Predicting Falls in People Aged 65 Years and Older From Insurance Claims
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Homer, Mark L.
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Homer, Mark L. 2016. Predicting Falls in People Aged 65 Years and Older From Insurance Claims. Master's thesis, Harvard Medical School.Abstract
IMPORTANCE: 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.
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