Literature DB >> 26846443

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

Rozalina G McCoy1,2, Sidna M Tulledge-Scheitel1, James M Naessens3, Amy E Glasgow3, Robert J Stroebel1, Sarah J Crane1, Kari S Bunkers4, Nilay D Shah3.   

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. © Health Research and Educational Trust.

Entities:  

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

Mesh:

Year:  2016        PMID: 26846443      PMCID: PMC5134196          DOI: 10.1111/1475-6773.12453

Source DB:  PubMed          Journal:  Health Serv Res        ISSN: 0017-9124            Impact factor:   3.402


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1.  Patient attribution: why the method matters.

Authors:  Rozalina G McCoy; Kari S Bunkers; Priya Ramar; Sarah K Meier; Lorelle L Benetti; Robert E Nesse; James M Naessens
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2.  Comparison of Electronic Health Record-Based and Claims-Based Diabetes Care Quality Measures: Causes of Discrepancies.

Authors:  Michael Barton Laws; Joanne Michaud; Renee Shield; William McQuade; Ira B Wilson
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3.  Using Clinical Data Standards to Measure Quality: A New Approach.

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