A model's purpose is to inform medical decisions and health care resource allocation. Modelers employ quantitative methods to structure the clinical, epidemiological, and economic evidence base and gain qualitative insight to assist decision makers in making better decisions. From a policy perspective, the value of a model-based analysis lies not simply in its ability to generate a precise point estimate for a specific outcome but also in the systematic examination and responsible reporting of uncertainty surrounding this outcome and the ultimate decision being addressed. Different concepts relating to uncertainty in decision modeling are explored. Stochastic (first-order) uncertainty is distinguished from both parameter (second-order) uncertainty and from heterogeneity, with structural uncertainty relating to the model itself forming another level of uncertainty to consider. The article argues that the estimation of point estimates and uncertainty in parameters is part of a single process and explores the link between parameter uncertainty through to decision uncertainty and the relationship to value of information analysis. The article also makes extensive recommendations around the reporting of uncertainty, in terms of both deterministic sensitivity analysis techniques and probabilistic methods. Expected value of perfect information is argued to be the most appropriate presentational technique, alongside cost-effectiveness acceptability curves, for representing decision uncertainty from probabilistic analysis.

Key Points Question What screening and isolation programs for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) will keep students at US residential colleges safe and permit the reopening of campuses? Findings This analytic modeling study of a hypothetical cohort of 4990 college-age students without SARS-CoV-2 infection and 10 students with undetected asymptomatic cases of SARS-CoV-2 infection suggested that frequent screening (every 2 days) of all students with a low-sensitivity, high-specificity test might be required to control outbreaks with manageable isolation dormitory utilization at a justifiable cost. Meaning In this modeling study, symptom-based screening alone was not sufficient to contain an outbreak, and the safe reopening of campuses in fall 2020 may require screening every 2 days, uncompromising vigilance, and continuous attention to good prevention practices.

In all but the lowest-risk populations, routine, voluntary screening for HIV once every three to five years is justified on both clinical and cost-effectiveness grounds. One-time screening in the general population may also be cost-effective.

Background Total knee arthroplasty (TKA) relieves pain and improves quality of life for persons with advanced knee osteoarthritis. However, to our knowledge, the cost-effectiveness of TKA and the influences of hospital volume and patient risk on TKA cost-effectiveness have not been investigated in the United States. Methods We developed a Markov, state-transition, computer simulation model and populated it with Medicare claims data and cost and outcomes data from national and multinational sources. We projected lifetime costs and quality-adjusted life expectancy (QALE) for different risk populations and varied TKA intervention and hospital volume. Cost-effectiveness of TKA was estimated across all patient risk and hospital volume permutations. Finally, we conducted sensitivity analyses to determine various parameters’ influences on cost-effectiveness. Results Overall, TKA increased QALE from 6.822 to 7.957 quality-adjusted life years (QALYs). Lifetime costs rose from $37 100 (no TKA) to $57 900 after TKA, resulting in an incremental cost-effectiveness ratio of $18 300 per QALY. For high-risk patients, TKA increased QALE from 5.713 to 6.594 QALY, yielding a cost-effectiveness ratio of $28 100 per QALY. At all risk levels, TKA was more costly and less effective in low-volume centers than in high-volume centers. Results were insensitive to variations of key input parameters within policy-relevant, clinically plausible ranges. The greatest variations were seen for the quality of life gain after TKA and the cost of TKA. Conclusions Total knee arthroplasty appears to be cost-effective in the US Medicare-aged population, as currently practiced across all risk groups. Policy decisions should be made on the basis of available local options for TKA. However, when a high-volume hospital is available, TKAs performed in a high-volume hospital confer even greater value per dollar spent than TKAs performed in low-volume centers.

The appropriate development of a model begins with understanding the problem that is being represented. The aim of this article was to provide a series of consensus-based best practices regarding the process of model conceptualization. For the purpose of this series of articles, we consider the development of models whose purpose is to inform medical decisions and health-related resource allocation questions. We specifically divide the conceptualization process into two distinct components: the conceptualization of the problem, which converts knowledge of the health care process or decision into a representation of the problem, followed by the conceptualization of the model itself, which matches the attributes and characteristics of a particular modeling type with the needs of the problem being represented. Recommendations are made regarding the structure of the modeling team, agreement on the statement of the problem, the structure, perspective, and target population of the model, and the interventions and outcomes represented. Best practices relating to the specific characteristics of model structure and which characteristics of the problem might be most easily represented in a specific modeling method are presented. Each section contains a number of recommendations that were iterated among the authors, as well as among the wider modeling taskforce, jointly set up by the International Society for Pharmacoeconomics and Outcomes Research and the Society for Medical Decision Making.