Resources Repository
-
ReviewPublication 2021Review of Web-Based Tools for Value-of-Information Analysis
Value-of-information analysis (VOI) is an analytic approach used to inform research priorities, guide clinical trial …
Value-of-information analysis (VOI) is an analytic approach used to inform research priorities, guide clinical trial design, and provide information for decisions about reimbursement. The authors review existing web-based tools to facilitate VOI calculations. These include Sheffield Accelerated Value of Information (SAVI), the web interface to the BCEA (Bayesian Cost-Effectiveness Analysis) R package (BCEAweb), Rapid Assessment of Need for Evidence (RANE), and Value of Information for Cardiovascular Trials and Other Comparative Research (VICTOR).
Value of Information | Health/Medicine | Economics/Finance | Decision Theory | Priority Setting/Ethics | Cost-Effectiveness Analysis -
ArticlePublication 2007Decision Analysis: A Personal Account of How It Got Started and Evolved
In this chapter, Howard Raiffa discusses the evolution of decision analysis and his personal involvement …
In this chapter, Howard Raiffa discusses the evolution of decision analysis and his personal involvement in its development. He describes the early days of Operations Research (OR) in the late 1940s with its approach to complex, strategic decision making. After reading John von Neumann and Oskar Morgenstern’s Theory of Games and Economic Behavior (1947) and Abraham Wald’s two books (1947, 1950), he became involved in statistical decision theory. A few years later, after reading Leonard…
Probability/Bayes | Health/Medicine | Economics/Finance | Decision Theory | Preferences/Values | Decision Analysis | Operations Research | Business/Industry | Energy/Engineering -
ArticlePublication 2022Economic Value of Clinical Artificial Intelligence
Artificial intelligence (AI) is increasingly used in clinical applications. Nevertheless, its flexibility and difficulties around …
Artificial intelligence (AI) is increasingly used in clinical applications. Nevertheless, its flexibility and difficulties around collecting data on its clinical impacts make value assessment challenging. This article uses a value framework as the basis for assessing how AI may create value depending on how it is used. Authors also provide advice to health economists seeking to model AI’s clinical impacts. There are multiple ways that AI challenges traditional health technology assessment methodology. Authors highlight several…
Value of Information | Economics/Finance | Technology Assessment | Science/Technology | Global -
ArticlePublication 2022Emerging Therapies for COVID-19: The Value of Information From More Clinical Trials
The COVID-19 pandemic necessitated time-sensitive policy and implementation decisions regarding new therapies in the face …
The COVID-19 pandemic necessitated time-sensitive policy and implementation decisions regarding new therapies in the face of uncertainty. This study aimed to quantify consequences of approving therapies or pursuing further research. The authors used a cohort state-transition model for hospitalized patients with COVID-19 to estimate quality-adjusted life-years (QALYs) and costs associated with multiple drug regimens and usual care. For each they assessed immediate approval, use only in research, emergency use authorization or reject. They conducted cost-effectiveness…
Value of Information | Economics/Finance | State-Transition | Benefit-Cost Analysis | Infectious Diseases | Policy/Regulation | North America | Europe -
ArticlePublication 2020Testing for SARS-CoV-2 Antibodies
Antibody testing can determine previous exposure to SARS-CoV-2 virus. Recently, the UK government has made …
Antibody testing can determine previous exposure to SARS-CoV-2 virus. Recently, the UK government has made antibody testing available to anyone wanting it, even if there is no clinical indication. The purpose of this article is to provide guidance for when to consider antibody testing in individuals with and without symptoms suggestive of current or past SARS-CoV-2 infection. Key points made by the authors include: (1) antibody testing is likely to be most useful 2 weeks…
Probability/Bayes | Health/Medicine | Test Performance | Technology Assessment | Infectious Diseases | Clinical Care -
ArticlePublication 2020Bayes' Theorem, COVID-19, and Screening Tests
This article reviews the implications of increased testing for COVID-19 using reverse transcriptase polymerase chain …
This article reviews the implications of increased testing for COVID-19 using reverse transcriptase polymerase chain reaction (rRT-PCR) through the application of Bayes’ Theorem for three hypothetical, stylized case scenarios. The scenarios involve three patients with a low, moderate, and high pre-test probability of COVID-19 infection. The category of low probability would include "asymptomatic individuals in a presumed low prevalence environment" and might vary from 10 to 20%. The category of moderate probability would include "individuals…
Probability/Bayes | Health/Medicine | Test Performance | Infectious Diseases | Clinical Care -
ArticlePublication 2020Interpreting COVID-19 Test Results: A Bayesian Approach
This article considers the following question with respect to interpreting the results of polymerase chain reaction …
This article considers the following question with respect to interpreting the results of polymerase chain reaction (PCR) assays from nasal and pharyngeal swabs for COVID-19 to inform clinical decision making: "While a positive result in an acutely ill patient is straightforward, how should physicians interpret negative tests in patients with suspected COVID-19 infection?" Using an assumption of near-perfect specificity of PCR assays for COVID-19, the authors acknowledge the uncertainty of test sensitivity. They consider two clinical scenarios…
Probability/Bayes | Health/Medicine | Test Performance | Infectious Diseases | Science/Technology | Global -
ArticlePublication 2020Clinical Decision Making: Using a Diagnostic Test
This article is part of a 6-part series on clinical decision making. The authors use …
This article is part of a 6-part series on clinical decision making. The authors use two clinical examples to review the principles of interpreting diagnostic test results. They outline an approach that can be used to determine how to select and apply tests and their results to the practice of internal medicine. Topics covered in the two case studies include sensitivity and specificity, positive predictive and negative predictive value of tests, and how to estimate…
Probability/Bayes | Health/Medicine | Test Performance | Clinical Care