Prospectively identifying older adults at risk for potentially avoidable hospitalizations in Korea using...

The purpose of this study is to develop and validate a prediction model to identify older adults at risk for potentially avoidable hospitalizations (PAHs) using variables readily available in routinely collected health administrative data.

Population-based, retrospective observational study using National Health Insurance Service-National Sample Cohort (NHIS-NSC) data.

Primary care settings in South Korea.

The sample includes 113 612 older NHI beneficiaries in the year 2011, among which 2856 had one or more PAHs in 2012.

We examined multi-dimensional risk factors of PAHs in the base year and developed and validated prediction models of hospitalization risk using the following year. The predictive power of the developed models was examined with samples generated by the bootstrap method. The performance of the final model was evaluated with further test statistics at different risk thresholds.

Predicting PAHs.

The c-statistic of the final predictive model was 0.784 (CI: 0.769-0.799). The final model including all selected predictors showed the greatest marginal improvement (integrated discrimination improvement of 365%) compared to the base model. The positive predictive value was good.

Our prediction model based on health administrative data can assist the insurer and practitioners to proactively identify and intervene with older adults at risk for a PAH.