Use of Data-Driven Methods to Predict Long-term Patterns of Health Care Spending for Medicare Patients.

ABSTRACT:

Importance

Current approaches to predicting health care costs generally rely on a single composite value of spending and focus on short time horizons. By contrast, examining patients' spending patterns using dynamic measures applied over longer periods may better identify patients with different spending and help target interventions to those with the greatest need.

Objective

To classify patients by their long-term, dynamic health care spending patterns using a data-driven approach and assess the ability to predict spending patterns, particularly using characteristics that are potentially modifiable through intervention.

Design, setting, and participants

This cohort study used a retrospective cohort design from a random nationwide sample of Medicare fee-for-service ad

SUBMITTER: Lauffenburger JC 

PROVIDER: S-EPMC7573679 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature