Objectives: To assess two models for the prediction of health utilization and functions using standardized in-person assessments of frailty and administrative claims-based geriatric risk measures among Medicare fee-for-service beneficiaries aged 65 years and above. Methods: Outcomes of hospitalizations, death, and functional help were investigated for participants in the 2011 National Health and Aging Trends Study. For each outcome, multivariable logistic regression model was used to investigate claims-based geriatric risk and survey-based frailty. Results: Both claims-based and survey-based models showed moderate discrimination. The c-statistic of the standardized frailty models ranged from 0.67 (for any hospitalization) to 0.84 (for any IADL [instrumental activities of daily living] help). Models using administrative data ranged from 0.71 (for any hospitalization) to 0.81 (for any IADL help). Discussion: Models based on existing administrative data appear to be as discriminate as survey-based models. Health care providers and insurance plans can effectively apply existing data resources to help identify high-risk individuals for potential care management interventions.
Objectives: To assess two models for the prediction of health utilization and functions using standardized in-person assessments of frailty and administrative claims-based geriatric risk measures among Medicare fee-for-service beneficiaries aged 65 years and above. Methods: Outcomes of hospitalizations, death, and functional help were investigated for participants in the 2011 National Health and Aging Trends Study. For each outcome, multivariable logistic regression model was used to investigate claims-based geriatric risk and survey-based frailty. Results: Both claims-based and survey-based models showed moderate discrimination. The c-statistic of the standardized frailty models ranged from 0.67 (for any hospitalization) to 0.84 (for any IADL [instrumental activities of daily living] help). Models using administrative data ranged from 0.71 (for any hospitalization) to 0.81 (for any IADL help). Discussion: Models based on existing administrative data appear to be as discriminate as survey-based models. Health care providers and insurance plans can effectively apply existing data resources to help identify high-risk individuals for potential care management interventions.
Entities:
Keywords:
frailty; geriatric syndrome; health care utilization; predictive modeling
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