Date of Award

1-1-2017

Language

English

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

College/School/Department

Department of Information Science

Content Description

1 online resource (vi, 117 pages) : color illustrations.

Dissertation/Thesis Chair

Suraj Commuri

Committee Members

Ӧzlem Uzuner, Jagdish Gangolly, Priya Nambisan, Robert Dachs

Keywords

medication reconciliation, preventable medication errors, Medication errors, Medical informatics, Decision support systems

Subject Categories

Library and Information Science

Abstract

Discrepancies in medication information lead to medication errors that impose an enormous, yet preventable burden on patients, the healthcare system, and society. The inordinate amount of attention given to the process of reconciling discrepancies has bestowed such inorganic dominance upon the process itself that the primal goals of medication management and patient safety have devolved into implicit considerations. A chief impediment that continues to forestall the homogeneous application of medication reconciliation is the absence of standardization. This dissertation disassembles the most significant barrier to standardization by unbundling the role of clinicians from the process, and additionally challenges the lethargy in engaging physicians more centrally. Empirical evidence presented here demonstrates that simple machine-based logic is able to effectively replace the experience, nuance, and reflection of highly trained clinical pharmacists in identifying discrepancies reliably, but with greater efficiency and parsimony. Uniform implementation of such an approach built upon simple machine-based logic not only holds potential for achieving superior medication reconciliation compared to its current instantiation, but also paves the way for yielding richer interactions with patients, reducing costs for both patients and the healthcare system, influencing process redesign, and informing the domains of information and healthcare policy.

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