Predictors of 1-year change in patient activation in older adults with diabetes mellitus and heart disease

Published: July 1, 2012
Category: Bibliography > Papers
Authors: Anderson ML, Chubak J, Hubbard RA, Liss DT, Morales LS, Reid RJ, Saunders KW, Tuzzio L
Countries: United States
Language: null
Types: Population Health
Settings: Academic

J Am Geriatr Soc 60:1316-1321.

Group Health Research Institute, Seattle, Washington, USA

OBJECTIVES: To identify patterns and predictors of 1-year change in patient activation in chronically ill older adults.

DESIGN: Prospective cohort study.

SETTING: Integrated healthcare delivery system.

PARTICIPANTS: Members of an integrated delivery system from 2007 to 2009 in western Washington state aged 65 and older with diabetes mellitus or heart disease; participants responded to baseline and 1-year follow-up mailed surveys about their health and health care (N = 2,341).

MEASUREMENTS: Patient activation was measured using the 13-item Patient Activation Measure (PAM) at baseline and follow-up. Automated diagnoses and procedure data were extracted from databases. Multinomial logistic regression, stratified according to baseline activation stage, was used to estimate the odds ratios for increasing or decreasing activation stage associated with participant characteristics and serious adverse health events.

RESULTS: Fifty-two percent of participants changed activation stage between baseline and follow-up. Of people who changed stage, 54% increased, and 46% decreased. Older age and worse baseline self-reported health were independent predictors of activation change in multivariate models. Changes in health status or serious adverse health events such as the occurrence of hospitalizations, new major diagnoses, or procedures were not related to changes in activation in this age group.

CONCLUSION: Patient activation, as measured using the PAM, changes over time in elderly adults with chronic diseases. Clinicians and researchers who use the PAM for patient care or as an outcome measure in research studies should be aware of its fluctuation over time in chronically ill older persons.

PMID: 22788389

Age,High-Impact Chronic Conditions,Targeted Program,United States,80 and over,Delivery of Health Care,Integrated,Disease Progression,Gender,Logistic Models,Predictive Value of Tests,Prospective Studies,Surveys and Questionnaires,Washington

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