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Process and outcome indicators for infection control and prevention in European acute care hospitals in 2011 to 2012 – Results of the PROHIBIT study

Process and outcome indicators for infection control and prevention in European acute care... Research article Process and outcome indicators for infection control and prevention in European acute care hospitals in 2011 to 2012 – Results of the PROHIBIT study Sonja Hansen¹, Frank Schwab¹, Walter Zingg², Petra Gastmeier¹, the PROHIBIT study group³ 1. Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute for Hygiene and Environmental Medicine, Berlin, Germany 2. University of Geneva Hospitals, Infection Control Programme, Switzerland 3. The members of the PROHIBIT study group are listed at the end of the article Correspondence :Sonja Hansen (sonja.hansen@charite.de) Citation style for this artic le: Hansen Sonja, Schwab Frank, Zingg Walter, Gastmeier Petra, the PROHIBIT study group. Process and outcome indicators for infection control and prevention in European acute care hospitals in 2011 to 2012 – Results of the PROHIBIT study. Euro Sur veill. 2018;23(21):pii=1700513. https://doi.org/10.2807/1560-7917. ES.2018.23.21.1700513 Ar ticle submitted on 26 Jul 2017 / accepted on 17 Apr 2018 / published on 24 May 2018 Introduction H : ospitals from 24 European countries (PN), bloodstream infections (BSI), and gastrointes- were asked for information on infection prevention tinal infections, with  Clostridium difficile  infection and control (IPC) indicators as part of the Prevention (CDI) accounting for a high proportion in the latter. of Hospital Infections by Intervention and Training HCAIs result in increased morbidity and mortality, (PROHIBIT) survey. Methods: Leading IPC personnel of and emerging  antibiotic resistance  complicates 297 hospitals with established healthcare-associated their  treatment. The cumulative burden of HCAIs is infection (HCAI) surveillance provided information on higher than the total burden of other communicable local surveillance and feedback by using a question- diseases in Europe [2]. naire. Results:  Most hospitals focused on bloodstream infection (BSI) (n = 251) and surgical site infection (SSI) Surveillance as the ‘ongoing systematic collection and (n = 254), with a SSI post-discharge surveillance in analysis of health data for the planning, implementa- 148 hospitals. As part of the HCAI surveillance, met- tion, and evaluation, of public health practice’ [3] is a icillin-resistant  Staphylococcus aureus  (MRSA) was key measure in HCAI prevention and control. Even in the leading multidrug-resistant organism (MDRO) the absence of specific prevention actions, sur veillance under surveillance. Seventy-nine per cent of hospitals and feedback of outcome indicators decrease HCAI by (n = 236) monitored alcohol-based hand rub (ABHR) raising awareness for the issue among healthcare pro- consumption. Feedback to the local IPC committees fessionals [4-7]. Surveillance, preferably as part of a mainly included outcome data on HCAI (n = 259; 87%) network, was identified as one of the key components and MDRO among HCAI (n = 245; 83%); whereupon a in effective HCAI prevention and an important tool for feedback of MDRO data depended on hospital size monitoring the effectiveness of prevention and control (p = 0.012).  Discussion/conclusion  :Objectives and measures by the ‘Systematic Review and Evidence- methods of surveillance vary across Europe, with BSI, based Guidance on Organization of Hospital Infection SSI and MRSA receiving considerably more attention Control Programmes’ (SIGHT) project [8]. than indicators such as pneumonia and urinary tract infection, which may be equally important. In order to Since the 1990s, many European countries have been maximise prevention and control of HCAI and MDRO developing national surveillance networks, either by in Europe, surveillance should be further improved by applying the United States’ (US) Centers for Disease targeting relevant HCAI. The role of feedback should Control and Prevention (CDC) National Nosocomial be explored in more detail. Infection Surveillance/National Healthcare Safety Network (NNIS/NHSN) protocol, or by using adapted Introduction methods to better take into account local diagnos- Based on the results of the first European point prev- tic practices [9]. In 2010, the European Centre for alence survey (PPS) in 2011–12 an estimated 3.2 mil- Disease Prevention and Control (ECDC) established the lion patients acquire a healthcare-associated infection Healthcare-Associated Infections surveillance Network (HCAI) in acute care hospitals in Europe every year [1]. (HAI-Net), integrating the Hospitals in Europe Link for The most common types of HCAI are surgical site infec- Infection Control through Surveillance (HELICS) project tions (SSI), urinary tract infections (UTI), pneumonia www.eurosurveillance.org 1 (2000–4) and the Improving Patient Safety in Europe carbapenemase-producing Enterobacteriaceae, car- (IPSE) network (2005–8) [10]. bapenem-resistant  Pseudomonas aeruginosa  and mul- tiresistant Acinetobacter baumannii. Surveillance of alcohol-based hand rub (ABHR) con- sumption has become a mandatory quality indicator Local IPC professionals were also asked to provide with public repor ting in France since 2006 [11], and was data on hospital characteristics such as status (pub- integrated into the national Krankenhaus-Infektions- lic/private) and size of the hospital (number of beds), Surveillance-System (KISS) in 2008 in Germany [12]. and the full time equivalent (FTE) of infection control Furthermore, national strategies on measuring hand personnel. hygiene compliance by direct observation have been organised in a number of European countries [13]. Furthermore, country characteristics such as the United Nations (UN) European geographical region, and Aspects of specific surveillance activities in European healthcare expenditure (HCE) as share on the national hospitals were obtained as part of the Prevention gross domestic product (GDP) were collected [15,16]. of Hospital Infections by Intervention and Training (PROHIBIT) project. The PROHIBIT survey was con- Data analysis ducted as the first pan-European survey on infec- Descriptive data analysis was performed and results tion prevention and control (IPC) in order to describe summarised as totals and strata of the following four which IPC recommendations are actually being used parameters: hospital size (small: ≤ 300 beds; medium: across Europe and to provide information on gaps in 301–600 beds; large: > 600 beds), UN European geo- hospitals’ IPC policies and practices for policymakers, graphical regions, full-time-equivalent (FTE) infection hospital managers and healthcare workers for further control nurses (ICN) (internal staff and external staff ) improvement of HCAI prevention. This article summa- per 1,000 acute care hospital beds ≤ / > the median of rises data on findings from 24 European countries. all participating hospitals (3.72 FTE ICN/1,000 beds) and HCE as share on GDP [15,16]. HCE was modelled Methods as a dichotomous variable and considered low or high if below or above the European mean HCE of 9%. Participating countries and hospitals Differences in the process and outcome indicators ECDC national contact points (NCPs) and IPC experts between the strata of the four parameters described of European countries outside of the European Union above were tested by logistic regressions models. In (EU) were invited to organise national polls. The NCPs the regression analysis with indicator parameters as invited national hospitals for participation between outcome, only the independent variables were included September 2011 and March 2012. Participation in the in the generalised estimating equation (GEE) models, PROHIBIT sur vey was based mainly on hospital interest adjusting for cluster effects by country. A two-sided rather than on a systematic sampling process. p value < 0.05 in the type III test was considered sig- nificant. All analyses were performed with SPSS (IBM Survey description SPSS statistics, Somer, NY, US) and SAS (SAS Institute, The survey was developed by an interdisciplinary Cary, NC, US). group and discussed with the HAI-Net representa- tives. It included four questionnaires in order to assess Results IPC structure and process indicators (i) at the hospi- tal level, (ii) in intensive care units (ICU), (iii) in non- Participating countries and hospitals ICU medical wards and (iv) in non-ICU surgical wards. Of 32 invited countries, 24 participated (Table 1) with Questionnaires addressed organisation and activities 309 acute care hospitals. From all 309 acute care hos- of IPC at those various levels. pitals participating in the PROHIBIT survey, 297 hospi- tals (96%) had some method of HCAI surveillance in The complete method of the survey and the character- place. Hospitals with HCAI surveillance had a median istics of the participating hospitals are described in of 426 beds (interquartile range (IQR): 260–277), and more detail elsewhere [14]. were most often public hospitals (253 hospitals, 85%). For the present analysis, data on HCAI surveillance, Medical conditions/disease outcome where process and outcome indicators (e.g. ABHR con- HCAI surveillance applies sumption, HCAI), direct hand hygiene observations, Surveillance in the hospitals mainly focused on SSI feedback practices, and persons performing sur- and BSI, and less often on PN, CDI and UTI (Table 2). veillance are described at hospital level. Hospitals Surveillance of UTI depended on countries’ HCE with were asked whether the following multidrug-resist- significantly higher proportions in countries with low ant organisms (MDRO) were monitored among HCAI: HCE. For PN, significant differences were observed in meticillin-resistant  Staphylococcus aureus  (MRSA), accordance to the hospital size, with more medium to vancomycin-resistant Enterococci (VRE), extended- large hospitals having PN surveillance in place com- spectrum beta-lactamase (ESBL)-producing pared to smaller hospitals. Significantly more hospitals Enterobacteriaceae, carbapenem nonsusceptible or from countries with low HCE performed hospital-wide 2 www.eurosurveillance.org surveillance of PN and UTI. Hospital-wide surveillance direct hand hygiene compliance obser vations, 152 hos- of BSI varied significantly with the UN regions. pitals provided immediate feedback to the observed personnel and 131 hospitals provided a later summary Surveillance of CDI was reported most often by hospi- feedback. tals in Northern Europe and more often by hospitals in countries with high HCE; but these differences were As shown in the Figure, IPC committees mainly received not statistically significant. data on HCAI (n = 259; 87%) and the proportion of MDRO among HCAIs (n = 245; 83%) but less often on Hip prosthesis implantation (HPRO) was the most com- hand hygiene performance indicators. Feedback on mon indicator operation of SSI sur veillance with higher MDRO among HCAIs was most often provided in larger percentages in countries with high HCE; but these dif- hospitals (p = 0.012). IPC committees in hospitals with ferences were not statistically significant. In 148 of 254 ICN rates above the European median received signifi- hospitals with SSI surveillance (58%), post-discharge cantly more often feedback on hand hygiene compli- surveillance (PDS) was in place. ance data compared to IPC committees in hospitals with ICN rates below the median (p = 0.039). Feedback Multidrug-resistant organisms surveyed among on hand hygiene per formance (ABHR consumption and/ HCAIs or hand hygiene compliance) was significantly more MRSA was the most commonly observed MDRO among often provided in countries with high HCE (p = 0.042). HCAI in almost all hospitals (n = 273), followed by No feedback was given to IPC committees in 23 (8%) ESBL-producing Enterobacteriaceae  (n = 243) and VRE hospitals. (n = 228). Multidrug-resistant  Acinetobacter bauman- nii sur veillance was reported by 204 hospitals, carbap- Discussion enem nonsusceptible or carbapenemase-producing To our knowledge, the data of the PROHIBIT sur vey offer Enterobacteriaceae by 189 hospitals, and carbapenem- the first broad analysis of HCAI and MDRO surveillance resistant Pseudomonas aeruginosa by 185 hospitals. activities in European acute care hospitals. The find- ings show that content and methods of surveillance Monitoring hand hygiene compliance and the role of feedback vary widely across Europe. Consumption of ABHR and hand hygiene compliance Hospitals focused more frequently on the surveillance was obser ved in 79% and 78% of the hospitals, respec- of outcome indicators as BSI and SSI than on PN, CDI tively (Table 2). Hospitals in countries in Northern or UTI. This may be due to numerous success stories Europe preferred monitoring hand hygiene compli- of BSI and SSI preventability, which raised hospitals’ ance to monitoring ABHR consumption, while hospitals awareness towards these two infection types [17-19]. in countries in Western Europe preferred monitoring ABHR consumption to monitoring hand hygiene compli- Fifty-eight per cent of hospitals with SSI surveillance ance (Table 2). reported to have PDS in place. Such additional surveil- lance as described by Woelber et al. in 2016, par tly pre- Operators involved in HCAI surveillance vents under-reporting of SSI in Europe [20]. The finding Table 3  summarises the operators involved in HCAI that HPRO is the most common indicator procedure for surveillance. Most surveillance activities are per- SSI surveillance corresponds to the results of ECDC’s formed by IPC personnel. Although the overall num- HAI-Net surveillance of SSI with HPRO being the most bers are low, it appeared that hospitals in countries of frequently reported type of surgery, representing 33% Northern Europe had a higher percentage of specific of all operations in 2010–11 [21]. staff dedicated to surveillance of HCAI compared to other regions. In almost half of the hospitals, data on Nevertheless, successful preventability of HCAIs such HCAI were collected by IPC personnel, whereas sur veil- as PN and UTI has also been described [22,23] and data lance exclusively performed by ward personnel was by of the PPS from 2011–12 indicate that respiratory tract reported by 9% of all hospitals, and 18% of hospitals infections and UTI are common HCAIs all over Europe. in Eastern Europe. Interestingly, UTI surveillance was significantly more frequently reported in countries with low HCE. Data of Feedback on the HCAI situation and hand the PPS for countries with high HCE however, showed hygiene compliance frequencies of UTIs up to 31%, indicating that patients In almost all hospitals, healthcare workers (HCW) hospitalised in such countries are also at risk for this received feedback on HCAI (n = 106 more than twice type of HCAI [1]. a year, n = 61 twice a year, n = 115 once a year, n = 15 less than once a year). Of the 236 hospitals that per- Resources are limited; and thus, priorities must be formed ABHR consumption surveillance, 200 hospitals made in HCAI sur veillance, even if a broad sur veillance provided feedback at least once a year (n = 41 more strategy including process and outcome indicators is than twice a year, n = 32 twice a year, n = 127 once a considered helpful to tailor intervention activities for year), while in 35 hospitals feedback was given less HCAI prevention. Prospective hospital-wide HCAI sur- than once a year and for one hospital information on veillance is resource-intensive, and in this sense, it the frequency of feedback was unavailable. Concerning was surprising to find that the proportion of hospitals www.eurosurveillance.org 3 Figure Feedback of surveillance data to the infection control committees in European acute care hospitals with established healthcare-associated infection surveillance, stratified by healthcare expenditure, infection control nurse rate, United Nation regions and hospital size – The Prevention of Hospital Infection by Intervention and Training (PROHIBIT) survey, 2011–2012 (n = 297 hospita ls) a b A. Healthcare expenditure B. Infection control nurse rate 0.042 0.039 60 60 50 51 HCAI MDRO ABHRC HHC ABHRC /HHC HCAI MDRO ABHRC HHC ABHRC /HHC Low High ≤Median >Median c d C. United Nations regions D. Hospital size 0.012 90 90 91 91 73 73 73 70 72 69 69 66 68 60 55 50 52 0 0 HCAI MDRO ABHRC HHC ABHRC /HHC HCAI MDRO ABHRC HHC ABHRC /HHC Eastern Europe Sou thern Euro pe ≤ 300 beds 301–600 beds > 600 beds Northern Euro pe Western Europe ABHRC: alcohol-based hand rub consumption; ABHRC/HHC: ABHRC and/or hand hygiene compliance; FTE: full time equivalent; HCAI: healthcare-associated infections; HCE: healthcare expenditure; HHC: hand hygiene compliance; ICN: infection control nurse; MDRO: multidrug-resistant organisms. Low/high HCE defined as the share of the gross domestic product ≤ / > the European mean in 2010 (9%) [16]; low HCE (n = 127), high HCE (n = 170). FTE ICN (internal staff and external staff ) per 1,000 acute care hospital beds ≤ / > the median of all participating hospitals (3.72 FTE ICN/1,000 beds); ‘≤ median’ (n = 150), ‘> median’ (n = 147). Geographical regions according to United Nations grouping [15]; Eastern Europe (n = 82), Northern Europe (n = 70), Southern Europe (n = 81), Wester n Europe (n = 64). Hospital size according to number of acute care beds; ‘≤ 300 beds’ (n = 87), ‘301–600 beds’ (n = 109), ‘> 600 beds’ (n = 98); information available for 294 hospitals. P values were calculated by logistic regression using generalised estimating equations, which account for cluster effects by country. 4 www.eurosurveillance.org Percentage Percentage Percentage Percentage Table 1 Distribution of hospitals providing data on healthcare-associated infection surveillance and national healthcare expenditure as part of the gross domestic product by country – the Prevention of Hospital Infection by Intervention and Training (PROHIBIT) survey, Europe, 2011–2012 (n = 297 hospitals) Number of participating hospitals a b United Nations region Countr y Total HCE as % of GDP n % Finland 8.9 11 3.7 Ireland 9.2 12 4 Latvia 6.8 7 2.4 Lithuania 7 13 4.4 Nor ther n Europe, n = 70 Sweden 9.6 6 2 United Kingdom, England 5 1.7 United Kingdom, Scotland 9.6 3 1 United Kingdom, Wales 13 4.3 Bulgaria 7.2 19 6.4 Hungar y 7.8 30 10.1 Easter n Europe, n = 82 Poland 7 9 3 Slovakia 9 24 8.1 Croatia 7.8 5 1.7 Italy 9.3 18 6.1 Malta 8.6 1 0.3 Souther n Europe, n = 81 Portugal 10.7 26 8.8 Slovenia 9 8 2.7 Spain 9.6 23 7.7 Austria 11 8 2.7 Belgium 10.5 5 1.7 France 11.6 8 2.7 Wester n Europe, n = 64 Germany 11.6 29 9.8 Switzerland 11.4 6 2 The Netherlands 12 8 2.7 All NA NA 297 100 GDP: gross domestic product; HCE: healthcare expenditure; NA: not applicable.  Geographical regions according to United Nations grouping [15].  HCE as the share of the GDP [16]. with hospital-wide PN and UTI surveillance was sig- testing and missing awareness as a consequence nificantly higher in hospitals from countries with low [1,25]. The high number of hospitals performing CDI HCE compared to hospitals from countries with high surveillance in Northern Europe can be seen as a HCE. Generally, hospital-wide surveillance of HCAI consequence of public reporting on CDI in the United is time-consuming and repeated PPSs on HCAI or an Kingdom (UK). The new European protocol of CDI sur- automated surveillance linking administrative data veillance for acute care hospitals, which was devel- and clinical databases including microbiology may be oped in 2013, offers a standardised cross-country a better approach. surveillance, with the option of integrating clinical and molecular data, and can contribute to enhanced moni- Large healthcare-associated outbreaks of CDI in the toring of CDI in all parts of Europe [26]. first decade of 2000 sparked increased awareness of CDI prevention in Europe, and resulted in European Although low, still 10% of hospitals in Europe, and nearly guidelines on CDI prevention in 2008, recommending 20% of hospitals in Eastern Europe, collect HCAI data CDI surveillance [24]. Data of our survey showed that by ward personnel only. This method of case finding fewer hospitals in countries with low HCE established can be interpreted as a more passive rather than active CDI surveillance, indicating that surveillance activities surveillance, with potential bias of under-reporting. As as a whole may be influenced by financial constraints recommended by the Association for Professionals in in Europe. The low level of CDI surveillance activities Infection Control and Epidemiology (APIC), appropriate in these hospitals may be due to absent national CDI education to apply infection surveillance definitions or surveillance systems, but also to a lack of diagnostic www.eurosurveillance.org 5 Table 2 Surveillance of process and outcome indicators in European acute care hospitals, stratified by healthcare expenditure, United Nation regions, hospital size, rate of infection control nurses – the Prevention of Hospital Infection by Intervention and Training (PROHIBIT) survey, 2011–2012 (n = 297 hospitals) a b c d HCE United Nations region Hospital size ICN/1,000 beds Healthcare- associated 301– Total Eastern Nor thern Southern Western ≤ 300 > 600 infections Low High 600 ≤ median > median Europe Europe Europe Europe beds beds under beds sur veillance N % N % N % N % N % N % N % N % N % N % N % N % with particular procedures 297 127 170 82 70 81 64 87 109 98 150 147 sur veilled Healthcare-associated infections under surveillance Bloodstream 251 85 112 88 139 82 79 96 58 83 65 80 49 77 67 77 96 88 85 87 127 85 124 84 infections e,f • Hospital-wide 175 59 91 72 84 49 68 83 49 70 42 52 16 25 50 57 72 66 51 52 79 53 96 65 Pneumonia 211 71 103 81 108 64 74 90 39 56 56 69 42 66 49 56 84 77 76 78 113 75 98 67 e,h • Hospital-wide 97 33 67 53 30 18 49 60 20 29 22 27 6 9 26 30 42 39 29 30 48 32 49 33 Urinary tract 187 63 101 80 86 51 74 90 28 40 49 60 36 56 49 56 69 63 68 69 103 69 84 57 infections e,h • Hospital-wide 109 37 72 57 37 22 54 66 22 31 27 33 6 9 31 36 47 43 31 32 52 35 57 39 Clostridium dif ficile- 203 68 76 60 127 75 50 61 54 77 55 68 44 69 51 59 73 67 76 78 91 61 112 76 associated infections • Hospital-wide 191 64 71 56 120 71 45 55 54 77 51 63 41 64 46 53 69 63 73 74 86 57 105 71 SSI 254 86 112 88 142 84 75 91 63 90 62 77 54 84 68 78 92 84 91 93 129 86 125 85 Procedures Cholecystectomy 130 44 71 56 59 35 48 59 22 31 33 41 27 42 31 36 57 52 42 43 71 47 59 40 Colon surgery 129 43 56 44 73 43 39 48 19 27 43 53 28 44 30 34 54 50 44 45 64 43 65 44 Caesarean 126 42 63 50 63 37 45 55 35 50 23 28 23 36 26 30 54 50 44 45 62 41 64 44 section Hip prosthesis 164 55 57 45 107 63 32 39 48 69 48 59 36 56 40 46 65 60 56 57 75 50 89 61 implantation Knee prosthesis 138 46 42 33 96 55 24 29 41 59 43 53 30 47 33 38 57 52 45 46 57 38 81 55 implantation Post discharge surveillance of 148 50 54 43 94 55 35 43 40 57 43 53 30 47 39 45 59 54 48 49 64 43 84 57 SSI Monitoring of alcohol- 236 79 105 83 131 77 65 79 47 67 71 88 53 83 68 78 82 75 85 87 124 83 112 76 based handrub consumption • Hospital-wide 215 72 95 75 120 71 57 70 46 66 65 80 47 73 59 68 80 73 75 77 114 76 101 69 Monitoring of hand hygiene 231 78 101 80 130 76 62 76 67 96 66 81 36 56 72 83 81 74 75 77 109 73 122 83 compliance e,c • Hospital-wide 173 58 79 62 94 55 48 59 62 89 38 47 25 39 59 68 64 59 49 50 79 53 94 64 F TE: full time equivalent; HCE: healthcare expenditure; ICN: infection control nurse; SSI: surgical site infection. P values were calculated by logistic regression using generalised estimating equations, which account for cluster effects by country.  Low/high HCE defined as the share of the gross domestic product ≤ / > the European mean in 2010 (9%) [16].  Geographical regions according to United Nations grouping [15]; Eastern Europe, Northern Europe, Southern Europe, Western Europe.  Hospital size according to number of acute care beds; ≤ 300 beds, 301 – 600 beds, > 600 beds; information available for 294 hospitals.  F TE ICN (internal staff and external staff ) per 1,000 acute care hospital beds ≤ / > the median of all participating hospitals (3.72 F TE ICN/1,000 beds).  Hospital-wide describes that the surveillance takes place in all units and wards of the hospital.  Differences between United Nations regions p < 0.05.  Differences between ≤ 300 beds / 301 – 600 beds / > 600 beds; p < 0.05.  Differences between low/high HCE; p < 0.05. to perform detailed risk factor collection is indispensa- observation, enables hospitals to identify gaps and ble [27]. improve adherence to IPC measures more promptly than by focusing on outcome data alone. Interestingly, In addition to the surveillance of outcomes, many hos- our study identified a discrepancy between a relatively pitals assess data on hand hygiene performance indi- high number of hospitals monitoring ABHR consump- cators. Monitoring process indicators and assessment tion and a relatively low number of hospitals giv- of adherence to IPC measures such as hand hygiene ing feedback on ABHR consumption data to their IPC 6 www.eurosurveillance.org www.eurosurveillance.org 7 Table 3 Personnel involved in data collection for healthcare-associated infection (HCAI) surveillance in European acute care hospitals with HCAI surveillance, stratified by healthcare expenditure, United Nation regions, hospital size and infection control nurse rate – the Prevention of Hospital Infection by Intervention and Training (PROHIBIT) survey, 2011– 2012 (n = 297 hospita ls) Hospital size a b d HCE United Nation region ICN/1,000 beds in terms of number of beds Total Personnel involved in data collection for HCAI sur veillance Low High Eastern Nor thern Southern Western ≤ 300 301–600 > 600 ≤ median > median n = 297 % n = 127 % n = 170 % n = 82 % n = 70 % n = 81 % n = 64 % n = 87 % n = 109 % n = 98 % n = 150 % n = 1 47 % ICN 217 73 70 55 147 86 45 55 50 71 65 80 57 89 62 71 79 72 73 74 99 66 118 80 Infection control physician 146 49 54 43 92 54 34 41 36 51 51 63 25 39 32 37 54 50 58 59 79 53 67 46 Ward nurse 61 21 31 24 30 18 21 26 22 31 13 16 5 8 19 22 28 26 13 13 28 19 33 22 Ward physician 97 33 39 31 58 34 26 32 29 41 25 31 17 27 31 36 39 36 26 27 44 29 53 36 Specific surveillance staff e.g. nurse 9 3 5 4 4 2 5 6 2 3 2 2 0 0 1 1 4 4 3 3 6 4 3 2 or administrator Audit nurse 46 15 22 17 24 14 13 16 18 26 9 11 6 9 10 11 16 15 19 19 23 15 23 16 Infection control personnel exclusively (ICN and/or infection 143 48 56 44 87 51 36 44 24 34 43 53 40 63 39 45 49 45 53 54 76 51 67 46 control physician) Ward personnel exclusively (ward 27 9 19 15 8 5 15 18 7 10 4 5 1 2 13 15 12 11 2 2 14 9 13 9 nurse and/or ward physician) Infection control personnel and 97 33 38 30 59 35 24 29 29 41 27 33 17 27 28 32 38 35 30 31 45 30 52 35 ward personnel FTE: full time equivalent; GDP: gross domestic product; HCE: healthcare expenditure; ICN: infection control nurse. P values were calculated by logistic regression using generalised estimating equations, which account for cluster effects by country.  Low/high HCE defined as the share of the GDP ≤ / > the European mean in 2010 (9%) [16].  Geographical regions according to United Nations grouping [15]; Eastern Europe, Northern Europe, Southern Europe, Western Europe.  Hospital size according to number of acute care beds; ≤ 300 beds, 301 – 600 beds, > 600 beds; information available for 294 hospitals.   ≤ / > median defined as FTE ICN (internal staff and external staff ) per 1,000 acute care hospital beds ≤ / > the median of all participating hospitals (3.72 FTE ICN/1,000 beds).  Differences between ≤ 300 beds / 301 – 600 beds / > 600 beds p < 0.05.  Differences between low/high HCE p < 0.05. committees. This may be due the fact that many hos- the number of participating hospitals might have been pitals start surveillance activities focusing on outcome lower. indicators and still work on the feedback of these indi- cators rather on repor ting ABHR. In addition, ABHR data The UN geographical regions are not homogeneous are often collected yearly, and thus, may be reported in terms of GDP, healthcare organisation and cul- less frequently to IPC committees. On the other hand, ture. However, by also reporting data in reference process indicators are better candidates to be used to countries’ HCE, we tried to take into account such for a realistic target-setting both at ward and hospi- heterogeneity. tal level. Reference data on these indicators facilitate Our findings show that objectives and methods of sur- inter-hospital comparison to support improving their veillance var y across Europe. Some outcome indicators, processes [28]. Europe-wide surveys as the ECDC-PPS such as BSI, SSI and MRSA, seem to receive consider- or PROHIBIT [1,14] already offer reference data on fac- ably more attention than others that are equally impor- tors such as IPC personnel or isolation capacities and tant, such as PN, UTI or CDI. future projects may generate more, possibly stratified reference data for relevant structural and process IPC Hospitals’ IPC committees mainly receive data on out- parameters. come indicators as HCAI and MDRO, but less often on process indicators as hand hygiene performance In order to alter their behaviour in HCAI prevention indicators. HCWs have to be aware of the problem of HCAI in their setting. Data of our survey indicate that HCWs do In order to better address prevention of HCAI and anti- receive feedback on HCAI rates in order to raise aware- microbial resistance in Europe surveillance should be ness. However, more research is needed to explore further improved by targeting all relevant HCAI and how surveillance data are communicated and per- MDRO and providing active surveillance by trained ceived, and how this process can be further optimised. personnel. To what extent surveillance of process indi- Feedback of data may be combined with behaviourally cators prevent HCAI must be further analysed. In addi- informed approaches such as the setting of long-term tion, the role of feedback and behaviourally informed goals and encouraging involvement/participation of approaches should be explored in more detail. HCWs for creating local ownership and reflection on achievements and further activities. The PROHIBIT study group Since successful implementation of IPC measures Pittet Didier, Zingg Walter, Sax Hugo, Gastmeier Petra, requires the participation of HCWs and other stake- Hansen Sonja, Grundmann Hajo, van Benthem Birgit, van der Kooi Tjallie, Dettenkofer Markus, Martin Maria, Richet holders, feedback to members of the IPC committee is Hervé, Szilágyi Emese, Heczko Piotr, Holmes Alison, Kyratsis essential. Especially in smaller hospitals, feedback is Yannis, Ahmad Raheelah, Allegranzi Benedetta, Magiorakos not always established yet. In which way the size of a Anna-Pelagia, Cookson Barry, Wu Albert. hospital influences feedback of MDRO data to hospi- tals’ stakeholders cannot be fully answered. It can be speculated that larger hospitals see more MDROs, and Acknowledgements thus, data are perceived more relevant, particularly The authors would like to thank all participating hospitals for because they care more frequently for patients with their invaluable input and the following colleagues for their severe and/or chronic diseases. suppor t and organization of the sur vey: Angel Asensio, Pascal Astagneau, Birgit Van Benthem, Ermira Tartari Bonnici, Ana Budimir, Karen Burns, Barry Cookson, Ana Cristina Costa, In the future, all hospitals’ IPC committees should be Elina Dimina, Uga Dumpis, Greta Gailiene, Michiyo Iwami, encouraged to work with MDRO data in order to address Irena Klavs, Tommi Kärki, Andrea Kološova, Andrea Kurcz, supporting organisational factors such as leadership David Nicholas Looker, Outi Lyytikäinen, Maria Luisa Moro, support and communication in MDRO transmission Karl Merten, Enrico Ricchizzi, Lisa Ritchie, Kestutis Rudaitis, prevention and antibiotic stewardship programmes Emese Szilágyi, Jadwiga Wójkowska, Tjallie van der Kooi, Rossitza Vatcheva–Dobrevska, Inga Zetterqvist. [29,30]. Funding sources: The current survey gives insight into established sur- veillance activities of European hospitals. However, PROHIBIT was funded by the European Union’s Seventh there are some limitations: Framework Programme (FP7), Grant No. 241928. Participation in the survey was voluntary, and thus, based mainly on hospitals’ interest rather than on a Conf lict of interest randomised sampling process. Therefore, the data None declared. may have overestimated surveillance activities in European hospitals. A randomly selected sample would have improved representation of hospitals in Authors’ contributions Europe. However, the questionnaire could not have Didier Pittet, Walter Zingg, Hugo Sax, Petra Gastmeier, been imposed on hospitals, and thus, data quality and Sonja Hansen, Hajo Grundmann, Birgit van Benthem, Tjallie 8 www.eurosurveillance.org 13. Wetzker W, Bunte-Schönberger K, Walter J, Pilarski G, van der Kooi, Markus Dettenkofer, Maria Martin, Hervé Gastmeier P, Reichardt Ch. Compliance with hand hygiene: Richet, Emese Szilágyi, Piotr Heczko, Alison Holmes, Yannis reference data from the national hand hygiene campaign Kyratsis, Raheelah Ahmad, Benedetta Allegranzi, Anna- in Germany. J Hosp Infect. 2016;92(4):328-31. https://doi. Pelagia Magiorakos, Barry Cookson and Albert Wu contrib- org/10.1016/j.jhin.2016.01.022 PMID: 26984282 uted to the design of the PROHIBIT study. 14. Hansen S, Zingg W, Ahmad R, Kyratsis Y, Behnke M, Schwab F, et al. PROHIBIT study group. Organization of infection control in European hospitals. J Hosp Infect. 2015;91(4):338-45. Petra Gastmeier led the sur vey ( Work package 3 of PROHIBIT ). https://doi.org/10.1016/j.jhin.2015.07.011 PMID: 26542950 15. United Nations. Composition of macro geographic (continental) Sonja Hansen managed and coordinated the survey, Frank regions, geographical sub-regions, and selected economic and Schwab analysed the data. Petra Gastmeier, Sonja Hansen, other groupings. New York: United Nations Statistics Division; Frank Schwab and Walter Zingg interpreted the results. 31 Oct 2013. [Accessed 24 Jul 2017]. Available from: http:// unstats.un.org/unsd/methods/m49/m49regin.htm Sonja Hansen wrote the manuscript. Petra Gastmeier, Frank 16. Organisation for Economic Co-operation and Development Schwab and Walter Zingg reviewed and commented on the (OECD). Health at a glance: Europe 2012. Health expenditure in manuscript. relation to GDP. Paris: OECD Publishing; 2012. 17. Pronovost P, Needham D, Berenholtz S, Sinopoli D, Chu H, Cosgrove S, et al. An intervention to decrease catheter- related bloodstream infections in the ICU. N Engl J Med. References 2006;355(26):2725-32. https://doi.org/10.1056/NEJMoa061115 1. European Centre for Disease Prevention and Control (ECDC). PMID: 17192537 Point prevalence survey of healthcare-associated infections 18. Geubbels EL, Bakker HG, Houtman P, van Noort-Klaassen and antimicrobial use in European acute care hospitals. MA, Pelk MS, Sassen TM, et al. Promoting quality through 2011-2012. Stockholm: ECDC; 2013. [Accessed 24Jul 2017]. surveillance of surgical site infections: five prevention success Available from: http://www.ecdc.europa.eu/en/publications/ stories. Am J Infect Control. 2004;32(7):424-30. https://doi. Publications/healthcare-associated-infections-antimicrobial- org/10.1016/j.ajic.2004.07.001 PMID: 15525920 use-PPS.pdf 19. Dellinger EP, Hausmann SM, Bratzler DW, Johnson RM, Daniel 2. Cassini A, Plachouras D, Eckmanns T, Abu Sin M, Blank HP, DM, Bunt KM, et al. Hospitals collaborate to decrease surgical Ducomble T, et al. Burden of Six Healthcare-Associated site infections. Am J Surg. 2005;190(1):9-15. https://doi. Infections on European Population Health: Estimating org/10.1016/j.amjsurg.2004.12.001 PMID: 15972163 Incidence-Based Disability-Adjusted Life Years through a 20. Woelber E, Schrick EJ, Gessner BD, Evans HL. Proportion of Population Prevalence-Based Modelling Study. PLoS Med. Surgical Site Infections Occurring after Hospital Discharge: A 2016;13(10):e1002150. https://doi.org/10.1371/journal. Systematic Review. Surg Infect (Larchmt). 2016;17(5):510-9. pmed.1002150 PMID: 27755545 https://doi.org/10.1089/sur.2015.241 PMID: 27463235 3. Langmuir AD. The surveillance of communicable diseases 21. European Centre for Disease Prevention and Control (ECDC). of national importance. N Engl J Med. 1963;268(4):182- Surveillance of surgical site infections in Europe 2010-2011. 92. https://doi.org/10.1056/NEJM196301242680405 PMID: Stockholm: ECDC; 2013. [Accessed 24 Jul 2017]. Available from: https://ecdc.europa.eu/en/publications-data/ 4. Haley RW, Culver DH, White JW, Morgan WM, Emori TG, Munn sur veillance-surgical-site-infections-europe-2010-2011 VP, et al. The efficacy of infection surveillance and control 22. Vanhems P, Baratin D, Voirin N, Savey A, Caillat-Vallet E, programs in preventing nosocomial infections in US hospitals. Metzger MH, et al. Reduction of urinary tract infections Am J Epidemiol. 1985;121(2):182-205. https://doi.org/10.1093/ acquired in an intensive care unit during a 10-year surveillance oxfordjournals.aje.a113990 PMID: 4014115 program. Eur J Epidemiol. 2008;23(9):641-5. https://doi. 5. Gastmeier P, Schwab F, Sohr D, Behnke M, Geffers C. org/10.1007/s10654-008-9270-2 PMID: 18618273 Reproducibility of the surveillance effect to decrease 23. Zuschneid I, Schwab F, Gastmeier P, Geffers C, Behnke M, nosocomial infection rates. Infect Control Hosp Epidemiol. Rüden H. Trends in ventilator-associated pneumonia rates 2009;30(10):993-9. https://doi.org/10.1086/605720 PMID: within the German nosocomial infection surveillance system (KISS). Infect Control Hosp Epidemiol. 2007;28(3):314-8. 6. Gaynes R, Richards C, Edwards J, Emori TG, Horan T, Alonso- https://doi.org/10.1086/507823 PMID: 17326022 Echanove J, et al. Feeding back surveillance data to prevent 24. Vonberg RP, Kuijper EJ, Wilcox MH, Barbut F, Tüll P, Gastmeier hospital-acquired infections. Emerg Infect Dis. 2001;7(2):295-8. P, et al. European C difficile-Infection Control GroupEuropean https://doi.org/10.3201/eid0702.010230 PMID: 11294727 Centre for Disease Prevention and Control (ECDC). Infection 7. Gastmeier P, Sohr D, Schwab F, Behnke M, Zuschneid I, Brandt control measures to limit the spread of Clostridium difficile. C, et al. Ten years of KISS: the most important requirements Clin Microbiol Infect. 2008;14(Suppl 5):2-20. https://doi. for success. J Hosp Infect. 2008;70(Suppl 1):11-6. https://doi. org/10.1111/j.1469-0691.2008.01992.x PMID: 18412710 org/10.1016/S0195-6701(08)60005-5 PMID: 18994676 25. Kola A, Wiuff C, Akerlund T, van Benthem BH, Coignard 8. Zingg W, Holmes A, Dettenkofer M, Goetting T, Secci F, Clack B, Lyytikäinen O, et al. members of ECDIS-Net. Survey L, et al. systematic review and evidence-based guidance of Clostridium difficile infection surveillance systems in on organization of hospital infection control programmes Europe, 2011. Euro Surveill. 2016;21(29):30291. https://doi. (SIGHT ) study group. Hospital organisation, management, org/10.2807/1560-7917.ES.2016.21.29.30291 PMID: 27469420 and structure for prevention of health-care-associated 26. van Dorp SM, Kinross P, Gastmeier P, Behnke M, Kola A, infection: a systematic review and expert consensus. Lancet Delmée M, et al. European Clostridium difficile Infection Infect Dis. 2015;15(2):212-24. https://doi.org/10.1016/S1473- Surveillance Network (ECDIS-Net) on behalf of all participants. 3099(14)70854-0 PMID: 25467650 Standardised surveillance of Clostridium difficile infection 9. Gastmeier P. European perspective on surveillance. J Hosp in European acute care hospitals: a pilot study, 2013. Euro Infect. 2007;65(Suppl 2):159-64. https://doi.org/10.1016/ Surveill. 2016;21(29):30293. https://doi.org/10.2807/1560- S0195-6701(07)60036-X PMID: 17540263 7917.ES.2016.21.29.30293 PMID: 27472820 10. European Centre for Disease Prevention and Control 27. Lee TB, Montgomery OG, Marx J, Olmsted RN, Scheckler (ECDC). Healthcare-associated Infections Surveillance WEAssociation for Professionals in Infection Control and Network (HAI-Net). Stockholm: ECDC. [Accessed 24 Jul Epidemiology. Recommended practices for surveillance: 2017]. Available from: https://ecdc.europa.eu/en/about-us/ Association for Professionals in Infection Control and partnerships-and-networks/disease-and-laborator y-networks/ Epidemiology (APIC), Inc. Am J Infect Control. 2007;35(7):427- hai-net 40. https://doi.org/10.1016/j.ajic.2007.07.002 PMID: 11. Carlet J, Astagneau P, Brun-Buisson C, Coignard B, Salomon V, Tran B, et al. French National Program for Prevention 28. Behnke M, Clausmeyer JO, Reichardt C, Gastmeier P. of Healthcare-Associated Infections and Antimicrobial Alcohol-based hand rub consumption surveillance in Resistance. French national program for prevention of German hospitals—latest results. Antimicrob Resist healthcare-associated infections and antimicrobial resistance, Infect Control. 2015;4(Suppl 1):P293. https://doi. 1992-2008: positive trends, but perseverance needed. Infect org/10.1186/2047-2994-4-S1-P293 Control Hosp Epidemiol. 2009;30(8):737-45. https://doi. 29. Edwards R, Sevdalis N, Vincent C, Holmes A. Communication org/10.1086/598682 PMID: 19566444 strategies in acute health care: evaluation within the context of 12. Behnke M, Gastmeier P, Geffers C, Mönch N, Reichardt C. infection prevention and control. J Hosp Infect. 2012;82(1):25- Establishment of a national surveillance system for alcohol- 9. https://doi.org/10.1016/j.jhin.2012.05.016 PMID: 22809856 based hand rub consumption and change in consumption over 30. Brannigan ET, Murray E, Holmes A. Where does infection 4 years. Infect Control Hosp Epidemiol. 2012;33(6):618-20. control fit into a hospital management structure? J Hosp Infect. https://doi.org/10.1086/665729 PMID: 22561718 www.eurosurveillance.org 9 2009;73(4):392-6. https://doi.org/10.1016/j.jhin.2009.03.031 PMID: 19699008 License and copyright This is an open-access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0) Licence. 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Process and outcome indicators for infection control and prevention in European acute care hospitals in 2011 to 2012 – Results of the PROHIBIT study

Eurosurveillance , Volume 23 (21) – May 24, 2018

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Abstract

Research article Process and outcome indicators for infection control and prevention in European acute care hospitals in 2011 to 2012 – Results of the PROHIBIT study Sonja Hansen¹, Frank Schwab¹, Walter Zingg², Petra Gastmeier¹, the PROHIBIT study group³ 1. Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute for Hygiene and Environmental Medicine, Berlin, Germany 2. University of Geneva Hospitals, Infection Control Programme, Switzerland 3. The members of the PROHIBIT study group are listed at the end of the article Correspondence :Sonja Hansen (sonja.hansen@charite.de) Citation style for this artic le: Hansen Sonja, Schwab Frank, Zingg Walter, Gastmeier Petra, the PROHIBIT study group. Process and outcome indicators for infection control and prevention in European acute care hospitals in 2011 to 2012 – Results of the PROHIBIT study. Euro Sur veill. 2018;23(21):pii=1700513. https://doi.org/10.2807/1560-7917. ES.2018.23.21.1700513 Ar ticle submitted on 26 Jul 2017 / accepted on 17 Apr 2018 / published on 24 May 2018 Introduction H : ospitals from 24 European countries (PN), bloodstream infections (BSI), and gastrointes- were asked for information on infection prevention tinal infections, with  Clostridium difficile  infection and control (IPC) indicators as part of the Prevention (CDI) accounting for a high proportion in the latter. of Hospital Infections by Intervention and Training HCAIs result in increased morbidity and mortality, (PROHIBIT) survey. Methods: Leading IPC personnel of and emerging  antibiotic resistance  complicates 297 hospitals with established healthcare-associated their  treatment. The cumulative burden of HCAIs is infection (HCAI) surveillance provided information on higher than the total burden of other communicable local surveillance and feedback by using a question- diseases in Europe [2]. naire. Results:  Most hospitals focused on bloodstream infection (BSI) (n = 251) and surgical site infection (SSI) Surveillance as the ‘ongoing systematic collection and (n = 254), with a SSI post-discharge surveillance in analysis of health data for the planning, implementa- 148 hospitals. As part of the HCAI surveillance, met- tion, and evaluation, of public health practice’ [3] is a icillin-resistant  Staphylococcus aureus  (MRSA) was key measure in HCAI prevention and control. Even in the leading multidrug-resistant organism (MDRO) the absence of specific prevention actions, sur veillance under surveillance. Seventy-nine per cent of hospitals and feedback of outcome indicators decrease HCAI by (n = 236) monitored alcohol-based hand rub (ABHR) raising awareness for the issue among healthcare pro- consumption. Feedback to the local IPC committees fessionals [4-7]. Surveillance, preferably as part of a mainly included outcome data on HCAI (n = 259; 87%) network, was identified as one of the key components and MDRO among HCAI (n = 245; 83%); whereupon a in effective HCAI prevention and an important tool for feedback of MDRO data depended on hospital size monitoring the effectiveness of prevention and control (p = 0.012).  Discussion/conclusion  :Objectives and measures by the ‘Systematic Review and Evidence- methods of surveillance vary across Europe, with BSI, based Guidance on Organization of Hospital Infection SSI and MRSA receiving considerably more attention Control Programmes’ (SIGHT) project [8]. than indicators such as pneumonia and urinary tract infection, which may be equally important. In order to Since the 1990s, many European countries have been maximise prevention and control of HCAI and MDRO developing national surveillance networks, either by in Europe, surveillance should be further improved by applying the United States’ (US) Centers for Disease targeting relevant HCAI. The role of feedback should Control and Prevention (CDC) National Nosocomial be explored in more detail. Infection Surveillance/National Healthcare Safety Network (NNIS/NHSN) protocol, or by using adapted Introduction methods to better take into account local diagnos- Based on the results of the first European point prev- tic practices [9]. In 2010, the European Centre for alence survey (PPS) in 2011–12 an estimated 3.2 mil- Disease Prevention and Control (ECDC) established the lion patients acquire a healthcare-associated infection Healthcare-Associated Infections surveillance Network (HCAI) in acute care hospitals in Europe every year [1]. (HAI-Net), integrating the Hospitals in Europe Link for The most common types of HCAI are surgical site infec- Infection Control through Surveillance (HELICS) project tions (SSI), urinary tract infections (UTI), pneumonia www.eurosurveillance.org 1 (2000–4) and the Improving Patient Safety in Europe carbapenemase-producing Enterobacteriaceae, car- (IPSE) network (2005–8) [10]. bapenem-resistant  Pseudomonas aeruginosa  and mul- tiresistant Acinetobacter baumannii. Surveillance of alcohol-based hand rub (ABHR) con- sumption has become a mandatory quality indicator Local IPC professionals were also asked to provide with public repor ting in France since 2006 [11], and was data on hospital characteristics such as status (pub- integrated into the national Krankenhaus-Infektions- lic/private) and size of the hospital (number of beds), Surveillance-System (KISS) in 2008 in Germany [12]. and the full time equivalent (FTE) of infection control Furthermore, national strategies on measuring hand personnel. hygiene compliance by direct observation have been organised in a number of European countries [13]. Furthermore, country characteristics such as the United Nations (UN) European geographical region, and Aspects of specific surveillance activities in European healthcare expenditure (HCE) as share on the national hospitals were obtained as part of the Prevention gross domestic product (GDP) were collected [15,16]. of Hospital Infections by Intervention and Training (PROHIBIT) project. The PROHIBIT survey was con- Data analysis ducted as the first pan-European survey on infec- Descriptive data analysis was performed and results tion prevention and control (IPC) in order to describe summarised as totals and strata of the following four which IPC recommendations are actually being used parameters: hospital size (small: ≤ 300 beds; medium: across Europe and to provide information on gaps in 301–600 beds; large: > 600 beds), UN European geo- hospitals’ IPC policies and practices for policymakers, graphical regions, full-time-equivalent (FTE) infection hospital managers and healthcare workers for further control nurses (ICN) (internal staff and external staff ) improvement of HCAI prevention. This article summa- per 1,000 acute care hospital beds ≤ / > the median of rises data on findings from 24 European countries. all participating hospitals (3.72 FTE ICN/1,000 beds) and HCE as share on GDP [15,16]. HCE was modelled Methods as a dichotomous variable and considered low or high if below or above the European mean HCE of 9%. Participating countries and hospitals Differences in the process and outcome indicators ECDC national contact points (NCPs) and IPC experts between the strata of the four parameters described of European countries outside of the European Union above were tested by logistic regressions models. In (EU) were invited to organise national polls. The NCPs the regression analysis with indicator parameters as invited national hospitals for participation between outcome, only the independent variables were included September 2011 and March 2012. Participation in the in the generalised estimating equation (GEE) models, PROHIBIT sur vey was based mainly on hospital interest adjusting for cluster effects by country. A two-sided rather than on a systematic sampling process. p value < 0.05 in the type III test was considered sig- nificant. All analyses were performed with SPSS (IBM Survey description SPSS statistics, Somer, NY, US) and SAS (SAS Institute, The survey was developed by an interdisciplinary Cary, NC, US). group and discussed with the HAI-Net representa- tives. It included four questionnaires in order to assess Results IPC structure and process indicators (i) at the hospi- tal level, (ii) in intensive care units (ICU), (iii) in non- Participating countries and hospitals ICU medical wards and (iv) in non-ICU surgical wards. Of 32 invited countries, 24 participated (Table 1) with Questionnaires addressed organisation and activities 309 acute care hospitals. From all 309 acute care hos- of IPC at those various levels. pitals participating in the PROHIBIT survey, 297 hospi- tals (96%) had some method of HCAI surveillance in The complete method of the survey and the character- place. Hospitals with HCAI surveillance had a median istics of the participating hospitals are described in of 426 beds (interquartile range (IQR): 260–277), and more detail elsewhere [14]. were most often public hospitals (253 hospitals, 85%). For the present analysis, data on HCAI surveillance, Medical conditions/disease outcome where process and outcome indicators (e.g. ABHR con- HCAI surveillance applies sumption, HCAI), direct hand hygiene observations, Surveillance in the hospitals mainly focused on SSI feedback practices, and persons performing sur- and BSI, and less often on PN, CDI and UTI (Table 2). veillance are described at hospital level. Hospitals Surveillance of UTI depended on countries’ HCE with were asked whether the following multidrug-resist- significantly higher proportions in countries with low ant organisms (MDRO) were monitored among HCAI: HCE. For PN, significant differences were observed in meticillin-resistant  Staphylococcus aureus  (MRSA), accordance to the hospital size, with more medium to vancomycin-resistant Enterococci (VRE), extended- large hospitals having PN surveillance in place com- spectrum beta-lactamase (ESBL)-producing pared to smaller hospitals. Significantly more hospitals Enterobacteriaceae, carbapenem nonsusceptible or from countries with low HCE performed hospital-wide 2 www.eurosurveillance.org surveillance of PN and UTI. Hospital-wide surveillance direct hand hygiene compliance obser vations, 152 hos- of BSI varied significantly with the UN regions. pitals provided immediate feedback to the observed personnel and 131 hospitals provided a later summary Surveillance of CDI was reported most often by hospi- feedback. tals in Northern Europe and more often by hospitals in countries with high HCE; but these differences were As shown in the Figure, IPC committees mainly received not statistically significant. data on HCAI (n = 259; 87%) and the proportion of MDRO among HCAIs (n = 245; 83%) but less often on Hip prosthesis implantation (HPRO) was the most com- hand hygiene performance indicators. Feedback on mon indicator operation of SSI sur veillance with higher MDRO among HCAIs was most often provided in larger percentages in countries with high HCE; but these dif- hospitals (p = 0.012). IPC committees in hospitals with ferences were not statistically significant. In 148 of 254 ICN rates above the European median received signifi- hospitals with SSI surveillance (58%), post-discharge cantly more often feedback on hand hygiene compli- surveillance (PDS) was in place. ance data compared to IPC committees in hospitals with ICN rates below the median (p = 0.039). Feedback Multidrug-resistant organisms surveyed among on hand hygiene per formance (ABHR consumption and/ HCAIs or hand hygiene compliance) was significantly more MRSA was the most commonly observed MDRO among often provided in countries with high HCE (p = 0.042). HCAI in almost all hospitals (n = 273), followed by No feedback was given to IPC committees in 23 (8%) ESBL-producing Enterobacteriaceae  (n = 243) and VRE hospitals. (n = 228). Multidrug-resistant  Acinetobacter bauman- nii sur veillance was reported by 204 hospitals, carbap- Discussion enem nonsusceptible or carbapenemase-producing To our knowledge, the data of the PROHIBIT sur vey offer Enterobacteriaceae by 189 hospitals, and carbapenem- the first broad analysis of HCAI and MDRO surveillance resistant Pseudomonas aeruginosa by 185 hospitals. activities in European acute care hospitals. The find- ings show that content and methods of surveillance Monitoring hand hygiene compliance and the role of feedback vary widely across Europe. Consumption of ABHR and hand hygiene compliance Hospitals focused more frequently on the surveillance was obser ved in 79% and 78% of the hospitals, respec- of outcome indicators as BSI and SSI than on PN, CDI tively (Table 2). Hospitals in countries in Northern or UTI. This may be due to numerous success stories Europe preferred monitoring hand hygiene compli- of BSI and SSI preventability, which raised hospitals’ ance to monitoring ABHR consumption, while hospitals awareness towards these two infection types [17-19]. in countries in Western Europe preferred monitoring ABHR consumption to monitoring hand hygiene compli- Fifty-eight per cent of hospitals with SSI surveillance ance (Table 2). reported to have PDS in place. Such additional surveil- lance as described by Woelber et al. in 2016, par tly pre- Operators involved in HCAI surveillance vents under-reporting of SSI in Europe [20]. The finding Table 3  summarises the operators involved in HCAI that HPRO is the most common indicator procedure for surveillance. Most surveillance activities are per- SSI surveillance corresponds to the results of ECDC’s formed by IPC personnel. Although the overall num- HAI-Net surveillance of SSI with HPRO being the most bers are low, it appeared that hospitals in countries of frequently reported type of surgery, representing 33% Northern Europe had a higher percentage of specific of all operations in 2010–11 [21]. staff dedicated to surveillance of HCAI compared to other regions. In almost half of the hospitals, data on Nevertheless, successful preventability of HCAIs such HCAI were collected by IPC personnel, whereas sur veil- as PN and UTI has also been described [22,23] and data lance exclusively performed by ward personnel was by of the PPS from 2011–12 indicate that respiratory tract reported by 9% of all hospitals, and 18% of hospitals infections and UTI are common HCAIs all over Europe. in Eastern Europe. Interestingly, UTI surveillance was significantly more frequently reported in countries with low HCE. Data of Feedback on the HCAI situation and hand the PPS for countries with high HCE however, showed hygiene compliance frequencies of UTIs up to 31%, indicating that patients In almost all hospitals, healthcare workers (HCW) hospitalised in such countries are also at risk for this received feedback on HCAI (n = 106 more than twice type of HCAI [1]. a year, n = 61 twice a year, n = 115 once a year, n = 15 less than once a year). Of the 236 hospitals that per- Resources are limited; and thus, priorities must be formed ABHR consumption surveillance, 200 hospitals made in HCAI sur veillance, even if a broad sur veillance provided feedback at least once a year (n = 41 more strategy including process and outcome indicators is than twice a year, n = 32 twice a year, n = 127 once a considered helpful to tailor intervention activities for year), while in 35 hospitals feedback was given less HCAI prevention. Prospective hospital-wide HCAI sur- than once a year and for one hospital information on veillance is resource-intensive, and in this sense, it the frequency of feedback was unavailable. Concerning was surprising to find that the proportion of hospitals www.eurosurveillance.org 3 Figure Feedback of surveillance data to the infection control committees in European acute care hospitals with established healthcare-associated infection surveillance, stratified by healthcare expenditure, infection control nurse rate, United Nation regions and hospital size – The Prevention of Hospital Infection by Intervention and Training (PROHIBIT) survey, 2011–2012 (n = 297 hospita ls) a b A. Healthcare expenditure B. Infection control nurse rate 0.042 0.039 60 60 50 51 HCAI MDRO ABHRC HHC ABHRC /HHC HCAI MDRO ABHRC HHC ABHRC /HHC Low High ≤Median >Median c d C. United Nations regions D. Hospital size 0.012 90 90 91 91 73 73 73 70 72 69 69 66 68 60 55 50 52 0 0 HCAI MDRO ABHRC HHC ABHRC /HHC HCAI MDRO ABHRC HHC ABHRC /HHC Eastern Europe Sou thern Euro pe ≤ 300 beds 301–600 beds > 600 beds Northern Euro pe Western Europe ABHRC: alcohol-based hand rub consumption; ABHRC/HHC: ABHRC and/or hand hygiene compliance; FTE: full time equivalent; HCAI: healthcare-associated infections; HCE: healthcare expenditure; HHC: hand hygiene compliance; ICN: infection control nurse; MDRO: multidrug-resistant organisms. Low/high HCE defined as the share of the gross domestic product ≤ / > the European mean in 2010 (9%) [16]; low HCE (n = 127), high HCE (n = 170). FTE ICN (internal staff and external staff ) per 1,000 acute care hospital beds ≤ / > the median of all participating hospitals (3.72 FTE ICN/1,000 beds); ‘≤ median’ (n = 150), ‘> median’ (n = 147). Geographical regions according to United Nations grouping [15]; Eastern Europe (n = 82), Northern Europe (n = 70), Southern Europe (n = 81), Wester n Europe (n = 64). Hospital size according to number of acute care beds; ‘≤ 300 beds’ (n = 87), ‘301–600 beds’ (n = 109), ‘> 600 beds’ (n = 98); information available for 294 hospitals. P values were calculated by logistic regression using generalised estimating equations, which account for cluster effects by country. 4 www.eurosurveillance.org Percentage Percentage Percentage Percentage Table 1 Distribution of hospitals providing data on healthcare-associated infection surveillance and national healthcare expenditure as part of the gross domestic product by country – the Prevention of Hospital Infection by Intervention and Training (PROHIBIT) survey, Europe, 2011–2012 (n = 297 hospitals) Number of participating hospitals a b United Nations region Countr y Total HCE as % of GDP n % Finland 8.9 11 3.7 Ireland 9.2 12 4 Latvia 6.8 7 2.4 Lithuania 7 13 4.4 Nor ther n Europe, n = 70 Sweden 9.6 6 2 United Kingdom, England 5 1.7 United Kingdom, Scotland 9.6 3 1 United Kingdom, Wales 13 4.3 Bulgaria 7.2 19 6.4 Hungar y 7.8 30 10.1 Easter n Europe, n = 82 Poland 7 9 3 Slovakia 9 24 8.1 Croatia 7.8 5 1.7 Italy 9.3 18 6.1 Malta 8.6 1 0.3 Souther n Europe, n = 81 Portugal 10.7 26 8.8 Slovenia 9 8 2.7 Spain 9.6 23 7.7 Austria 11 8 2.7 Belgium 10.5 5 1.7 France 11.6 8 2.7 Wester n Europe, n = 64 Germany 11.6 29 9.8 Switzerland 11.4 6 2 The Netherlands 12 8 2.7 All NA NA 297 100 GDP: gross domestic product; HCE: healthcare expenditure; NA: not applicable.  Geographical regions according to United Nations grouping [15].  HCE as the share of the GDP [16]. with hospital-wide PN and UTI surveillance was sig- testing and missing awareness as a consequence nificantly higher in hospitals from countries with low [1,25]. The high number of hospitals performing CDI HCE compared to hospitals from countries with high surveillance in Northern Europe can be seen as a HCE. Generally, hospital-wide surveillance of HCAI consequence of public reporting on CDI in the United is time-consuming and repeated PPSs on HCAI or an Kingdom (UK). The new European protocol of CDI sur- automated surveillance linking administrative data veillance for acute care hospitals, which was devel- and clinical databases including microbiology may be oped in 2013, offers a standardised cross-country a better approach. surveillance, with the option of integrating clinical and molecular data, and can contribute to enhanced moni- Large healthcare-associated outbreaks of CDI in the toring of CDI in all parts of Europe [26]. first decade of 2000 sparked increased awareness of CDI prevention in Europe, and resulted in European Although low, still 10% of hospitals in Europe, and nearly guidelines on CDI prevention in 2008, recommending 20% of hospitals in Eastern Europe, collect HCAI data CDI surveillance [24]. Data of our survey showed that by ward personnel only. This method of case finding fewer hospitals in countries with low HCE established can be interpreted as a more passive rather than active CDI surveillance, indicating that surveillance activities surveillance, with potential bias of under-reporting. As as a whole may be influenced by financial constraints recommended by the Association for Professionals in in Europe. The low level of CDI surveillance activities Infection Control and Epidemiology (APIC), appropriate in these hospitals may be due to absent national CDI education to apply infection surveillance definitions or surveillance systems, but also to a lack of diagnostic www.eurosurveillance.org 5 Table 2 Surveillance of process and outcome indicators in European acute care hospitals, stratified by healthcare expenditure, United Nation regions, hospital size, rate of infection control nurses – the Prevention of Hospital Infection by Intervention and Training (PROHIBIT) survey, 2011–2012 (n = 297 hospitals) a b c d HCE United Nations region Hospital size ICN/1,000 beds Healthcare- associated 301– Total Eastern Nor thern Southern Western ≤ 300 > 600 infections Low High 600 ≤ median > median Europe Europe Europe Europe beds beds under beds sur veillance N % N % N % N % N % N % N % N % N % N % N % N % with particular procedures 297 127 170 82 70 81 64 87 109 98 150 147 sur veilled Healthcare-associated infections under surveillance Bloodstream 251 85 112 88 139 82 79 96 58 83 65 80 49 77 67 77 96 88 85 87 127 85 124 84 infections e,f • Hospital-wide 175 59 91 72 84 49 68 83 49 70 42 52 16 25 50 57 72 66 51 52 79 53 96 65 Pneumonia 211 71 103 81 108 64 74 90 39 56 56 69 42 66 49 56 84 77 76 78 113 75 98 67 e,h • Hospital-wide 97 33 67 53 30 18 49 60 20 29 22 27 6 9 26 30 42 39 29 30 48 32 49 33 Urinary tract 187 63 101 80 86 51 74 90 28 40 49 60 36 56 49 56 69 63 68 69 103 69 84 57 infections e,h • Hospital-wide 109 37 72 57 37 22 54 66 22 31 27 33 6 9 31 36 47 43 31 32 52 35 57 39 Clostridium dif ficile- 203 68 76 60 127 75 50 61 54 77 55 68 44 69 51 59 73 67 76 78 91 61 112 76 associated infections • Hospital-wide 191 64 71 56 120 71 45 55 54 77 51 63 41 64 46 53 69 63 73 74 86 57 105 71 SSI 254 86 112 88 142 84 75 91 63 90 62 77 54 84 68 78 92 84 91 93 129 86 125 85 Procedures Cholecystectomy 130 44 71 56 59 35 48 59 22 31 33 41 27 42 31 36 57 52 42 43 71 47 59 40 Colon surgery 129 43 56 44 73 43 39 48 19 27 43 53 28 44 30 34 54 50 44 45 64 43 65 44 Caesarean 126 42 63 50 63 37 45 55 35 50 23 28 23 36 26 30 54 50 44 45 62 41 64 44 section Hip prosthesis 164 55 57 45 107 63 32 39 48 69 48 59 36 56 40 46 65 60 56 57 75 50 89 61 implantation Knee prosthesis 138 46 42 33 96 55 24 29 41 59 43 53 30 47 33 38 57 52 45 46 57 38 81 55 implantation Post discharge surveillance of 148 50 54 43 94 55 35 43 40 57 43 53 30 47 39 45 59 54 48 49 64 43 84 57 SSI Monitoring of alcohol- 236 79 105 83 131 77 65 79 47 67 71 88 53 83 68 78 82 75 85 87 124 83 112 76 based handrub consumption • Hospital-wide 215 72 95 75 120 71 57 70 46 66 65 80 47 73 59 68 80 73 75 77 114 76 101 69 Monitoring of hand hygiene 231 78 101 80 130 76 62 76 67 96 66 81 36 56 72 83 81 74 75 77 109 73 122 83 compliance e,c • Hospital-wide 173 58 79 62 94 55 48 59 62 89 38 47 25 39 59 68 64 59 49 50 79 53 94 64 F TE: full time equivalent; HCE: healthcare expenditure; ICN: infection control nurse; SSI: surgical site infection. P values were calculated by logistic regression using generalised estimating equations, which account for cluster effects by country.  Low/high HCE defined as the share of the gross domestic product ≤ / > the European mean in 2010 (9%) [16].  Geographical regions according to United Nations grouping [15]; Eastern Europe, Northern Europe, Southern Europe, Western Europe.  Hospital size according to number of acute care beds; ≤ 300 beds, 301 – 600 beds, > 600 beds; information available for 294 hospitals.  F TE ICN (internal staff and external staff ) per 1,000 acute care hospital beds ≤ / > the median of all participating hospitals (3.72 F TE ICN/1,000 beds).  Hospital-wide describes that the surveillance takes place in all units and wards of the hospital.  Differences between United Nations regions p < 0.05.  Differences between ≤ 300 beds / 301 – 600 beds / > 600 beds; p < 0.05.  Differences between low/high HCE; p < 0.05. to perform detailed risk factor collection is indispensa- observation, enables hospitals to identify gaps and ble [27]. improve adherence to IPC measures more promptly than by focusing on outcome data alone. Interestingly, In addition to the surveillance of outcomes, many hos- our study identified a discrepancy between a relatively pitals assess data on hand hygiene performance indi- high number of hospitals monitoring ABHR consump- cators. Monitoring process indicators and assessment tion and a relatively low number of hospitals giv- of adherence to IPC measures such as hand hygiene ing feedback on ABHR consumption data to their IPC 6 www.eurosurveillance.org www.eurosurveillance.org 7 Table 3 Personnel involved in data collection for healthcare-associated infection (HCAI) surveillance in European acute care hospitals with HCAI surveillance, stratified by healthcare expenditure, United Nation regions, hospital size and infection control nurse rate – the Prevention of Hospital Infection by Intervention and Training (PROHIBIT) survey, 2011– 2012 (n = 297 hospita ls) Hospital size a b d HCE United Nation region ICN/1,000 beds in terms of number of beds Total Personnel involved in data collection for HCAI sur veillance Low High Eastern Nor thern Southern Western ≤ 300 301–600 > 600 ≤ median > median n = 297 % n = 127 % n = 170 % n = 82 % n = 70 % n = 81 % n = 64 % n = 87 % n = 109 % n = 98 % n = 150 % n = 1 47 % ICN 217 73 70 55 147 86 45 55 50 71 65 80 57 89 62 71 79 72 73 74 99 66 118 80 Infection control physician 146 49 54 43 92 54 34 41 36 51 51 63 25 39 32 37 54 50 58 59 79 53 67 46 Ward nurse 61 21 31 24 30 18 21 26 22 31 13 16 5 8 19 22 28 26 13 13 28 19 33 22 Ward physician 97 33 39 31 58 34 26 32 29 41 25 31 17 27 31 36 39 36 26 27 44 29 53 36 Specific surveillance staff e.g. nurse 9 3 5 4 4 2 5 6 2 3 2 2 0 0 1 1 4 4 3 3 6 4 3 2 or administrator Audit nurse 46 15 22 17 24 14 13 16 18 26 9 11 6 9 10 11 16 15 19 19 23 15 23 16 Infection control personnel exclusively (ICN and/or infection 143 48 56 44 87 51 36 44 24 34 43 53 40 63 39 45 49 45 53 54 76 51 67 46 control physician) Ward personnel exclusively (ward 27 9 19 15 8 5 15 18 7 10 4 5 1 2 13 15 12 11 2 2 14 9 13 9 nurse and/or ward physician) Infection control personnel and 97 33 38 30 59 35 24 29 29 41 27 33 17 27 28 32 38 35 30 31 45 30 52 35 ward personnel FTE: full time equivalent; GDP: gross domestic product; HCE: healthcare expenditure; ICN: infection control nurse. P values were calculated by logistic regression using generalised estimating equations, which account for cluster effects by country.  Low/high HCE defined as the share of the GDP ≤ / > the European mean in 2010 (9%) [16].  Geographical regions according to United Nations grouping [15]; Eastern Europe, Northern Europe, Southern Europe, Western Europe.  Hospital size according to number of acute care beds; ≤ 300 beds, 301 – 600 beds, > 600 beds; information available for 294 hospitals.   ≤ / > median defined as FTE ICN (internal staff and external staff ) per 1,000 acute care hospital beds ≤ / > the median of all participating hospitals (3.72 FTE ICN/1,000 beds).  Differences between ≤ 300 beds / 301 – 600 beds / > 600 beds p < 0.05.  Differences between low/high HCE p < 0.05. committees. This may be due the fact that many hos- the number of participating hospitals might have been pitals start surveillance activities focusing on outcome lower. indicators and still work on the feedback of these indi- cators rather on repor ting ABHR. In addition, ABHR data The UN geographical regions are not homogeneous are often collected yearly, and thus, may be reported in terms of GDP, healthcare organisation and cul- less frequently to IPC committees. On the other hand, ture. However, by also reporting data in reference process indicators are better candidates to be used to countries’ HCE, we tried to take into account such for a realistic target-setting both at ward and hospi- heterogeneity. tal level. Reference data on these indicators facilitate Our findings show that objectives and methods of sur- inter-hospital comparison to support improving their veillance var y across Europe. Some outcome indicators, processes [28]. Europe-wide surveys as the ECDC-PPS such as BSI, SSI and MRSA, seem to receive consider- or PROHIBIT [1,14] already offer reference data on fac- ably more attention than others that are equally impor- tors such as IPC personnel or isolation capacities and tant, such as PN, UTI or CDI. future projects may generate more, possibly stratified reference data for relevant structural and process IPC Hospitals’ IPC committees mainly receive data on out- parameters. come indicators as HCAI and MDRO, but less often on process indicators as hand hygiene performance In order to alter their behaviour in HCAI prevention indicators. HCWs have to be aware of the problem of HCAI in their setting. Data of our survey indicate that HCWs do In order to better address prevention of HCAI and anti- receive feedback on HCAI rates in order to raise aware- microbial resistance in Europe surveillance should be ness. However, more research is needed to explore further improved by targeting all relevant HCAI and how surveillance data are communicated and per- MDRO and providing active surveillance by trained ceived, and how this process can be further optimised. personnel. To what extent surveillance of process indi- Feedback of data may be combined with behaviourally cators prevent HCAI must be further analysed. In addi- informed approaches such as the setting of long-term tion, the role of feedback and behaviourally informed goals and encouraging involvement/participation of approaches should be explored in more detail. HCWs for creating local ownership and reflection on achievements and further activities. The PROHIBIT study group Since successful implementation of IPC measures Pittet Didier, Zingg Walter, Sax Hugo, Gastmeier Petra, requires the participation of HCWs and other stake- Hansen Sonja, Grundmann Hajo, van Benthem Birgit, van der Kooi Tjallie, Dettenkofer Markus, Martin Maria, Richet holders, feedback to members of the IPC committee is Hervé, Szilágyi Emese, Heczko Piotr, Holmes Alison, Kyratsis essential. Especially in smaller hospitals, feedback is Yannis, Ahmad Raheelah, Allegranzi Benedetta, Magiorakos not always established yet. In which way the size of a Anna-Pelagia, Cookson Barry, Wu Albert. hospital influences feedback of MDRO data to hospi- tals’ stakeholders cannot be fully answered. It can be speculated that larger hospitals see more MDROs, and Acknowledgements thus, data are perceived more relevant, particularly The authors would like to thank all participating hospitals for because they care more frequently for patients with their invaluable input and the following colleagues for their severe and/or chronic diseases. suppor t and organization of the sur vey: Angel Asensio, Pascal Astagneau, Birgit Van Benthem, Ermira Tartari Bonnici, Ana Budimir, Karen Burns, Barry Cookson, Ana Cristina Costa, In the future, all hospitals’ IPC committees should be Elina Dimina, Uga Dumpis, Greta Gailiene, Michiyo Iwami, encouraged to work with MDRO data in order to address Irena Klavs, Tommi Kärki, Andrea Kološova, Andrea Kurcz, supporting organisational factors such as leadership David Nicholas Looker, Outi Lyytikäinen, Maria Luisa Moro, support and communication in MDRO transmission Karl Merten, Enrico Ricchizzi, Lisa Ritchie, Kestutis Rudaitis, prevention and antibiotic stewardship programmes Emese Szilágyi, Jadwiga Wójkowska, Tjallie van der Kooi, Rossitza Vatcheva–Dobrevska, Inga Zetterqvist. [29,30]. Funding sources: The current survey gives insight into established sur- veillance activities of European hospitals. However, PROHIBIT was funded by the European Union’s Seventh there are some limitations: Framework Programme (FP7), Grant No. 241928. Participation in the survey was voluntary, and thus, based mainly on hospitals’ interest rather than on a Conf lict of interest randomised sampling process. Therefore, the data None declared. may have overestimated surveillance activities in European hospitals. A randomly selected sample would have improved representation of hospitals in Authors’ contributions Europe. However, the questionnaire could not have Didier Pittet, Walter Zingg, Hugo Sax, Petra Gastmeier, been imposed on hospitals, and thus, data quality and Sonja Hansen, Hajo Grundmann, Birgit van Benthem, Tjallie 8 www.eurosurveillance.org 13. Wetzker W, Bunte-Schönberger K, Walter J, Pilarski G, van der Kooi, Markus Dettenkofer, Maria Martin, Hervé Gastmeier P, Reichardt Ch. Compliance with hand hygiene: Richet, Emese Szilágyi, Piotr Heczko, Alison Holmes, Yannis reference data from the national hand hygiene campaign Kyratsis, Raheelah Ahmad, Benedetta Allegranzi, Anna- in Germany. J Hosp Infect. 2016;92(4):328-31. https://doi. Pelagia Magiorakos, Barry Cookson and Albert Wu contrib- org/10.1016/j.jhin.2016.01.022 PMID: 26984282 uted to the design of the PROHIBIT study. 14. Hansen S, Zingg W, Ahmad R, Kyratsis Y, Behnke M, Schwab F, et al. PROHIBIT study group. Organization of infection control in European hospitals. J Hosp Infect. 2015;91(4):338-45. Petra Gastmeier led the sur vey ( Work package 3 of PROHIBIT ). https://doi.org/10.1016/j.jhin.2015.07.011 PMID: 26542950 15. United Nations. Composition of macro geographic (continental) Sonja Hansen managed and coordinated the survey, Frank regions, geographical sub-regions, and selected economic and Schwab analysed the data. Petra Gastmeier, Sonja Hansen, other groupings. New York: United Nations Statistics Division; Frank Schwab and Walter Zingg interpreted the results. 31 Oct 2013. [Accessed 24 Jul 2017]. Available from: http:// unstats.un.org/unsd/methods/m49/m49regin.htm Sonja Hansen wrote the manuscript. Petra Gastmeier, Frank 16. Organisation for Economic Co-operation and Development Schwab and Walter Zingg reviewed and commented on the (OECD). Health at a glance: Europe 2012. Health expenditure in manuscript. relation to GDP. Paris: OECD Publishing; 2012. 17. Pronovost P, Needham D, Berenholtz S, Sinopoli D, Chu H, Cosgrove S, et al. An intervention to decrease catheter- related bloodstream infections in the ICU. N Engl J Med. References 2006;355(26):2725-32. https://doi.org/10.1056/NEJMoa061115 1. European Centre for Disease Prevention and Control (ECDC). PMID: 17192537 Point prevalence survey of healthcare-associated infections 18. Geubbels EL, Bakker HG, Houtman P, van Noort-Klaassen and antimicrobial use in European acute care hospitals. MA, Pelk MS, Sassen TM, et al. Promoting quality through 2011-2012. Stockholm: ECDC; 2013. [Accessed 24Jul 2017]. surveillance of surgical site infections: five prevention success Available from: http://www.ecdc.europa.eu/en/publications/ stories. Am J Infect Control. 2004;32(7):424-30. https://doi. Publications/healthcare-associated-infections-antimicrobial- org/10.1016/j.ajic.2004.07.001 PMID: 15525920 use-PPS.pdf 19. Dellinger EP, Hausmann SM, Bratzler DW, Johnson RM, Daniel 2. Cassini A, Plachouras D, Eckmanns T, Abu Sin M, Blank HP, DM, Bunt KM, et al. Hospitals collaborate to decrease surgical Ducomble T, et al. Burden of Six Healthcare-Associated site infections. Am J Surg. 2005;190(1):9-15. https://doi. Infections on European Population Health: Estimating org/10.1016/j.amjsurg.2004.12.001 PMID: 15972163 Incidence-Based Disability-Adjusted Life Years through a 20. Woelber E, Schrick EJ, Gessner BD, Evans HL. Proportion of Population Prevalence-Based Modelling Study. PLoS Med. Surgical Site Infections Occurring after Hospital Discharge: A 2016;13(10):e1002150. https://doi.org/10.1371/journal. Systematic Review. Surg Infect (Larchmt). 2016;17(5):510-9. pmed.1002150 PMID: 27755545 https://doi.org/10.1089/sur.2015.241 PMID: 27463235 3. Langmuir AD. The surveillance of communicable diseases 21. European Centre for Disease Prevention and Control (ECDC). of national importance. N Engl J Med. 1963;268(4):182- Surveillance of surgical site infections in Europe 2010-2011. 92. https://doi.org/10.1056/NEJM196301242680405 PMID: Stockholm: ECDC; 2013. [Accessed 24 Jul 2017]. Available from: https://ecdc.europa.eu/en/publications-data/ 4. Haley RW, Culver DH, White JW, Morgan WM, Emori TG, Munn sur veillance-surgical-site-infections-europe-2010-2011 VP, et al. The efficacy of infection surveillance and control 22. Vanhems P, Baratin D, Voirin N, Savey A, Caillat-Vallet E, programs in preventing nosocomial infections in US hospitals. Metzger MH, et al. Reduction of urinary tract infections Am J Epidemiol. 1985;121(2):182-205. https://doi.org/10.1093/ acquired in an intensive care unit during a 10-year surveillance oxfordjournals.aje.a113990 PMID: 4014115 program. Eur J Epidemiol. 2008;23(9):641-5. https://doi. 5. Gastmeier P, Schwab F, Sohr D, Behnke M, Geffers C. org/10.1007/s10654-008-9270-2 PMID: 18618273 Reproducibility of the surveillance effect to decrease 23. Zuschneid I, Schwab F, Gastmeier P, Geffers C, Behnke M, nosocomial infection rates. Infect Control Hosp Epidemiol. Rüden H. Trends in ventilator-associated pneumonia rates 2009;30(10):993-9. https://doi.org/10.1086/605720 PMID: within the German nosocomial infection surveillance system (KISS). Infect Control Hosp Epidemiol. 2007;28(3):314-8. 6. Gaynes R, Richards C, Edwards J, Emori TG, Horan T, Alonso- https://doi.org/10.1086/507823 PMID: 17326022 Echanove J, et al. Feeding back surveillance data to prevent 24. Vonberg RP, Kuijper EJ, Wilcox MH, Barbut F, Tüll P, Gastmeier hospital-acquired infections. Emerg Infect Dis. 2001;7(2):295-8. P, et al. European C difficile-Infection Control GroupEuropean https://doi.org/10.3201/eid0702.010230 PMID: 11294727 Centre for Disease Prevention and Control (ECDC). Infection 7. Gastmeier P, Sohr D, Schwab F, Behnke M, Zuschneid I, Brandt control measures to limit the spread of Clostridium difficile. C, et al. Ten years of KISS: the most important requirements Clin Microbiol Infect. 2008;14(Suppl 5):2-20. https://doi. for success. J Hosp Infect. 2008;70(Suppl 1):11-6. https://doi. org/10.1111/j.1469-0691.2008.01992.x PMID: 18412710 org/10.1016/S0195-6701(08)60005-5 PMID: 18994676 25. Kola A, Wiuff C, Akerlund T, van Benthem BH, Coignard 8. Zingg W, Holmes A, Dettenkofer M, Goetting T, Secci F, Clack B, Lyytikäinen O, et al. members of ECDIS-Net. Survey L, et al. systematic review and evidence-based guidance of Clostridium difficile infection surveillance systems in on organization of hospital infection control programmes Europe, 2011. Euro Surveill. 2016;21(29):30291. https://doi. (SIGHT ) study group. Hospital organisation, management, org/10.2807/1560-7917.ES.2016.21.29.30291 PMID: 27469420 and structure for prevention of health-care-associated 26. van Dorp SM, Kinross P, Gastmeier P, Behnke M, Kola A, infection: a systematic review and expert consensus. Lancet Delmée M, et al. European Clostridium difficile Infection Infect Dis. 2015;15(2):212-24. https://doi.org/10.1016/S1473- Surveillance Network (ECDIS-Net) on behalf of all participants. 3099(14)70854-0 PMID: 25467650 Standardised surveillance of Clostridium difficile infection 9. Gastmeier P. European perspective on surveillance. J Hosp in European acute care hospitals: a pilot study, 2013. Euro Infect. 2007;65(Suppl 2):159-64. https://doi.org/10.1016/ Surveill. 2016;21(29):30293. https://doi.org/10.2807/1560- S0195-6701(07)60036-X PMID: 17540263 7917.ES.2016.21.29.30293 PMID: 27472820 10. European Centre for Disease Prevention and Control 27. Lee TB, Montgomery OG, Marx J, Olmsted RN, Scheckler (ECDC). Healthcare-associated Infections Surveillance WEAssociation for Professionals in Infection Control and Network (HAI-Net). Stockholm: ECDC. [Accessed 24 Jul Epidemiology. Recommended practices for surveillance: 2017]. Available from: https://ecdc.europa.eu/en/about-us/ Association for Professionals in Infection Control and partnerships-and-networks/disease-and-laborator y-networks/ Epidemiology (APIC), Inc. Am J Infect Control. 2007;35(7):427- hai-net 40. https://doi.org/10.1016/j.ajic.2007.07.002 PMID: 11. Carlet J, Astagneau P, Brun-Buisson C, Coignard B, Salomon V, Tran B, et al. French National Program for Prevention 28. Behnke M, Clausmeyer JO, Reichardt C, Gastmeier P. of Healthcare-Associated Infections and Antimicrobial Alcohol-based hand rub consumption surveillance in Resistance. French national program for prevention of German hospitals—latest results. Antimicrob Resist healthcare-associated infections and antimicrobial resistance, Infect Control. 2015;4(Suppl 1):P293. https://doi. 1992-2008: positive trends, but perseverance needed. Infect org/10.1186/2047-2994-4-S1-P293 Control Hosp Epidemiol. 2009;30(8):737-45. https://doi. 29. Edwards R, Sevdalis N, Vincent C, Holmes A. Communication org/10.1086/598682 PMID: 19566444 strategies in acute health care: evaluation within the context of 12. Behnke M, Gastmeier P, Geffers C, Mönch N, Reichardt C. infection prevention and control. J Hosp Infect. 2012;82(1):25- Establishment of a national surveillance system for alcohol- 9. https://doi.org/10.1016/j.jhin.2012.05.016 PMID: 22809856 based hand rub consumption and change in consumption over 30. Brannigan ET, Murray E, Holmes A. Where does infection 4 years. Infect Control Hosp Epidemiol. 2012;33(6):618-20. control fit into a hospital management structure? J Hosp Infect. https://doi.org/10.1086/665729 PMID: 22561718 www.eurosurveillance.org 9 2009;73(4):392-6. https://doi.org/10.1016/j.jhin.2009.03.031 PMID: 19699008 License and copyright This is an open-access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0) Licence. 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