Resources Repository
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EditorialPublication 2021Scientific and Regulatory Challenges in Designing mHealth Interventions
Scientists looking for innovative ways to deliver health care have long searched for mechanisms that …
Scientists looking for innovative ways to deliver health care have long searched for mechanisms that can enable the right intervention to be delivered at the right time. Traditional delivery mechanisms have been limited both to the availability of a provider (e.g., a physician) and the location of care (e.g., a hospital or outpatient clinic). In recent years, however, numerous technological advancements—including wearable devices, mobile technologies, and the widespread development and use of user-friendly smartphone applications—have…
Technology Assessment | Health/Medicine | Science/Technology | North America -
ArticlePublication 2020Data-Driven Management of Post-Transplant Medications
Organ-transplanted patients typically receive high amounts of immunosuppressive drugs as a mechanism to reduce their …
Organ-transplanted patients typically receive high amounts of immunosuppressive drugs as a mechanism to reduce their risk of organ rejection. However, because of the diabetogenic effect of these drugs, this practice exposes them to a greater risk of new-onset diabetes after transplantation (NODAT), and hence, becoming insulin dependent. This study develops effective medication management strategies to address the common conundrum of balancing the risk of organ rejection versus that of NODAT. The article presents a robust…
Operations Research | Mathematical Models | Chronic Disease/Risk | Health/Medicine | North America -
ArticlePublication 2021Employee Health Plans Powered by Analytics
This article describes a business model for the employee health plans of large firms to …
This article describes a business model for the employee health plans of large firms to bypass insurers and instead use direct contracts with hospitals which have been designated as centers of excellence. The authors propose methods of machine learning and data analytics to identify efficient and effective delivery systems, with the ultimate goal of improving health care quality.
Operations Research | Health Systems | 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…
Test Performance | Probability/Bayes | Infectious Diseases | Clinical Care | 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…
Test Performance | Probability/Bayes | Infectious Diseases | Clinical Care | Health/Medicine | Science/Technology | High School | College | Graduate | Doctoral | Professional | Graphics/Visualization | Quantitative Literacy -
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…
Test Performance | Probability/Bayes | Infectious Diseases | Health/Medicine | Science/Technology | Global -
ArticlePublication 2020Translating Population Evidence to Individual Patients
In this paper, the authors describe the differences in population level outcomes compared to individual …
In this paper, the authors describe the differences in population level outcomes compared to individual patients and discuss ways that these are differences. The authors cover topics including the difference between relative and absolute risk and benefit. They use an example of the decision to start anticoagulation in new-onset atrial fibrillation to discuss translating population level evidence to treatment of an individual. These options include generalizability, subgroup analysis, prediction rules, following response to therapy, and even…
Test Performance | Evidence Synthesis | Health Systems | Clinical Care | Health/Medicine -
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…
Test Performance | Probability/Bayes | Clinical Care | Health/Medicine -
ToolInteractive, Teaching Resource 2020RAND Critical Care Surge Response Tool
This Excel-based model allows decisionmakers at all levels (i.e., hospitals, health care systems, states, regions) …
This Excel-based model allows decisionmakers at all levels (i.e., hospitals, health care systems, states, regions) to examine the current critical care capacity in the nation’s hospitals and rapidly explore strategies for increasing capacity to provide care for the sickest COVID-19 patients. The tool was developed by the RAND Corporation in response to the 2020 COVID-19 pandemic. Model input parameters to the Excel spreadsheet include baseline number of beds, critical care doctors and nurses, respiratory therapists,…
Operations Research | Priority Setting/Ethics | Mathematical Models | Infectious Diseases | Health/Medicine | North America | Professional | Policy Translation