McCoy Rozalina G, Tulledge-Scheitel Sidna M, Naessens James M, Glasgow Amy E, Stroebel Robert J, Crane Sarah J, Bunkers Kari S, Shah Nilay D
Division of Primary Care Internal Medicine, Department of Medicine, Mayo Clinic, Rochester, MN.
Department of Health Sciences Research, Mayo Clinic, Rochester, MN.
Health Serv Res. 2016 Dec;51(6):2206-2220. doi: 10.1111/1475-6773.12453. Epub 2016 Feb 4.
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).
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.
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.
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.
医疗服务提供者、支付方和患者都会使用绩效评估。过去,绩效评估主要通过行政数据来完成,而现在越来越多地使用登记系统来跟踪和改善医疗服务。我们评估了使用索赔数据与登记系统计算时,所衡量的糖尿病护理质量有何不同。
数据来源/研究背景:对2012年一个多专科综合医疗系统中患者的行政索赔数据和电子健康记录(EHR)进行横断面分析(n = 368,883)。
我们计算了队列中糖化血红蛋白<8.0%、低密度脂蛋白胆固醇<100mg/dL、血压<140/90mmHg以及不吸烟(D4)的患者百分比,这些队列分别通过医疗保险责任医疗组织/明尼苏达社区测量(ACO-MNCM;基于索赔数据)、医疗保健有效性数据和信息集(HEDIS;基于索赔数据)以及登记系统(基于EHR)来确定。
数据收集/提取方法:将索赔数据与EHR关联,以创建符合绩效评估条件的患者数据集。
ACO-MNCM、HEDIS和登记系统分别识别出6475例、6989例和6425例符合测量条件的患者。其中一半患者在不同方法中是相同的;差异是由于归因、年龄限制和就诊要求所致。与登记系统队列(43.74%)相比,ACO-MNCM队列(36.09%)和HEDIS队列(37.51%)中达到D4的比例较低。
基于登记系统和基于索赔数据的绩效评估方法识别出不同的患者,导致质量指标的达成率不同,这对创新型人群健康管理具有重要意义。