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Comparative Study
. 2016 Dec;51(6):2206-2220.
doi: 10.1111/1475-6773.12453. Epub 2016 Feb 4.

The Method for Performance Measurement Matters: Diabetes Care Quality as Measured by Administrative Claims and Institutional Registry

Rozalina G McCoy  1   2 , Sidna M Tulledge-Scheitel  1 , James M Naessens  3 , Amy E Glasgow  3 , Robert J Stroebel  1 , Sarah J Crane  1 , Kari S Bunkers  4 , Nilay D Shah  3
Affiliations
Comparative Study

The Method for Performance Measurement Matters: Diabetes Care Quality as Measured by Administrative Claims and Institutional Registry

Rozalina G McCoy et al. Health Serv Res. 2016 Dec.

Abstract

Objectives: Performance measurement is used by health care providers, payers, and patients. Historically accomplished using administrative data, registries are used increasingly to track and improve care. We assess how measured diabetes care quality differs when calculated using claims versus registry.

Data sources/study setting: Cross-sectional analysis of administrative claims and electronic health records (EHRs) of patients in a multispecialty integrated health system in 2012 (n = 368,883).

Study design: We calculated percent of patients attaining glycohemoglobin <8.0 percent, LDL cholesterol <100 mg/dL, blood pressure <140/90 mmHg, and nonsmoking (D4) in cohorts, identified by Medicare Accountable Care Organization/Minnesota Community Measures (ACO-MNCM; claims-based), Healthcare Effectiveness Data and Information Set (HEDIS; claims-based), and registry (EHR-based).

Data collection/extraction methods: Claims were linked to EHR to create a dataset of performance-eligible patients.

Principal findings: ACO-MNCM, HEDIS, and registry identified 6,475, 6,989, and 6,425 measurement-eligible patients. Half were common among the methods; discrepancies were due to attribution, age restriction, and encounter requirements. D4 attainment was lower in ACO-MNCM (36.09 percent) and HEDIS (37.51 percent) compared to registry (43.74 percent) cohorts.

Conclusions: Registry- and claims-based performance measurement methods identify different patients, resulting in different rates of quality metric attainment with implications for innovative population health management.

Keywords: Performance measures; population health; quality improvement; registry.

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Figures

Figure 1
Figure 1
Diabetes Population, Overlap, and Performance Measures Based on Each of the Attribution Methods. The Same Population Was Subjected to Patient Selection for Eligibility Criteria and Application of Diabetes Performance Measurement as Specified by ACO‐MNCM (A), HEDIS (H), or Registry (R) Notes. Displayed are the total number of patients per category and percent of patients in each category meeting the composite performance diabetes measure.
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References

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