Literature DB >> 28525558

Electronic clinical quality measure reporting challenges: findings from the Medicare EHR Incentive Program's Controlling High Blood Pressure Measure.

Dawn M Heisey-Grove1, Hilary K Wall2, Janet S Wright2.   

Abstract

Objective: To identify physician and practice characteristics associated with high clinical and technical performance on the electronic clinical quality measure (eCQM) that calculates the proportion of patients with hypertension who have controlled blood pressure. Materials and
Methods: The study included 268 602 physicians participating in the Medicare Electronic Health Record Incentive Program between 2011 and 2014. Independent variables included delivery reform participation and physician, practice level, and area characteristics. Successful technical performance was a reported eCQM with non-zero values in both the numerator and denominator. Successful clinical performance was a reported eCQM value of ≥70% hypertension control.
Results: Physicians with longer experience using certified health information technology, participants in delivery reform programs, and specialists that traditionally manage hypertension were 5%-15% more likely to achieve 70% control. Physicians in smaller and rural practices and a subset of physicians unlikely to primarily manage hypertension were more likely to submit measures with a zero value in either the numerator or denominator. Discussion: More physicians are using eCQMs to track and report their quality improvement efforts. This research presents the first examination of national eCQM data to identify physician and practice-level characteristics associated with performance.
Conclusion: With careful selection of measures relevant to the clinician's specialty, complete data entry, and support for continuous quality improvement, health care professionals can excel technically and clinically. As care delivery transitions from fee-for-service to quality- and value-based models, high performers may realize financial gains and better patient outcomes. These analyses suggest patterns that may inform steps to improve performance.
© The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Entities:  

Keywords:  Million Hearts; clinical quality measures; health IT; hypertension; incentive program

Mesh:

Year:  2018        PMID: 28525558     DOI: 10.1093/jamia/ocx049

Source DB:  PubMed          Journal:  J Am Med Inform Assoc        ISSN: 1067-5027            Impact factor:   4.497


  6 in total

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

Authors:  Joshua E Richardson; Luke V Rasmussen; David A Dorr; Jenna T Sirkin; Donna Shelley; Adovich Rivera; Winfred Wu; Samuel Cykert; Deborah J Cohen; Abel N Kho
Journal:  Appl Clin Inform       Date:  2022-05-04       Impact factor: 2.762

2.  Observing Provider Utilization of Electronic Health Records to Improve Clinical Quality Metrics.

Authors:  Kevin Brooks; Molly Polverento; Laura Houdeshell-Putt; Erin Sarzynski; Sabrina Ford
Journal:  Perspect Health Inf Manag       Date:  2022-01-01

3.  Primary Care Practices' Ability to Report Electronic Clinical Quality Measures in the EvidenceNOW Southwest Initiative to Improve Heart Health.

Authors:  Kyle E Knierim; Tristen L Hall; L Miriam Dickinson; Donald E Nease; Dionisia R de la Cerda; Douglas Fernald; Molly J Bleecker; Robert L Rhyne; W Perry Dickinson
Journal:  JAMA Netw Open       Date:  2019-08-02

4.  Challenges to electronic clinical quality measurement using third-party platforms in primary care practices: the healthy hearts in the heartland experience.

Authors:  Faraz S Ahmad; Luke V Rasmussen; Stephen D Persell; Joshua E Richardson; David T Liss; Pauline Kenly; Isabel Chung; Dustin D French; Theresa L Walunas; Andy Schriever; Abel N Kho
Journal:  JAMIA Open       Date:  2019-09-20

5.  Practice and market factors associated with provider volume of health information exchange.

Authors:  Nate C Apathy; Joshua R Vest; Julia Adler-Milstein; Justin Blackburn; Brian E Dixon; Christopher A Harle
Journal:  J Am Med Inform Assoc       Date:  2021-07-14       Impact factor: 4.497

6.  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

  6 in total

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