Literature DB >> 25326598

Completeness, accuracy, and computability of National Quality Forum-specified eMeasures.

Andy Amster1, Joseph Jentzsch1, Ham Pasupuleti2, K G Subramanian2.   

Abstract

OBJECTIVE: To analyze the completeness, computability, and accuracy of specifications for five National Quality Forum-specified (NQF) eMeasures spanning ambulatory, post-discharge, and emergency care within a comprehensive, integrated electronic health record (EHR) environment.
MATERIALS AND METHODS: To evaluate completeness, we assessed eMeasure logic, data elements, and value sets. To evaluate computability, we assessed the translation of eMeasure algorithms to programmable logic constructs and the availability of EHR data elements to implement specified data criteria, using a de-identified clinical data set from Kaiser Permanente Northwest. To assess accuracy, we compared eMeasure results with those obtained independently by existing audited chart abstraction methods used for external and internal reporting.
RESULTS: One measure specification was incomplete; missing applicable LOINC codes rendered it non-computable. For three of four computable measures, data availability issues occurred; the literal specification guidance for a data element differed from the physical implementation of the data element in the EHR. In two cases, cross-referencing specified data elements to EHR equivalents allowed variably accurate measure computation. Substantial data availability issues occurred for one of the four computable measures, producing highly inaccurate results. DISCUSSION: Existing clinical workflows, documentation, and coding in the EHR were significant barriers to implementing eMeasures as specified. Implementation requires redesigning business or clinical practices and, for one measure, systemic EHR modifications, including clinical text search capabilities.
CONCLUSIONS: Five NQF eMeasures fell short of being machine-consumable specifications. Both clinical domain and technological expertise are required to implement manually intensive steps from data mapping to text mining to EHR-specific eMeasure implementation.
© The Author 2014. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Keywords:  Electronic Health Record; Healthcare Quality Indicators/Methods; Meaningful Use; Process Assessment (Health Care)

Mesh:

Year:  2014        PMID: 25326598     DOI: 10.1136/amiajnl-2014-002865

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


  8 in total

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2.  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

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Journal:  J Am Med Inform Assoc       Date:  2022-04-13       Impact factor: 4.497

Review 5.  A new era of quality measurement in rheumatology: electronic clinical quality measures and national registries.

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6.  Using a stakeholder-engaged approach to develop and validate electronic clinical quality measures.

Authors:  Jill Boylston Herndon; Krishna Aravamudhan; Ronald L Stephenson; Ryan Brandon; Jesley Ruff; Frank Catalanotto; Huong Le
Journal:  J Am Med Inform Assoc       Date:  2017-05-01       Impact factor: 4.497

7.  Desiderata for computable representations of electronic health records-driven phenotype algorithms.

Authors:  Huan Mo; William K Thompson; Luke V Rasmussen; Jennifer A Pacheco; Guoqian Jiang; Richard Kiefer; Qian Zhu; Jie Xu; Enid Montague; David S Carrell; Todd Lingren; Frank D Mentch; Yizhao Ni; Firas H Wehbe; Peggy L Peissig; Gerard Tromp; Eric B Larson; Christopher G Chute; Jyotishman Pathak; Joshua C Denny; Peter Speltz; Abel N Kho; Gail P Jarvik; Cosmin A Bejan; Marc S Williams; Kenneth Borthwick; Terrie E Kitchner; Dan M Roden; Paul A Harris
Journal:  J Am Med Inform Assoc       Date:  2015-09-05       Impact factor: 4.497

8.  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

  8 in total

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