Reducing latency in medication reconciliation after hospital discharge

Abstract

Techniques for discovering or predicting that a patient is eligible for a post-hospital discharge medication reconciliation process are disclosed. The prediction is based on automatically applying a machine learning model to one or more incoming prescription orders, where the model has been generated from statistically analyzing a plurality of historical prescriptions to determine prescription attributes and/or values thereof that are more strongly correlated to hospital discharges than are other prescription attributes and/or values. When a prescription order is discovered to be associated with a hospital discharge, the named patient is deemed eligible for medication reconciliation, and an alert is generated so that pharmacy personnel may initiate a post-hospital discharge medication reconciliation process for the patient. As such, patient health outcomes may be improved after being discharged from the hospital, as post-hospital discharge medication reconciliations are able to be completed within 30 days of the patient's discharge using the disclosed techniques.