Using HCAHPS data to model correlates of medication understanding at hospital discharge
Received 2 August 2016
Accepted for publication 6 December 2016
Published 3 February 2017 Volume 2017:7 Pages 1—7
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 3
Editor who approved publication: Dr Cindy Hudson
Rebecca J Bartlett Ellis,1 Karen L Werskey,2 Rachel M Stangland,2 Susan Ofner,1,3 Giorgos Bakoyannis1,3
1Indiana University School of Nursing, Indianapolis, IN, 2Schneck Medical Center, Seymour, IN, 3Department of Biostatistics, School of Medicine, Indiana University, Indianapolis, IN, USA
Background: Hospitals are challenged to improve hospital transitions to home and are held accountable through public reporting.
Design: This cross-sectional study used patients’ self-reported experience data from the publicly reported Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey to describe correlates of medication understanding at hospital discharge, using data collected from adult patients discharged from one Midwestern community hospital (N=154).
Results: The final logistic regression model included four correlates of medication understanding: 1) nurse always communicates well, 2) physician always communicates well, 3) new prescriptions during hospital stay, and 4) very good or better mental health, and these classified 72.6% of the cases. Significant correlates of the patient strongly agreeing that they understood discharge medications were the “nurse always communicates well” (odds ratio =3.10, 95% confidence interval: 1.25, 7.66) and “very good or better self-perceived mental health” (odds ratio =2.17, 95% confidence interval: 1.02, 4.64).
Conclusion: HCAHPS data can be used to model correlates of medication understanding, which are then useful for evaluating intervention effects following quality improvement.
Keywords: medication, nurse communication, provider communication, hospital quality, nurse, nursing, physician, patient experience, patient satisfaction
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