Dataset Information

Validation of the JEN frailty index in the National Long-Term Care Survey community population: identifying functionally impaired older adults from claims data.

ABSTRACT:

Background

Use of a claims-based index to identify persons with physical function impairment and at risk for long-term institutionalization would facilitate population health and comparative effectiveness research. The JEN Frailty Index [JFI] is comprised of diagnosis domains representing impairments and multimorbid clusters with high long-term institutionalization [LTI] risk. We test the index's discrimination of activities-of-daily-living [ADL] dependency and 1-year LTI and mortality in a nationally representative sample of over 12,000 Medicare beneficiaries, and compare long-term community survival stratified by ADL and JFI.

Methods

2004 U.S. National Long-Term Care Survey data were linked to Medicare, Minimum Data Set, Veterans Health Administration files and vital statistics. ADL dependencies, JFI score, age and sex were measured at baseline survey. ADL and JFI groups were cross-tabulated generating likelihood ratios and classification statistics. Logistic regression compared discrimination (areas under receiver operating characteristic curves), multivariable calibration and accuracy of the JFI and, separately, ADLs, in predicting 1-year outcomes. Hall-Wellner bands facilitated contrasts of JFI- and ADL-stratified 5-year community survival.

Results

Likelihood ratios rose evenly across JFI risk categories. Areas under the curves of functional dependency at ≥3 and ≥ 2 for JFI, age and sex models were 0.807 [95% c.i.: 0.795, 0.819] and 0.812 [0.801, 0.822], respectively. The area under the LTI curve for JFI and age (0.781 [0.747, 0.815]) discriminated less well than the ADL-based model (0.829 [0.799, 0.860]). Community survival separated by JFI strata was comparable to ADL strata.

Conclusions

The JEN Frailty Index with demographic covariates is a valid claims-based measure of concurrent activities-of-daily-living impairments and future long-term institutionalization risk in older populations lacking functional information.

SUBMITTER: Kinosian B

PROVIDER: S-EPMC6267903 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

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Publications

Validation of the JEN frailty index in the National Long-Term Care Survey community population: identifying functionally impaired older adults from claims data.

Kinosian Bruce B Wieland Darryl D Gu Xiliang X Stallard Eric E Phibbs Ciaran S CS Intrator Orna O

BMC health services research 20181129 1

<h4>Background</h4>Use of a claims-based index to identify persons with physical function impairment and at risk for long-term institutionalization would facilitate population health and comparative effectiveness research. The JEN Frailty Index [JFI] is comprised of diagnosis domains representing impairments and multimorbid clusters with high long-term institutionalization [LTI] risk. We test the index's discrimination of activities-of-daily-living [ADL] dependency and 1-year LTI and mortality i ...[more]

PMID: 30497450

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Project description:Background In aortic valve disease, the relationship between claims-based frailty indices (CFIs) and validated measures of frailty constructed from in-person assessments is unclear but may be relevant for retrospective ascertainment of frailty status when otherwise unmeasured. Methods and Results We linked adults aged ≥65 years in the US CoreValve Studies (linkage rate, 67%; mean age, 82.7±6.2 years, 43.1% women), to Medicare inpatient claims, 2011 to 2015. The Johns Hopkins CFI, validated on the basis of the Fried index, was generated for each study participant, and the association between CFI tertile and trial outcomes was evaluated as part of the EXTEND-FRAILTY substudy. Among 2357 participants (64.9% frail), higher CFI tertile was associated with greater impairments in nutrition, disability, cognition, and self-rated health. The primary outcome of all-cause mortality at 1 year occurred in 19.3%, 23.1%, and 31.3% of those in tertiles 1 to 3, respectively (tertile 2 versus 1: hazard ratio, 1.22; 95% CI, 0.98-1.51; P=0.07; tertile 3 versus 1: hazard ratio, 1.73; 95% CI, 1.41-2.12; P<0.001). Secondary outcomes (bleeding, major adverse cardiovascular and cerebrovascular events, and hospitalization) were more frequent with increasing CFI tertile and persisted despite adjustment for age, sex, New York Heart Association class, and Society of Thoracic Surgeons risk score. Conclusions In linked Medicare and CoreValve study data, a CFI based on the Fried index consistently identified individuals with worse impairments in frailty, disability, cognitive dysfunction, and nutrition and a higher risk of death, hospitalization, bleeding, and major adverse cardiovascular and cerebrovascular events, independent of age and risk category. While not a surrogate for validated metrics of frailty using in-person assessments, use of this CFI to ascertain frailty status among patients with aortic valve disease may be valid and prognostically relevant information when otherwise not measured.

Project description:BackgroundThe conventional count-based physical frailty phenotype (PFP) dichotomizes its criterion predictors-an approach that creates information loss and depends on the availability of population-derived cut-points. This study proposes an alternative approach to computing the PFP by developing and validating a model that uses PFP components to predict the frailty index (FI) in community-dwelling older adults, without the need for predictor dichotomization.MethodsA sample of 998 community-dwelling older adults (mean [SD], 68 [7] years) participated in this prospective cohort study. Participants completed a multi-domain geriatric screen and a physical fitness assessment from which the count-based PFP and the 36-item FI were computed. One-year prospective falls and hospitalization rates were also measured. Bayesian beta regression analysis, allowing for nonlinear effects of the non-dichotomized PFP criterion predictors, was used to develop a model for FI ("model-based PFP"). Approximate leave-one-out (LOO) cross-validation was used to examine model overfitting.ResultsThe model-based PFP showed good calibration with the FI, and it had better out-of-sample predictive performance than the count-based PFP (LOO-R2, 0.35 vs 0.22). In clinical terms, the improvement in prediction (i) translated to improved classification agreement with the FI (Cohen's kw, 0.47 vs 0.36) and (ii) resulted primarily in a 23% (95%CI, 18-28%) net increase in FI-defined "prefrail/frail" participants correctly classified. The model-based PFP showed stronger prognostic performance for predicting falls and hospitalization than did the count-based PFP.ConclusionThe developed model-based PFP predicted FI and clinical outcomes more strongly than did the count-based PFP in community-dwelling older adults. By not requiring predictor cut-points, the model-based PFP potentially facilitates usage and feasibility. Future validation studies should aim to obtain clear evidence on the benefits of this approach.

Project description:ObjectiveTo create an electronic frailty index (eFRAGICAP) using electronic health records (EHR) in Catalunya (Spain) and assess its predictive validity with a two-year follow-up of the outcomes: homecare need, institutionalization and mortality in the elderly. Additionally, to assess its concurrent validity compared to other standardized measures: the Clinical Frailty Scale (CFS) and the Risk Instrument for Screening in the Community (RISC).MethodsThe eFRAGICAP was based on the electronic frailty index (eFI) developed in United Kingdom, and includes 36 deficits identified through clinical diagnoses, prescriptions, physical examinations, and questionnaires registered in the EHR of primary health care centres (PHC). All subjects > 65 assigned to a PHC in Barcelona on 1st January, 2016 were included. Subjects were classified according to their eFRAGICAP index as: fit, mild, moderate or severe frailty. Predictive validity was assessed comparing results with the following outcomes: institutionalization, homecare need, and mortality at 24 months. Concurrent validation of the eFRAGICAP was performed with a sample of subjects (n = 333) drawn from the global cohort and the CFS and RISC. Discrimination and calibration measures for the outcomes of institutionalization, homecare need, and mortality and frailty scales were calculated.Results253,684 subjects had their eFRAGICAP index calculated. Mean age was 76.3 years (59.5% women). Of these, 41.1% were classified as fit, and 32.2% as presenting mild, 18.7% moderate, and 7.9% severe frailty. The mean age of the subjects included in the validation subsample (n = 333) was 79.9 years (57.7% women). Of these, 12.6% were classified as fit, and 31.5% presented mild, 39.6% moderate, and 16.2% severe frailty. Regarding the outcome analyses, the eFRAGICAP was good in the detection of subjects who were institutionalized, required homecare assistance, or died at 24 months (c-statistic of 0.841, 0.853, and 0.803, respectively). eFRAGICAP was also good in the detection of frail subjects compared to the CFS (AUC 0.821) and the RISC (AUC 0.848).ConclusionThe eFRAGICAP has a good discriminative capacity to identify frail subjects compared to other frailty scales and predictive outcomes.

Dataset Information

Validation of the JEN frailty index in the National Long-Term Care Survey community population: identifying functionally impaired older adults from claims data.

Background

Methods

Results

Conclusions

Publications

Validation of the JEN frailty index in the National Long-Term Care Survey community population: identifying functionally impaired older adults from claims data.

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