Jibby E Kurichi1, Pui L Kwong2, Dawei Xie3, Hillary R Bogner4. 1. Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Perelman School of Medicine, 423 Guardian Dr, 907 Blockley Hall, Philadelphia, PA 19104-6021(∗). Electronic address: jkurichi@mail.med.upenn.edu. 2. Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA(†). 3. Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA(‡). 4. Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA; Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA(§).
Abstract
BACKGROUND: Prediction models can help clinicians provide the best and most appropriate care to their patients and can help policy makers design services for groups at highest risk for poor outcomes. OBJECTIVE: To develop prediction models identifying both risk factors and protective factors for functional deterioration, institutionalization, and death. DESIGN: Cohort study using data from the Medicare Current Beneficiary Survey (MCBS). SETTING: Community survey. PARTICIPANTS: This study included 21,264 Medicare beneficiaries 65 years of age and older who participated in the MCBS from the 2001-2008 entry panels and were followed up for 2 years. METHODS: The index was derived in 60% and validated in the remaining 40%. β Coefficients from a multinomial logistic regression model were used to derive points, which were added together to create scores associated with the outcome. MAIN OUTCOME MEASURE: The outcome was activity of daily living (ADL) stage transitions over 2 years following entry into the MCBS. Beneficiaries were categorized into 1 of 4 outcome categories: stable or improved function, functional deterioration, institutionalization, or death. RESULTS: Our model identified 16 factors for functional deterioration (age, gender, education, living arrangement, dual eligibility, proxy use, Alzheimer disease/dementia, angina pectoris/coronary heart disease, diabetes, emphysema/asthma/chronic obstructive pulmonary disease, mental/psychiatric disorder, Parkinson disease, stroke/brain hemorrhage, hearing impairment, vision impairment, and baseline ADL stage) after backward selection (P < .05). Compared to stable or improved function, the risk of functional deterioration ranged from ≤1 to ≥6, ≤4 to ≥22 for the risk of institutionalization, and ≤3 to ≥16 for the risk of death. CONCLUSION: Predictive indices, or point and scoring systems used to predict outcomes, can identify elderly Medicare beneficiaries at risk for functional deterioration, institutionalization, and death and can aid policy makers, clinicians, and family members in improving care for older adults and supporting successful aging in the community. LEVEL OF EVIDENCE: III.
BACKGROUND: Prediction models can help clinicians provide the best and most appropriate care to their patients and can help policy makers design services for groups at highest risk for poor outcomes. OBJECTIVE: To develop prediction models identifying both risk factors and protective factors for functional deterioration, institutionalization, and death. DESIGN: Cohort study using data from the Medicare Current Beneficiary Survey (MCBS). SETTING: Community survey. PARTICIPANTS: This study included 21,264 Medicare beneficiaries 65 years of age and older who participated in the MCBS from the 2001-2008 entry panels and were followed up for 2 years. METHODS: The index was derived in 60% and validated in the remaining 40%. β Coefficients from a multinomial logistic regression model were used to derive points, which were added together to create scores associated with the outcome. MAIN OUTCOME MEASURE: The outcome was activity of daily living (ADL) stage transitions over 2 years following entry into the MCBS. Beneficiaries were categorized into 1 of 4 outcome categories: stable or improved function, functional deterioration, institutionalization, or death. RESULTS: Our model identified 16 factors for functional deterioration (age, gender, education, living arrangement, dual eligibility, proxy use, Alzheimer disease/dementia, angina pectoris/coronary heart disease, diabetes, emphysema/asthma/chronic obstructive pulmonary disease, mental/psychiatric disorder, Parkinson disease, stroke/brain hemorrhage, hearing impairment, vision impairment, and baseline ADL stage) after backward selection (P < .05). Compared to stable or improved function, the risk of functional deterioration ranged from ≤1 to ≥6, ≤4 to ≥22 for the risk of institutionalization, and ≤3 to ≥16 for the risk of death. CONCLUSION: Predictive indices, or point and scoring systems used to predict outcomes, can identify elderly Medicare beneficiaries at risk for functional deterioration, institutionalization, and death and can aid policy makers, clinicians, and family members in improving care for older adults and supporting successful aging in the community. LEVEL OF EVIDENCE: III.
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