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Use of Electronic Health Records and Quality of Ambulatory Healthcare

Background This study aimed to measure the association between electronic health record (EHR) use and quality measures in ambulatory healthcare. Methodology A quantitative, retrospective, cross-sectional design was used by examining secondary data from the 2015-2016 National Ambulatory Medical Care...

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Autores principales: Alammari, Duaa, Banta, Jim E, Shah, Huma, Reibling, Ellen, Talsania, Shrenik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cureus 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9664254/
https://www.ncbi.nlm.nih.gov/pubmed/36407230
http://dx.doi.org/10.7759/cureus.30343
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author Alammari, Duaa
Banta, Jim E
Shah, Huma
Reibling, Ellen
Talsania, Shrenik
author_facet Alammari, Duaa
Banta, Jim E
Shah, Huma
Reibling, Ellen
Talsania, Shrenik
author_sort Alammari, Duaa
collection PubMed
description Background This study aimed to measure the association between electronic health record (EHR) use and quality measures in ambulatory healthcare. Methodology A quantitative, retrospective, cross-sectional design was used by examining secondary data from the 2015-2016 National Ambulatory Medical Care Survey. The relationship between EHR use and seven quality measures was examined using the Donabedian model as a framework. Quality measures included (a) diabetes measures, (b) obesity measures, (c) blood pressure screening, (d) depression screening, and (e) breast cancer screening. A total of 37,290 office visits were included, representing 817 million national office visits. For each of the quality measures, we determined the (a) associations using unadjusted and adjusted regression models based on subsets of the sample that met the inclusion criteria for quality measures; and (b) the changes in the area under the curve (AUC). Results Approximately 75% of office visits fulfilled all EHR use. Positive associations were found between EHR use and better quality for the following three out of seven measures: higher odds of screening for obesity (odds ratio (OR) = 2.2; p = <0.0001), blood pressure (OR = 2.5; p = <0.0001), and breast cancer (OR = 1.8; p = 0.0166). Receiver operating curve results showed the highest gain in the AUC for process-grouped measures. Hence, it was considered to be a strong predictor for all quality measures. Conclusions Evidence showed improvement in some quality measures (screening for obesity, blood pressure, and breast cancer). Common and standardized health processes were more likely to be completed and recorded than others. Future policies concerning health information technology can shift the focus from improving EHR use to enhancing patient and quality outcomes. Further research is needed to identify circumstances where quality is improved.
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spelling pubmed-96642542022-11-17 Use of Electronic Health Records and Quality of Ambulatory Healthcare Alammari, Duaa Banta, Jim E Shah, Huma Reibling, Ellen Talsania, Shrenik Cureus Healthcare Technology Background This study aimed to measure the association between electronic health record (EHR) use and quality measures in ambulatory healthcare. Methodology A quantitative, retrospective, cross-sectional design was used by examining secondary data from the 2015-2016 National Ambulatory Medical Care Survey. The relationship between EHR use and seven quality measures was examined using the Donabedian model as a framework. Quality measures included (a) diabetes measures, (b) obesity measures, (c) blood pressure screening, (d) depression screening, and (e) breast cancer screening. A total of 37,290 office visits were included, representing 817 million national office visits. For each of the quality measures, we determined the (a) associations using unadjusted and adjusted regression models based on subsets of the sample that met the inclusion criteria for quality measures; and (b) the changes in the area under the curve (AUC). Results Approximately 75% of office visits fulfilled all EHR use. Positive associations were found between EHR use and better quality for the following three out of seven measures: higher odds of screening for obesity (odds ratio (OR) = 2.2; p = <0.0001), blood pressure (OR = 2.5; p = <0.0001), and breast cancer (OR = 1.8; p = 0.0166). Receiver operating curve results showed the highest gain in the AUC for process-grouped measures. Hence, it was considered to be a strong predictor for all quality measures. Conclusions Evidence showed improvement in some quality measures (screening for obesity, blood pressure, and breast cancer). Common and standardized health processes were more likely to be completed and recorded than others. Future policies concerning health information technology can shift the focus from improving EHR use to enhancing patient and quality outcomes. Further research is needed to identify circumstances where quality is improved. Cureus 2022-10-16 /pmc/articles/PMC9664254/ /pubmed/36407230 http://dx.doi.org/10.7759/cureus.30343 Text en Copyright © 2022, Alammari et al. https://creativecommons.org/licenses/by/3.0/This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Healthcare Technology
Alammari, Duaa
Banta, Jim E
Shah, Huma
Reibling, Ellen
Talsania, Shrenik
Use of Electronic Health Records and Quality of Ambulatory Healthcare
title Use of Electronic Health Records and Quality of Ambulatory Healthcare
title_full Use of Electronic Health Records and Quality of Ambulatory Healthcare
title_fullStr Use of Electronic Health Records and Quality of Ambulatory Healthcare
title_full_unstemmed Use of Electronic Health Records and Quality of Ambulatory Healthcare
title_short Use of Electronic Health Records and Quality of Ambulatory Healthcare
title_sort use of electronic health records and quality of ambulatory healthcare
topic Healthcare Technology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9664254/
https://www.ncbi.nlm.nih.gov/pubmed/36407230
http://dx.doi.org/10.7759/cureus.30343
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