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Applied Use of Composite Quality Measures for EHR-enabled Practices

INTRODUCTION: The Primary Care Information Project (PCIP) of the New York City Department of Health and Mental Hygiene has been assisting providers to implement health information technology such as electronic health records (EHRs) since its founding in 2005. Currently, all practices affiliated with...

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Autores principales: Amoah, Aurora O., Amirfar, Sam, Silfen, Sheryl L., Singer, Jesse, Wang, Jason J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AcademyHealth 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4537085/
https://www.ncbi.nlm.nih.gov/pubmed/26290881
http://dx.doi.org/10.13063/2327-9214.1118
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author Amoah, Aurora O.
Amirfar, Sam
Silfen, Sheryl L.
Singer, Jesse
Wang, Jason J.
author_facet Amoah, Aurora O.
Amirfar, Sam
Silfen, Sheryl L.
Singer, Jesse
Wang, Jason J.
author_sort Amoah, Aurora O.
collection PubMed
description INTRODUCTION: The Primary Care Information Project (PCIP) of the New York City Department of Health and Mental Hygiene has been assisting providers to implement health information technology such as electronic health records (EHRs) since its founding in 2005. Currently, all practices affiliated with PCIP are offered technical support services in order to improve the use of the EHR. We studied the performance of clinical practices on EHR-derived Composite Quality Measures (CQMs) over time. Because specific EHR functionalities are important to calculating the quality measures, we hypothesize that performance on each of the CQMs will differ according to the EHR functionalities, and that this can inform the process of developing targeted technical assistance for the practices. METHODS: We created four CQMs: (1) Screening, (2) Assessment, (3) Control-BP, and (4) Control-Other. Using data from 93 practices, we identified three tertiles of CQM performance (premier, average, and low tiers) for each measure. A scatterplot of CQMs in 2010 versus 2011 was used to examine the individual movement of practices by tier. A dependent t-test compared the change in mean CQMs, and a chi-square test examined the association between the score and performance tier changes. RESULTS: Over a one-year period, low tier practices demonstrated the highest gains, average tier practices had modest gains, and premier tier practices had gains in some measures, but losses in others. On the Screening CQM 70 percent of practices remained within the same tier, with 60 percent on Assessment, 52 percent on Control-BP, and 38 percent on Control-Other; the Control-Other group showed the greatest improvement. DISCUSSION: By considering EHR functionalities associated with each of the four CQMs, we suggest that technical assistance can be better targeted to low-tier performing practices. In addition, there is still the potential for improvement over time at practices more familiar with key functionalities.
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spelling pubmed-45370852015-08-19 Applied Use of Composite Quality Measures for EHR-enabled Practices Amoah, Aurora O. Amirfar, Sam Silfen, Sheryl L. Singer, Jesse Wang, Jason J. EGEMS (Wash DC) Articles INTRODUCTION: The Primary Care Information Project (PCIP) of the New York City Department of Health and Mental Hygiene has been assisting providers to implement health information technology such as electronic health records (EHRs) since its founding in 2005. Currently, all practices affiliated with PCIP are offered technical support services in order to improve the use of the EHR. We studied the performance of clinical practices on EHR-derived Composite Quality Measures (CQMs) over time. Because specific EHR functionalities are important to calculating the quality measures, we hypothesize that performance on each of the CQMs will differ according to the EHR functionalities, and that this can inform the process of developing targeted technical assistance for the practices. METHODS: We created four CQMs: (1) Screening, (2) Assessment, (3) Control-BP, and (4) Control-Other. Using data from 93 practices, we identified three tertiles of CQM performance (premier, average, and low tiers) for each measure. A scatterplot of CQMs in 2010 versus 2011 was used to examine the individual movement of practices by tier. A dependent t-test compared the change in mean CQMs, and a chi-square test examined the association between the score and performance tier changes. RESULTS: Over a one-year period, low tier practices demonstrated the highest gains, average tier practices had modest gains, and premier tier practices had gains in some measures, but losses in others. On the Screening CQM 70 percent of practices remained within the same tier, with 60 percent on Assessment, 52 percent on Control-BP, and 38 percent on Control-Other; the Control-Other group showed the greatest improvement. DISCUSSION: By considering EHR functionalities associated with each of the four CQMs, we suggest that technical assistance can be better targeted to low-tier performing practices. In addition, there is still the potential for improvement over time at practices more familiar with key functionalities. AcademyHealth 2015-07-23 /pmc/articles/PMC4537085/ /pubmed/26290881 http://dx.doi.org/10.13063/2327-9214.1118 Text en All eGEMs publications are licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License http://creativecommons.org/licenses/by-nc-nd/3.0/
spellingShingle Articles
Amoah, Aurora O.
Amirfar, Sam
Silfen, Sheryl L.
Singer, Jesse
Wang, Jason J.
Applied Use of Composite Quality Measures for EHR-enabled Practices
title Applied Use of Composite Quality Measures for EHR-enabled Practices
title_full Applied Use of Composite Quality Measures for EHR-enabled Practices
title_fullStr Applied Use of Composite Quality Measures for EHR-enabled Practices
title_full_unstemmed Applied Use of Composite Quality Measures for EHR-enabled Practices
title_short Applied Use of Composite Quality Measures for EHR-enabled Practices
title_sort applied use of composite quality measures for ehr-enabled practices
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4537085/
https://www.ncbi.nlm.nih.gov/pubmed/26290881
http://dx.doi.org/10.13063/2327-9214.1118
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