- theory and concepts
- decision theory
- decision psychology
- probability/bayes
- preferences/values
- priority setting/ethics
- calibration/validation
- approaches and applications
- decision analysis
- risk analysis
- benefit-cost analysis
- cost-effectiveness analysis
- technology assessment
- operations research
- clinical care
Resources Repository
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ArticlePublication 2019Global Childhood Cancer Survival Estimates and Priority-Setting: A Simulation-Based Analysis
This modelling study provides estimates of global childhood cancer survival, accounting for the impact of …
This modelling study provides estimates of global childhood cancer survival, accounting for the impact of multiple factors that affect cancer outcomes in children. The authors developed a microsimulation model to simulate childhood cancer survival for 200 countries/territories, accounting for clinical and epidemiologic factors, including country-specific treatment variables, such as availability of chemotherapy, radiation, and surgery, and calibrated the model to empirical data from the CONCORD-2 and CONCORD-3 studies using an Approximate Bayesian Computation approach. The…
Priority Setting/Ethics | Clinical Care | Health Outcomes | Microsimulation | Child/Nutrition | Chronic Disease/Risk | Global -
ArticlePublication 2021Impact of Treatment and Imaging Modalities on Global Breast Cancer Survival
This analysis used a microsimulation model of global cancer survival to simulate 5-year net survival …
This analysis used a microsimulation model of global cancer survival to simulate 5-year net survival for women with newly diagnosed breast cancer in 200 countries/territories in 2018, accounting for the availability and stage-specific survival impact of specific treatment modalities (chemotherapy, radiotherapy, surgery, and targeted therapy), imaging modalities (ultrasound, x-ray, CT, MRI, PET, and single-photon emission computed tomography [SPECT]), and quality of cancer care. The model was calibrated to empirical data on 5-year net breast cancer…
Calibration/Validation | Clinical Care | Health Outcomes | Microsimulation | Chronic Disease/Risk | Health Systems | Global -
ArticlePublication 2021Cost-Effectiveness of Hypertension Treatment by Pharmacists in Black Barbershops
The Los Angeles Barbershop Blood Pressure Study (LABBPS) examined the effectiveness and cost of a …
The Los Angeles Barbershop Blood Pressure Study (LABBPS) examined the effectiveness and cost of a one-year pharmacist-led hypertension care intervention in Black-owned barbershops in Los Angeles County, focused on non-Hispanic Black men with uncontrolled hypertension. Using a discrete event simulation, the researchers projected the 10-year health outcomes and health care costs associated with the intervention compared to a control group. The costs and quality-adjusted life-years (QALYs) were calculated from a health care sector perspective, with…
Cost-Effectiveness Analysis | Clinical Care | Mathematical Models | Chronic Disease/Risk | Health/Medicine | North America -
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 -
Resource PackPublication, Teaching Resource 2022Resource Pack: Decision Analysis & Childhood Obesity
This resource pack on childhood obesity was curated by the Center for Health Decision Science …
This resource pack on childhood obesity was curated by the Center for Health Decision Science to showcase existing cost-effectiveness analyses and motivate students, educators, and others to pursue new applications of decision science methods to the public health challenge of obesity. The resource pack was motivated by the NEJM article entitled Simulation of Growth Trajectories of Childhood Obesity into Adulthood published on November 30, 2017, with CHDS co-authors Zach Ward and Stephen Resch. Citation: Ward Z, Long M,…
Cost-Effectiveness Analysis | Clinical Care | Costing Methods | Health Outcomes | Child/Nutrition | Chronic Disease/Risk | Policy/Regulation | Culture/Society | Economics/Finance | Food/Agriculture | Health/Medicine | North America -
ArticlePublication 2019Cost-Effectiveness of Community-Based Childhood Obesity Prevention Interventions in Australia
This study examined the cost-effectiveness of community-based obesity prevention interventions (CBIs) consisting of strategies to …
This study examined the cost-effectiveness of community-based obesity prevention interventions (CBIs) consisting of strategies to promote healthy eating and physical activity for Australian children aged between 5-18 years. A multiple cohort Markov model that simulates diseases associated with overweight and obesity was used to estimate the health benefits, measured as health-adjusted life years (HALYs) and healthcare-related cost offsets from diseases averted due to exposure to the intervention. Health and cost outcomes were estimated over the…
Cost-Effectiveness Analysis | Clinical Care | Health Outcomes | State-Transition | Child/Nutrition | Chronic Disease/Risk | Health Systems | Food/Agriculture | Health/Medicine | Oceania -
ArticlePublication 2019Long-Term Cost-Effectiveness of Obesity Prevention Interventions in the Early Years of Life
This analysis estimated the long-term health benefits and health care cost-savings of reductions in body …
This analysis estimated the long-term health benefits and health care cost-savings of reductions in body mass index (BMI) for the Australian population of children aged between 2 and 5 years. A proportional multistate, multiple cohort, lifetable model estimated the health benefits and health care cost-savings related to hypothetical reductions in BMI, informed by a scoping review of systematic reviews reporting the effectiveness of obesity prevention interventions in preschool aged children. Results suggested significant potential for…
Cost-Effectiveness Analysis | Clinical Care | Child/Nutrition | Chronic Disease/Risk | Health Systems | Economics/Finance | Health/Medicine | Oceania -
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.
Priority Setting/Ethics | Clinical Care | Evidence Synthesis | Health/Medicine