Predicting 30-day risk from benzodiazepine/Z-drug dispensations in older adults using administrative data: A prognostic machine learning approach.

Developing ML models using only administrative health data may not provide health regulators with sufficient informative predictions to use as decision aids for potential interventions, especially if considering daily or quarterly classifications of BZRA risks in older adults. ML models may be informative for this context if yearly classifications are preferred. Health regulators should have access to other types of data to improve ML prediction.