Dataset Information

Measuring Frailty in Administrative Claims Data: Comparative Performance of Four Claims-Based Frailty Measures in the U.S. Medicare Data.

ABSTRACT: BACKGROUND:There has been increasing effort to measure frailty in the U.S. Medicare data. The performance of claims-based frailty measures has not been compared. METHODS:This cross-sectional study included 3,097 community-dwelling fee-for-service Medicare beneficiaries (mean age 75.6 years) who participated in the 2008 Health and Retirement Study examination. Four claims-based frailty measures developed by Davidoff, Faurot, Segal, and Kim were compared against frailty phenotype, a deficit-accumulation frailty index (FI), and activities of daily living (ADL) dependence using Spearman correlation coefficients and C-statistics. RESULTS:Claims-based frailty measures were positively associated with frailty phenotype (prevalence in ?10th vs >90th percentile: 8.0% vs 41.3% for Davidoff; 5.9% vs 53.1% for Faurot; 3.3% vs 48.0% for Segal; 2.9% vs 51.0% for Kim) and FI (mean in ?10th vs >90th percentile: 0.17 vs 0.33 for Davidoff; 0.13 vs 0.37 for Faurot; 0.12 vs 0.31 for Segal; 0.10 vs 0.37 for Kim). The age and sex-adjusted C-statistics for frailty phenotype for Davidoff, Faurot, Segal, and Kim indices were 0.73, 0.74, 0.73, and 0.78, respectively, and partial correlation coefficients with FI were 0.18, 0.32, 0.26, and 0.55, respectively. The results for ADL dependence were similar (prevalence in ?10th vs >90th percentile: 3.7% vs 50.5% for Davidoff; 2.3% vs 55.0% for Faurot; 3.0% vs 38.3% for Segal; 2.3% vs 50.8% for Kim). The age and sex-adjusted C-statistics for the indices were 0.79, 0.80, 0.74, and 0.81, respectively. CONCLUSIONS:The choice of a claims-based frailty measure can influence the identification of older adults with frailty and disability in Medicare data.

SUBMITTER: Kim DH

PROVIDER: S-EPMC7243587 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Measuring Frailty in Administrative Claims Data: Comparative Performance of Four Claims-Based Frailty Measures in the U.S. Medicare Data.

Kim Dae Hyun DH Patorno Elisabetta E Pawar Ajinkya A Lee Hemin H Schneeweiss Sebastian S Glynn Robert J RJ

The journals of gerontology. Series A, Biological sciences and medical sciences 20200501 6

<h4>Background</h4>There has been increasing effort to measure frailty in the U.S. Medicare data. The performance of claims-based frailty measures has not been compared.<h4>Methods</h4>This cross-sectional study included 3,097 community-dwelling fee-for-service Medicare beneficiaries (mean age 75.6 years) who participated in the 2008 Health and Retirement Study examination. Four claims-based frailty measures developed by Davidoff, Faurot, Segal, and Kim were compared against frailty phenotype, a ...[more]

PMID: 31566201

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Project description:ObjectivesAdministrative claims data sets are often used for emergency care research and policy investigations of healthcare resource utilization, acute care practices, and evaluation of quality improvement interventions. Despite the high profile of emergency department (ED) visits in analyses using administrative claims, little work has evaluated the degree to which existing definitions based on claims data accurately captures conventionally defined hospital-based ED services. We sought to construct an operational definition for ED visitation using a comprehensive Medicare data set and to compare this definition to existing operational definitions used by researchers and policymakers.MethodsWe examined four operational definitions of an ED visit commonly used by researchers and policymakers using a 20% sample of the 2012 Medicare Chronic Condition Warehouse (CCW) data set. The CCW data set included all Part A (hospital) and Part B (hospital outpatient, physician) claims for a nationally representative sample of continuously enrolled Medicare fee-for-services beneficiaries. Three definitions were based on published research or existing quality metrics including: 1) provider claims-based definition, 2) facility claims-based definition, and 3) CMS Research Data Assistance Center (ResDAC) definition. In addition, we developed a fourth operational definition (Yale definition) that sought to incorporate additional coding rules for identifying ED visits. We report levels of agreement and disagreement among the four definitions.ResultsOf 10,717,786 beneficiaries included in the sample data set, 22% had evidence of ED use during the study year under any of the ED visit definitions. The definition using provider claims identified a total of 4,199,148 ED visits, the facility definition 4,795,057 visits, the ResDAC definition 5,278,980 ED visits, and the Yale definition 5,192,235 ED visits. The Yale definition identified a statistically different (p < 0.05) collection of ED visits than all other definitions including 17% more ED visits than the provider definition and 2% fewer visits than the ResDAC definition. Differences in ED visitation counts between each definition occurred for several reasons including the inclusion of critical care or observation services in the ED, discrepancies between facility and provider billing regulations, and operational decisions of each definition.ConclusionCurrent operational definitions of ED visitation using administrative claims produce different estimates of ED visitation based on the underlying assumptions applied to billing data and data set availability. Future analyses using administrative claims data should seek to validate specific definitions and inform the development of a consistent, consensus ED visitation definitions to standardize research reporting and the interpretation of policy interventions.

Project description:ImportanceRisk adjustment models using claims-based data are central in evaluating health care performance. Although US Centers for Medicare & Medicaid Services (CMS) models apply well-vetted statistical approaches, recent changes in the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) coding system and advances in computational capabilities may provide an opportunity for enhancement.ObjectiveTo examine whether changes using already available data would enhance risk models and yield greater discrimination in hospital-level performance measures.Design, setting, and participantsThis comparative effectiveness study used ICD-9-CM codes from all Medicare fee-for-service beneficiary claims for hospitalizations for acute myocardial infarction (AMI), heart failure (HF), or pneumonia among patients 65 years and older from July 1, 2013, through September 30, 2015. Changes to current CMS mortality risk models were applied incrementally to patient-level models, and the best model was tested on hospital performance measures to model 30-day mortality. Analyses were conducted from April 19, 2018, to September 19, 2018.Main outcomes and measuresThe main outcome was all-cause death within 30 days of hospitalization for AMI, HF, or pneumonia, examined using 3 changes to current CMS mortality risk models: (1) incorporating present on admission coding to better exclude potential complications of care, (2) separating index admission diagnoses from those of the 12-month history, and (3) using ungrouped ICD-9-CM codes.ResultsThere were 361 175 hospital admissions (mean [SD] age, 78.6 [8.4] years; 189 225 [52.4%] men) for AMI, 716 790 hospital admissions (mean [SD] age, 81.1 [8.4] years; 326 825 [45.6%] men) for HF, and 988 225 hospital admissions (mean [SD] age, 80.7 [8.6] years; 460 761 [46.6%] men) for pneumonia during the study; mean 30-day mortality rates were 13.8% for AMI, 12.1% for HF, and 16.1% for pneumonia. Each change to the models was associated with incremental gains in C statistics. The best model, incorporating all changes, was associated with significantly improved patient-level C statistics, from 0.720 to 0.826 for AMI, 0.685 to 0.776 for HF, and 0.715 to 0.804 for pneumonia. Compared with current CMS models, the best model produced wider predicted probabilities with better calibration and Brier scores. Hospital risk-standardized mortality rates had wider distributions, with more hospitals identified as good or bad performance outliers.Conclusions and relevanceIncorporating present on admission coding and using ungrouped index and historical ICD-9-CM codes were associated with improved patient-level and hospital-level risk models for mortality compared with the current CMS models for all 3 conditions.

Dataset Information

Measuring Frailty in Administrative Claims Data: Comparative Performance of Four Claims-Based Frailty Measures in the U.S. Medicare Data.

Publications

Measuring Frailty in Administrative Claims Data: Comparative Performance of Four Claims-Based Frailty Measures in the U.S. Medicare Data.

Similar Datasets

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