Literature DB >> 35508198

Generating and Reporting Electronic Clinical Quality Measures from Electronic Health Records: Strategies from EvidenceNOW Cooperatives.

Joshua E Richardson1, Luke V Rasmussen2, David A Dorr3, Jenna T Sirkin4, Donna Shelley5, Adovich Rivera6, Winfred Wu7, Samuel Cykert8, Deborah J Cohen9, Abel N Kho10.   

Abstract

BACKGROUND: Electronic clinical quality measures (eCQMs) from electronic health records (EHRs) are a key component of quality improvement (QI) initiatives in small-to-medium size primary care practices, but using eCQMs for QI can be challenging. Organizational strategies are needed to effectively operationalize eCQMs for QI in these practice settings.
OBJECTIVE: This study aimed to characterize strategies that seven regional cooperatives participating in the EvidenceNOW initiative developed to generate and report EHR-based eCQMs for QI in small-to-medium size practices.
METHODS: A qualitative study comprised of 17 interviews with representatives from all seven EvidenceNOW cooperatives was conducted. Interviewees included administrators were with both strategic and cooperative-level operational responsibilities and external practice facilitators were with hands-on experience helping practices use EHRs and eCQMs. A subteam conducted 1-hour semistructured telephone interviews with administrators and practice facilitators, then analyzed interview transcripts using immersion crystallization. The analysis and a conceptual model were vetted and approved by the larger group of coauthors.
RESULTS: Cooperative strategies consisted of efforts in four key domains. First, cooperative adaptation shaped overall strategies for calculating eCQMs whether using EHRs, a centralized source, or a "hybrid strategy" of the two. Second, the eCQM generation described how EHR data were extracted, validated, and reported for calculating eCQMs. Third, practice facilitation characterized how facilitators with backgrounds in health information technology (IT) delivered services and solutions for data capture and quality and practice support. Fourth, performance reporting strategies and tools informed QI efforts and how cooperatives could alter their approaches to eCQMs.
CONCLUSION: Cooperatives ultimately generated and reported eCQMs using hybrid strategies because they determined neither EHRs alone nor centralized sources alone could operationalize eCQMs for QI. This required cooperatives to devise solutions and utilize resources that often are unavailable to typical small-to-medium-sized practices. The experiences from EvidenceNOW cooperatives provide insights into how organizations can plan for challenges and operationalize EHR-based eCQMs. Thieme. All rights reserved.

Entities:  

Mesh:

Year:  2022        PMID: 35508198      PMCID: PMC9068273          DOI: 10.1055/s-0042-1748145

Source DB:  PubMed          Journal:  Appl Clin Inform        ISSN: 1869-0327            Impact factor:   2.762


  18 in total

1.  Achieving meaningful use of health information technology: a guide for physicians to the EHR incentive programs.

Authors:  Leah Marcotte; Joshua Seidman; Karen Trudel; Donald M Berwick; David Blumenthal; Farzad Mostashari; Sachin H Jain
Journal:  Arch Intern Med       Date:  2012-05-14

2.  Report of the AMIA EHR-2020 Task Force on the status and future direction of EHRs.

Authors:  Thomas H Payne; Sarah Corley; Theresa A Cullen; Tejal K Gandhi; Linda Harrington; Gilad J Kuperman; John E Mattison; David P McCallie; Clement J McDonald; Paul C Tang; William M Tierney; Charlotte Weaver; Charlene R Weir; Michael H Zaroukian
Journal:  J Am Med Inform Assoc       Date:  2015-05-28       Impact factor: 4.497

3.  Integration of Clinical Decision Support and Electronic Clinical Quality Measurement: Domain Expert Insights and Implications for Future Direction.

Authors:  Polina Kukhareva; Charlene R Weir; Catherine Staes; Damian Borbolla; Stacey Slager; Kensaku Kawamoto
Journal:  AMIA Annu Symp Proc       Date:  2018-12-05

4.  Specifications of Clinical Quality Measures and Value Set Vocabularies Shift Over Time: A Study of Change through Implementation Differences.

Authors:  Raja A Cholan; Nicole G Weiskopf; Douglas L Rhoton; Nicholas V Colin; Rachel L Ross; Melanie N Marzullo; Bhavaya Sachdeva; David A Dorr
Journal:  AMIA Annu Symp Proc       Date:  2018-04-16

5.  Quantifying the Effect of Data Quality on the Validity of an eMeasure.

Authors:  Steven G Johnson; Stuart Speedie; Gyorgy Simon; Vipin Kumar; Bonnie L Westra
Journal:  Appl Clin Inform       Date:  2017-12-14       Impact factor: 2.342

6.  EHRs in primary care practices: benefits, challenges, and successful strategies.

Authors:  Debora Goetz Goldberg; Anton J Kuzel; Lisa Bo Feng; Jonathan P DeShazo; Linda E Love
Journal:  Am J Manag Care       Date:  2012-02-01       Impact factor: 2.229

7.  Understanding the Impact of Variations in Measurement Period Reporting for Electronic Clinical Quality Measures.

Authors:  Nicholas V Colin; Raja A Cholan; Bhavaya Sachdeva; Benjamin E Nealy; Michael L Parchman; David A Dorr
Journal:  EGEMS (Wash DC)       Date:  2018-07-19

8.  Benchmarking is associated with improved quality of care in type 2 diabetes: the OPTIMISE randomized, controlled trial.

Authors:  Michel P Hermans; Moses Elisaf; Georges Michel; Erik Muls; Frank Nobels; Hans Vandenberghe; Carlos Brotons
Journal:  Diabetes Care       Date:  2013-07-11       Impact factor: 19.112

Review 9.  Do cardiology quality measures actually improve patient outcomes?

Authors:  Paula Chatterjee; Karen E Joynt
Journal:  J Am Heart Assoc       Date:  2014-02-07       Impact factor: 5.501

10.  Using Clinical Data Standards to Measure Quality: A New Approach.

Authors:  John D D'Amore; Chun Li; Laura McCrary; Jonathan M Niloff; Dean F Sittig; Allison B McCoy; Adam Wright
Journal:  Appl Clin Inform       Date:  2018-06-13       Impact factor: 2.342

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.