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Testing the Use of Data Drawn from the Electronic Health Record to Compare Quality

INTRODUCTION: Health systems spend $1.5 billion annually reporting data on quality, but efficacy and utility for benchmarking are limited due, in part, to limitations of data sources. Our objective was to implement and evaluate measures of pediatric quality for three conditions using electronic heal...

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Autores principales: Walsh, Kathleen E., Razzaghi, Hanieh, Hartley, David M., Utidjian, Levon, Alford, Shannon, Darwar, Rahul A., Shenkman, Elizabeth, Jonas, Susannah, Goodick, Mary, Finkelstein, Jonathan, Ozonoff, Al, Black, L. Vandy, Shapiro, Michael, Shaw, Kathryn, McCafferty-Fernandez, Jennifer, Marsolo, Keith, Kelly, Amy, Werk, Lloyd N., Smallwood, Jordan, Bailey, Charles
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8322494/
https://www.ncbi.nlm.nih.gov/pubmed/34345748
http://dx.doi.org/10.1097/pq9.0000000000000432
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author Walsh, Kathleen E.
Razzaghi, Hanieh
Hartley, David M.
Utidjian, Levon
Alford, Shannon
Darwar, Rahul A.
Shenkman, Elizabeth
Jonas, Susannah
Goodick, Mary
Finkelstein, Jonathan
Ozonoff, Al
Black, L. Vandy
Shapiro, Michael
Shaw, Kathryn
McCafferty-Fernandez, Jennifer
Marsolo, Keith
Kelly, Amy
Werk, Lloyd N.
Smallwood, Jordan
Bailey, Charles
author_facet Walsh, Kathleen E.
Razzaghi, Hanieh
Hartley, David M.
Utidjian, Levon
Alford, Shannon
Darwar, Rahul A.
Shenkman, Elizabeth
Jonas, Susannah
Goodick, Mary
Finkelstein, Jonathan
Ozonoff, Al
Black, L. Vandy
Shapiro, Michael
Shaw, Kathryn
McCafferty-Fernandez, Jennifer
Marsolo, Keith
Kelly, Amy
Werk, Lloyd N.
Smallwood, Jordan
Bailey, Charles
author_sort Walsh, Kathleen E.
collection PubMed
description INTRODUCTION: Health systems spend $1.5 billion annually reporting data on quality, but efficacy and utility for benchmarking are limited due, in part, to limitations of data sources. Our objective was to implement and evaluate measures of pediatric quality for three conditions using electronic health record (EHR)-derived data. METHODS: PCORnet networks standardized EHR-derived data to a common data model. In 13 health systems from 2 networks for 2015, we implemented the National Quality Forum measures: % children with sickle cell anemia who received a transcranial Doppler; % children on antipsychotics who had metabolic screening; and % pediatric acute otitis media with amoxicillin prescribed. Manual chart review assessed measure accuracy. RESULTS: Only 39% (N = 2,923) of 7,278 children on antipsychotics received metabolic screening (range: 20%–54%). If the measure indicated screening was performed, the chart agreed 88% of the time [95% confidence interval (CI): 81%–94%]; if it indicated screening was not done, the chart agreed 86% (95% CI: 78%–93%). Only 69% (N = 793) of 1,144 children received transcranial Doppler screening (range across sites: 49%–88%). If the measure indicated screening was performed, the chart agreed 98% of the time (95% CI: 94%–100%); if it indicated screening was not performed, the chart agreed 89% (95% CI: 82%–95%). For acute otitis media, chart review identified many qualifying cases missed by the National Quality Forum measure, which excluded a common diagnostic code. CONCLUSIONS: Measures of healthcare quality developed using EHR-derived data were valid and identified wide variation among network sites. This data can facilitate the identification and spread of best practices.
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spelling pubmed-83224942021-08-02 Testing the Use of Data Drawn from the Electronic Health Record to Compare Quality Walsh, Kathleen E. Razzaghi, Hanieh Hartley, David M. Utidjian, Levon Alford, Shannon Darwar, Rahul A. Shenkman, Elizabeth Jonas, Susannah Goodick, Mary Finkelstein, Jonathan Ozonoff, Al Black, L. Vandy Shapiro, Michael Shaw, Kathryn McCafferty-Fernandez, Jennifer Marsolo, Keith Kelly, Amy Werk, Lloyd N. Smallwood, Jordan Bailey, Charles Pediatr Qual Saf Multi-institutional collaborative and QI network research INTRODUCTION: Health systems spend $1.5 billion annually reporting data on quality, but efficacy and utility for benchmarking are limited due, in part, to limitations of data sources. Our objective was to implement and evaluate measures of pediatric quality for three conditions using electronic health record (EHR)-derived data. METHODS: PCORnet networks standardized EHR-derived data to a common data model. In 13 health systems from 2 networks for 2015, we implemented the National Quality Forum measures: % children with sickle cell anemia who received a transcranial Doppler; % children on antipsychotics who had metabolic screening; and % pediatric acute otitis media with amoxicillin prescribed. Manual chart review assessed measure accuracy. RESULTS: Only 39% (N = 2,923) of 7,278 children on antipsychotics received metabolic screening (range: 20%–54%). If the measure indicated screening was performed, the chart agreed 88% of the time [95% confidence interval (CI): 81%–94%]; if it indicated screening was not done, the chart agreed 86% (95% CI: 78%–93%). Only 69% (N = 793) of 1,144 children received transcranial Doppler screening (range across sites: 49%–88%). If the measure indicated screening was performed, the chart agreed 98% of the time (95% CI: 94%–100%); if it indicated screening was not performed, the chart agreed 89% (95% CI: 82%–95%). For acute otitis media, chart review identified many qualifying cases missed by the National Quality Forum measure, which excluded a common diagnostic code. CONCLUSIONS: Measures of healthcare quality developed using EHR-derived data were valid and identified wide variation among network sites. This data can facilitate the identification and spread of best practices. Lippincott Williams & Wilkins 2021-07-28 /pmc/articles/PMC8322494/ /pubmed/34345748 http://dx.doi.org/10.1097/pq9.0000000000000432 Text en Copyright © 2021 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY) (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Multi-institutional collaborative and QI network research
Walsh, Kathleen E.
Razzaghi, Hanieh
Hartley, David M.
Utidjian, Levon
Alford, Shannon
Darwar, Rahul A.
Shenkman, Elizabeth
Jonas, Susannah
Goodick, Mary
Finkelstein, Jonathan
Ozonoff, Al
Black, L. Vandy
Shapiro, Michael
Shaw, Kathryn
McCafferty-Fernandez, Jennifer
Marsolo, Keith
Kelly, Amy
Werk, Lloyd N.
Smallwood, Jordan
Bailey, Charles
Testing the Use of Data Drawn from the Electronic Health Record to Compare Quality
title Testing the Use of Data Drawn from the Electronic Health Record to Compare Quality
title_full Testing the Use of Data Drawn from the Electronic Health Record to Compare Quality
title_fullStr Testing the Use of Data Drawn from the Electronic Health Record to Compare Quality
title_full_unstemmed Testing the Use of Data Drawn from the Electronic Health Record to Compare Quality
title_short Testing the Use of Data Drawn from the Electronic Health Record to Compare Quality
title_sort testing the use of data drawn from the electronic health record to compare quality
topic Multi-institutional collaborative and QI network research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8322494/
https://www.ncbi.nlm.nih.gov/pubmed/34345748
http://dx.doi.org/10.1097/pq9.0000000000000432
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