Lauren E. Cipriano
Associate Professor, Management Science
Associate Professor, Epidemiology and Biostatistics
Deputy Editor, Medical Decision Making and Medical Decision Making Policy & Practice
Canada Research Chair in Healthcare Analytics, Management, and Policy
- Faculty >
Richard Ivey Building 2361
- Public Policy
- Health Care Management Science
- Health Economics
- Cost Effectiveness Analysis
- Markov Models
- Health Sector
- Technology adoption
- Spreadsheets & VBA
- Health Policy Evaluation
- To search for publications by a specific faculty member, select the database and then select the name from the Author drop down menu.
Lauren Cipriano is an Associate Professor in Management Science at the Ivey Business School. She holds cross appointments in the Department of Medicine and the Department of Epidemiology and Biostatistics at the Schulich School of Medicine & Dentistry.
Dr. Cipriano’s research expertise focuses on the application of statistics, decision analysis, economics, and operations research to health policy problems. She has specific expertise in the economic evaluation of clinical diagnostics and novel therapeutics, resource allocation, and infectious disease policy. Dr. Cipriano holds a Canada Research Chair in Healthcare Analytics, Management, and Policy.
Dr. Cipriano has consulted for the World Health Organization, US Veterans Health Administration, US Centers for Medicare and Medicaid Services, the US Institute for Clinical and Economic Review, and the Canadian Agency for Drugs and Technologies in Health (CADTH). During the pandemic, Dr. Cipriano served on the Ontario COVID-19 Science Advisory Table’s Modelling Consensus Table.
Dr. Cipriano sits on the Health Economics Methods Advisory Committee for the Canadian Agency for Drugs and Technologies in Health (CADTH) and was awarded the Dr. Maurice McGregor Award for Health Technology Assessment in 2018.
Dr. Cipriano is the Deputy Editor of the journals Medical Decision Making and MDM Policy & Practice.
Dr. Cipriano received her MS in Statistics and PhD in Management Science and Engineering from Stanford University. She previously worked at the Ontario Joint Replacement Registry at London Health Sciences Centre and the Institute for Technology Assessment at Massachusetts General Hospital.
Dr. Cipriano joined Ivey in 2013. At Ivey, Dr. Cipriano teaches undergraduate Decision Making with Analytics and graduate courses in Business Analytics and Statistics.
- Decision Making with Analytics, HBA core
- Multivariate Stats, PhD
- B.Sc., Honors Biochemistry, Western University
- HBA, Ivey Business School, Western University
- M.S., Statistics, Stanford University
- Ph.D., Management Science, Stanford University
Recent Refereed Articles
- Bansback, N. J.; Barbosa, C.; Barocas, J.; Bayoumi, A. M.; Behrends, C.; Chhatwal, J.; Cipriano, L. E.; Coffin, P.; Goldhaber-Fiebert, J. D.; Hoch, J., et al., 2021, "How simulation modeling can support the public health response to the opioid crisis in North America: Setting priorities and assessing value", International Journal of Drug Policy, April 88: 102726 - 102726.
Yarmol-Matusiak, E. A.; Cipriano, L. E.; Stranges, S., 2021, "A comparison of COVID-19 epidemiological indicators in Sweden, Norway, Denmark, and Finland", SCANDINAVIAN JOURNAL OF PUBLIC HEALTH, February 49(1): 69 - 78. Abstract: Aims: To compare the early impact of COVID-19 infections and mortality from February to July 2020 across the Nordic nations of Sweden, Norway, Denmark, and Finland through available public data sources and conduct a descriptive analysis of the potential factors that drove different epidemiological outcomes, with a focus on Sweden’s response. Methods: COVID-19 cases, deaths, tests, case age distribution, and the difference between 2020 all-cause mortality and the average mortality of the previous 5 years were compared across nations. Patterns in cell phone mobility data, testing strategies, and seniors’ care home deaths were also compared. Data for each nation were based on publicly available sources as of July 31, 2020. Results: Compared with its Nordic peers, Sweden had a higher incidence rate across all ages, a higher COVID-19-related death rate only partially explained by population demographics, a higher death rate in seniors’ care, and higher all-cause mortality. Sweden had approximately half as much mobility change as its Nordic neighbours until April and followed similar rates as its neighbours from April to July. Denmark led its Nordic peers in testing rates, while Sweden had the highest cumulative test-positivity rate continuously from mid-March. Conclusions: COVID-19 pushed Sweden’s health system to its capacity, exposed systemic weaknesses in the seniors’ care system, and revealed challenges with implementing effective contact tracing and testing strategies while experiencing a high case burden. Looser government restrictions at the beginning of the outbreak are likely to have played a role in the impact of COVID-19 in Sweden. In an effort to improve epidemic control, Sweden has increased testing rates, implemented more restrictive prevention measures, and increased their intensive care unit bed capacity.
Link(s) to publication:
Fairley, M.; Cipriano, L. E.; Goldhaber-Fiebert, J. D., 2020, "Optimal Allocation of Research Funds under a Budget Constraint", Medical Decision Making, August 40(6): 797 - 814. Abstract: Purpose. Health economic evaluations that include the expected value of sample information support implementation decisions as well as decisions about further research. However, just as decision makers must consider portfolios of implementation spending, they must also identify the optimal portfolio of research investments. Methods. Under a fixed research budget, a decision maker determines which studies to fund; additional budget allocated to one study to increase the study sample size implies less budget available to collect information to reduce decision uncertainty in other implementation decisions. We employ a budget-constrained portfolio optimization framework in which the decisions are whether to invest in a study and at what sample size. The objective is to maximize the sum of the studies’ population expected net benefit of sampling (ENBS). We show how to determine the optimal research portfolio and study-specific levels of investment. We demonstrate our framework with a stylized example to illustrate solution features and a real-world application using 6 published cost-effectiveness analyses. Results. Among the studies selected for nonzero investment, the optimal sample size occurs at the point at which the marginal population ENBS divided by the marginal cost of additional sampling is the same for all studies. Compared with standard ENBS optimization without a research budget constraint, optimal budget-constrained sample sizes are typically smaller but allow more studies to be funded. Conclusions. The budget constraint for research studies directly implies that the optimal sample size for additional research is not the point at which the ENBS is maximized for individual studies. A portfolio optimization approach can yield higher total ENBS. Ultimately, there is a maximum willingness to pay for incremental information that determines optimal sample sizes.
Link(s) to publication:
Roseborough, A. D.; Langdon, K. D.; Hammond, R.; Cipriano, L. E.; Pasternak, S. H.; Whitehead, S. N.; Khan, A. R., 2020, "Post-mortem 7 Tesla MRI detection of white matter hyperintensities: A multidisciplinary voxel-wise comparison of imaging and histological correlates", NeuroImage: Clinical, July 27 Abstract: White matter hyperintensities (WMH) occur in normal aging and across diagnostic categories of neurodegeneration. Ultra-high field imaging (UHF) MRI machines offer the potential to improve our understanding of WMH. Post-mortem imaging using UHF magnetic resonance imaging (MRI) is a useful way of assessing WMH, however, the responsiveness of UHF-MRI to pathological changes within the white matter has not been characterized. In this study we report post-mortem MRI sequences of white matter hyperintensities in normal aging, Alzheimer’s disease, and cerebrovascular disease. Seven Tesla post-mortem MRI reliably detected periventricular WMH using both FLAIR and T2 sequences and reflects underlying pathology of myelin and axon density despite prolonged fixation time. Co-registration of histological images to MRI allowed for direct voxel- wise comparison of imaging findings and pathological changes. Myelin content and cerebrovascular pathology were the most significant predictors of MRI white matter intensity as revealed by linear mixed models. Future work investigating the utility of UHF- MRI in studying cell-specific changes within WMH is required to better understand radio-pathologic correlations.
Link(s) to publication:
Azarpazhooh, M. R.; Avan, A.; Cipriano, L. E.; Munoz, D. G.; Erfanian, M.; Amiri, A.; Stranges, S.; Hachinski, V., 2020, "A third of community-dwelling elderly with intermediate and high level of Alzheimer's neuropathologic changes are not demented: A meta-analysis", Ageing Research Reviews, March 58 Abstract: This systematic review and meta-analysis assessed the bidirectional association between AD pathology and dementia in community-dwelling elderly populations. We searched PubMed/MEDLINE, Embase, Scopus, Web of Science, and references of the pertinent articles for community/population-based longitudinal cohorts with regular assessment of cognitive status of participants followed by postmortem neuropathology data, with no language and date restrictions, until 20 September 2019. Finally, we retrieved 18 articles with data from 17 cohorts comprising 4677 persons. Dementia was twice as likely in participants with definitive neuropathological indicator for AD compared to those without it: moderate/high Braak and Braak (BB) stages III–VI of neurofibrillary tangles (54 % vs. 26 % in participants with BB stages 0–II), the Consortium to Establish a Registry for AD (CERAD) moderate/frequent neuritic plaques scores (64 % vs. 33 % in participants with CERAD none/infrequent), and National Institute on Aging and the Reagan Institute of the Alzheimer's Association criteria intermediate/high AD probability (52 % vs. 28 % in participants with no/low AD probability). Accordingly, a substantial proportion of community-dwelling elderly people with definitive AD pathology may not develop dementia. Brain reserve or contribution of other factors and pathologies, such as vascular and degenerative pathology to dementia might explain this apparent discrepancy. These findings also suggest caution in equating Alzheimer pathology biomarkers with dementia.
Link(s) to publication:
Cipriano, L. E.; Goldhaber-Fiebert, J. D., 2019, "Population health and cost-effectiveness implications of a “treat all” recommendation for HCV: A review of the model-based evidence", Medical Decision Making: Policy & Practice, June 3(1) Abstract: The World Health Organization HCV Guideline Development Group is considering a “treat all” recommendation for persons infected with hepatitis C virus (HCV). We reviewed the model-based evidence of cost-effectiveness and population health impacts comparing expanded treatment policies to more limited treatment access policies, focusing primarily on evaluations of all-oral directly acting antivirals published after 2012. Searching PubMed, we identified 2,917 unique titles. Sequentially reviewing titles and abstracts identified 226 potentially relevant articles for full-text review. Sixty-nine articles met all inclusion criteria—42 cost-effectiveness analyses and 30 models of population-health impacts, with 3 articles presenting both types of analysis. Cost-effectiveness studies for many countries concluded that expanding treatment to people with mild liver fibrosis, who inject drugs (PWID), or who are incarcerated is generally cost-effective compared to more restrictive treatment access policies at country-specific prices. For certain patient subpopulations in some countries—for example, elderly individuals without fibrosis—treatment is only cost-effective at lower prices. A frequent limitation is the omission of benefits and consequences of HCV transmission (i.e., treatment as prevention; risks of reinfection), which may underestimate or overestimate the cost-effectiveness of a “treat all” policy. Epidemiologic modeling studies project that through a combination of prevention, aggressive screening and diagnosis, and prompt treatment for all fibrosis stages, it may be possible to virtually eliminate HCV in many countries. Studies show that if resources are not available to diagnose and treat all HCV-infected individuals, treatment prioritization may be needed, with alternative prioritization strategies resulting in tradeoffs between reducing mortality or reducing incidence. Notably, because most new HCV infections are among PWID in many settings, HCV elimination requires unrestricted treatment access combined with injection transmission disruption strategies. The model-based evidence suggests that a properly constructed strategy that substantially expands HCV treatment could achieve cost-effective improvements in population health in many countries.
Link(s) to publication:
Chehrazi, N.; Cipriano, L. E.; Enns, E. A., 2019, "Dynamics of drug resistance: Optimal control of an infectious disease", Operations Research, June 67(3): 599 - 904. Abstract: Antimicrobial resistance is a significant public health threat. In the United States alone, two million people are infected, and 23,000 die each year from antibiotic-resistant bacterial infections. In many cases, infections are resistant to all but a few remaining drugs. We examine the case in which a single drug remains and solve for the optimal treatment policy for a susceptible–infected–susceptible infectious disease model, incorporating the effects of drug resistance. The problem is formulated as an optimal control problem with two continuous state variables: the disease prevalence and drug’s “quality” (the fraction of infections that are drug-susceptible). The decision maker’s objective is to minimize the discounted cost of the disease to society over an infinite horizon. We provide a new generalizable solution approach that allows us to thoroughly characterize the optimal treatment policy analytically. We prove that the optimal treatment policy is a bang-bang policy with a single switching time. The action/inaction regions can be described by a single boundary that is strictly increasing when viewed as a function of drug quality, indicating that, when the disease transmission rate is constant, the policy of withholding treatment to preserve the drug for a potentially more serious future outbreak is not optimal. We show that the optimal value function and/or its derivatives are neither C1 nor Lipschitz continuous, suggesting that numerical approaches to this family of dynamic infectious disease models may not be computationally stable. Furthermore, we demonstrate that relaxing the standard assumption of a constant disease transmission rate can fundamentally change the shape of the action region, add a singular arc to the optimal control, and make preserving the drug for a serious outbreak optimal. In addition, we apply our framework to the case of antibiotic-resistant gonorrhea.
Link(s) to publication:
- Ma, C.; Guizzetti, L.; Cipriano, L. E.; Parker, C.; Nguyen, T.; Gregor, J.; Chande, N.; Feagan, B.; Jairath, V., 2019, "Systematic review and meta-analysis: high prevalence and cost of continued aminosalicylate use in patients with ulcerative colitis escalated to immunosuppressive and biological therapies", Alimentary Pharmacology and Therapeutics, February 49(4): 364 - 374.
Cerasuolo, J. O.; Azarpazhooh, M. R.; Kapral, M. K.; Cipriano, L. E.; Hachinski, V., 2019, "Evidence of Concomitantly Increasing Stroke and Dementia Prevalence among those 80 Years and Older in Ontario, Canada, 2003-04 to 2012-13", Canadian Journal of Neurological Sciences, January 46(1): 105 - 107. Abstract: Among those aged 80 years and older in Ontario, Canada, stroke and dementia incidence declined concomitantly from 2002-03 to 2013-14. This study aimed to report the concurrent temporal trends of stroke and dementia prevalence in Ontario among the same age demographic. The prevalence of both stroke and dementia increased from 2003-04 to 2012-13 in both sexes and the magnitude in which prevalence of dementia increased over time exceeded that of stroke. The substantial increase in the prevalence of dementia may be because of increased recognition and diagnoses of dementia and increased survival of stroke patients who are at higher risk of developing dementia.
Link(s) to publication:
Sheehan, D.; Criss, S.; Chen, Y.; Eckel, A.; Palazzo, L.; Tramontano, A.; Hur, C.; Cipriano, L. E.; Kong, C. Y., 2019, "Lung cancer costs by treatment strategy and phase of care among patients enrolled in Medicare", Cancer Medicine, January 8(1): 94 - 103. Abstract: Background: We studied trends in lung cancer treatment cost over time by phase of care, treatment strategy, age, stage at diagnosis, and histology. Methods: Using the Surveillance, Epidemiology, and End Results (SEER)‐Medicare database for years 1998‐2013, we allocated total and patient‐liability costs into the following phases of care for 145 988 lung cancer patients: prediagnosis, staging, surgery, initial, continuing, and terminal. Patients served as self‐controls to determine cancer‐attributable costs based on individual precancer diagnosis healthcare costs. We fit linear regression models to determine cost by age and calendar year for each stage at diagnosis, histology, and treatment strategy and presented all costs in 2017 US dollars. Results: Monthly healthcare costs prior to lung cancer diagnosis were $861 for a 70 years old in 2017 and rose by an average of $17 per year (P < 0.001). Surgery in 2017 cost $30 096, decreasing by $257 per year (P = 0.007). Chemotherapy and radiation costs remained stable or increased for most stage and histology groups, ranging from $4242 to $8287 per month during the initial six months of care. Costs during the final six months of life decreased for those who died of lung cancer or other causes. Conclusions: Cost‐effectiveness analyses of lung cancer control interventions in the United States have been using outdated and incomplete treatment cost estimates. Our cost estimates enable updated cost‐effectiveness analyses to determine the benefit of lung cancer control from a health economics point of view.
Link(s) to publication:
Mickle, K.; Lasser, K. E.; Hoch, J. S.; Cipriano, L. E.; Dreitlein, W. B.; Pearson, S. D., 2019, "The effectiveness and value of patisiran and inotersen for hereditary transthyretin amyloidosis: A summary from the Institute for Clinical and Economic Review’s midwest comparative effectiveness public advisory council", Journal of Managed Care and Specialty Pharmacy, January 25(1): 10 - 15. Abstract: DISCLOSURES: Funding for this summary was contributed by the Laura and John Arnold Foundation, Blue Shield of California, and California Health Care Foundation to the Institute for Clinical and Economic Review (ICER), an independent organization that evaluates the evidence on the value of health care interventions. ICER’s annual policy summit is supported by dues from Aetna, AHIP, Anthem, Blue Shield of California, CVS Caremark, Express Scripts, Harvard Pilgrim Health Care, Cambia Health Solutions, United Healthcare, Kaiser Permanente, Premera Blue Cross, AstraZeneca, Genentech, GlaxoSmithKline, Johnson & Johnson, Merck, National Pharmaceutical Council, Prime Therapeutics, Sanofi, Spark Therapeutics, Health Care Service Corporation, Editas, Alnylam, Regeneron, Mallinkrodt, Biogen, HealthPartners, and Novartis. Mickle, Dreitlein, and Pearson are ICER employees. Lasser, Cipriano, and Hoch have nothing to disclose. Hereditary transthyretin amyloidosis (hATTR) is a rare, autosomal dominant disease caused by the misfolding of the liver protein transthyretin (TTR). Patients ultimately develop TTR depositions across multiple body systems and organs leading most prominently to progressive polyneuropathy or cardiac dysfunction, with many patients experiencing both. Polyneuropathy associated with hATTR significantly impairs motor, autonomic, and sensory nerve function. Initial neuropathic pain is followed by progressive motor weakness, ultimately leading to the inability to walk. Gastrointestinal impairment due to autonomic neuropathy is also disabling, and it can progress to later-stage wasting and cachexia.2 TTR deposition in cardiac tissue can result in thickening of ventricular walls, diastolic dysfunction, arrhythmia, and heart failure. Approximately 10,000 people worldwide have been diagnosed with hATTR-related neuropathy, of which 3,000-3,500 patients are in the United States. The incidence of cardiomyopathy due to hATTR is largely unknown because of varying estimates of the proportion of patients who develop clinical disease (7%-80%), although prevalence is known to increase with advancing age. The median age at onset of symptoms is 68.1 years, and the median survival time from diagnosis is 5-15 years; survival is shorter for individuals with cardiac involvement (2.5-4 years). Standard treatment for hATTR includes diflunisal and liver transplantation, but neither approach reverses the damage caused by TTR deposits, and both treatments are restricted to relatively healthy patients due to safety and mortality risks. The Institute for Clinical and Economic Review (ICER) recently conducted a review of 2 new first-in-class drugs for hATTR: patisiran (Onpattro, Alnylam Pharmaceuticals) and inotersen (Tegsedi, Akcea Therapeutics). Both drugs aim to reduce TTR by targeting the RNA that produces the misfolded protein, either by enhancing RNA degradation (inotersen) or by reducing its production (patisiran). The U.S. Food and Drug Administration (FDA) approved patisiran on August 10, 2018; when ICER concluded its assessment in September 2018, inotersen was still undergoing FDA review. Here, we present a summary of the systematic literature review, cost-effectiveness analyses, and policy discussion with key stakeholders regarding the overall value of these RNA-targeted therapies. The full report is published on ICER’s website at www.icer-review.org.
Link(s) to publication:
Cipriano, L. E.; Weber, T. A., 2018, "Population-level intervention and information collection in dynamic healthcare policy", Health Care Management Science, December 21(4): 604 - 631. Abstract: © 2017 The Author(s) We develop a general framework for optimal health policy design in a dynamic setting. We consider a hypothetical medical intervention for a cohort of patients where one parameter varies across cohorts with imperfectly observable linear dynamics. We seek to identify the optimal time to change the current health intervention policy and the optimal time to collect decision-relevant information. We formulate this problem as a discrete-time, infinite-horizon Markov decision process and we establish structural properties in terms of first and second-order monotonicity. We demonstrate that it is generally optimal to delay information acquisition until an effect on decisions is sufficiently likely. We apply this framework to the evaluation of hepatitis C virus (HCV) screening in the general population determining which birth cohorts to screen for HCV and when to collect information about HCV prevalence.
Link(s) to publication:
Ruiz Vargas, E.; Sposato, L. A.; Lee, S. A. W.; Hachinski, V.; Cipriano, L. E., 2018, "Anticoagulation therapy for atrial fibrillation in patients with dementia: a cost effectiveness analysis", Stroke, December 49(12): 2844 - 2850. Abstract: Background and Purpose—
Direct oral anticoagulants (DOACs) are safer, at least equally efficacious, and cost-effective compared to warfarin for stroke prevention in atrial fibrillation (AF) but they remain underused, particularly in demented patients. We estimated the cost-effectiveness of DOACs compared with warfarin in patients with AF and Alzheimer’s disease (AD).
We constructed a microsimulation model to estimate the lifetime costs, quality-adjusted life-years (QALYs), and cost-effectiveness of anticoagulation therapy (adjusted-dose warfarin and various DOACs) in 70-year-old patients with AF and AD from a US societal perspective. We stratified patient cohorts based on stage of AD and care setting. Model parameters were estimated from secondary sources. Health benefits were measured in the number of acute health events, life-years, and QALYs gained. We classified alternatives as cost-effective using a willingness-to-pay threshold of $100 000 per QALY gained.
For patients with AF and AD, compared with warfarin, DOACs increase costs but also increase QALYs by reducing the risk of stroke. For mild-AD patients living in the community, edoxaban increased lifetime costs by $6603 and increased QALYs by 0.076 compared to warfarin, yielding an incremental cost-effectiveness ratio of $86 882/QALY gained. Even though DOACs increased QALYs compared with warfarin for all patient groups (ranging from 0.019 to 0.085 additional QALYs), no DOAC treatment alternative had an incremental cost-effectiveness ratio <$150 000/QALY gained for patients with moderate to severe AD. For patients living in a long-term care facility with mild AD, the DOAC with the lowest incremental cost-effectiveness ratio (rivaroxaban) costs $150 169 per QALY gained; for patients with more severe AD, the incremental cost-effectiveness ratios were higher.
For patients with AF and mild AD living in the community, edoxaban is cost-effective compared with warfarin. Even though patients with moderate and severe AD living in the community and patients with any stage of AD living in a long-term care setting may obtain positive clinical benefits from anticoagulation treatment, DOACs are not cost-effective compared with warfarin for these populations. Compared to aspirin, no oral anticoagulation (warfarin or any DOAC) is cost effective in patients with AF and AD.
Link(s) to publication:
Cipriano, L. E.; Zaric, G. S., 2018, "Cost-effectiveness of naloxone kits in secondary schools", Drug and Alcohol Dependence, November 192: 352 - 361. Abstract: Background We seek to identify conditions under which a plan by the Toronto District School Board (TDSB) to equip high schools with naloxone kits would be cost-effective. Methods We developed a decision-analytic model to evaluate the costs, benefits, and cost-effectiveness of a school-based naloxone program. We estimated model inputs from the medical literature and used Toronto-specific sources whenever available. We present our results varying both the expected total number of opioid overdoses per year across all 112 TDSB high schools and the effectiveness of a school-based naloxone program in reducing mortality. Results A school naloxone program likely costs less than CAD$50,000 per quality-adjusted life-year gained if the overdose frequency is at least once each year and it reduces opioid poisoning mortality by at least 40% (from 10% to <6.0%) or if the overdose frequency is at least two per year and the program reduces mortality by at least 20% (from 10% to <8.0%). The results are sensitive to the intensity and cost of staff training, the lifetime costs and life-expectancy of overdose survivors, and the probability of an overdose being fatal in the absence of a school naloxone program. Conclusions School naloxone programs are relatively inexpensive, but that does not ensure that they are a cost-effective use of resources. While potentially cost-effective, if the risk of an overdose in a Toronto high school is low, then other programs aimed at improving the health and wellbeing of students may be better use of limited resources.
Link(s) to publication:
Cipriano, L. E.; Liu, S.; Shahzada, K. S.; Holodniy, M.; Goldhaber-Fiebert, J. D., 2018, "Economically efficient hepatitis C virus treatment prioritization improves health outcomes", Medical Decision Making, October 38(7): 849 - 865. Abstract: BACKGROUND:
The total cost of treating the 3 million Americans chronically infected with hepatitis C virus (HCV) represents a substantial affordability challenge requiring treatment prioritization. This study compares the health and economic outcomes of alternative treatment prioritization schedules.
We developed a multiyear HCV treatment budget allocation model to evaluate the tradeoffs of 7 prioritization strategies. We used optimization to identify the priority schedule that maximizes population net monetary benefit (NMB). We compared prioritization schedules in terms of the number of individuals treated, the number of individuals who progress to end-stage liver disease (ESLD), and population total quality-adjusted life years (QALYs). We applied the model to the population of treatment-naive patients with a total annual HCV treatment budget of US$8.6 billion.
First-come, first-served (FCFS) treats the fewest people with advanced fibrosis, prevents the fewest cases of ESLD, and gains the fewest QALYs. A schedule developed from optimizing population NMB prioritizes treatment in the first year to patients with moderate to severe fibrosis who are younger than 65 years, followed by older individuals with moderate to severe fibrosis. While this strategy yields the greatest population QALYs, prioritization by disease severity alone prevents more cases of ESLD. Sensitivity analysis indicated that the differences between prioritization schedules are greater when the budget is smaller. A 10% annual treatment price reduction enabled treatment 1 year sooner to several patient subgroups, specifically older patients and those with less severe liver fibrosis.
In the absence of a sufficient budget to treat all patients, explicit prioritization targeting younger people with more severe disease first provides the greatest health benefits. We provide our spreadsheet model so that decision makers can compare health tradeoffs of different budget levels and various prioritization strategies with inputs tailored to their population.
Link(s) to publication:
Honours & Awards
- Decision making in dynamic systems with strategic information acquisition” Natural Sciences and Engineering Research Council of Canada (NSERC)
- Seth Bonder Foundation Research Award, 2012
- Lee B. Lusted Student Prize Award for outstanding presentations of research in Applied Health Economics, Annual Meeting of the Society for Medical Decision Making, 2012
- Course Assistant Award, Department of Management Science & Engineering, Stanford University, 2012
- Seth Bonder Scholarship for Applied Operations Research in Health Services, INFORMS, 2011
- Award for Outstanding Short Course, Annual Meeting of the Society for Medical Decision Making, 2010, 2011
- Centennial Teaching Assistant Award, Stanford University, 2011
- Visiting Researcher, Management of Technology and Entrepreneurship Institute (MTEI), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (Spring 2012)
- Research Scientist. Institute for Technology Assessment, Massachusetts General Hospital, Boston, MA (2006-2008)
- Queuing Project Manager, Ontario Joint Replacement Registry, London Health Sciences Centre, London, ON (2004-2006)