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Empirical research

From Concepts and Codes to Healthcare Quality Measurement: Understanding Variations in Value Set Vocabularies for a Statin Therapy Clinical Quality Measure

Authors:

Raja A. Cholan ,

Oregon Health & Science University
About Raja A.
BS
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Nicole G. Weiskopf,

Oregon Health & Science University
About Nicole G.
PhD
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Doug L. Rhoton,

Oregon Health & Science University
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Bhavaya Sachdeva,

Oregon Health & Science University
About Bhavaya
MPH
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Nicholas V. Colin,

Oregon Health & Science University
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MA
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Shelby J. Martin,

Oregon Health & Science University
About Shelby J.
MS, RD
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David A. Dorr

Oregon Health & Science University
About David A.
MD, MS
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Abstract

Objective: To understand the impact of distinct concept to value set mapping on the measurement of quality of care.

Background: Clinical quality measures (CQMs) intend to measure the quality of healthcare services provided, and to help promote evidence-based therapies. Most CQMs consist of grouped codes from vocabularies - or ‘value sets’ - that represent the unique identifiers (i.e., object identifiers), concepts (i.e., value set names), and concept definitions (i.e., code groups) that define a measure’s specifications. In the development of a statin therapy CQM, two unique value sets were created by independent measure developers for the same global concepts.

Methods: We first identified differences between the two value set specifications of the same CQM. We then implemented the various versions in a quality measure calculation registry to understand how the differences affected calculated prevalence of risk and measure performance.

Results: Global performance rates only differed by 0.8%, but there were up to 2.3 times as many patients included with key conditions, and differing performance rates of 7.5% for patients with ‘myocardial infarction’ and 3.5% for those with ‘ischemic vascular disease’.

Conclusion: The decisions CQM developers make about which concepts and code groups to include or exclude in value set vocabularies can lead to inaccuracies in the measurement of quality of care. One solution is that developers could provide rationale for these decisions. Endorsements are needed to encourage system vendors, payers, informaticians, and clinicians to collaborate in the creation of more integrated terminology sets.

How to Cite: Cholan RA, Weiskopf NG, Rhoton DL, Sachdeva B, Colin NV, Martin SJ, et al.. From Concepts and Codes to Healthcare Quality Measurement: Understanding Variations in Value Set Vocabularies for a Statin Therapy Clinical Quality Measure. eGEMs (Generating Evidence & Methods to improve patient outcomes). 2017;5(1):19. DOI: http://doi.org/10.13063/egems.1300
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Published on 04 Sep 2017.
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