Evidence map›Paper›PMID 37008604›Full record

ArticleJournal of clinical and translational science2023

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

Maureen A Smith, Matthew Gigot, Abbey Harburn, Lauren Bednarz, Katherine Curtis, Jomol Mathew, Dorothy Farrar-Edwards

Abstract readCase Reports
In one paragraph

Article in Journal of clinical and translational science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Maureen A SmithDepartment of Population Health Sciences, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.ORCID https://orcid.org/0000-0003-4370-000X
Matthew GigotWisconsin Collaborative for Healthcare Quality, Madison, WI, USA.
Abbey HarburnWisconsin Collaborative for Healthcare Quality, Madison, WI, USA.
Lauren BednarzDepartment of Population Health Sciences, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
Katherine CurtisDepartment of Community and Environmental Sociology, University of Wisconsin-Madison, Madison, WI, USA.
Jomol MathewDepartment of Population Health Sciences, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
Dorothy Farrar-EdwardsDepartments of Kinesiology and Medicine, University of Wisconsin-Madison, Madison, WI, USA.

Funding

University of Wisconsin Institute for Clinical and Translational ResearchUL1TR002373 · NCATS · UNIVERSITY OF WISCONSIN-MADISON · PI ELIZABETH S BURNSIDE, Allan R. Brasier · 2017 to 2026
$75.9M
NCATS NIH HHS UL1 TR002373
6 · The paper itself

Abstract

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.

Indexed as

electronic health recordshealth disparitiesHealth equitylearning health systemspublic reportingquality improvement collaborativessocial determinants of health

Identifiers

PMID37008604
PMCPMC10052445

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.