Making Evidence Actionable: Interactive Dashboards, Bayes, and Health Care Innovation
| Autor: | James H. Derzon, Kevin Smith, Timothy J. Day, Nikki L. B. Freeman, Anupa Bir, Rob Chew |
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| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
evidence
business.industry Computer science health care innovation Dashboard (business) Bayesian probability Qualitative property Empirical Research lcsh:Computer applications to medicine. Medical informatics Bayesian Data science data science data visualization Bayes' theorem Data visualization Frequentist inference Health care lcsh:R858-859.7 health economics and policy business |
| Zdroj: | eGEMs (Generating Evidence & Methods to improve patient outcomes); Vol 7, No 1 (2019); 40 eGEMs, Vol 7, Iss 1 (2019) eGEMs |
| ISSN: | 2327-9214 |
| Popis: | The results of many large-scale federal or multi-site evaluations are typically compiled into long reports which end up sitting on policymaker’s shelves. Moreover, the information policymakers need from these reports is often buried in the report, may not be remembered, understood, or readily accessible to the policymaker when it is needed. This is not a new challenge for evaluators, and advances in statistical methodology, while they have created greater opportunities for insight, may compound the challenge by creating multiple lenses through which evidence can be viewed. The descriptive evidence from traditional frequentist models, while familiar, are frequently misunderstood, while newer Bayesian methods provide evidence which is intuitive, but less familiar. These methods are complementary but presenting both increases the amount of evidence stakeholders and policymakers may find useful. In response to these challenges, we developed an interactive dashboard that synthesizes quantitative and qualitative data and allows users to access the evidence they want, when they want it, allowing each user a customized, and customizable view into the data collected for one large-scale federal evaluation. This offers the opportunity for policymakers to select the specifics that are most relevant to them at any moment, and also apply their own risk tolerance to the probabilities of various outcomes. |
| Databáze: | OpenAIRE |
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