Resources Repository
-
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 | Decision Psychology | Health/Medicine | Clinical Care | Decision Theory | Preferences/Values | Chronic Disease/Risk | Business/Industry | Economics/Finance | High School | College | Graduate | Doctoral | Professional | Critical Thinking/Analysis | Decision Making/Leadership | Quantitative Literacy -
ArticlePublication 2023Simulation-Based Comparative Effectiveness Analysis of Policies to Improve Global Maternal Health Outcomes
The Sustainable Development Goals include a target to reduce the global maternal mortality ratio (MMR) …
The Sustainable Development Goals include a target to reduce the global maternal mortality ratio (MMR) to less than 70 maternal deaths per 100,000 live births by 2030, with no individual country exceeding 140. However, on current trends the goals are unlikely to be met. The authors used an empirically calibrated Global Maternal Health microsimulation model, which simulates individual women in 200 countries and territories to evaluate the impact of different interventions and strategies from 2022…
Calibration/Validation | Health/Medicine | Clinical Care | Health Outcomes | Mathematical Models | Microsimulation | Maternal/Reproductive Health | Health Systems | Global -
ArticlePublication 2023Simulation-Based Estimates and Projections of Global, Regional and Country-Level Maternal Mortality by Cause, 1990-2050
While progress has been made globally to reduce maternal deaths, measurement remains a challenge given …
While progress has been made globally to reduce maternal deaths, measurement remains a challenge given the many causes and frequent underreporting of maternal deaths. The authors developed a structural microsimulation model of Global Maternal Health (GMatH) for 200 countries and territories using demographic, epidemiologic, clinical and health system data synthesized from the medical literature, Civil Registration Vital Statistics systems and Demographic and Health Survey data. The model was calibrated to empirical data from 1990 to…
Calibration/Validation | Health/Medicine | Clinical Care | Health Outcomes | Evidence Synthesis | Microsimulation | Maternal/Reproductive Health | Health Systems | Global -
Resource PackWeb Portal, Teaching Resource 2023Resource Pack: Maternal Health Models and CEA
This resource pack, curated by the Center for Health Decision Science, provides selected examples of …
This resource pack, curated by the Center for Health Decision Science, provides selected examples of modeling approaches used to conduct analyses relevant to maternal and reproductive health. Some papers focus on a particular problem (e.g., screening for prenatal syphilis, comparison of alternative strategies for safe abortion), while others explore strategies for reducing morbidity and mortality from the entire spectrum of pregnancy and childbirth-related complications. Several of the examples model the primary drivers of maternal mortality (e.g.,…
Calibration/Validation | Health/Medicine | Clinical Care | Costing Methods | Evidence Synthesis | Mathematical Models | Microsimulation | Cost-Effectiveness Analysis | Maternal/Reproductive Health | Health Systems | Science/Technology | Global | Sub-Saharan Africa | Middle East & North Africa | Latin America & Caribbean | Asia & Pacific -
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 | Clinical Care | Test Performance | Technology Assessment | Infectious Diseases -
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 | Health/Medicine | Clinical Care | Test Performance | Technology Assessment | Infectious Diseases | 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 | Health/Medicine | Clinical Care | Test Performance | Infectious Diseases -
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 | Health/Medicine | Clinical Care | Test Performance | Infectious Diseases | 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 | Health/Medicine | Clinical Care | Test Performance