s . In the general public, support for the opt-out collection method was higher in over 55s (58%) than 18–34 (49%) and 35–54s (49%) . Those over 55 were more likely to say to say that they would allow their data to be used for medical research compared to those aged 16–24 . Education Respondents with lower educational qualifications were more Compared with participants with higher degrees, likely to expect to be asked for explicit consent before their individuals with no academic qualifications were less deidentified records were accessed . likely to say that they would worry about security if their record was part of a national EHR . Compared with completion of third level education, completion of only primary level education was associated with increased likelihood of reporting that any info can be provided to researchers without asking for consent . Socioeconomic Those of a lower socioeconomic status were more likely to be Those in the lower socioeconomic group DE (43%) Status concerned about privacy . were more likely to support companies using health data collected in the NHS to help target health products at different groups of people . Those in socioeconomic groups C2 and DE were less likely than those in AB and C1 to view the use of health data as having a potential benefit to society . Those in the lower socioeconomic group DE were less likely to say they trusted a variety of people with their health data; say that the advantages outweigh the disadvantages of using health data in research; and say that researcher can use data without prior consent than Abs . Those in socioeconomic groups C1 and C2 were less likely than ABs to allow their health data to be used . Those in socioeconomic groups DE (46%) were less likely Those in socioeconomic groups DE (26%) were to support commercial organisations to undertaking health less likely to support commercial organisations to research with health data than AB (62%) . undertaking health research with health data than AB (30%) . Ethnicity Black British respondents were more likely to say they would Compared with White British groups White non-British, not support the development of a national EHR system Asian, British Asian, Black-African, Caribbean, and compared with White British respondents . British Black groups were more likely to say that EHRs are as secure, or more secure that paper records . Respondents identifying as belonging to an ethnic group other than White British were more likely to expect to be asked for explicit consent before their deidentified records were accessed . Those whose ethnicity was not White British were more likely to be concerned about the invasion of privacy . Page 12 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 just in the sharing of their information, but in the subsequent use of data usage, and for expressing the concept of public opinion and that information too (e.g. using personal information for profit). attitudes. We cast a wide net and spent time excluding papers, and believe this review encompasses all available research meeting our criteria up until the search was conducted. Our Participants feared adverse outcomes less when they trusted both findings were deliberately limited to UK and the Republic of the motivation of research organisations to conduct research Ireland to create a manageable, relevant and comparable body of for the common good, and the competence of organisations to literature. This enabled us to look for underlying principles for handle the data safely and without compromise. When evaluat- publics exposed to a particular type of healthcare system, but ing opinions on consent mechanisms, findings suggested that findings are obviously only applicable within these contexts. educational and deliberative research into public opinion may There may also have been differences between UK and Irish provide different answers from snapshot surveys. This is because respondents due to differences in these healthcare systems. Both after weighing up a range of issues involved, participants could systems have a general practice plus hospital system. However, often see the benefit to research quality of opt-out schemes. Results in the UK, all GP and hospital visits are free at the point of use, suggested a range of mechanisms to increase public trust, and whereas in Ireland, around two thirds of the population must the overarching theme here was transparency of motivation, data pay a fee for GP or hospital care. This financial transaction may handling and data flow. influence how patients perceive ownership and use of their medical data, although we found no literature on this. Core Ethical Principles The foundational moral principles which Beauchamp and Synthesis of results was also challenging as there was a wide Childress identify as paramount to governing biomedical range of study types, using different methods. The small, practice, and which Belmont identified as important for medical convenience samples and low response rates in the majority of research can be used as a lens for understanding and interpret- studies is also likely to have introduced bias into the findings, ing these findings. Where we find that public reasoning maps to as it is probable that only members of the public most interested these basic principles, it can be inferred that these core ethical in the issues consented to take part in the research. This means principles are a constituent part of non-specialist thinking that each study likely represents a narrow range of views, and about the ethical practicalities of healthcare and medicine. This views expressed may have been influenced by the means of data in turn identifies these ethical principles as a suitable structure for collection. It is not clear how this might have affected results guiding reasoning on future data sharing challenges. across the whole range of studies, but it is likely that the themes and views represented here are not a complete picture of the For instance, the included studies indicate that there is a wide- public’s opinions. This may have contributed to the inability spread willingness to share EHRs for secondary purposes, in to find systematic differences in views between demographic principle. This willingness was held on the basis that, using and groups. Additionally, certain research questions of particular accessing data in such a way can bring about benefits which interest were not asked of participants and therefore our under- are in the interests of all individuals, or in other words, the standing of public opinion is still limited. One example of this is “common good”. The basis of this belief may be the general whether the use of medical text (in contrast to structured data expectation that if members of the public can contribute to the in medical records) elicits specific privacy concerns for the welfare of each other by sharing data, then they feel a moral public. obligation to do so. We could reinterpret this as the principle of beneficence, which urges us to act, where we can, to promote Our analysis was informed and influenced by our respective good. backgrounds in philosophy, psychology and epidemiology. While attempting to be data-led, we must acknowledge that we Willingness to share data rarely led to unqualified support of may not have been wholly neutral in approach. However, our the schemes designed to enable secondary use. Support was review highlights similar themes to Aitken et al. , suggesting a withheld because, in practice, it was felt that key values would consistency with other syntheses in this area. not, or could not, be ensured, thus bringing with it the risk of individual and collective harm. The public might feel justified Future directions in objecting to irresponsible, or insecure use of data because This review demonstrates and makes explicit the extent to which it is likely to cause individual harm; a direct violation of the public attitudes to sharing health data are based on reasoning principle of non-maleficence. Similarly, the use of data for in line with established bioethics principles. Decision makers, private gain may be said to be in violation of the principle of who evaluate data-sharing proposals can therefore draw on an justice because it is generally unfair to exploit something for explicit framework of ethical principles to address challenges reasons other than what it was intended for. Finally, the use of around the sharing of patient data. It is becoming increasingly patient data without transparency or consent may be seen to accepted that the use of patient data for research or for the violate the principle of respect for autonomy. development of novel healthcare technologies should be sup- ported by a social licence to operate . According to social licence Strengths and limitations theory, the public expect that organisations who are institut- We conducted a wide search and sifted a huge number of papers, ing potentially controversial schemes (such as patient data shar- including grey literature reports. The search was challenging due ing) will go beyond the requirements of formal regulation and to wide range of terms used within the literature for secondary Page 13 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 adhere to voluntary codes of trustworthy behaviour . Where the that the public and patients benefit from the data usage as well public are satisfied that the motivations of the organisation are as the company. Benefits which come from patient data research trustworthy, they confer a “social licence” to operate. It has been should additionally be publicised and communicated, so that hypothesised that previous patient data-sharing initiatives, such these common gains become part of the public consciousness. as Care.data, have failed to secure public support because they Examples of good practice in this sphere can be seen in the UK 9 56 lacked a social licence for their operation . Farr Institute and the Wellcome Trust Initiative “Understanding Patient Data” . Public views are complex, and interpreting them to guide policy 4. Could granting access to the data, or granting a can be difficult. A simple and explicit framework may act as a particular use of the data, lead to individual or collective focussing lens, reducing complexity by pulling out underpinning harm? (Non-maleficence) moral principles in participants’ views. Establishing core values held by the public may facilitate identification of the types of Participants in the studies we reviewed articulated a range of safeguards which could help to secure a social licence for harms that they fear could arise from re-use of patient data. sharing patient data. We make recommendations about how pub- Possible risks may include individual harms, such as re-iden- lic views could fit into the four tenets of the Beauchamp and tification and discrimination from insurance companies or Childress framework, and could be used to guide decision mak- government agencies. However, ethical bodies and regulators ers or regulators. We phrase these suggestions as guiding should also consider the risk of collective harms from pursuing questions, which could be asked of research proposals by ethics certain research agendas. For example, failure to achieve fair- committees and regulators. ness or transparency in data-sharing agreements may result in 1. Do the methods of data collection and usage in the a loss of public trust in the endeavours of research, or in public proposal respect individual patient autonomy? (Respect institutions’ policies on keeping data safe. Such a loss of pub- for Autonomy) lic trust would put at risk any gains made in securing a social licence for sharing patient data. In addition, infrastructure put in place to safeguard patient privacy must be made transparent to Patient autonomy can only be achieved if inclusion of stakehold- stakeholders to increase trustworthiness. These may include ers and transparency of motivation and data flows are assured at high standards for data storage security, restrictions on data all parts of the research process, from study design, through linkage where necessary, evaluation of analytical methods, and ethics approvals, to analysis and interpretation of results . It is consistently applied sanctions for any breaches in data security. also essential that individuals have the possibility to opt-out of any data collecting schemes. Notably, the opt-out is only a meaningful way of ensuring individual autonomy if transpar- Conclusions ency of data usage, and stakeholder inclusion, is guaranteed. This Our interpretation of a range of studies of public views combination (opt-out plus full transparency) is also the pub- suggests that the public generally support the use of patient data 53,54 lic’s preferred approach , and is thus vital for maximising for research purposes. However, the public demand that projects public trust, and securing a social licence, for any initiative. One of this nature are conducted in a secure way to prioritise privacy, example of operationalising a transparent patient opt out was and minimise individual and collective harm; that projects set launched by the NHS in the UK in May 2018. Known as the research objectives (or negotiate agreements with third parties) National Data Opt-Out , it was originally recommended and which are primarily concerned with contributing to the common designed by the UK National Data Guardian’s Office. good; and that they do this in a spirit of transparency and inclu- sivity of stakeholder views. So long as these values are main- 2. Are the objectives and the intended outputs primarily tained, it is likely that the majority of the public will willingly concerned with contributing to the public good? Do they share their patient data for research purposes. have clear scientific value? (Beneficence) 3. Is any agreement between the NHS and organisations We have shown that public thinking about the privacy issues providing analytics (private or public) fair and just? around sharing patient data for research maps onto established (Justice) biomedical ethical principles, and such understanding may help researchers or regulators to identify how the public comes to confer a social licence on patient data research. These core One almost universal finding was that the public generally principles can be developed to frame guidance for data custo- support research using patient data if the research is for the com- dians, regulators and researchers when planning or approving mon or public good. They tend not to support research using research projects using patient data. patient data which enables private companies to increase profits. Thus, to retain a social licence, ethical bodies and regulators must evaluate proposals on the basis of their intended aims and whether they contribute significantly towards the common good. The engagement of industry and private companies to Grant information provide data analytics will be crucial to maximise benefits from This work was supported by the Wellcome Trust [202133]. patient data in the future. Where private companies are involved, there should be clear and transparent communication to all The funders had no role in study design, data collection and stakeholders about how a fair settlement has been negotiated, so analysis, decision to publish, or preparation of the manuscript. Page 14 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 Supplementary material Supplementary File 1: PRISMA checklist. Click here to access the data. Supplementary File 2: PRISMA flowchart, showing the number of records identified, included and excluded. Click here to access the data References 1. Academy of Medical Sciences: Personal data for public good:  using health  pilot Mixed Methods Appraisal  Tool (MMAT) for systematic mixed studies  information in medical research . London, UK: Academy of Medical Sciences; review. Int J Nurs Stud. 2012; 49(1): 47–53. 2006. PubMed Abstract   Publisher Full  Text  Reference Sourc e 19. Smith J, Firth J: Qualitative data analysis:  the framework approach. Nurse Res. 2. Kim KK, Joseph JG, Ohno-Machado L: Comparison of consumers’  views on  2011; 18(2): 52–62. electronic data sharing for healthcare and research. J Am Med Inform Assoc. PubMed Abstract   Publisher Full  Text  2015; 22(4): 821–30. 20. Braun V, Clarke V: Using thematic analysis in psychology. Qual Res Psychol. PubMed Abstract   Publisher Full  Text  Free Full  Text  | | 2006; 3(2): 77–101. 3. Botkin JR, Rothwell E, Anderson R, et al.: Public attitudes regarding the use of  Publisher Full  Text  electronic health information and residual clinical tissues for research. 21. Dixon-Woods M, Cavers D, Agarwal S, et al.: Conducting a critical interpretive  J Community Genet. 2014; 5(3): 205–13. synthesis of the literature on access to healthcare by vulnerable groups. BMC PubMed Abstract   Publisher Full  Text  Free Full  Text  | | Med Res Methodol. 2006; 6: 35. 4. Clerkin P, Buckley BS, Murphy AW, et al.: Patients’ views about the use of  PubMed Abstract   Publisher Full  Text  Free Full  Text  | | their personal information from general practice medical records in health  22. Thomas J, Harden A: Methods  for  the  thematic  synthesis  of  qualitative  research  research: a qualitative study in Ireland. Fam Pract. 2013; 30(1): 105–12. in systematic reviews. BMC Med Res Methodol. 2008; 8: 45. PubMed Abstract   Publisher Full  Text  | PubMed Abstract   Publisher Full  Text  Free Full  Text  | | 5. Grande D, Mitra N, Shah A, et al.: Public preferences about secondary uses  23. Noblit G, Hare R: Meta-ethnography: synthesizing qualitative studies. Thousand of electronic health information. JAMA Intern Med. 2013; 173(19): 1798–806. Oaks, US: Sage Publications; 1988. PubMed Abstract   Publisher Full  Text  Free Full  Text  | | Publisher Full  Text 6. Teschke K, Marino S, Chu R, et al.: Public opinions about participating in health  24. Nebeker C, Harlow J, Espinoza Giacinto R, et al.: Ethical and regulatory  research. Can J Public Health. 2010; 101(2): 159–64. challenges of research using pervasive sensing and other emerging  PubMed Abstract   Publisher Full  Text  | technologies: IRB perspectives. AJOB Empir Bioeth. 2017; 8(4): 266–276. 7. Weitzman ER, Kaci L, Mandl KD: Sharing medical data for health research:  the  PubMed Abstract   Publisher Full  Text  early personal health record experience. J Med Internet Res. 2010; 12(2): e14. 25. Clouser KD, Gert B: A critique of principlism. J Med Philos. 1990; 15(2): 219–36. PubMed Abstract   Publisher Full  Text  Free Full  Text  | | PubMed Abstract   Publisher Full  Text  8. NHS England: NHS England sets out the next steps of public awareness about  26. Huxtable R: For  and  against  the  four  principles  of  biomedical  ethics. Clin Ethics. Care.Data. 2013, [cited 2017 6th September]. 2013; 8(2–3): 39–43. Reference Sourc e Publisher Full  Text  9. Carter P, Laurie GT, Dixon-Woods M: The social licence for research:  why  Care. 27. Audrey S, Brown L, Campbell R, et al.: Young people’s views about consenting  Data ran into trouble. J Med Ethics. 2015; 41(5): 404–9. to data linkage:  findings from the PEARL qualitative study. BMC Med Res PubMed Abstract   Publisher Full  Text  Free Full  Text  | | Methodol. 2016; 16: 34. 10. Ramesh R: £140 could buy private firms data on NHS patients . The Guardian; PubMed Abstract   Publisher Full  Text  Free Full  Text  | | 2013, [cited 2017 26th September]. 28. Baird W, Jackson R, Ford H, et al.: Holding personal information in a disease- Reference Sourc e specific register:  the perspectives of people with multiple sclerosis and  11. GPRD and research - An overview for researchers. UK Research and Innovation. professionals on consent and access. J Med Ethics. 2009; 35(2): 92–6. 2018; [cited 2018 18th November]. PubMed Abstract   Publisher Full  Text  Reference Sourc e 29. Barrett G, Cassell JA, Peacock JL, et al.: National survey of British public’s  12. Jones KH, Laurie G, Stevens L, et al.: The other side of the coin:  Harm due to  views on use of identifiable medical data by the National Cancer Registry. the non-use of health-related data. Int J Med Inform. 2017; 97: 43–51. BMJ. 2006; 332(7549): 1068–72. PubMed Abstract   Publisher Full  Text  PubMed Abstract   Publisher Full  Text  Free Full  Text  | | | 13. Aitken M, de St Jorre J, Pagliari C, et al.: Public responses to the sharing  30. Buckley BS, Murphy AW, MacFarlane AE: Public attitudes to the use in research  and linkage of health data for research purposes:  a systematic review and  of personal health information from general practitioners’  records:  a survey of  thematic synthesis of qualitative studies. BMC Med Ethics. 2016; 17(1): 73. the Irish general public. J Med Ethics. 2011; 37(1): 50–5. PubMed Abstract   Publisher Full  Text  Free Full  Text  PubMed Abstract   Publisher Full  Text  | | | 14. Beauchamp T, Childress J: Principles of biomedical ethics . 6th ed, 2013 ed. New 31. Campbell B, Thomson H, Slater J, et al.: Extracting information from hospital  York, US: Oxford University Press; 1979. records: what patients think about consent. Qual Saf Health Care. 2007; 16(6): Reference Sourc e 404–8. PubMed Abstract   Publisher Full  Text  Free Full  Text  | | 15. The Belmont report . Washington, US: National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research, Department of Health, 32. Summary report of qualitative research into public attitudes to personal data  Education and Welfare (DHEW); 1978. and linking personal data. CM Insight, Wellcome Trust; 2013. Reference Sourc e Reference Sourc e 16. Dittrich D, Kenneally E: The menlo report:  Ethical principles guiding information  33. Grant A, Ure J, Nicolson DJ, et al.: Acceptability and perceived barriers and  and communication technology research . U.S. Department of Homeland facilitators to creating a national research register to enable  ‘direct to patient’   Security; 2012. enrolment into research:  the Scottish Health Research Register (SHARE). BMC Reference Sourc e Health Serv Res. 2013; 13: 422. PubMed Abstract   Publisher Full  Text  Free Full  Text  17. Moher D, Liberati A, Tetzlaff J, et al.: Preferred reporting items for systematic  | | reviews and meta-analyses:   The PRISMA statement. Ann Intern Med. 2009; 34. Haddow G, Bruce A, Sathanandam S, et al.: ‘Nothing is really safe’:  a focus  151(4): 264–9. group study on the processes of anonymizing and sharing of health data for  PubMed Abstract   Publisher Full  Text  research purposes. J Eval Clin Pract. 2011; 17(6): 1140–6. PubMed Abstract   Publisher Full  Text  18. Pace R, Pluye P, Bartlett G, et al.: Testing the reliability and efficiency of the  Page 15 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 35. Hays R, Daker-White G: The Care.data consensus? A qualitative analysis of  45. Stevenson F, Lloyd N, Harrington L, et al.: Use of electronic patient records for  opinions expressed on  Twitter. BMC Public Health. 2015; 15(1): 838. research:  Views of patients and staff in general practice. Fam Pract. 2013; PubMed Abstract   Publisher Full  Text  Free Full  Text  30(2): 227–32. | | PubMed Abstract   Publisher Full  Text  36. Hill EM, Turner EL, Martin RM, et al.: “Let’s get the best quality research we  | can”: public awareness and acceptance of consent to use existing data in  46. Robinson G, Dolk H: Public attitudes to data sharing in Northern Ireland . health research:  a systematic review and qualitative study. BMC Med Res Administrative Data Research Centre, Northern Ireland, 2016. Methodol. 2013; 13(1): 72. Reference Sourc e PubMed Abstract   Publisher Full  Text  Free Full  Text  | | 47. Stevenson F: The use of electronic patient records for medical research:   37. The use of personal health information in medical research general public  conflicts and contradictions. BMC Health Serv Res. 2015; 15(1): 124. consultation. Ipsos Mori, Medical Research Council; 2007. PubMed Abstract   Publisher Full  Text  Free Full  Text  | | Reference Sourc e 48. Westin A: Privacy and freedom . New York, US: Atheneum; 1967. 38. Perceptions of the Cancer Registry:  Attitudes towards and awareness of  Reference Sourc e cancer data collection. Ipsos Mori, Macmillan, Cancer Support Cancer Research 49. Parent WA: Privacy, morality,  and the law. Philosophy & Public Affairs. 1983; UK; 2016. 12(4): 269–88. Reference Sourc e Reference Sourc e 39. The one-way mirror:  public attitudes to commercial access to health data. 50. DeCew J: In pursuit of privacy:  Law,  ethics,  and the rise of technology . Ithaca, Ipsos Mori, Wellcome Trust; 2016. US: Cornell University Press; 1997. Reference Sourc e Reference Sourc e 40. Wellcome  Trust monitor report wave 3:   Tracking public views on science and  51. Gunningham N, Kagan R, Thornton D: Social license and environmental  biomedical research. Ipsos Mori, Wellcome Trust; 2016. protection:  Why businesses go beyond compliance. Law & Soc Inquiry. 2004; Reference Sourc e 29(2): 307–41. 41. Luchenski SA, Reed JE, Marston C, et al.: Patient and public views on electronic  Publisher Full  Text  health records and their uses in the United Kingdom:  cross-sectional survey. 52. Ford E, Boyd A, Bowles J: Our data,  our society,  our health:  A vision for  J Med Internet Res. 2013; 15(8): e160. inclusive and transparent health data science.  A position statement . submitted. PubMed Abstract   Publisher Full  Text  Free Full  Text  | | 53. Tully MP, Bozentko K, Clement S, et al.: Investigating the Extent to  Which  42. Papoutsi C, Reed JE, Marston C, et al.: Patient and public views about the  Patients  Should  Control  Access  to  Patient  Records  for  Research:  A  Deliberative  security and privacy of Electronic Health Records (EHRs) in the UK:  results  Process  Using  Citizens’  Juries. J Med Internet Res. 2018; 20(3): e112. from a mixed methods study. BMC Med Inform Decis Mak. 2015; 15(1): 86. PubMed Abstract   Publisher Full  Text  Free Full  Text  | | PubMed Abstract   Publisher Full  Text  Free Full  Text  | | 54. Ford E, Oswald M, Hassan L: Should free text data in electronic patient records  43. Riordan F, Papoutsi C, Reed JE, et al.: Patient and public attitudes towards  be shared for research? A citizens’  jury study . submitted. informed consent models and levels of awareness of Electronic Health  55. National  data  opt-out  programme: NHS  Digital. 2018; [cited 2018 18th November]. Records in the UK. Int J Med Inform. 2015; 84(4): 237–47. Reference Sourc e PubMed Abstract   Publisher Full  Text  Free Full  Text  | | 56. Annual  report  2016-2017. The Farr Institute of Health Informatics Research. 2017. 44. Spencer K, Sanders C, Whitley EA, et al.: Patient Perspectives on Sharing  Reference Sourc e Anonymized Personal Health Data Using a Digital System for Dynamic  57. Understanding Patient Data launches today. Wellcome Trust. 2017; [cited 2018 Consent and Research Feedback:  A Qualitative Study. J Med Internet Res. 18th November]. 2016; 18(4): e66. Reference Sourc e PubMed Abstract   Publisher Full  Text  Free Full  Text  | | Page 16 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 Open Peer Review Current Referee Status: Version 2 Referee Report 04 March 2019 https://doi.org/10.21956/wellcomeopenres.16368.r34595 Chrysanthi Papoutsi  Department of Primary Care Health Sciences, University of Oxford, Oxford, UK No further comments - the authors have done an excellent job in addressing issues raised previously. Competing Interests: No competing interests were disclosed. I have read this submission. I believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Referee Report 18 February 2019 https://doi.org/10.21956/wellcomeopenres.16368.r34596 Sarah Cunningham-Burley    Usher Institute, Edinburgh Medical School, University of Edinburgh, Edinburgh, UK The authors have made careful revisions.  The paper is clearer and more cogently argued. The review will be useful to all those engaged in research with patient medical data and its governance:  the challenge now is the extension to health-relevant data and to understand and benefit from diverse approaches within the UK devolved administrations, particularly Scotland with its Data Linkage Strategy. Competing Interests: No competing interests were disclosed. Reviewer Expertise: Sociology of health and illness, public engagement in health research and medical technologies I have read this submission. I believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Version 1 Referee Report 12 February 2018 https://doi.org/10.21956/wellcomeopenres.14693.r29910 Page 17 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 Chrysanthi Papoutsi  Department of Primary Care Health Sciences, University of Oxford, Oxford, UK This paper on public opinions about the use of patient data provides a comprehensive overview of relevant studies. The synthesis covers significant ground in drawing together findings from a mix of study designs. Despite long-standing debates in this area, the topic continues to be of importance for policy and practice. Please see some suggestions for improvement below. Perhaps revise some of the full quotes provided in the introduction so that the text flows better. Can you please elaborate on how this review differs from existing systematic reviews on this topic and its contribution to knowledge? The paper follows systematic processes for literature searching and screening. The approach to analysing the data has been methodical. More explanation is needed on whether the paper has followed any established approaches for systematically reviewing mixed methods, secondary data (e.g. see 1 2 Dixon-Woods et al. (2005)  or Thomas and Harden (2008) ) and if not, why not. Could you please provide more details on the following: ‘we undertook a deeper analysis of meaning within findings guided 20 9 by both metasynthesis principles  and established principles of bioethics ’. Please elaborate on the application of the Mixed Methods Appraisal Tool (MMAT) for assessing quality across different study designs. The findings section draws heavily on qualitative data, however, these studies tend to be ranked lower in terms of ‘quality’ – are studies being prioritised based on a hierarchy of evidence or are they judged based on the merit of each study design, and what does this mean for the topic studied here? How has the study using Twitter data been assessed for quality and inclusion (e.g. is it clear whether participants are from the UK or Ireland for example)? Please revise the PRISMA diagram to clarify which studies were only quantitative, which were only qualitative and which were mixed methods (these numbers are provided correctly in the text). It is difficult to interpret syntheses of results presented as a list of percentages e.g. ‘Among the 36 35 quantitative studies, public support for a national EHR system was reported at 62.5% , 62.47% , and 23 32 81% , while support for sharing information in general was reported 73% .’ What do the authors mean by national EHR system, what does ‘public support mean’, what does ‘sharing information’ mean and what do these percentages refer to? Of course these terms are artifacts of the studies reviewed here but it would be helpful to provide more context for the reader who has not seen the original studies, when presenting percentages across the document. There are differences in the healthcare and EHR systems across the UK and Ireland – it would be worth reflecting on this when synthesising results from different studies. Academic literature on privacy may help clarify some of the nuances around control and self-determination (e.g. when it is mentioned that ‘Privacy was widely conceptualised as a process whereby an individual determines for themselves what happens with the information relating to them.’) Further use of background literature and theory could inform the analysis. It would be useful to elaborate on the use of the Beauchamp and Childress framework. Are there any pre-existing applications of this framework to study patient attitudes? How do the nine questions used for data analysis fit with the Beauchamp and Childress framework? Was the framework used as part of the analysis or as a lens to discuss the findings? If the latter, more extensive and critical discussion is needed Page 18 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 analysis or as a lens to discuss the findings? If the latter, more extensive and critical discussion is needed – perhaps reflecting on how normative ethical frameworks can encompass the messiness of everyday reality and practice. The paper mentions contradictions between studies based on demographic characteristics. It would be useful to reflect on why these differences may have occurred and how qualitative data could help explain them. The future directions section needs further development – this links back to the use of the Beauchamp and Childress framework. The authors present 4 questions for policy and practice but may need to further clarify how these would be used, how some of the terms need to be understood (e.g. what constitutes patient autonomy is in itself a challenging topic of philosophical contention) and whether the answer to these 4 questions could ever be straightforward in practice. References 1. Dixon-Woods M, Agarwal S, Jones D, Young B, Sutton A: Synthesising qualitative and quantitative evidence: A review of possible methods. Journal of Health Services Research & Policy. 2005; 10 (1): 45-53 Publisher Full Text  2. Thomas J, Harden A: Methods for the thematic synthesis of qualitative research in systematic reviews. BMC Med Res Methodol. 2008; 8: 45 PubMed Abstract | Publisher Full Text  Are the rationale for, and objectives of, the Systematic Review clearly stated? Yes Are sufficient details of the methods and analysis provided to allow replication by others? Yes Is the statistical analysis and its interpretation appropriate? Not applicable Are the conclusions drawn adequately supported by the results presented in the review? Yes Competing Interests: No competing interests were disclosed. I have read this submission. I believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. Author Response 04 Jan 2019 Elizabeth Ford, Brighton and Sussex Medical School, UK We would like to thank you for these very helpful comments, which have enabled us to substantially improve the paper. We spent a lot of time discussing these insightful comments in order to best make improvements to the manuscript. We detail point by point below how we have addressed each comment. We have highlighted our changes in our revised manuscript in red font. 1) Perhaps revise some of the full quotes provided in the introduction so that the text flows better. Page 19 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 flows better. We have completely updated the paragraph with the quotes, to reflect new changes in the law due to GDPR. No quotes are included in the new paragraph (page 3).  2) Can you please elaborate on how this review differs from existing systematic reviews on this topic and its contribution to knowledge? We have added a new section on this on page 4 in the “Striking a balance” paragraph. We have described how by using a well-recognized ethical framework we can draw underlying themes from the results which may help to organize policy. 3) More explanation is needed on whether the paper has followed any established approaches for systematically reviewing mixed methods, secondary data (e.g. see Dixon-Woods et al. (2005) or Thomas and Harden (2008)) and if not, why not. Could you please provide more details on the following: ‘we undertook a deeper analysis of meaning within findings guided by both metasynthesis principles and established principles of bioethics’. We have included a new section on data synthesis in the methods section page 6, outlining how we used a thematic analysis to interpret the data (a method recommended by both Dixon-Woods et al. and Thomas and Harden). We have extended this section to explain how the Beauchamp and Childress framework informed our analysis. 4) Please elaborate on the application of the Mixed Methods Appraisal Tool (MMAT) for assessing quality across different study designs. The findings section draws heavily on qualitative data, however, these studies tend to be ranked lower in terms of ‘quality’ – are studies being prioritised based on a hierarchy of evidence or are they judged based on the merit of each study design, and what does this mean for the topic studied here? How has the study using Twitter data been assessed for quality and inclusion (e.g. is it clear whether participants are from the UK or Ireland for example)? We treated insights from qualitative and quantitative studies as having different roles but equal value in our enquiry, and therefore if they met MMAT criteria we did not further differentiate between methodologies in terms of a hierarchy. We have explained this on page 6. 5) Please revise the PRISMA diagram to clarify which studies were only quantitative, which were only qualitative and which were mixed methods (these numbers are provided correctly in the text).  We have revised the PRISMA diagram as requested (supplementary file 2) 6) It is difficult to interpret syntheses of results presented as a list of percentages e.g. ‘Among the quantitative studies, public support for a national EHR system was reported at 36 35 23 62.5% , 62.47% , and 81% , while support for sharing information in general was reported 73% .’ We revised the reporting of results in this section, because, when we considered its value within the paper, we found the sentence that the reviewer referred to did not answer any of the outlined research objectives. We now only present evidence on participants’ willingness to share their patient data for research in this section. 7) There are differences in the healthcare and EHR systems across the UK and Ireland – it would be worth reflecting on this when synthesising results from different studies. We have added a paragraph reflecting on the differences in the two systems and how this could influence results. Page 24. Page 20 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 influence results. Page 24. 8) Academic literature on privacy may help clarify some of the nuances around control and self-determination (e.g. when it is mentioned that ‘Privacy was widely conceptualised as a process whereby an individual determines for themselves what happens with the information relating to them.’) Further use of background literature and theory could inform the analysis. We have added a paragraph in the discussion on pages 22-23, to describe further literature on the nuances around the conceptualisation of privacy. 9) It would be useful to elaborate on the use of the Beauchamp and Childress framework. Are there any pre-existing applications of this framework to study patient attitudes? We reference the Beauchamp and Childress framework, but note its similarity to other ethical principles such as Belmont. While we have not found such basic principles applied to study patient attitudes (now explained on page 6), we have found them applied to information technology research (Menlo report, now described and referenced, page 4). We used this simple framework to cast a lens on the findings of our review, as a way of sorting and filtering through the complexity of public opinions. A stable and concise framework might enable policy makers and regulators to more efficiently apply stakeholder views to their decision making, thus facilitating securing a social license for research. 10) How do the nine questions used for data analysis fit with the Beauchamp and Childress framework? The nine questions for the data analysis were driven by the problem of data sharing for health research as it manifested itself, rather than our interpretation of the problem through the Beauchamp and Childress framework. They represent the first iteration of our search for themes within the data. We have made this clearer on page 6. Our assimilation of the results was data-driven, and Beauchamp and Childress only used to add the highest levels of interpretation. 11) Was the framework used as part of the analysis or as a lens to discuss the findings? If the latter, more extensive and critical discussion is needed – perhaps reflecting on how normative ethical frameworks can encompass the messiness of everyday reality and practice. We have provided much more clarity on our use of this framework, on page 4. We say: “We use these widely accepted principles as a tool to identify patient reasoning in the analysis, and additionally as a lens to discuss the findings in terms of the newly adopted social license theory for patient data research. Identifying a framework which describes the core moral or ethical values underlying public views may help us to understand approaches to sharing patient data for research that the public will deem as acceptable, and help us to predict the reaction of the public to new data sharing challenges in the future.” 12) The paper mentions contradictions between studies based on demographic characteristics. It would be useful to reflect on why these differences may have occurred and how qualitative data could help explain them. In our investigation of differences in views by demographic characteristics, we did not find any replicable trends across quantitative studies. This may be because quantitative studies were limited in their ability to rigorously identify differences, or because such difference do not exist. Therefore we cannot speculate on reasons for differences, because we have not got any firm evidence that these differences exist. We have added a sentence on this to the discussion. Page Page 21 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 13) The future directions section needs further development – this links back to the use of the Beauchamp and Childress framework. The authors present 4 questions for policy and practice but may need to further clarify how these would be used, how some of the terms need to be understood (e.g. what constitutes patient autonomy is in itself a challenging topic of philosophical contention) and whether the answer to these 4 questions could ever be straightforward in practice. Many thanks for these suggestions. We have substantially re-written this section.  Competing Interests: No competing interests were disclosed. Referee Report 30 January 2018 https://doi.org/10.21956/wellcomeopenres.14693.r29907 Sarah Cunningham-Burley    Usher Institute, Edinburgh Medical School, University of Edinburgh, Edinburgh, UK On the whole this is a clearly presented systematic review (a copy edit is required as there are a few typos) and it reinforces the findings of a similar systematic review that I am co-author on, as the authors note in their conclusion. However, this review included quantitative studies and focused only on UK and Ireland, so the articles included do not fully overlap - the reviews were different in scope. So this is an additional contribution to the literature on public attitudes to data linkage and sharing for health research.  The process of the systematic review is delineated well and there is sufficient information on each included article for the reader to be able to access these and also to relate the findings of the review to those articles.  The authors also cite some other relevant literature not included in the review. The authors are appropriately cautious in their interpretation of the findings from various studies, as these are often small scale, limited response rates etc.  I have a few concerns about the paper. The authors do not seem to be aware of existing governance structures, carefully developed alongside research on public attidues and legal and ethical analyses. Health is a devolved matter in the UK. They need to read and make reference to the Scottish Government’s Data Linkage Framework (http://www.gov.scot/Topics/Statistics/datalinkageframework), the Guiding Principles for Data Linkage, and the terms of reference for the Public Benefits and Privacy Panel for Health and Social Care. Perhaps also look at the FARR Institute website to see how this major initiative is promoting safe use of health data for research purposes. There are some key reports that have not been identified by their search that are highly relevant: Public Acceptability of Cross-Sectoral Data Linkage (http://www.gov.scot/Publications/2012/08/9455); Public acceptability of data sharing between public, private and third sectors for research purposes (http://www.gov.scot/resource/0043/00435458.pdf ); Aitken et al (2011) . These would all help the authors craft more apposite recommendations.  A few other points – while supportive of an approach that identifies core principles, I’m not sure that Beauchamp and Childress’ four principles for biomedical research translate as easily as they suggest. I think some reference to emergent frameworks that speak to a social licence might be more compelling and the core principles that might underpin such a license. Public health ethics might help here.  Page 22 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 and the core principles that might underpin such a license. Public health ethics might help here.  A more minor point – the authors start by referring the medical data but really they are focussed on health data – a broader term. I also wonder why they use the term public opinion instead of attitudes. It may be that these terms are used differently in quantitative and qualitative research perhaps, but some justification would be helpful. During the presentation of the findings of the review, they also refer to GP records, the Electronic Health Record, Cancer Registries – maybe clarify what type of records the studies they are referring to – or use the overarching term of EHR. The authors touch on the differences in the way in which public’s views are accessed and I think that point bears further elaboration. References 1. Aitken M, Cunningham-Burley S, Pagliari C: Moving from trust to trustworthiness: Experiences of public engagement in the Scottish Health Informatics Programme.Sci Public Policy. 2016; 43 (5): 713-723  PubMed Abstract | Publisher Full Text  Are the rationale for, and objectives of, the Systematic Review clearly stated? Yes Are sufficient details of the methods and analysis provided to allow replication by others? Yes Is the statistical analysis and its interpretation appropriate? Not applicable Are the conclusions drawn adequately supported by the results presented in the review? Yes Competing Interests: No competing interests were disclosed. Reviewer Expertise: Sociology of health and illness, public engagement in health research and medical technologies I have read this submission. I believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. Author Response 04 Jan 2019 Elizabeth Ford, Brighton and Sussex Medical School, UK Many thanks for your helpful comments which have enabled us to substantially improve the paper. We detail point by point below how we have addressed each comment. We have highlighted our changes in the manuscript in red font. 1) Copy edit is required. Thank you, we have thoroughly proofread the paper. 2) The authors do not seem to be aware of existing governance structures, carefully developed alongside research on public attidues and legal and ethical analyses. Health is a devolved matter in the UK. They need to read and make reference to the Scottish Government’s Data Linkage Framework Page 23 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 Government’s Data Linkage Framework (http://www.gov.scot/Topics/Statistics/datalinkageframework), the Guiding Principles for Data Linkage, and the terms of reference for the Public Benefits and Privacy Panel for Health and Social Care. Thank you for pointing out the regional differences and the link to the Scottish framework. We have replaced this section with a general overview of the new EU GDPR legislation (page 3) and its general implications for the sharing of patient data, with no references made to specific countries’ frameworks or data access policies. 3) Perhaps also look at the FARR Institute website to see how this major initiative is promoting safe use of health data for research purposes We have included reference to Farr, and the Wellcome trust initiative Understanding Patient Data as key exemplars of disseminators of public benefits of patient data research, in the discussion page 25 4) There are some key reports that have not been identified by their search that are highly relevant: Public Acceptability of Cross-Sectoral Data Linkage (http://www.gov.scot/Publications/2012/08/9455); Public acceptability of data sharing between public, private and third sectors for research purposes (http://www.gov.scot/resource/0043/00435458.pdf); Aitken et al (2011) . recommendations. Many thanks for suggesting these reports. We scrutinised these reports in detail and found they did not meet our eligibility criterion that studies must be about sharing health data in particular and not personal data in general. 5) A few other points – while supportive of an approach that identifies core principles, I’m not sure that Beauchamp and Childress’ four principles for biomedical research translate as easily as they suggest. I think some reference to emergent frameworks that speak to a social licence might be more compelling and the core principles that might underpin such a license. Public health ethics might help here. Many thanks for these suggestions which mirror recommendations from reviewer 1 and have helped us to strengthen the main messages of the paper. We have substantially rewritten the future directions section and the majority of the discussion. We have given more background information on the use of key ethical principles such as Beauchamp and Childress in the introduction, and have related these principles to social license theory throughout the paper. 6) A more minor point – the authors start by referring the medical data but really they are focussed on health data – a broader term. I also wonder why they use the term public opinion instead of attitudes. It may be that these terms are used differently in quantitative and qualitative research perhaps, but some justification would be helpful. Papers used a variety of different terms denoting that they were capturing the thoughts of patients and the public, including: views, perspectives, attitudes, perceptions, opinions, acceptance, awareness, thoughts. We have decided to use generically the term public “views” because this feels like the most general term, and we have made this consistent throughout. We agree with the reviewers on the need for clarification of the terms medical and health data. We have described the type of data we are focusing on in the methods (page 5), as “electronic hospital records, electronic general practice records, and data extracted from these records, for example cancer registries and national disease databases” and have used the terms patient data or EHRs to represent these data throughout the manuscript. We preferred the term “patient data” to keep our language consistent with public facing initiatives such as the Wellcome Trust “Understanding Page 24 of 25 Wellcome Open Research 2019, 3:6 Last updated: 04 MAR 2019 our language consistent with public facing initiatives such as the Wellcome Trust “Understanding Patient Data” initiative. 7) During the presentation of the findings of the review, they also refer to GP records, the Electronic Health Record, Cancer Registries – maybe clarify what type of records the studies they are referring to – or use the overarching term of EHR. The authors touch on the differences in the way in which public’s views are accessed and I think that point bears further elaboration. Please see response to the point above regarding terms for patient data. We have added a sentence to the limitations about how the views expressed may have been affected by methods of studies. (Page 24)  Competing Interests: No competing interests were disclosed. Page 25 of 25

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Published: Jan 17, 2019

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