Resources Repository
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Tutorial/PrimerPublication, Teaching Resource 2024Tutorial: Building Decision Trees
This tutorial illustrates the basic steps needed to develop decision trees in Amua using a …
This tutorial illustrates the basic steps needed to develop decision trees in Amua using a disease screening example. It details the process of how to build the structure of a decision tree, parameterize the model with probabilities and relevant outcomes (i.e., life expectancy), evaluate three alternative screening strategies in a baseline scenario, and perform one-way sensitivity analyses to assess the robustness of the results to different parameter values. Amua, the Swahili word meaning “decide”/“solve”, is…
Probability/Bayes | Clinical Care | Mathematical Models | Decision Analysis | Health/Medicine | Graduate | Doctoral | Professional -
Teaching PackWeb Portal, Teaching Resource 2023Teaching Pack: Heuristics with Joe Pliskin
This teaching pack, curated by the Center for Health Decision Science, features videos introducing heuristics …
This teaching pack, curated by the Center for Health Decision Science, features videos introducing heuristics used in decision making. While these “mental shortcuts” can be useful in some circumstances, they can lead to more errors than deliberate, rational thinking. An awareness of these heuristics is useful to decision makers. This series of videos on heuristics was developed by Professor Joe Pliskin during his residency with the CHDS Media Hub led by Jake Waxman. They reflect…
Probability/Bayes | Clinical Care | Decision Theory | Decision Psychology | Preferences/Values | Chronic Disease/Risk | Business/Industry | Economics/Finance | Health/Medicine | High School | College | Graduate | Doctoral | Professional | Critical Thinking/Analysis | Decision Making/Leadership | Quantitative Literacy -
ExerciseNone, Teaching Resource 2024Lab: Giant Cell Arteritis Decision Tree Model
This tutorial walks through the development of a decision tree model focused on Giant Cell …
This tutorial walks through the development of a decision tree model focused on Giant Cell Arteritis. It describes how to build the model structure, assign probabilities and outcomes based on imperfect test characteristics and epidemiologic estimates, evaluate alternative treatment strategies, and conduct one-way sensitivity analyses to assess which model parameters may impact the optimal treatment choice. Amua, the Swahili word meaning “decide”/“solve”, is an open source modeling framework and probabilistic programming language for decision analysis…
Probability/Bayes | Clinical Care | Mathematical Models | Decision Analysis | Health/Medicine | Graduate | Doctoral | Professional -
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 | Clinical Care | Test Performance | Technology Assessment | Infectious Diseases | Health/Medicine -
ToolInteractive 2020COVID-19 Antibody Tests: Calculator for Interpreting Test Results
Antibody testing can determine previous exposure to SARS-CoV-2 virus. This interactive calculator, linked to the article …
Antibody testing can determine previous exposure to SARS-CoV-2 virus. This interactive calculator, linked to the article below* on antibody testing for SARS-CoV-2 virus, allows users to vary the prior probability of infection, the sensitivity of SARS-CoV-2 antibody testing, and the specificity of SARS-CoV-2 antibody testing. Key points made in the article accompanying the interactive include: (1) antibody testing is likely to be most useful 2 weeks after infection, (2) sensitivity and specificity will vary over time and…
Probability/Bayes | Clinical Care | Test Performance | Technology Assessment | Infectious Diseases | Health/Medicine | Science/Technology -
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 | Clinical Care | Test Performance | Infectious Diseases | Health/Medicine -
Tools/ModelsInteractive, Teaching Resource 2020Interactive Graphic: Interpreting a COVID-19 Test Result
Currently, the most common diagnostic test for COVID-19 relies on reverse transcriptase polymerase chain reaction …
Currently, the most common diagnostic test for COVID-19 relies on reverse transcriptase polymerase chain reaction (RT-PCR), and most often uses samples obtained from the respiratory tract by nasopharyngeal swab. This interactive graphic demonstrates the influence of the prior probability of COVID-19, the test sensitivity (i.e., the probability of a positive test conditional on disease presence), and the test specificity (i.e., the probability of a negative test conditional on disease absence) on the post-test probability of…
Probability/Bayes | Clinical Care | Test Performance | Infectious Diseases | Health/Medicine | Science/Technology | High School | College | Graduate | Doctoral | Professional | Graphics/Visualization | Quantitative Literacy -
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 | Clinical Care | Test Performance | Health/Medicine