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Vancomycin-resistant enterococci (VRE) screening and isolation in the general medicine ward: a cost-effectiveness analysis

Vancomycin-resistant enterococci (VRE) screening and isolation in the general medicine ward: a... Background: Vancomycin-resistant enterococci (VRE) are a serious antimicrobial resistant threat in the healthcare setting. We assessed the cost-effectiveness of VRE screening and isolation for patients at high-risk for colonisation on a general medicine ward compared to no VRE screening and isolation from the healthcare payer perspective. Methods: We developed a microsimulation model using local data and VRE literature, to simulate a 20-bed general medicine ward at a tertiary-care hospital with up to 1000 admissions, approximating 1 year. Primary outcomes were accrued over the patient’s lifetime, discounted at 1.5%, and included expected health outcomes (VRE colonisations, VRE infections, VRE-related bacteremia, and deaths subsequent to VRE infection), quality-adjusted life years (QALYs), healthcare costs, and incremental cost-effectiveness ratio (ICER). Probabilistic sensitivity analysis (PSA) and scenario analyses were conducted to assess parameter uncertainty. Results: In our base-case analysis, VRE screening and isolation prevented six healthcare-associated VRE colonisations per 1000 admissions (6/1000), 0.6/1000 VRE-related infections, 0.2/1000 VRE-related bacteremia, and 0.1/1000 deaths subsequent to VRE infection. VRE screening and isolation accrued 0.0142 incremental QALYs at an incremental cost of $112, affording an ICER of $7850 per QALY. VRE screening and isolation practice was more likely to be cost- effective (> 50%) at a cost-effectiveness threshold of $50,000/QALY. Stochasticity (randomness) had a significant impact on the cost-effectiveness. Conclusion: VRE screening and isolation can be cost-effective in majority of model simulations at commonly used cost-effectiveness thresholds, and is likely economically attractive in general medicine settings. Our findings strengthen the understanding of VRE prevention strategies and are of importance to hospital program planners and infection prevention and control. Keywords: Infection control, Vancomycin-resistant enterococci, VRE, Hospital-acquired infection, Antimicrobial resistance, Health economics, Cost-effectiveness analysis Introduction (e.g. immunocompromised, oncology, transplant) are at Vancomycin-resistant enterococci (VRE) are a class of a higher risk of developing VRE-related bacteremia and antimicrobial resistant (AMR) bacteria most commonly other infections [2]. Consequently, patients who develop transmitted within healthcare settings [1]. While im- VRE-related infections require longer hospital stays, munocompetent patients have a low risk of acquiring have a higher risk of mortality, and substantially higher VRE infections post-colonisation, other patient groups medical costs. A study from Canada estimated the mean attributable cost and length of stay for patients with VRE colonisation/infection to be $17,949 and 13.8 days, * Correspondence: sm.mac@mail.utoronto.ca respectively, when compared to patients without VRE [3]. Institute of Health Policy, Management and Evaluation, University of Toronto, 155 College Street, Suite 425, Toronto, ON M5T 3M6, Canada Guidelines for control of VRE from health agencies Toronto Health Economics and Technology Assessment (THETA) (e.g. Centers of Disease Control and Prevention) in the Collaborative, University Health Network, 200 Elizabeth Street, 10th Floor, United States and the United Kingdom recommend Room 247, Toronto, ON M5G 2C4, Canada Full list of author information is available at the end of the article © The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Mac et al. Antimicrobial Resistance and Infection Control (2019) 8:168 Page 2 of 10 control of VRE spread through vancomycin usage, Model structure and patient population screening and isolation of patients with VRE in hospital A microsimulation model was developed to capture the settings, education, cleaning and contact precautions natural history of VRE health burden starting at hospital (e.g. gloves) [4, 5]. Similarly in Canada, provincial com- admission. Schematics of the model are presented in mittees recommend the implementation of active VRE Figs. 1, 2 and 3. The model simulated a dynamic popula- screening programs for patients at high-risk of VRE col- tion of 20 patients in the general medicine ward, i.e., pa- onisation [6]. Risk factors for VRE colonisation include: tient flow was simulated by admitting a new patient to previous admission to healthcare facilities (e.g. hospital); the ward once an existing patient was discharged back dialysis recipient; transfer from long-term care facilities; into the community, or died during their hospital stay. and previous receipt of certain classes of antibiotics (e.g. Admitted patients were considered to be from the commu- cephalosporin) [6]. nity; we did not take into account entry from long-term In 2014, the Canadian Agency for Drugs and Technol- care facilities, readmissions, or ICU step-downs. For base- ogy for Health (CADTH) conducted a rapid response re- case analysis, we evaluated the cost-effectiveness of VRE view on the cost-effectiveness of patient screening and screening and isolation through 1000 admissions, approxi- isolation for VRE and identified one economic evaluation mating 1 year. After 1000 admissions, hospital admissions from France, where the direct cost of an outbreak trig- stopped, and patients were followed over their lifetime. All gered by a failure in systematic VRE screening had a direct modelling and analyses were conducted using TreeAge Pro cost of €60,524 [7]. Two economic evaluations from hos- 2018 (TreeAge Software, Inc., Williamstown, MA). pital settings reported a net benefit of using a VRE control strategy [8, 9]. VRE transmission Based on the current literature, there are no cost- A two-state dynamic transmission component simulated effectiveness analyses for VRE screening and isolation VRE transmission. The probability of acquiring VRE re- practices that included health outcomes in evaluating sponds to changes to the number of VRE-colonised pa- the value of this control strategy. The objective of our tients in the ward who are not isolated and was modeled study was to conduct a cost-effectiveness analysis of ac- using the following equation [12]: tive VRE screening and isolation compared to no VRE ‐βCt=N screening and isolation in the general medicine ward of C =S ¼ 1‐e tþ1 t a tertiary care hospital. Due to conflicting evidence on the value of prevention programs for VRE, we decided Where t represents the specific cycle or time period, to model a general medicine ward instead of an intensive C is the number of patients who are VRE colonised t+1 care unit (ICU) because of its heterogeneous nature (but not isolated) in the current cycle, N is total number (i.e. varying patient risk for VRE colonisation and in- of patients, S represents the total number of patients fections). Evidence from this model can inform decision- susceptible to VRE colonisation in the previous cycle, makers, program planners and clinicians contemplating and β is the basic reproductive number of VRE. The control strategies for healthcare-associated VRE-related basic reproductive number was defined as the number of infections. new infections generated per infected (non-isolated) in- dividual per unit of time. For our model, we assumed a Methods constant basic reproductive number of 1.32. A cost-effectiveness analysis (CEA) was conducted from the Ontario healthcare payer perspective (Ministry of Key assumptions Health and Long-Term Care). Health outcomes were Several key assumptions were made on VRE transmis- accrued over a patients’ lifetime and included: sion and isolation parameters. These included: 1) VRE healthcare-associated VRE colonisations, VRE-related rectal swab screen are completed concurrently with infections (e.g. bacteremia and other infections), deaths Methicillin-resistant Staphylococcus aureus (MRSA) rec- subsequent to VRE infection, and quality-adjusted life tal swab screening (i.e., only additional cost is processing years (QALY). All publicly-funded healthcare costs the swab), and results are delivered within 24 h, a period (2017 Canadian dollars) were included. The primary in which colonized patients can contribute to transmis- outcomes were total healthcare costs, QALYs, and the sion; 2) transmission is based solely on mass-action mix- incremental cost-effectiveness ratio (ICER) expressed in ing; 3) optimal adherence to isolation (i.e. isolation is $ per QALY gained. Cost-effectiveness of VRE screen- 100% effective in reducing transmission); 4) cost of pri- ing and isolation was assessed against the commonly vate (single-bed) room, which is typically considered used cost-effectiveness threshold (CET) of $50,000 per hospital revenue, is captured in the healthcare payer per- QALY gained [10]. We followed CADTH guidelines spective; 5) the general medicine ward has 20 single-bed and reported outcomes discounted at 1.5% [11]. rooms, always at maximum capacity; and 6) colonization Mac et al. Antimicrobial Resistance and Infection Control (2019) 8:168 Page 3 of 10 Fig. 1 Schematic illustrating the possible trajectory of an admitted inpatient (screened or not, depending on the strategy) Fig. 2 Schematic illustrating the trajectory of vancomycin-resistant enterococcus (VRE)-colonised patient Mac et al. Antimicrobial Resistance and Infection Control (2019) 8:168 Page 4 of 10 Fig. 3 Schematic illustrating the possible trajectory of patient not VRE-colonised status of the prior patient in the room was not factored VRE-related infection) [28]. Due to data limitations, into transmission. bacteremia utility (0.56) was extracted from a MRSA- related bacteremia study [23]. Since urinary tract infec- Data sources tions (UTI) represented the greatest percentage of VRE- A targeted literature search was conducted to extract related infections [3, 31], we used the UTI utility of 0.60 outcome probabilities, costs and quality-of-life parame- for all other infections [24]. We assumed a disutility with ters related to VRE health states (Table 1). When pos- being isolated (i.e. being isolated leads to less visits from sible, Canadian-specific parameters were used. Where healthcare workers, reduced socialization, and space con- “assumption” is indicated in Table 1, we were guided by finement), which was equivalent to mild depression (un- expert opinion. treated), and applied a multiplicative 0.895 reduction factor [27]. Probabilities The basic reproductive rate for VRE was uncertain and Costs can vary depending on the environment. We used results All direct costs were extracted from the literature (Table from a meta-analysis of 10 studies that reported a repro- 1). We counted the cost of the screening as a one-time up- ductive rate of 1.32 (95% CI, 1.03–1.46) [13]. Length of stay front cost at ward admission between $12 and $24, (LOS) estimates used for patients with VRE infections was depending on the culture result (positive results being 39 days (IQR, 22–81 days) and without VRE infections was more expensive due to additional microbiologist time re- 3days (IQR, 1–6 days), extracted from a case-control study quired) [9]. All costs were converted and standardized to in Canada [2]. We used a screening rectal swab sensitivity 2017 Canadian dollars. For private room costs, we used the of 0.99 (95% CI, 0.952–1.00) and specificity of 0.948 (95% median from estimates across Ontario ($290 per night) CI, 0.922–0.968) from an United States study evaluating [21]. the swab detection of E. faecium and E. faecalis [16]. Preva- lence of VRE for low-risk patients was 0.023, which was Analysis extracted from a Canadian study in 2012 [14]. The prob- The base-case analysis was defined as follows: screening ability that a patient was at “high-risk” of colonisation was with 95% specificity and 99% sensitivity, VRE basic re- guided by the average age (61 years) of the cohort of pa- productive number of 1.32 [13], and mean age of high- tients who acquired VRE-bacteremia in Canada [2]. All- risk patients at 61 years [2]. The baseline prevalence of cause mortality from all-causes were derived from life ta- VRE was 0.023 and we assumed patients at higher risk bles from Statistics Canada [29]. for VRE colonisation were four times more likely to be colonised (0.092). The base-case analysis was conducted Utilities from a Canadian perspective. To properly value health outcomes for CEAs, we used We conducted multiple scenario analysis including: uni- health state utility values (utilities), which is a preference- versal screening and isolation for all patients, increased based value expressing the quality-of-life associated with duration of the program (5000 admissions), number of health states [30]. Utilities for this study could have ranged beds, and a lower effectiveness (compliance) of the isola- between 0 (health state equivalent to death) to one (per- tion program. fect health). The utility of a VRE-colonised patient was We conducted a probabilistic sensitivity analysis (PSA) considered to be the same as that of a general inpatient using gamma distributions for costs, beta distributions (0.642), which was obtained from a mixed population of for utilities and transitional probabilities, and normal inpatients using the EuroQol rating scale [25]. The utility distributions for other patient or VRE-related parame- for the well outpatient state was derived from a study of ters (see Table 1). From the PSA, we generated a cost- community-dwelling adults using the Health Utilities effectiveness acceptability curve (CEAC) to determine Index to be 0.93 (0.86 for patients who recovered from a the probability of VRE screening and isolation being Mac et al. Antimicrobial Resistance and Infection Control (2019) 8:168 Page 5 of 10 Table 1 Input parameter base-case values, plausible ranges and distributions Variable Base-case value Range Range Type Standard Error Distribution Source VRE-Related Parameters Beta, basic reproductive number 1.32 1.03–1.46 Full 0.12 Gamma Satilmis 2016 [13] VRE prevalence, general 0.023 0–0.18 Full 0.001 Beta Williams 2015 [14] VRE prevalence, high-risk patients 0.092 0–0.36 Plausible 0.002 Beta Conly 2001 [15] LOS | without VRE infection, days 3 1.0–6.0 Full (IQR) 0.38 Gamma Johnstone 2018 [2] LOS | other VRE infection, days 6 1.0–6.0 Full (IQR) 0.77 Gamma Assumption; Johnstone 2018 [2] LOS | VRE-bacteremia, days 39 22.0–81.0 Full (IQR) 4.97 Gamma Johnstone 2018 [2] Screening Parameters Sensitivity, rectal swab 0.991 0.95–1.00 Full 0.02 Beta Stamper 2010 [16] Specificity, rectal swab 0.949 0.92–0.97 Full 0.01 Beta Stamper 2010 [16] Effectiveness of isolation 1.00 0.75–1.00 Plausible – Assumption Discount rate, annual 0.015 0–0.03 Full –– CADTH 2017 [11] Patient Parameters and Transition Probabilities Average age high-risk, years 61 –– 1.15 Normal Johnstone 2018 [2] Probability infected | colonised 0.025 0.018–0.031 Plausible 0.003 Beta Williams 2015 [14] Probability bacteremia | infected 0.155 0.12–0.19 Plausible 0.02 Beta Saunders 2004 [17] Odds ratio bacteremia | infected, high-risk 1.55 0.56–4.29 Full 1.68 Lognormal Johnstone 2018 [2] Average days of treatment for BSI 14 11–18 Plausible 1.79 Gamma Daneman 2016 [18] Average days of treatment for other infections 7 5–9 Plausible 0.89 Gamma Daneman 2016 [18] Probability of death from VRE bacteremia, 0.37 0.27–0.46 Plausible 0.05 Beta Billington 2014 [19] average, 14 days Probability of death from VRE bacteremia, 0.46 0.35–0.58 Plausible 0.06 Beta Linden 1996 [20] high-risk, 14 days Number of room visits by all HCW, per day 24 18–30 Plausible 3.06 Normal Assumption Costs Rectal swab screen 3.13 2.35–3.91 Plausible 0.40 Gamma Muto 2002 [9] Culture, positive test 21.36 16.02–26.7 Plausible 2.72 Gamma Muto 2002 [9] Culture, negative test 8.97 6.73–11.21 Plausible 1.14 Gamma Muto 2002 [9] PPE, per room visit 2.10 1.58–2.63 Plausible 0.27 Gamma Muto 2002 [9] Nurse time, per test 7.12 5.34–8.9 Plausible 0.91 Gamma Muto 2002 [9] Private room, daily 290 245–410 Full –– St. Joseph’s Hospital 2017 [21] Antibiotics, bacteremia, daily 524.22 393.17–655.28 Plausible 66.87 Gamma Nasr 2011 [22] Antibiotics, other infections, daily 35.8 26.85–44.75 Plausible 4.57 Gamma Nasr 2011 [22] Utilities VRE bacteremia 0.56 0.51–0.61 Full 0.023 Beta Lee 2010 [23] Other local infections (UTI) 0.60 0.58–0.62 Full 0.01 Beta Haran 2005 [24] Inpatient 0.642 0.54–0.74 Full 0.05 Beta Tengs, 2000 [25]; Selai 1995 [26] Mild depression, no treatment 0.88 0.84–0.92 Full 0.02 Beta Revicki 1997 [27] Well, chronic conditions, recovered from 0.86 0.34–0.89 Full 0.15 Beta Mittmann 1999 [28] previous VRE-related infection Well, chronic conditions, no previous 0.93 0.88–0.94 Full 0.083 Beta Mittmann 1999 [28] VRE-related infection BSI bloodstream infection, CADTH Canadian Agency for Drugs and Technology in Health, HCW healthcare workers, IQR interquartile range, LOS length of stay, PPE personal protective equipment, UTI urinary tract infection, VRE vancomycin-resistant enterococcus Mac et al. Antimicrobial Resistance and Infection Control (2019) 8:168 Page 6 of 10 cost-effective at CET of $0 to $100,000 per QALY. We Uncertainty: probabilistic sensitivity analysis also assessed expected value of perfect information at Figure 4 illustrates a CEAC where at low CETs below several CETs to assess the value of information; i.e., $7500/QALY, it was unlikely that VRE screening and whether or not to invest more resources to reduce par- isolation was a cost-effective strategy. At a CET of ap- ameter uncertainty. As recommended by CADTH, we proximately $7500/QALY, VRE screening and isolation did not conduct deterministic sensitivity analysis because became more likely to be cost-effective (over 50% of the of model stochasticity and the non-linear relationship of iterations). As the CET increased to $50,000 per QALY, VRE prevalence and transmission parameters. We re- the probability of this program being cost-effective as- ported results following the Consolidated Health Eco- ymptotes at approximately 51.4%. nomic Evaluation Reporting Standards (CHEERS) Since VRE screening and isolation reached a plateau of Guidelines (Additional file 1)[32]. 51% likelihood of being cost-effective, an expected value of perfect information (EVPI) analysis was conducted to determine the value of reducing further uncertainty at Results three points. At a CET of $7500, and $50,000 per QALY, Base-case analysis the EVPI (assuming 1000 patients) was $1065, and $7093, In Table 2, we summarized the estimated health out- respectively. comes, costs and ICER for the VRE screening and isola- tion strategy compared to no VRE screening and Scenario analysis isolation over 1000 admissions for our base-case ana- In the scenario where the prevalence is lower (i.e. reduced lysis. We calculated the difference in the health out- by half; 0.0115), VRE screening and isolation becomes a comes and the relative change using the “no VRE dominated strategy: the program cost an additional $123 screening and isolation” strategy as the baseline. VRE but resulted in fewer QALYs. On the other hand, we mod- screening and isolation reduced healthcare-associated eled a scenario similar to outbreaks in the literature where VRE colonisations by six per 1000 patients (2/1000 with the VRE prevalence was about 10-fold higher (0.23), and screening and isolation vs. 8/1000 without, 73% reduc- estimated that VRE screening and isolation cost $122.79 tion), VRE-related infections by 0.6 per 1000 patients for an incremental increase of 0.0525 QALY. Under this (5.7/1000 with screening and isolation vs. 6.3/1000 with- increased prevalence scenario over 1000 hospital admis- out, 10%), VRE-related bacteremia by 0.2 per 1000 pa- sions, the ICER was $2340/QALY. All scenarios are sum- tients (2.5/1000 with screening and isolation vs. 2.7/1000 marized in Table 3. without, 7%) and deaths subsequent to VRE infection by Scenario analysis was conducted where the private room 0.1 per 1000 (0.5/1000 with screening and isolation vs. costs were excluded due to conflicting views on whether 0.6/1000 without, 8%). these costs are considered from the Ontario healthcare The incremental cost and effect for VRE screening and payer perspective. In this scenario, VRE screening and iso- isolation was $110 ($118.37 with screening and isolation lation program cost an additional $20.58 for 0.0077 vs. $6.72 without), and 0.0142 QALY gained (20.5607 QALYs, resulting in an ICER of $2682/QALY. The num- QALY with screening and isolation vs. 20.5465 QALY ber of beds in the simulated general medicine ward was without), respectively. The ICER for VRE screening and increased to 30. The cost-effectiveness of VRE screening isolation was $7850 per QALY gained. and isolation over 5000 admissions was also estimated. Table 2 Base-case results (health and economic outcomes) Outcomes VRE screening and isolation No VRE screening and isolation Difference (%) Non-isolated cases 11/1000 60/1000 −49/1000 (82%) Healthcare-associated VRE-colonisation 2/1000 8/1000 −6/1000 (73%) Infected cases 5.7/1000 6.3/1000 −0.6/1000 (10%) VRE-related bacteremia 2.6/1000 2.8/1000 −0.2/1000 (7%) Other VRE infections (e.g. UTI) 3.2/1000 3.6/1000 −0.4/1000 (12%) Deaths subsequent to VRE infection 0.5/1000 0.6/1000 −0.1/1000 (8%) ICER ($/QALY) 7850 Total costs ($) 118.37 6.72 112 Total QALY gained 20.5607 20.5465 0.0142 Difference for health outcomes were calculated by subtracting “no VRE screening and isolation strategy” outcomes from “VRE screening and isolation strategy” outcomes. Percentage change was calculated relative to “no VRE screening and isolation strategy” outcomes ICER incremental cost-effectiveness ration, QALY quality-adjusted life years, UTI urinary tract infection, VRE vancomycin-resistant enterococci Mac et al. Antimicrobial Resistance and Infection Control (2019) 8:168 Page 7 of 10 Fig. 4 Cost-effectiveness acceptability curve (CEAC) for cost-effectiveness thresholds from $0 to $50,000/QALY The estimated ICERs for these scenarios were $11,812/ ICER of $7850 per QALY when compared to commonly QALY and $50,094/QALY, respectively. used cost-effectiveness thresholds of $50,000/QALY [10]. Universal VRE screening and isolation for all patients, Overall, our model’s results were consistent with the regardless of whether they identified as high-risk for col- findings of several other published studies [34–37]. A onisation, was a dominated strategy (i.e. resulted in in- study by Shadel et al. found that active VRE screening cremental cost of $151.44 and QALYs lost). We also and isolation resulted in 91% of VRE colonisations being estimated the cost-effectiveness of this program if the identified on an ICU; our model suggested 82% of VRE isolation effectiveness was reduced to 75%. In this sce- positive patients were isolated under an active, targeted nario, VRE screening and isolation cost an additional screening strategy in a general medicine ward [34]. A $99.52 for 0.0002 QALYs, resulting in an ICER of $510, mathematical model of a 10-bed ICU active screening 676/QALY. program for VRE predicted 9.9 cases of VRE colonisa- tion/infection prevented over 1000 model simulations in the ICU with a prevalence rate of 5% [35]. Similarly, our Discussion model predicts a reduction of 6 cases of VRE colonisa- Based on our base-case analysis, VRE screening and isola- tions over 1000 admissions. Our model underestimated tion for patients at high-risk for VRE colonisation pre- the effect of the VRE screening and isolation compared to vented healthcare-associated colonisations, and ultimately both studies, likely because it was modeled after a general VRE-related infections and deaths subsequent to infec- medicine ward which has a lower proportion of high-risk tions. The program was considered cost-effective with an patients (for VRE colonisation and infection) than the Table 3 Incremental cost-effectiveness ratios for VRE screening and isolation program in various scenarios Scenario Incremental Cost Incremental QALYs ICER ($/QALY) Probability of CE Probability of CE (at $7500/QALY) (at $50,000/QALY) VRE Prevalence in-hospital, 10x (outbreak) 122.79 0.0525 2340 0.545 0.556 Room costs excluded ($0) 20.58 0.0077 2682 0.506 0.508 Number of beds in ward [33] 109.78 0.0093 11,812 0.505 0.518 Program length (5000 admissions) 113.05 0.0023 50,094 0.457 0.499 Isolation, decreased effectiveness (0.75) 99.52 0.0002 510,676 0.458 0.476 Time horizon, 1 year 109.61 0.0001 856,297 0 0.259 Universal screening VRE screening 151.44 −0.0039 Dominated 0.484 0.500 and isolation VRE Prevalence in-hospital, 0.5x 108.41 −0.0112 Dominated 0.479 0.501 Signifies asymptote at that probability at $50,000/QALY CE cost-effectiveness, ICER incremental cost-effectiveness ratio, QALY quality-adjusted life year, VRE vancomycin-resistant enterococci Mac et al. Antimicrobial Resistance and Infection Control (2019) 8:168 Page 8 of 10 ICU. However, similar to other studies, our model esti- study by Huskins and colleagues suggesting prevention mated that active VRE screening and isolation strategy effectiveness of 75% (range 62–82%) [40], and the ICER was cost-effective by reducing the number of VRE-related increased to $510,676/QALY. In this scenario, VRE bacteremia events by 2/10,000 patients [36, 37]. screening and isolation would unlikely be cost-effective Our study has several limitations. Health state utilities at commonly used thresholds. Due to stochasticity (ran- were not specific to VRE infections and preference elicit- domness), it is likely that the cost-effectiveness and iso- ation was heterogeneous. To address this and other param- lation effectiveness have a nonlinear relationship. This eter uncertainty (e.g. costs and transition probabilities), we may be of note to decision-makers and infection preven- conducted a PSA with the appropriate underlying distribu- tion and control practitioners, to ensure implementation tion for all parameters to generate a CEAC for cost- of this program is as seamless as possible. effectiveness thresholds of $0 to $50,000/QALY. VRE Cost-effectiveness analyses for screening programs of screening and isolation was more likely to be cost-effective other AMR bacteria such as carbapenemase-producing than no VRE screening and isolation at a CET of $7500/ Enterobacteriaceae and MRSA have been published in QALY or greater. However, as the CET increased to $50, the literature [41, 42]. Similar to these other economic 000/QALY, the likelihood of the program being cost- evaluations on AMR bacteria screening and isolation, effective in extended simulations remained steady at 51%, our results indicated that VRE screening and isolation suggesting that stochasticity (randomness) is a significant was likely to be cost-effective. To our knowledge, this is factor in determining the value of this control program. the first cost-effectiveness analysis for VRE screening This was expected for this type of intervention since indi- and isolation in any hospital setting that incorporated vidual level uncertainty with patients entering a general costs, health outcomes, and QALYs, accrued over a pa- medicine ward and the baseline VRE prevalence can influ- tient’s lifetime. We reported health outcomes per 1000 ence VRE transmission. patients to allow for transferability of our results to gen- Our study assumed a general medicine ward that was eral medicine wards in different jurisdictions. Moreover, set up with 20 single bed rooms, which may not be the the results of this cost-effectiveness analysis can be configuration of all general medicine wards. In a sce- generalizable to other jurisdictions (countries) with simi- nario where 30-beds were used, the ICER increased to lar healthcare system financing to Canada such as $11,812/QALY. These results suggest that an increase in Australia, the United Kingdom, and parts of Europe. We the number of beds would still yield cost-effective VRE also estimated the cost-effectiveness of this program in screening and isolation practices due to the homoge- varying scenarios (e.g. varying VRE prevalence, number neous mixing assumption. This assumption was made of beds) to provide decision-makers with economic evi- despite knowing that VRE transmission can be highly dence to support local health policy given the import- complex and depend on colonization pressure and dens- ance of local context. ity of bacteria [33]. Incorporating such detail of VRE Given the limited body of evidence in this area, we were colonization levels within the transmission modeling of unable to find a suitable source of data against which to this CEA would require much more sophisticated VRE validate our results. As more local research on AMR bac- surveillance data that was not available. We did not ex- teria continues, it will allow for future models to be cross- plore the value of this program in which patients shared validated to health outcomes using health administrative rooms. However, based on Hamel et al., the hazard ratio data, ward caseload (e.g. bed capacity), admission data for VRE colonisation was 1.11 (95% CI, 1.02–1.21) for (e.g. population characteristics), and number of VRE- the number of roommate exposures per day [38]. Our related bacteremia cases. estimates using a single-bed room assumption was a conservative approach, and therefore likely underesti- mated the cost-effectiveness of a VRE screening and iso- Conclusion lation control program. Our model likely provided a VRE screening and isolation for patients at risk for col- conservative estimate of the cost-effectiveness (i.e. un- onisation in the general medicine ward can be consid- derestimates the value) of VRE screening and isolation ered a cost-effective infection prevention and control due to key assumptions required for our analysis (e.g. intervention in this simulation study. The intervention’s did not incorporate time dependency within the ward, cost-effectiveness varied depending on VRE prevalence or re-admissions). and isolation effectiveness. This model would need to be Isolation was assumed to be completely effective in adapted to more accurately estimate the impact in spe- our base-case analysis, which can be considered optimis- cific local contexts but can provide broad economic evi- tic in current healthcare settings given the potential for dence to inform infection prevention and control human errors, and overall burden on healthcare workers practitioners, program planners and health policy [39, 40]. We performed a scenario analysis based on a decision-makers. Mac et al. Antimicrobial Resistance and Infection Control (2019) 8:168 Page 9 of 10 Supplementary information 2. Johnstone J, Chen C, Rosella L, Adomako K, Policarpio ME, Lam F, et al. Supplementary information accompanies this paper at https://doi.org/10. Patient- and hospital-level predictors of vancomycin-resistant Enterococcus 1186/s13756-019-0628-x. (VRE) bacteremia in Ontario, Canada. Am J Infect Control. 2018;46(11):1266–71. 3. Lloyd-Smith P, Younger J, Lloyd-Smith E, Green H, Leung V, Romney MG. Economic analysis of vancomycin-resistant enterococci at a Canadian hospital: Additional file 1. CHEERS Checklist. assessing attributable cost and length of stay. J Hosp Infect. 2013;85(1):54–9. 4. Siegel JD, Rhinehart E, Jackson M, Chiarello L, Gordon SM, Harrell LJ, et al. 2007 guideline for isolation precautions: preventing transmission of Abbreviations infectious agents in health care settings. Am J Infect Control. 2007;35:S65–164. AMR: Antimicrobial resistant; CADTH: Canadian Agency for Drugs and 5. Cookson BD, Macrae MB, Barrett SP, Brown DFJ, Chadwick C, French GL, Technology for Health; CEAC: Cost-effectiveness acceptability curve; et al. Guidelines for the control of glycopeptide-resistant enterococci in CET: Cost-effectiveness threshold; CHEERS: Consolidated Health Economic hospitals *. J Hosp Infect. 2006;62:6–21. Evaluation Reporting Standards; CI: Confidence interval; EVPI: Expected value 6. Ontario Agency for Health Protection and Promotion PIDAC. Annex A: of perfect information; ICER: Incremental cost-effectiveness ratio; Screening, Testing and Surveillance for Antibiotic-Resistant Organisms ICU: Intensive care unit; IQR: Interquartile range; LOS: Length of stay; (AROs) in All Health Care Settings. Toronto, ON; 2013. MRSA: Methicillin-resistant Staphylococcus aureus; PPE: Personal protective 7. Canadian Agency for Drugs and Technologies in Health. 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Vancomycin-resistant enterococci (VRE) screening and isolation in the general medicine ward: a cost-effectiveness analysis

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Biomedicine; Medical Microbiology; Drug Resistance; Infectious Diseases
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Abstract

Background: Vancomycin-resistant enterococci (VRE) are a serious antimicrobial resistant threat in the healthcare setting. We assessed the cost-effectiveness of VRE screening and isolation for patients at high-risk for colonisation on a general medicine ward compared to no VRE screening and isolation from the healthcare payer perspective. Methods: We developed a microsimulation model using local data and VRE literature, to simulate a 20-bed general medicine ward at a tertiary-care hospital with up to 1000 admissions, approximating 1 year. Primary outcomes were accrued over the patient’s lifetime, discounted at 1.5%, and included expected health outcomes (VRE colonisations, VRE infections, VRE-related bacteremia, and deaths subsequent to VRE infection), quality-adjusted life years (QALYs), healthcare costs, and incremental cost-effectiveness ratio (ICER). Probabilistic sensitivity analysis (PSA) and scenario analyses were conducted to assess parameter uncertainty. Results: In our base-case analysis, VRE screening and isolation prevented six healthcare-associated VRE colonisations per 1000 admissions (6/1000), 0.6/1000 VRE-related infections, 0.2/1000 VRE-related bacteremia, and 0.1/1000 deaths subsequent to VRE infection. VRE screening and isolation accrued 0.0142 incremental QALYs at an incremental cost of $112, affording an ICER of $7850 per QALY. VRE screening and isolation practice was more likely to be cost- effective (> 50%) at a cost-effectiveness threshold of $50,000/QALY. Stochasticity (randomness) had a significant impact on the cost-effectiveness. Conclusion: VRE screening and isolation can be cost-effective in majority of model simulations at commonly used cost-effectiveness thresholds, and is likely economically attractive in general medicine settings. Our findings strengthen the understanding of VRE prevention strategies and are of importance to hospital program planners and infection prevention and control. Keywords: Infection control, Vancomycin-resistant enterococci, VRE, Hospital-acquired infection, Antimicrobial resistance, Health economics, Cost-effectiveness analysis Introduction (e.g. immunocompromised, oncology, transplant) are at Vancomycin-resistant enterococci (VRE) are a class of a higher risk of developing VRE-related bacteremia and antimicrobial resistant (AMR) bacteria most commonly other infections [2]. Consequently, patients who develop transmitted within healthcare settings [1]. While im- VRE-related infections require longer hospital stays, munocompetent patients have a low risk of acquiring have a higher risk of mortality, and substantially higher VRE infections post-colonisation, other patient groups medical costs. A study from Canada estimated the mean attributable cost and length of stay for patients with VRE colonisation/infection to be $17,949 and 13.8 days, * Correspondence: sm.mac@mail.utoronto.ca respectively, when compared to patients without VRE [3]. Institute of Health Policy, Management and Evaluation, University of Toronto, 155 College Street, Suite 425, Toronto, ON M5T 3M6, Canada Guidelines for control of VRE from health agencies Toronto Health Economics and Technology Assessment (THETA) (e.g. Centers of Disease Control and Prevention) in the Collaborative, University Health Network, 200 Elizabeth Street, 10th Floor, United States and the United Kingdom recommend Room 247, Toronto, ON M5G 2C4, Canada Full list of author information is available at the end of the article © The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Mac et al. Antimicrobial Resistance and Infection Control (2019) 8:168 Page 2 of 10 control of VRE spread through vancomycin usage, Model structure and patient population screening and isolation of patients with VRE in hospital A microsimulation model was developed to capture the settings, education, cleaning and contact precautions natural history of VRE health burden starting at hospital (e.g. gloves) [4, 5]. Similarly in Canada, provincial com- admission. Schematics of the model are presented in mittees recommend the implementation of active VRE Figs. 1, 2 and 3. The model simulated a dynamic popula- screening programs for patients at high-risk of VRE col- tion of 20 patients in the general medicine ward, i.e., pa- onisation [6]. Risk factors for VRE colonisation include: tient flow was simulated by admitting a new patient to previous admission to healthcare facilities (e.g. hospital); the ward once an existing patient was discharged back dialysis recipient; transfer from long-term care facilities; into the community, or died during their hospital stay. and previous receipt of certain classes of antibiotics (e.g. Admitted patients were considered to be from the commu- cephalosporin) [6]. nity; we did not take into account entry from long-term In 2014, the Canadian Agency for Drugs and Technol- care facilities, readmissions, or ICU step-downs. For base- ogy for Health (CADTH) conducted a rapid response re- case analysis, we evaluated the cost-effectiveness of VRE view on the cost-effectiveness of patient screening and screening and isolation through 1000 admissions, approxi- isolation for VRE and identified one economic evaluation mating 1 year. After 1000 admissions, hospital admissions from France, where the direct cost of an outbreak trig- stopped, and patients were followed over their lifetime. All gered by a failure in systematic VRE screening had a direct modelling and analyses were conducted using TreeAge Pro cost of €60,524 [7]. Two economic evaluations from hos- 2018 (TreeAge Software, Inc., Williamstown, MA). pital settings reported a net benefit of using a VRE control strategy [8, 9]. VRE transmission Based on the current literature, there are no cost- A two-state dynamic transmission component simulated effectiveness analyses for VRE screening and isolation VRE transmission. The probability of acquiring VRE re- practices that included health outcomes in evaluating sponds to changes to the number of VRE-colonised pa- the value of this control strategy. The objective of our tients in the ward who are not isolated and was modeled study was to conduct a cost-effectiveness analysis of ac- using the following equation [12]: tive VRE screening and isolation compared to no VRE ‐βCt=N screening and isolation in the general medicine ward of C =S ¼ 1‐e tþ1 t a tertiary care hospital. Due to conflicting evidence on the value of prevention programs for VRE, we decided Where t represents the specific cycle or time period, to model a general medicine ward instead of an intensive C is the number of patients who are VRE colonised t+1 care unit (ICU) because of its heterogeneous nature (but not isolated) in the current cycle, N is total number (i.e. varying patient risk for VRE colonisation and in- of patients, S represents the total number of patients fections). Evidence from this model can inform decision- susceptible to VRE colonisation in the previous cycle, makers, program planners and clinicians contemplating and β is the basic reproductive number of VRE. The control strategies for healthcare-associated VRE-related basic reproductive number was defined as the number of infections. new infections generated per infected (non-isolated) in- dividual per unit of time. For our model, we assumed a Methods constant basic reproductive number of 1.32. A cost-effectiveness analysis (CEA) was conducted from the Ontario healthcare payer perspective (Ministry of Key assumptions Health and Long-Term Care). Health outcomes were Several key assumptions were made on VRE transmis- accrued over a patients’ lifetime and included: sion and isolation parameters. These included: 1) VRE healthcare-associated VRE colonisations, VRE-related rectal swab screen are completed concurrently with infections (e.g. bacteremia and other infections), deaths Methicillin-resistant Staphylococcus aureus (MRSA) rec- subsequent to VRE infection, and quality-adjusted life tal swab screening (i.e., only additional cost is processing years (QALY). All publicly-funded healthcare costs the swab), and results are delivered within 24 h, a period (2017 Canadian dollars) were included. The primary in which colonized patients can contribute to transmis- outcomes were total healthcare costs, QALYs, and the sion; 2) transmission is based solely on mass-action mix- incremental cost-effectiveness ratio (ICER) expressed in ing; 3) optimal adherence to isolation (i.e. isolation is $ per QALY gained. Cost-effectiveness of VRE screen- 100% effective in reducing transmission); 4) cost of pri- ing and isolation was assessed against the commonly vate (single-bed) room, which is typically considered used cost-effectiveness threshold (CET) of $50,000 per hospital revenue, is captured in the healthcare payer per- QALY gained [10]. We followed CADTH guidelines spective; 5) the general medicine ward has 20 single-bed and reported outcomes discounted at 1.5% [11]. rooms, always at maximum capacity; and 6) colonization Mac et al. Antimicrobial Resistance and Infection Control (2019) 8:168 Page 3 of 10 Fig. 1 Schematic illustrating the possible trajectory of an admitted inpatient (screened or not, depending on the strategy) Fig. 2 Schematic illustrating the trajectory of vancomycin-resistant enterococcus (VRE)-colonised patient Mac et al. Antimicrobial Resistance and Infection Control (2019) 8:168 Page 4 of 10 Fig. 3 Schematic illustrating the possible trajectory of patient not VRE-colonised status of the prior patient in the room was not factored VRE-related infection) [28]. Due to data limitations, into transmission. bacteremia utility (0.56) was extracted from a MRSA- related bacteremia study [23]. Since urinary tract infec- Data sources tions (UTI) represented the greatest percentage of VRE- A targeted literature search was conducted to extract related infections [3, 31], we used the UTI utility of 0.60 outcome probabilities, costs and quality-of-life parame- for all other infections [24]. We assumed a disutility with ters related to VRE health states (Table 1). When pos- being isolated (i.e. being isolated leads to less visits from sible, Canadian-specific parameters were used. Where healthcare workers, reduced socialization, and space con- “assumption” is indicated in Table 1, we were guided by finement), which was equivalent to mild depression (un- expert opinion. treated), and applied a multiplicative 0.895 reduction factor [27]. Probabilities The basic reproductive rate for VRE was uncertain and Costs can vary depending on the environment. We used results All direct costs were extracted from the literature (Table from a meta-analysis of 10 studies that reported a repro- 1). We counted the cost of the screening as a one-time up- ductive rate of 1.32 (95% CI, 1.03–1.46) [13]. Length of stay front cost at ward admission between $12 and $24, (LOS) estimates used for patients with VRE infections was depending on the culture result (positive results being 39 days (IQR, 22–81 days) and without VRE infections was more expensive due to additional microbiologist time re- 3days (IQR, 1–6 days), extracted from a case-control study quired) [9]. All costs were converted and standardized to in Canada [2]. We used a screening rectal swab sensitivity 2017 Canadian dollars. For private room costs, we used the of 0.99 (95% CI, 0.952–1.00) and specificity of 0.948 (95% median from estimates across Ontario ($290 per night) CI, 0.922–0.968) from an United States study evaluating [21]. the swab detection of E. faecium and E. faecalis [16]. Preva- lence of VRE for low-risk patients was 0.023, which was Analysis extracted from a Canadian study in 2012 [14]. The prob- The base-case analysis was defined as follows: screening ability that a patient was at “high-risk” of colonisation was with 95% specificity and 99% sensitivity, VRE basic re- guided by the average age (61 years) of the cohort of pa- productive number of 1.32 [13], and mean age of high- tients who acquired VRE-bacteremia in Canada [2]. All- risk patients at 61 years [2]. The baseline prevalence of cause mortality from all-causes were derived from life ta- VRE was 0.023 and we assumed patients at higher risk bles from Statistics Canada [29]. for VRE colonisation were four times more likely to be colonised (0.092). The base-case analysis was conducted Utilities from a Canadian perspective. To properly value health outcomes for CEAs, we used We conducted multiple scenario analysis including: uni- health state utility values (utilities), which is a preference- versal screening and isolation for all patients, increased based value expressing the quality-of-life associated with duration of the program (5000 admissions), number of health states [30]. Utilities for this study could have ranged beds, and a lower effectiveness (compliance) of the isola- between 0 (health state equivalent to death) to one (per- tion program. fect health). The utility of a VRE-colonised patient was We conducted a probabilistic sensitivity analysis (PSA) considered to be the same as that of a general inpatient using gamma distributions for costs, beta distributions (0.642), which was obtained from a mixed population of for utilities and transitional probabilities, and normal inpatients using the EuroQol rating scale [25]. The utility distributions for other patient or VRE-related parame- for the well outpatient state was derived from a study of ters (see Table 1). From the PSA, we generated a cost- community-dwelling adults using the Health Utilities effectiveness acceptability curve (CEAC) to determine Index to be 0.93 (0.86 for patients who recovered from a the probability of VRE screening and isolation being Mac et al. Antimicrobial Resistance and Infection Control (2019) 8:168 Page 5 of 10 Table 1 Input parameter base-case values, plausible ranges and distributions Variable Base-case value Range Range Type Standard Error Distribution Source VRE-Related Parameters Beta, basic reproductive number 1.32 1.03–1.46 Full 0.12 Gamma Satilmis 2016 [13] VRE prevalence, general 0.023 0–0.18 Full 0.001 Beta Williams 2015 [14] VRE prevalence, high-risk patients 0.092 0–0.36 Plausible 0.002 Beta Conly 2001 [15] LOS | without VRE infection, days 3 1.0–6.0 Full (IQR) 0.38 Gamma Johnstone 2018 [2] LOS | other VRE infection, days 6 1.0–6.0 Full (IQR) 0.77 Gamma Assumption; Johnstone 2018 [2] LOS | VRE-bacteremia, days 39 22.0–81.0 Full (IQR) 4.97 Gamma Johnstone 2018 [2] Screening Parameters Sensitivity, rectal swab 0.991 0.95–1.00 Full 0.02 Beta Stamper 2010 [16] Specificity, rectal swab 0.949 0.92–0.97 Full 0.01 Beta Stamper 2010 [16] Effectiveness of isolation 1.00 0.75–1.00 Plausible – Assumption Discount rate, annual 0.015 0–0.03 Full –– CADTH 2017 [11] Patient Parameters and Transition Probabilities Average age high-risk, years 61 –– 1.15 Normal Johnstone 2018 [2] Probability infected | colonised 0.025 0.018–0.031 Plausible 0.003 Beta Williams 2015 [14] Probability bacteremia | infected 0.155 0.12–0.19 Plausible 0.02 Beta Saunders 2004 [17] Odds ratio bacteremia | infected, high-risk 1.55 0.56–4.29 Full 1.68 Lognormal Johnstone 2018 [2] Average days of treatment for BSI 14 11–18 Plausible 1.79 Gamma Daneman 2016 [18] Average days of treatment for other infections 7 5–9 Plausible 0.89 Gamma Daneman 2016 [18] Probability of death from VRE bacteremia, 0.37 0.27–0.46 Plausible 0.05 Beta Billington 2014 [19] average, 14 days Probability of death from VRE bacteremia, 0.46 0.35–0.58 Plausible 0.06 Beta Linden 1996 [20] high-risk, 14 days Number of room visits by all HCW, per day 24 18–30 Plausible 3.06 Normal Assumption Costs Rectal swab screen 3.13 2.35–3.91 Plausible 0.40 Gamma Muto 2002 [9] Culture, positive test 21.36 16.02–26.7 Plausible 2.72 Gamma Muto 2002 [9] Culture, negative test 8.97 6.73–11.21 Plausible 1.14 Gamma Muto 2002 [9] PPE, per room visit 2.10 1.58–2.63 Plausible 0.27 Gamma Muto 2002 [9] Nurse time, per test 7.12 5.34–8.9 Plausible 0.91 Gamma Muto 2002 [9] Private room, daily 290 245–410 Full –– St. Joseph’s Hospital 2017 [21] Antibiotics, bacteremia, daily 524.22 393.17–655.28 Plausible 66.87 Gamma Nasr 2011 [22] Antibiotics, other infections, daily 35.8 26.85–44.75 Plausible 4.57 Gamma Nasr 2011 [22] Utilities VRE bacteremia 0.56 0.51–0.61 Full 0.023 Beta Lee 2010 [23] Other local infections (UTI) 0.60 0.58–0.62 Full 0.01 Beta Haran 2005 [24] Inpatient 0.642 0.54–0.74 Full 0.05 Beta Tengs, 2000 [25]; Selai 1995 [26] Mild depression, no treatment 0.88 0.84–0.92 Full 0.02 Beta Revicki 1997 [27] Well, chronic conditions, recovered from 0.86 0.34–0.89 Full 0.15 Beta Mittmann 1999 [28] previous VRE-related infection Well, chronic conditions, no previous 0.93 0.88–0.94 Full 0.083 Beta Mittmann 1999 [28] VRE-related infection BSI bloodstream infection, CADTH Canadian Agency for Drugs and Technology in Health, HCW healthcare workers, IQR interquartile range, LOS length of stay, PPE personal protective equipment, UTI urinary tract infection, VRE vancomycin-resistant enterococcus Mac et al. Antimicrobial Resistance and Infection Control (2019) 8:168 Page 6 of 10 cost-effective at CET of $0 to $100,000 per QALY. We Uncertainty: probabilistic sensitivity analysis also assessed expected value of perfect information at Figure 4 illustrates a CEAC where at low CETs below several CETs to assess the value of information; i.e., $7500/QALY, it was unlikely that VRE screening and whether or not to invest more resources to reduce par- isolation was a cost-effective strategy. At a CET of ap- ameter uncertainty. As recommended by CADTH, we proximately $7500/QALY, VRE screening and isolation did not conduct deterministic sensitivity analysis because became more likely to be cost-effective (over 50% of the of model stochasticity and the non-linear relationship of iterations). As the CET increased to $50,000 per QALY, VRE prevalence and transmission parameters. We re- the probability of this program being cost-effective as- ported results following the Consolidated Health Eco- ymptotes at approximately 51.4%. nomic Evaluation Reporting Standards (CHEERS) Since VRE screening and isolation reached a plateau of Guidelines (Additional file 1)[32]. 51% likelihood of being cost-effective, an expected value of perfect information (EVPI) analysis was conducted to determine the value of reducing further uncertainty at Results three points. At a CET of $7500, and $50,000 per QALY, Base-case analysis the EVPI (assuming 1000 patients) was $1065, and $7093, In Table 2, we summarized the estimated health out- respectively. comes, costs and ICER for the VRE screening and isola- tion strategy compared to no VRE screening and Scenario analysis isolation over 1000 admissions for our base-case ana- In the scenario where the prevalence is lower (i.e. reduced lysis. We calculated the difference in the health out- by half; 0.0115), VRE screening and isolation becomes a comes and the relative change using the “no VRE dominated strategy: the program cost an additional $123 screening and isolation” strategy as the baseline. VRE but resulted in fewer QALYs. On the other hand, we mod- screening and isolation reduced healthcare-associated eled a scenario similar to outbreaks in the literature where VRE colonisations by six per 1000 patients (2/1000 with the VRE prevalence was about 10-fold higher (0.23), and screening and isolation vs. 8/1000 without, 73% reduc- estimated that VRE screening and isolation cost $122.79 tion), VRE-related infections by 0.6 per 1000 patients for an incremental increase of 0.0525 QALY. Under this (5.7/1000 with screening and isolation vs. 6.3/1000 with- increased prevalence scenario over 1000 hospital admis- out, 10%), VRE-related bacteremia by 0.2 per 1000 pa- sions, the ICER was $2340/QALY. All scenarios are sum- tients (2.5/1000 with screening and isolation vs. 2.7/1000 marized in Table 3. without, 7%) and deaths subsequent to VRE infection by Scenario analysis was conducted where the private room 0.1 per 1000 (0.5/1000 with screening and isolation vs. costs were excluded due to conflicting views on whether 0.6/1000 without, 8%). these costs are considered from the Ontario healthcare The incremental cost and effect for VRE screening and payer perspective. In this scenario, VRE screening and iso- isolation was $110 ($118.37 with screening and isolation lation program cost an additional $20.58 for 0.0077 vs. $6.72 without), and 0.0142 QALY gained (20.5607 QALYs, resulting in an ICER of $2682/QALY. The num- QALY with screening and isolation vs. 20.5465 QALY ber of beds in the simulated general medicine ward was without), respectively. The ICER for VRE screening and increased to 30. The cost-effectiveness of VRE screening isolation was $7850 per QALY gained. and isolation over 5000 admissions was also estimated. Table 2 Base-case results (health and economic outcomes) Outcomes VRE screening and isolation No VRE screening and isolation Difference (%) Non-isolated cases 11/1000 60/1000 −49/1000 (82%) Healthcare-associated VRE-colonisation 2/1000 8/1000 −6/1000 (73%) Infected cases 5.7/1000 6.3/1000 −0.6/1000 (10%) VRE-related bacteremia 2.6/1000 2.8/1000 −0.2/1000 (7%) Other VRE infections (e.g. UTI) 3.2/1000 3.6/1000 −0.4/1000 (12%) Deaths subsequent to VRE infection 0.5/1000 0.6/1000 −0.1/1000 (8%) ICER ($/QALY) 7850 Total costs ($) 118.37 6.72 112 Total QALY gained 20.5607 20.5465 0.0142 Difference for health outcomes were calculated by subtracting “no VRE screening and isolation strategy” outcomes from “VRE screening and isolation strategy” outcomes. Percentage change was calculated relative to “no VRE screening and isolation strategy” outcomes ICER incremental cost-effectiveness ration, QALY quality-adjusted life years, UTI urinary tract infection, VRE vancomycin-resistant enterococci Mac et al. Antimicrobial Resistance and Infection Control (2019) 8:168 Page 7 of 10 Fig. 4 Cost-effectiveness acceptability curve (CEAC) for cost-effectiveness thresholds from $0 to $50,000/QALY The estimated ICERs for these scenarios were $11,812/ ICER of $7850 per QALY when compared to commonly QALY and $50,094/QALY, respectively. used cost-effectiveness thresholds of $50,000/QALY [10]. Universal VRE screening and isolation for all patients, Overall, our model’s results were consistent with the regardless of whether they identified as high-risk for col- findings of several other published studies [34–37]. A onisation, was a dominated strategy (i.e. resulted in in- study by Shadel et al. found that active VRE screening cremental cost of $151.44 and QALYs lost). We also and isolation resulted in 91% of VRE colonisations being estimated the cost-effectiveness of this program if the identified on an ICU; our model suggested 82% of VRE isolation effectiveness was reduced to 75%. In this sce- positive patients were isolated under an active, targeted nario, VRE screening and isolation cost an additional screening strategy in a general medicine ward [34]. A $99.52 for 0.0002 QALYs, resulting in an ICER of $510, mathematical model of a 10-bed ICU active screening 676/QALY. program for VRE predicted 9.9 cases of VRE colonisa- tion/infection prevented over 1000 model simulations in the ICU with a prevalence rate of 5% [35]. Similarly, our Discussion model predicts a reduction of 6 cases of VRE colonisa- Based on our base-case analysis, VRE screening and isola- tions over 1000 admissions. Our model underestimated tion for patients at high-risk for VRE colonisation pre- the effect of the VRE screening and isolation compared to vented healthcare-associated colonisations, and ultimately both studies, likely because it was modeled after a general VRE-related infections and deaths subsequent to infec- medicine ward which has a lower proportion of high-risk tions. The program was considered cost-effective with an patients (for VRE colonisation and infection) than the Table 3 Incremental cost-effectiveness ratios for VRE screening and isolation program in various scenarios Scenario Incremental Cost Incremental QALYs ICER ($/QALY) Probability of CE Probability of CE (at $7500/QALY) (at $50,000/QALY) VRE Prevalence in-hospital, 10x (outbreak) 122.79 0.0525 2340 0.545 0.556 Room costs excluded ($0) 20.58 0.0077 2682 0.506 0.508 Number of beds in ward [33] 109.78 0.0093 11,812 0.505 0.518 Program length (5000 admissions) 113.05 0.0023 50,094 0.457 0.499 Isolation, decreased effectiveness (0.75) 99.52 0.0002 510,676 0.458 0.476 Time horizon, 1 year 109.61 0.0001 856,297 0 0.259 Universal screening VRE screening 151.44 −0.0039 Dominated 0.484 0.500 and isolation VRE Prevalence in-hospital, 0.5x 108.41 −0.0112 Dominated 0.479 0.501 Signifies asymptote at that probability at $50,000/QALY CE cost-effectiveness, ICER incremental cost-effectiveness ratio, QALY quality-adjusted life year, VRE vancomycin-resistant enterococci Mac et al. Antimicrobial Resistance and Infection Control (2019) 8:168 Page 8 of 10 ICU. However, similar to other studies, our model esti- study by Huskins and colleagues suggesting prevention mated that active VRE screening and isolation strategy effectiveness of 75% (range 62–82%) [40], and the ICER was cost-effective by reducing the number of VRE-related increased to $510,676/QALY. In this scenario, VRE bacteremia events by 2/10,000 patients [36, 37]. screening and isolation would unlikely be cost-effective Our study has several limitations. Health state utilities at commonly used thresholds. Due to stochasticity (ran- were not specific to VRE infections and preference elicit- domness), it is likely that the cost-effectiveness and iso- ation was heterogeneous. To address this and other param- lation effectiveness have a nonlinear relationship. This eter uncertainty (e.g. costs and transition probabilities), we may be of note to decision-makers and infection preven- conducted a PSA with the appropriate underlying distribu- tion and control practitioners, to ensure implementation tion for all parameters to generate a CEAC for cost- of this program is as seamless as possible. effectiveness thresholds of $0 to $50,000/QALY. VRE Cost-effectiveness analyses for screening programs of screening and isolation was more likely to be cost-effective other AMR bacteria such as carbapenemase-producing than no VRE screening and isolation at a CET of $7500/ Enterobacteriaceae and MRSA have been published in QALY or greater. However, as the CET increased to $50, the literature [41, 42]. Similar to these other economic 000/QALY, the likelihood of the program being cost- evaluations on AMR bacteria screening and isolation, effective in extended simulations remained steady at 51%, our results indicated that VRE screening and isolation suggesting that stochasticity (randomness) is a significant was likely to be cost-effective. To our knowledge, this is factor in determining the value of this control program. the first cost-effectiveness analysis for VRE screening This was expected for this type of intervention since indi- and isolation in any hospital setting that incorporated vidual level uncertainty with patients entering a general costs, health outcomes, and QALYs, accrued over a pa- medicine ward and the baseline VRE prevalence can influ- tient’s lifetime. We reported health outcomes per 1000 ence VRE transmission. patients to allow for transferability of our results to gen- Our study assumed a general medicine ward that was eral medicine wards in different jurisdictions. Moreover, set up with 20 single bed rooms, which may not be the the results of this cost-effectiveness analysis can be configuration of all general medicine wards. In a sce- generalizable to other jurisdictions (countries) with simi- nario where 30-beds were used, the ICER increased to lar healthcare system financing to Canada such as $11,812/QALY. These results suggest that an increase in Australia, the United Kingdom, and parts of Europe. We the number of beds would still yield cost-effective VRE also estimated the cost-effectiveness of this program in screening and isolation practices due to the homoge- varying scenarios (e.g. varying VRE prevalence, number neous mixing assumption. This assumption was made of beds) to provide decision-makers with economic evi- despite knowing that VRE transmission can be highly dence to support local health policy given the import- complex and depend on colonization pressure and dens- ance of local context. ity of bacteria [33]. Incorporating such detail of VRE Given the limited body of evidence in this area, we were colonization levels within the transmission modeling of unable to find a suitable source of data against which to this CEA would require much more sophisticated VRE validate our results. As more local research on AMR bac- surveillance data that was not available. We did not ex- teria continues, it will allow for future models to be cross- plore the value of this program in which patients shared validated to health outcomes using health administrative rooms. However, based on Hamel et al., the hazard ratio data, ward caseload (e.g. bed capacity), admission data for VRE colonisation was 1.11 (95% CI, 1.02–1.21) for (e.g. population characteristics), and number of VRE- the number of roommate exposures per day [38]. Our related bacteremia cases. estimates using a single-bed room assumption was a conservative approach, and therefore likely underesti- mated the cost-effectiveness of a VRE screening and iso- Conclusion lation control program. Our model likely provided a VRE screening and isolation for patients at risk for col- conservative estimate of the cost-effectiveness (i.e. un- onisation in the general medicine ward can be consid- derestimates the value) of VRE screening and isolation ered a cost-effective infection prevention and control due to key assumptions required for our analysis (e.g. intervention in this simulation study. The intervention’s did not incorporate time dependency within the ward, cost-effectiveness varied depending on VRE prevalence or re-admissions). and isolation effectiveness. This model would need to be Isolation was assumed to be completely effective in adapted to more accurately estimate the impact in spe- our base-case analysis, which can be considered optimis- cific local contexts but can provide broad economic evi- tic in current healthcare settings given the potential for dence to inform infection prevention and control human errors, and overall burden on healthcare workers practitioners, program planners and health policy [39, 40]. We performed a scenario analysis based on a decision-makers. Mac et al. Antimicrobial Resistance and Infection Control (2019) 8:168 Page 9 of 10 Supplementary information 2. Johnstone J, Chen C, Rosella L, Adomako K, Policarpio ME, Lam F, et al. Supplementary information accompanies this paper at https://doi.org/10. Patient- and hospital-level predictors of vancomycin-resistant Enterococcus 1186/s13756-019-0628-x. (VRE) bacteremia in Ontario, Canada. Am J Infect Control. 2018;46(11):1266–71. 3. Lloyd-Smith P, Younger J, Lloyd-Smith E, Green H, Leung V, Romney MG. Economic analysis of vancomycin-resistant enterococci at a Canadian hospital: Additional file 1. CHEERS Checklist. assessing attributable cost and length of stay. J Hosp Infect. 2013;85(1):54–9. 4. Siegel JD, Rhinehart E, Jackson M, Chiarello L, Gordon SM, Harrell LJ, et al. 2007 guideline for isolation precautions: preventing transmission of Abbreviations infectious agents in health care settings. Am J Infect Control. 2007;35:S65–164. AMR: Antimicrobial resistant; CADTH: Canadian Agency for Drugs and 5. Cookson BD, Macrae MB, Barrett SP, Brown DFJ, Chadwick C, French GL, Technology for Health; CEAC: Cost-effectiveness acceptability curve; et al. 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