Resources Repository
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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…
Preferences/Values | Probability/Bayes | Decision Psychology | Decision Theory | Clinical Care | Chronic Disease/Risk | Business/Industry | Economics/Finance | Health/Medicine | High School | College | Graduate | Doctoral | Professional | Critical Thinking/Analysis | Decision Making/Leadership | Quantitative Literacy -
ArticlePublication 2020Incorporating Perspective into Clinical Decisions
Part of a six-part series of articles on clinical decision making, in this article, the …
Part of a six-part series of articles on clinical decision making, in this article, the authors discuss how to incorporate perspective into clinical decisions, explicitly acknowledging that the treating physician is not the only stakeholder in these decisions. The authors use 2 case studies to demonstrate how changes in perspective can alter the clinical decision as well lead to both intended and unintended consequences to the outcomes.
Priority Setting/Ethics | Preferences/Values | Clinical Care | Health Outcomes | Health Systems | Health/Medicine -
ArticlePublication 2020Weighing Evidence to Inform Clinical Decisions
The authors use a clinical example to simulate how treatment discussions can be complicated when new evidence is introduced …
The authors use a clinical example to simulate how treatment discussions can be complicated when new evidence is introduced that conflicts with existing guidelines. Even when evidence is consistent, the authors point out that current guidelines can have interpretations that don't agree with available evidence. They develop a step-wise algorithm to help guide individual clinical decisions even in the absence of general consensus related to appropriate testing and treatment.
Evidence Synthesis | Priority Setting/Ethics | Clinical Care | Health/Medicine -
ArticlePublication 2015A Conceptual Model for Breast, Cervical, and Colorectal Cancer Screening
General frameworks of the cancer screening process are available, but none directly compare the process …
General frameworks of the cancer screening process are available, but none directly compare the process in detail across different organ sites. This limits the ability of medical and public health professionals to develop and evaluate coordinated screening programs that apply resources and population management strategies available for one cancer site to other sites. This paper presents a conceptual model that incorporates a single screening episode for breast, cervical, and colorectal cancers into a unified framework based…
Evidence Synthesis | Preferences/Values | Clinical Care | Health Outcomes | Test Performance | Microsimulation | Cost-Effectiveness Analysis | Chronic Disease/Risk | Health Systems | Health/Medicine | Science/Technology | North America -
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 -
Resource PackWeb Portal, Teaching Resource 2023Resource Pack: Cost-Effectiveness of Screening and Treatment for Hypertension
Hypertension is a relevant example for teaching clinical decision making, diagnostic test performance, positivity criterion, …
Hypertension is a relevant example for teaching clinical decision making, diagnostic test performance, positivity criterion, and cost-effectiveness analysis. This resource pack provides examples of decision analyses and cost-effectiveness analyses for the management and treatment of hypertension, with a predominant focus on the U.S. Analyses are included that predate the 2017 American College of Cardiology/American Heart Association Clinical Practice Guidelines, along with more recent examples that followed release of the guidelines. Resources are also included that…
Preferences/Values | Clinical Care | Test Performance | Decision Analysis | Cost-Effectiveness Analysis | Chronic Disease/Risk | Economics/Finance | Health/Medicine | Science/Technology | North America | Europe | Graduate | Doctoral | Professional | Critical Thinking/Analysis | Policy Translation | 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 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…
Evidence Synthesis | Clinical Care | Health Outcomes | Microsimulation | Calibration/Validation | Maternal/Reproductive Health | Health Systems | Health/Medicine | 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.,…
Evidence Synthesis | Clinical Care | Costing Methods | Mathematical Models | Microsimulation | Calibration/Validation | Cost-Effectiveness Analysis | Maternal/Reproductive Health | Health Systems | Health/Medicine | Science/Technology | Global | Sub-Saharan Africa | Middle East & North Africa | Latin America & Caribbean | Asia & Pacific