Greg Zaric a Professor of Management Science at Ivey and also a Professor in the Department of Epidemiology and Biostatistics in the Schulich School of Medicine and Dentistry. He is the Academic Director of the MSc Program as well as the MMA Program. He previously held the Canada Research Chair in Health Care Management Science. Greg is a member of several editorial boards and currently serves as Editor-in-Chief of the journal Health Care Management Science.
Greg’s research focuses on developing mathematical models to analyze problems in health economics, health policy, and healthcare operations. Greg has done consulting work with several organizations, such as the London Health Sciences Centre, Ontario Ministry of Health and Long Term Care, Canadian Agency for Drugs and Technologies in Health, and several pharmaceutical companies.
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Hong, M.; Devlin, R. A.; Zaric, G. S.; Thind, A.; Sarma, S., 2024, "Primary care services and emergency department visits in blended fee-for-service and blended capitation models: evidence from Ontario, Canada", The European Journal of Health Economics, April 25
Abstract: INTRODUCTION It is well-known that the way physicians are remunerated can affect delivery of health care services to the population. Fee-for-service (FFS) generally leads to oversupply of services, while capitation leads to undersupply of services. However, little evidence exists on the link between remuneration and emergency department (ED) visits. We fill this gap using two popular blended models introduced in Ontario, Canada: the Family Health Group (FHG), an enhanced/blended FFS model, and Family Health Organization (FHO), a blended capitation model. We compare primary care services and rates of emergency department ED visits between these two models. We also evaluate whether these outcomes vary by regular- and after-hours, and patient morbidity status. METHODS Physicians practicing in an FHG or FHO between April 2012 and March 2017 and their enrolled adult patients were included for analyses. The covariate-balancing propensity score weighting method was used to remove the influence of observable confounding and negative-binomial and linear regression models were used to evaluate the rates of primary care services, ED visits, and the dollar value of primary care services delivered between FHGs and FHOs. Visits were stratified as regular- and after-hours. Patients were stratified into three morbidity groups: non-morbid, single-morbid, and multimorbid (two or more chronic conditions). RESULTS 6184 physicians and their patients were available for analysis. Compared to FHG physicians, FHO physicians delivered 14% (95% CI 13%, 15%) fewer primary care services per patient per year, with 27% fewer services during after-hours (95% CI 25%, 29%). Patients enrolled to FHO physicians made 27% more less-urgent (95% CI 23%, 31%) and 10% more urgent (95% CI 7%, 13%) ED visits per patient per year, with no difference in very-urgent ED visits. Differences in the pattern of ED visits were similar during regular- and after-hours. Although FHO physicians provided fewer services, multimorbid patients in FHOs made fewer very-urgent and urgent ED visits, with no difference in less-urgent ED visits. CONCLUSION Primary care physicians practicing in Ontario's blended capitation model provide fewer primary care services compared to those practicing in a blended FFS model. Although the overall rate of ED visits was higher among patients enrolled to FHO physicians, multimorbid patients of FHO physicians make fewer urgent and very-urgent ED visits.
Link(s) to publication:
http://dx.doi.org/10.1007/s10198-023-01591-w
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Begen, M. A.; Rodrigues, F.; Rice, T.; Zaric, G. S., 2024, "A Forecasting Tool for a Hospital to Plan Inbound Transfers of COVID-19 Patients from Other Regions", Bmc Public Health, February 24(505)
Abstract: Background: In April 2021, Ontario, Canada, was at the peak of its third wave of the COVID-19 pandemic. Intensive Care Unit (ICU) capacity in the Toronto metropolitan area was insufficient to handle local COVID patients. As a result, some patients from the Toronto metropolitan area were transferred to other regions.
Methods: A spreadsheet-based Monte Carlo simulation tool was built to help a large tertiary hospital plan and make informed decisions about the number of transfer patients it could accept from other hospitals. The model was implemented in Microsoft Excel to enable it to be widely distributed and easily used. The model estimates the probability that each ward will be overcapacity and percentiles of utilization daily for a one-week planning horizon.
Results: The model was used from May 2021 to February 2022 to support decisions about the ability to accept transfers from other hospitals. The model was also used to ensure adequate inpatient bed capacity and human resources in response to various COVID-related scenarios, such as changes in hospital admission rates, managing the impact of intra-hospital outbreaks and balancing the COVID response with planned hospital activity.
Conclusions: Coordination between hospitals was necessary due to the high stress on the health care system. A simple planning tool can help to understand the impact of patient transfers on capacity utilization and improve the confidence of hospital leaders when making transfer decisions. The model was also helpful in investigating other operational scenarios and may be helpful when preparing for future outbreaks or public health emergencies.
Link(s) to publication:
http://dx.doi.org/10.1186/s12889-024-18038-3
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Hafeez, A.; Cipriano, L. E.; Kim, R. B.; Zaric, G. S.; Schwarz, U. I.; Sarma, S., 2024, "Cost-Effectiveness Analysis of Pharmacogenomics (PGx)-Based Warfarin, Apixaban, and Rivaroxaban Versus Standard Warfarin for the Management of Atrial Fibrillation in Ontario, Canada", PharmacoEconomics, January 42(1): 69 - 90.
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Murray, L. L.; Wilson, J. G.; Rodrigues, F.; Zaric, G. S., 2023, "Forecasting ICU Census by Combining Time Series and Survival Models", Critical Care Explorations, May 5(5)
Abstract: OBJECTIVES: Capacity planning of ICUs is essential for effective management of health safety, quality of patient care, and the allocation of ICU resources. Whereas ICU length of stay (LOS) may be estimated using patient information such as severity of illness scoring systems, ICU census is impacted by both patient LOS and arrival patterns. We set out to develop and evaluate an ICU census forecasting algorithm using the Multiple Organ Dysfunction Score (MODS) and the Nine Equivalents of Nursing Manpower Use Score (NEMS) for capacity planning purposes. DESIGN: Retrospective observational study. SETTING: We developed the algorithm using data from the Medical-Surgical ICU (MSICU) at University Hospital, London, Canada and validated using data from the Critical Care Trauma Centre (CCTC) at Victoria Hospital, London, Canada. PATIENTS: Adult patient admissions (7,434) to the MSICU and (9,075) to the CCTC from 2015 to 2021. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We developed an Autoregressive integrated moving average time series model that forecasts patients arriving in the ICU and a survival model using MODS, NEMS, and other factors to estimate patient LOS. The models were combined to create an algorithm that forecasts ICU census for planning horizons ranging from 1 to 7 days. We evaluated the algorithm quality using several fit metrics. The root mean squared error ranged from 2.055 to 2.890 beds/d and the mean absolute percentage error from 9.4% to 13.2%. We show that this forecasting algorithm provides a better fit when compared with a moving average or a time series model that directly forecasts ICU census. Additionally, we evaluated the performance of the algorithm using data during the global COVID-19 pandemic and found that the error of the forecasts increased proportionally with the number of COVID-19 patients in the ICU. CONCLUSIONS: It is possible to develop accurate tools to forecast ICU census. This type of algorithm may be important to clinicians and managers when planning ICU capacity as well as staffing and surgical demand planning over a short time horizon.
Link(s) to publication:
https://journals.lww.com/ccejournal/fulltext/2023/05000/forecasting_icu_census_by_combining_time_series.8.aspx
http://dx.doi.org/10.1097/CCE.0000000000000912
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Naderi, B.; Begen, M. A.; Zaric, G. S.; Roshanaei, V., 2023, "A Novel and Efficient Exact Technique for Integrated Staffing, Assignment, Routing, and Scheduling of Home Care Services Under Uncertainty", Omega-International Journal of Management Science, April 116: 102805 - 102805.
Abstract: We model and solve an integrated multi-period staffing, assignment, routing, and scheduling for home care services under uncertainty. The goal is to construct a weekly schedule that adheres to related operational considerations and determines optimal staffing of caregivers by minimizing caregivers’ fixed- and overtime costs. For tractability, we incorporate a priori generated visit patterns—an existing practical approach that deals effectively with hard assignment decisions in. First, we propose a novel mixed-integer program (MIP) for the nominal problem. We then incorporate uncertainty in service and travel times and develop a robust counterpart by hybridizing interval and polyhedral uncertainty sets. Second, we show that there is a special mathematical structure within the model that allows us to develop a novel logic-based Benders branching-decomposition algorithm that systematically delays the resolution of difficult routing/ scheduling problems and efficiently solves both the nominal and robust MIP models. Using a dataset from the literature, we show that CPLEX can solve our nominal and robust models with an average optimality gaps of 44.56% and 45.53%, respectively. Using the same dataset, we demonstrate that our new exact technique can solve our nominal and robust mixed-integer models to an average optimality gap of 2.8% and 4.5%, respectively. Third, we provide practical insights into (i) the price of robustness and (ii) the impacts of nurse flexibility and overtime. The average total cost does not increase beyond 12.7% than the nominal solution and the cost-savings of nurse flexibility is approximately five times higher than that of overtime.
Link(s) to publication:
https://www.sciencedirect.com/science/article/pii/S0305048322002110
http://dx.doi.org/10.1016/j.omega.2022.102805
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Strohbehn, G. W.; Cooperrider, J. H.; Yang, D.; Fendrick, A. M.; Ratain, M. J.; Zaric, G. S., 2022, "Pfizer and Palbociclib in China: Analyzing an Oncology Pay-for-Performance Plan", Value in Health Regional Issues, September 31: 34 - 38.
Abstract: Objectives: China is poised to become the world’s second-largest oncology drug market. Its ability to continue broadening health coverage is in question. Institutional innovations such as performance-based risk-sharing agreements (PBRSAs) have been developed to promote access to novel therapeutics beyond that provided by public health insurance and central procurement systems. We examine in depth the financial implications of a PBRSA developed in China for the breast cancer drug palbociclib.
Methods: We generated a 2-state Markov model from PBRSA information made publicly available. Model inputs included breast cancer outcomes data from the published literature. The primary analysis estimates the percentage reduction in overall drug expenditures due to the PBRSA. Sensitivity analyses explored the financial impact of varied computed tomography scan utilization, rebate rate, and rebate duration.
Results: Estimated palbociclib expenditures for the PBRSA cohort totaled $36 278 000. Based on the publicly available information for the PBRSA, an effective discount of 1.3% was estimated. The effective discount was insensitive to changes in computed tomography scan utilization.
Conclusions: The palbociclib PBRSA likely had negligible impact on patient access to therapy and limited downstream financial impact to patients and payers. The short duration of the rebate window, small rebate, and disease indolence contributed to the low expected rebate percentage.
Link(s) to publication:
http://dx.doi.org/10.1016/j.vhri.2022.01.007
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Naderi, B.; Begen, M. A.; Zaric, G. S., 2022, "Type-2 integrated process-planning and scheduling problem: Reformulation and solution algorithms", Computers and Operations Research, June 142
Abstract: We study the type-2 integrated process-planning and scheduling (IPPS) problem where each job is represented by a directed network graph. To the best of our knowledge, there is only one mathematical model in the literature implementing the type-2 IPPS partially, and the solution methods available for this problem are all based on heuristics and metaheuristics. We introduce three properties that enable us to fully formulate all aspects of the type-2 IPPS problem with a mathematical programming model for the first time. To solve our model, we develop a logic-based Benders decomposition method hybridized with constraint programming. We decompose the problem into two smaller ones such that we can use the best solution technique for each one, master problem and subproblem. To enhance our solution approach, we incorporate a combinatorial relaxation of subproblem into the master problem. We evaluate our method using a well-known benchmark including 24 instances and compare its performance with six existing solution methods solving the same benchmark. We solve all the 24 instances of this benchmark to optimality where seven of these 24 instances are solved to optimality for the first time. We also generate a new set of 144 larger instances to further evaluate our solution methods and provide insights on when each method performs better.
Link(s) to publication:
http://dx.doi.org/10.1016/j.cor.2022.105728
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Cipriano, L. E.; Haddara, W. M. R.; Zaric, G. S.; Enns, E. A., 2021, "Impact of University Re-opening on Total Community COVID-19 Burden", PLOS ONE, August 16(8): e0255782 - e0255782.
Abstract: Background: University students have higher average number of contacts than the general population. Students returning to university campuses may exacerbate COVID-19 dynamics in the surrounding community.
Methods: We developed a dynamic transmission model of COVID-19 in a mid-sized city currently experiencing a low infection rate. We evaluated the impact of 20,000 university students arriving on September 1 in terms of cumulative COVID-19 infections, time to peak infections, and the timing and peak level of critical care occupancy. We also considered how these impacts might be mitigated through screening interventions targeted to students.
Results: If arriving students reduce their contacts by 40% compared to pre-COVID levels, the total number of infections in the community increases by 115% (from 3,515 to 7,551), with 70% of the incremental infections occurring in the general population, and an incremental 19 COVID-19 deaths. Screening students every 5 days reduces the number of infections attributable to the student population by 42% and the total COVID-19 deaths by 8. One-time mass screening of students prevents fewer infections than 5-day screening, but is more efficient, requiring 196 tests needed to avert one infection instead of 237.
Interpretation: University students are highly inter-connected with the surrounding off-campus community. Screening targeted at this population provides significant public health benefits to the community through averted infections, critical care admissions, and COVID-19 deaths.
Link(s) to publication:
http://dx.doi.org/10.1371/journal.pone.0255782
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Ghamat, S.; Zaric, G. S.; Pun, H., 2021, "Care-coordination: Gain-sharing Agreements in Bundled Payment Models", Production and Operations Management, May 30(5): 1457 - 1474.
Abstract: We study gain-sharing agreements in a target price-minimum quality payment system. Our work is inspired by the Centers for Medicare and Medicaid Services’ (CMS) Comprehensive Care for Joint Replacement (CJR) bundled payment model. In our model, patients receive care from a hospital and a post-acute care provider. A third-party payer establishes target levels for total billing by the hospital and provider, and a target on the overall quality of care. The hospital and provider receive fee-for-service (FFS) billings during an episode of care, defined as the period that starts with an admission of a patient to the hospital and ends 90 days post-discharge. The hospital may also receive an incentive payment if total FFS billing by both parties is below the target price and total quality by both parties is above the minimum quality. The goal of the incentive payment is to encourage hospitals to enter into “gain-sharing” agreements with providers. We model the interactions between the three parties. We show that while using a gain-sharing agreement might be a “win-win-win” scenario for the three parties, good design of the payment scheme by the payer is essential to incentivize a hospital to participate in the bundled payment model (e.g., CJR) and sign a gain-sharing agreement with the provider. Furthermore, we illustrate that a target price-minimum quality bundled payment model would be more effective, in care-coordination, in healthcare settings where the provider is much more effective than the hospital in reducing its billing.
Link(s) to publication:
http://dx.doi.org/10.1111/poms.13332
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Bamimore, M. A.; Devlin, R. A.; Zaric, G. S.; Garg, A. X.; Sarma, S., 2021, "Quality of Diabetes Care in Blended Fee-for-Service and Blended Capitation Payment Systems", Canadian Journal of Diabetes, April 45(3): 261 - 268.
Abstract: © 2020 Canadian Diabetes Association Objectives: In the middle to late 2000s, many family physicians switched from a Family Health Group (FHG; a blended fee-for-service model) to a Family Health Organization (FHO; a blended capitation model) in Ontario, Canada. The evidence on the link between physician remuneration schemes and quality of diabetes care is mixed in the literature. We examined whether physicians who switched from the FHG to FHO model provided better care for individuals living with diabetes relative to those who remained in the FHG model. Methods: Using longitudinal health administrative data from 2006 to 2016, we investigated the impact of physicians switching from FHG to FHO on 8 quality indicators related to diabetes care. Because FHO physicians are likely to be systematically different from FHGs, we employed propensity-score-based inverse probability-weighted fixed-effects regression models. All analyses were conducted at the physician level. Results: We found that FHO physicians were more likely to provide glycated hemoglobin testing by 2.75% (95% confidence interval [CI], 1.89% to 3.60%), lipid assessment by 2.76% (CI, 1.95% to 3.57%), nephropathy screening by 1.08% (95% CI, 0.51% to 1.66%) and statin prescription by 1.08% (95% CI, 0.51% to 1.66%). Patients under FHOs had a lower estimated risk of mortality by 0.0124% (95% CI, 0.0123% to 0.0126%) per physician per year. However, FHG and FHO physicians were similar for annual eye examination, prescription of angiotensin-converting enzyme inhibitors (or angiotensin II receptor blockers) and patients’ risk of avoidable diabetes-related hospitalizations. Conclusions: Compared with blended fee-for-service, blended capitation payment is associated with a small, but statistically significant, improvement in some aspects of diabetes care.
Link(s) to publication:
http://dx.doi.org/10.1016/j.jcjd.2020.09.002
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Qu, X. M.; Chen, Y.; Zaric, G. S.; Senan, S.; Olson, R. A.; Harrow, S.; John-Baptiste, A.; Gaede, S.; Mulroy, L. A.; Schellenberg, D., et al., 2021, "Is SABR Cost-Effective in Oligometastatic Cancer? An Economic Analysis of the SABR-COMET Randomized Trial", International Journal of Radiation Oncology Biology Physics, April 109(5): 1176 - 1184.
Abstract: The phase 2 randomized study SABR-COMET demonstrated that in patients with controlled primary tumors and 1 to 5 oligometastatic lesions, SABR was associated with improved progression-free survival (PFS) compared with standard of care (SoC), but with higher costs and treatment-related toxicities. The aim of this study was to assess the cost-effectiveness of SABR versus SoC in this setting. Methods and Materials: A Markov model was constructed to perform a cost-utility analysis from the Canadian health care system perspective. Utility values and transition probabilities were derived from individual-level data from the SABR-COMET trial. One-way, 2-way, and probabilistic sensitivity analyses were performed. Costs were expressed in 2018 CAD. A separate analysis based on US payer's perspective was performed. An incremental cost-effectiveness ratio (ICER) at a willingness-to-pay threshold of $100,000 per quality-adjusted life year (QALY) was used. Results: In the base case scenario, SABR was cost-effective at an ICER of $37,157 per QALY gained. This finding was most sensitive to the number of metastatic lesions treated with SABR (ICER: $28,066 per QALY for 2, increasing to $64,429 per QALY for 5), difference in chemotherapy use (ICER: $27,173-$53,738 per QALY), and PFS hazard ratio (HR) between strategies (ICER: $31,548-$53,273 per QALY). Probabilistic sensitivity analysis revealed that SABR was cost-effective in 97% of all iterations. Two-way sensitivity analysis demonstrated a nonlinear relationship between the number of lesions and the PFS HR. To maintain cost-effectiveness for each additional metastasis, the HR must decrease by approximately 0.047. The US cost analysis yielded similar results, with an ICER of $54,564 (2018 USD per QALY) for SABR. Conclusions: SABR is cost-effective for patients with 1 to 5 oligometastatic lesions compared with SoC.
Link(s) to publication:
http://dx.doi.org/10.1016/j.ijrobp.2020.12.001
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Reid, G. J.; Stewart, S. L.; Barwick, M.; Cunningham, C.; Carter, J.; Evans, B.; Leschied, A.; Neufeld, R. W. J.; St. Pierre, J.; Tobon, J., et al., 2021, "Exploring Patterns of Service Utilization Within Children’s Mental Health Agencies", Journal of Child and Family Studies, February 30: 556 - 574.
Abstract: The natural history of psychopathology indicates that many children will re-experience mental health problems. However, little is known about service use over extended time periods. We explored service use of a 5-year time period, and expected to find that some children received mental health services for many months, and some received services in episodes. Administrative visit data from 6 child and youth mental health service agencies and over 7000 children, 4 to 11 years old at their first visit in 2000–2003, were analyzed. Episodes of care were coded based on having a minimum of three visits with 180-day free period between episodes. Chart reviews were conducted for a stratified random sample of 319 cases to obtain clinical and demographic sample characteristics not available in the administrative data. Five patterns of service use were identified in 5 years of visit data using latent class cluster analyses. Close to a third of children were involved for longer than a year, and 19% received two or more episodes of care within the 5-year study period. Children who had patterns of service use with long durations of involvement tended to have a higher percentage of cases with child welfare involvement, and children had fewer strengths in terms of relationships with peers and adults, and abilities to manage negative life experiences. Best methods of caring for children with ongoing or episodic problems need to be developed, and we need to improve methods for identifying those children who might benefit from alternative models of care.
Link(s) to publication:
http://dx.doi.org/10.1007/s10826-020-01859-2
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Schraeder, K. E.; Barwick, M.; Cairney, J.; Carter, J.; Kurdyak, P.; Neufeld, R. W. J.; Stewart, S. L.; Pierre, J. S.; Tobon, J.; Vingilis, E., et al., 2021, "Re-accessing mental health care after age 18: A longitudinal cohort study of youth involved with community-based child and youth mental health agencies in Ontario", Journal of the Canadian Academy of Child and Adolescent Psychiatry, February 30(1): 12 - 24.
Abstract: Objective: About 20-26% of children and youth with a mental health disorder (depending on age and respondent) report receiving services from a community-based Child and Youth Mental Health (CYMH) agency. However, because agencies have an upper age limit of 18-years old, youth requiring ongoing mental health services must “transition” to adult-oriented care. General healthcare providers (e.g., family physicians) likely provide this care. The objective of this study was to compare the likelihood of receiving physician-based mental health services after age 18 between youth who had received community-based mental health services and a matched population sample. Method: A longitudinal matched cohort study was conducted in Ontario, Canada. A CYMH cohort that received mental health care at one of five CYMH agencies, aged 7-14 years at their first visit (N=2,822), was compared to age, sex, region-matched controls (N=8,466). Results: CYMH youth were twice as likely as the comparison sample to have a physician-based mental health visit (i.e., by a family physician, pediatrician, psychiatrists) after age 18; median time to first visit was 3.3 years. Having a physician mental health visit before age 18 was associated with a greater likelihood of experiencing the outcome than community-based CYMH services alone. Conclusion: Most youth involved in community-based CYMH agencies will re-access services from physicians as adults. Youth receiving mental health services only within community agencies, and not from physicians, may be less likely to receive physician-based mental health services as adults. Collaboration between CYMH agencies and family physicians may be important for youth who require ongoing care into adulthood.
Link(s) to publication:
https://pubmed.ncbi.nlm.nih.gov/33552169/
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Hong, M.; Thind, A.; Zaric, G. S.; Sarma, S., 2021, "Emergency department use following incentives to provide after-hours primary care: A retrospective cohort study", Canadian Medical Association Journal, January 193(3): E85 - E93.
Abstract: BACKGROUND: Access to primary care outside of regular working hours is limited in many countries. This study investigates the relation between the after-hours premium, an incentive for primary care physicians to provide services after hours, and less-urgent visits to the emergency department in Ontario, Canada. METHODS: We analyzed a retrospective cohort of a random sample of Ontario residents from April 2002 to March 2006, and a subcohort of patients followed from April 2005 to March 2016. We linked patient and primary care physician data with emergency department visit data. We used fixed-effects regression models to analyze the association between the introduction of the after-hours premium, as well as subsequent increases in the value of the premium, and the number of monthly emergency department visits. RESULTS: The sample consisted of 586 534 patients between 2002 and 2006, and 201 594 patients from 2005 to 2016. After controlling for patient and physician characteristics, seasonality and time-invariant patient confounding factors, introduction of the after-hours premium was associated with a reduction of 1.26 less-urgent visits to the emergency department per 1000 patients per month (95% confidence interval -1.48 to -1.04). Most of this reduction was observed in after-hours visits. Sensitivity analysis showed that the monthly reduction in less-urgent visits to the emergency department was in the range of -1.24 to -1.16 per 1000 patients. Subsequent increases in the after-hours premium were associated with a small reduction in less-urgent visits to the emergency department. INTERPRETATION: Ontario's experience suggests that incentivizing physicians to improve access to after-hours primary care reduces some less-urgent visits to the emergency department. Other jurisdictions may consider incentives to limit less-urgent visits to the emergency department.
Link(s) to publication:
http://dx.doi.org/10.1503/cmaj.200277
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Zaric, G. S., 2021, "How Risky Is That Risk Sharing Agreement? Mean-Variance Tradeoffs and Unintended Consequences of Six Common Risk Sharing Agreements", Medical Decision Making: Policy & Practice, January 6(1): 238146832199040 - 238146832199040.
Abstract: Background. Pharmaceutical risk sharing agreements (RSAs) are commonly used to manage uncertainties in costs and/or clinical benefits when new drugs are added to a formulary. However, existing mathematical models of RSAs ignore the impact of RSAs on clinical and financial risk. Methods. We develop a model in which the number of patients, total drug consumption per patient, and incremental health benefits per patient are uncertain at the time of the introduction of a new drug. We use the model to evaluate the impact of six common RSAs on total drug costs and total net monetary benefit (NMB). Results. We show that, relative to not having an RSA in place, each RSA reduces expected total drug costs and increases expected total NMB. Each RSA also improves two measures of risk by reducing the probability that total drug costs exceed any threshold and reducing the probability of obtaining negative NMB. However, the effects on variance in both NMB and total drug costs are mixed. In some cases, relative to not having an RSA in place, implementing an RSA can increase variability in total drug costs or total NMB. We also show that, for some RSAs, when their parameters are adjusted so that they have the same impact on expected total drug cost, they can be rank-ordered in terms of their impact on variance in drug costs. Conclusions. Although all RSAs reduce expected total drug costs and increase expected total NMB, some RSAs may actually have the undesirable effect of increasing risk. Payers and formulary managers should be aware of these mean-variance tradeoffs and the potentially unintended results of RSAs when designing and negotiating RSAs.
Link(s) to publication:
http://dx.doi.org/10.1177/2381468321990404
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