Applied Use of Composite Quality Measures for EHR-enabled Practices.

EGEMS (Wash DC)

New York City Department of Health and Mental Hygiene.

Published: August 2015

AI Article Synopsis

  • The Primary Care Information Project (PCIP) in NYC supports healthcare providers in using electronic health records (EHRs) to enhance patient care since 2005, focusing on improving performance in quality measures.
  • The study examined four Composite Quality Measures (CQMs) across 93 practices to track their performance over a year, revealing that lower-performing practices showed the most significant progress.
  • Findings suggest that understanding which EHR functionalities impact each CQM can help tailor technical support for practices, especially those in the low performance tier, to foster further improvement.

Article Abstract

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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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4537085PMC
http://dx.doi.org/10.13063/2327-9214.1118DOI Listing

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