Predicting Falls in People Aged 65 Years and Older From Insurance Claims
Homer, Mark L.
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CitationHomer, Mark L. 2016. Predicting Falls in People Aged 65 Years and Older From Insurance Claims. Master's thesis, Harvard Medical School.
AbstractIMPORTANCE: Accidental falls among people aged 65 years and older caused approximately 2,700,000 injuries, 27,000 deaths, and cost more than 34 billion dollars in the United States annually in recent years.
OBJECTIVE: To identify elderly patients at risk for falls who should be targeted for intervention.
DESIGN: Predictive model based on a retrospective cohort. Insurance claims from a one year observational period were used to predict a fall related claim in the following two years.
SETTING: Individuals with Aetna health insurance coverage.
PARTICIPANTS: 120,881 individuals met the following major inclusion criteria: 65 years or older, participants in Aetna’s Medicare Advantage plans, and at least three years of contiguous insurance coverage.
EXPOSURES: The predictive model takes into account a person’s age, sex, prescriptions, and diagnoses extracted from their insurance claims.
OUTCOMES AND MEASURES: At least one accidental fall during the two-year follow-up period.
RESULTS: 12,431 out of 120,881 (10.3%) members fell. Members were stratified across 20 risk strata (approximately 6,000 members per level). Those in the highest stratum had a 36.4% risk of falling in the next two years and their relative risk for a fall was 13.3 compared with the lowest risk stratum, which had only a 1.8% chance of a fall.
CONCLUSIONS AND RELEVANCE: Cohorts at high risk of falls can be readily identified up to two years in advance, enabling intervention to be targeted.
Citable link to this pagehttp://nrs.harvard.edu/urn-3:HUL.InstRepos:42061440