Authors: Pamela A. Bozzo Silva, MD
Primary Advisor: Elmer V. Bernstam, MD, MSE, MS (co-author)
Committee Members: Eliz Markowitz (co-author); Todd R. Johnson, PhD (co-author); Jiajie Zhang, PhD (co-author); Jorge R. Herskovic, MD, PhD (co-author)
Masters thesis, The University of Texas School of Biomedical Informatics at Houston.
Abstract:
Medication reconciliation is a National Patient Safety Goal (NPSG) from The Joint Commission (TJC) that entails reviewing all medications a patient takes after a health care transition. Medication reconciliation is a resource intensive, error-prone task, and the resources to accomplish it may not be routinely available. Computer-based methods have the potential to overcome these barriers. We designed and explored a rule-based medication reconciliation algorithm to accomplish this task across different healthcare transitions. We tested our algorithm on a random sample of 94 transitions from the Clinical Data Warehouse at the University of Texas Health Science Center at Houston. We found that the algorithm reconciled, on average, 23.4% of the potentially reconcilable medications. Our study did not have sufficient statistical power to establish whether the kind of transition affects reconcilability. We conclude that automated reconciliation is possible and will help accomplish the NPSG.