Cargando…

Making Evidence Actionable: Interactive Dashboards, Bayes, and Health Care Innovation

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 access...

Descripción completa

Detalles Bibliográficos
Autores principales: Bir, Anupa, Freeman, Nikki, Chew, Robert, Smith, Kevin, Derzon, James, Day, Timothy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Ubiquity Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6688542/
https://www.ncbi.nlm.nih.gov/pubmed/31406697
http://dx.doi.org/10.5334/egems.300
_version_ 1783442905115918336
author Bir, Anupa
Freeman, Nikki
Chew, Robert
Smith, Kevin
Derzon, James
Day, Timothy
author_facet Bir, Anupa
Freeman, Nikki
Chew, Robert
Smith, Kevin
Derzon, James
Day, Timothy
author_sort Bir, Anupa
collection PubMed
description 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.
format Online
Article
Text
id pubmed-6688542
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher Ubiquity Press
record_format MEDLINE/PubMed
spelling pubmed-66885422019-08-12 Making Evidence Actionable: Interactive Dashboards, Bayes, and Health Care Innovation Bir, Anupa Freeman, Nikki Chew, Robert Smith, Kevin Derzon, James Day, Timothy EGEMS (Wash DC) Empirical Research 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. Ubiquity Press 2019-08-05 /pmc/articles/PMC6688542/ /pubmed/31406697 http://dx.doi.org/10.5334/egems.300 Text en Copyright: © 2019 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See http://creativecommons.org/licenses/by/4.0/.
spellingShingle Empirical Research
Bir, Anupa
Freeman, Nikki
Chew, Robert
Smith, Kevin
Derzon, James
Day, Timothy
Making Evidence Actionable: Interactive Dashboards, Bayes, and Health Care Innovation
title Making Evidence Actionable: Interactive Dashboards, Bayes, and Health Care Innovation
title_full Making Evidence Actionable: Interactive Dashboards, Bayes, and Health Care Innovation
title_fullStr Making Evidence Actionable: Interactive Dashboards, Bayes, and Health Care Innovation
title_full_unstemmed Making Evidence Actionable: Interactive Dashboards, Bayes, and Health Care Innovation
title_short Making Evidence Actionable: Interactive Dashboards, Bayes, and Health Care Innovation
title_sort making evidence actionable: interactive dashboards, bayes, and health care innovation
topic Empirical Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6688542/
https://www.ncbi.nlm.nih.gov/pubmed/31406697
http://dx.doi.org/10.5334/egems.300
work_keys_str_mv AT biranupa makingevidenceactionableinteractivedashboardsbayesandhealthcareinnovation
AT freemannikki makingevidenceactionableinteractivedashboardsbayesandhealthcareinnovation
AT chewrobert makingevidenceactionableinteractivedashboardsbayesandhealthcareinnovation
AT smithkevin makingevidenceactionableinteractivedashboardsbayesandhealthcareinnovation
AT derzonjames makingevidenceactionableinteractivedashboardsbayesandhealthcareinnovation
AT daytimothy makingevidenceactionableinteractivedashboardsbayesandhealthcareinnovation