Evidence map›Paper›PMID 29881739›Full record

ArticleEGEMS (Washington, DC)2017

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

Raja A Cholan, Nicole G Weiskopf, Doug Rhoton, Bhavaya Sachdeva, Nicholas V Colin, Shelby J Martin, David A Dorr

Abstract read
In one paragraph

Article in EGEMS (Washington, DC), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Raja A CholanOregon Health & Science University.
Nicole G WeiskopfOregon Health & Science University.
Doug RhotonOregon Health & Science University.
Bhavaya SachdevaOregon Health & Science University.
Nicholas V ColinOregon Health & Science University.
Shelby J MartinOregon Health & Science University.
David A DorrOregon Health & Science University.

Funding

The Northwest Coalition for Primary Care Practice SupportR18HS023908 · AHRQ · KAISER FOUNDATION HEALTH PLAN OF WASHINGTON · PI PARCHMAN, MICHAEL L · 2015 to 2017
$13.3M
AHRQ HHS R18 HS023908
6 · The paper itself

Abstract

objectiveTo understand the impact of distinct concept to value set mapping on the measurement of quality of care.

backgroundClinical 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.

methodsWe 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.

resultsGlobal 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'.

conclusionThe 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.

Identifiers

PMID29881739
PMCPMC5983064

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.