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Identifying Future High Cost Individuals within an Intermediate Cost Population.

Juan Lu1, Erin Britton1, Jacquelyn Ferrance1

  • 1Department of Family Medicine and Population Health, Division of Epidemiology, Virginia Commonwealth University.

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Summary
This summary is machine-generated.

Predicting high healthcare costs is possible using a simple model. Factors like chronic conditions and hospital visits help identify individuals needing targeted interventions to improve health and control costs.

Keywords:
Administrative Data UsesChronic DiseasesHealth Care CostPrimary Care

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Area of Science:

  • Health Services Research
  • Health Economics
  • Predictive Analytics

Background:

  • Controlling healthcare costs and improving population health necessitates predictive tools.
  • Identifying individuals at risk of high healthcare expenditure is crucial for resource allocation.

Purpose of the Study:

  • To identify factors predicting the transition of indigent care program enrollees to a high-cost segment.
  • To develop a predictive model for future healthcare costs.

Main Methods:

  • Analysis of 9,624 enrollees from the Virginia Coordinated Care program (2010-2013).
  • Logistic regression models used to identify individuals in the top 10% of future expenditures based on prior year data.
  • Evaluation of demographics, chronic condition counts/diagnoses, and utilization indicators.

Main Results:

  • The count of chronic conditions, congestive heart failure diagnosis, and utilization metrics (hospital visits, prescriptions) were significant predictors of high future costs.
  • A model incorporating demographics and utilization indicators demonstrated reasonable predictive discrimination (c=0.67).

Conclusions:

  • A straightforward model using demographics and health utilization indicators can predict high future healthcare costs.
  • Chronic condition burden and specific diagnoses enhance predictive accuracy.
  • Validated models can identify high-risk individuals for targeted interventions to reduce utilization and improve health outcomes.