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Insights into measuring health disparities using electronic health records from a statewide network of health systems: A case study

Within Wisconsin, our residents experience some of the worst health disparities in the nation. Public reporting on disparities in the quality of care is important to achieving accountability for reducing disparities over time and has been associated with improvements in care. Disparities reporting u...

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Autores principales: Smith, Maureen A., Gigot, Matthew, Harburn, Abbey, Bednarz, Lauren, Curtis, Katherine, Mathew, Jomol, Farrar-Edwards, Dorothy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10052445/
https://www.ncbi.nlm.nih.gov/pubmed/37008604
http://dx.doi.org/10.1017/cts.2022.521
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author Smith, Maureen A.
Gigot, Matthew
Harburn, Abbey
Bednarz, Lauren
Curtis, Katherine
Mathew, Jomol
Farrar-Edwards, Dorothy
author_facet Smith, Maureen A.
Gigot, Matthew
Harburn, Abbey
Bednarz, Lauren
Curtis, Katherine
Mathew, Jomol
Farrar-Edwards, Dorothy
author_sort Smith, Maureen A.
collection PubMed
description Within Wisconsin, our residents experience some of the worst health disparities in the nation. Public reporting on disparities in the quality of care is important to achieving accountability for reducing disparities over time and has been associated with improvements in care. Disparities reporting using statewide electronic health records (EHR) data would allow efficient and regular reporting, but there are significant challenges with missing data and data harmonization. We report our experience in creating a statewide, centralized EHR data repository to support health systems in reducing health disparities through public reporting. We partnered with the Wisconsin Collaborative for Healthcare Quality (the “Collaborative”), which houses patient-level EHR data from 25 health systems including validated metrics of healthcare quality. We undertook a detailed assessment of potential disparity indicators (race and ethnicity, insurance status and type, and geographic disparity). Challenges for each indicator are described, with solutions encompassing internal (health system) harmonization, central (Collaborative) harmonization, and centralized data processing. Key lessons include engaging health systems in identifying disparity indicators, aligning with system priorities, measuring indicators already collected in the EHR to minimize burden, and facilitating workgroups with health systems to build relationships, improve data collection, and develop initiatives to address disparities in healthcare.
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spelling pubmed-100524452023-03-30 Insights into measuring health disparities using electronic health records from a statewide network of health systems: A case study Smith, Maureen A. Gigot, Matthew Harburn, Abbey Bednarz, Lauren Curtis, Katherine Mathew, Jomol Farrar-Edwards, Dorothy J Clin Transl Sci Translational Science Case Study Within Wisconsin, our residents experience some of the worst health disparities in the nation. Public reporting on disparities in the quality of care is important to achieving accountability for reducing disparities over time and has been associated with improvements in care. Disparities reporting using statewide electronic health records (EHR) data would allow efficient and regular reporting, but there are significant challenges with missing data and data harmonization. We report our experience in creating a statewide, centralized EHR data repository to support health systems in reducing health disparities through public reporting. We partnered with the Wisconsin Collaborative for Healthcare Quality (the “Collaborative”), which houses patient-level EHR data from 25 health systems including validated metrics of healthcare quality. We undertook a detailed assessment of potential disparity indicators (race and ethnicity, insurance status and type, and geographic disparity). Challenges for each indicator are described, with solutions encompassing internal (health system) harmonization, central (Collaborative) harmonization, and centralized data processing. Key lessons include engaging health systems in identifying disparity indicators, aligning with system priorities, measuring indicators already collected in the EHR to minimize burden, and facilitating workgroups with health systems to build relationships, improve data collection, and develop initiatives to address disparities in healthcare. Cambridge University Press 2023-02-01 /pmc/articles/PMC10052445/ /pubmed/37008604 http://dx.doi.org/10.1017/cts.2022.521 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
spellingShingle Translational Science Case Study
Smith, Maureen A.
Gigot, Matthew
Harburn, Abbey
Bednarz, Lauren
Curtis, Katherine
Mathew, Jomol
Farrar-Edwards, Dorothy
Insights into measuring health disparities using electronic health records from a statewide network of health systems: A case study
title Insights into measuring health disparities using electronic health records from a statewide network of health systems: A case study
title_full Insights into measuring health disparities using electronic health records from a statewide network of health systems: A case study
title_fullStr Insights into measuring health disparities using electronic health records from a statewide network of health systems: A case study
title_full_unstemmed Insights into measuring health disparities using electronic health records from a statewide network of health systems: A case study
title_short Insights into measuring health disparities using electronic health records from a statewide network of health systems: A case study
title_sort insights into measuring health disparities using electronic health records from a statewide network of health systems: a case study
topic Translational Science Case Study
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10052445/
https://www.ncbi.nlm.nih.gov/pubmed/37008604
http://dx.doi.org/10.1017/cts.2022.521
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