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Predicting Potential Postdischarge Adverse Drug Events and 30-Day Unplanned Hospital Readmissions From Medication Regimen Complexity

Schoonover, Hilary MNurs, FNP; Corbett, Cynthia F. PhD, RN, MN, BA; Weeks, Douglas L. PhD; Willson, Megan N. PharmD; Setter, Stephen M. PharmD, DVM, CGP

doi: 10.1097/PTS.0000000000000067
Original Article

Objectives: To determine whether medication regimen complexity (MRC) could predict likelihood for occurrence of potential adverse drug events (ADEs), unplanned 30-day hospital readmission, or 30-day emergency department use in patients transitioning from hospital to home care.

Methods: Hospital discharge medication lists and medication lists constructed during visits to patients’ homes were analyzed for 213 participants. MRC was quantified with the Medication Regimen Complexity Index (MRCI). The potential for ADEs was based on medication discrepancies detected between the discharge and patient reported home medication lists. Unplanned acute care utilization in the 30 days after index hospitalization was tracked. Logistic regression analyses were used to approximate the odds for an ADE and postdischarge acute care utilization from MRCI scores.

Results: Home medication lists were less complex than hospital discharge medication lists. High home medication list MRCI scores increased the odds more than 4-fold for a potential ADE (P < 0.001). High discharge medication list MRCI scores increased the odds more than 5-fold for an unplanned 30-day hospital readmission (P = 0.026). High regimen complexity did not significantly elevate odds for emergency department use.

Conclusions: MRC was predictive of patients’ potential for ADEs and unplanned hospital readmission. MRC may be useful in identifying patients that would benefit from additional transitional care interventions. Results indicate that simplifying medication regimens may favorably impact postdischarge outcomes.

Correspondence: Hilary Schoonover, MNurs, FNP, 2288 N Merrit Creek Loop, Couer d’Alene, ID 83814-4959 (e-mail: hilary.cutler@email.wsu.edu).

Support for this work was provided, in part, by a grant from the Robert Wood Johnson Foundation’s Interdisciplinary Nursing Quality Research Initiative.

© 2014 by Lippincott Williams & Wilkins