Title | Quantifying the impact of health IT implementations on clinical workflow: a new methodological perspective. |
Publication Type | Journal Article |
Year of Publication | 2010 |
Authors | Zheng, K, Haftel, HM, Hirschl, RB, O'Reilly, M, Hanauer, DA |
Journal | J Am Med Inform Assoc |
Volume | 17 |
Issue | 4 |
Pagination | 454-61 |
Date Published | 2010 Jul-Aug |
ISSN | 1527-974X |
Keywords | Computer Graphics, Decision Support Systems, Management, Female, Health Plan Implementation, Humans, Intensive Care Units, Pediatric, Male, Medical Order Entry Systems, Michigan, Pattern Recognition, Automated, Time and Motion Studies, Workflow |
Abstract | Health IT implementations often introduce radical changes to clinical work processes and workflow. Prior research investigating this effect has shown conflicting results. Recent time and motion studies have consistently found that this impact is negligible; whereas qualitative studies have repeatedly revealed negative end-user perceptions suggesting decreased efficiency and disrupted workflow. We speculate that this discrepancy may be due in part to the design of the time and motion studies, which is focused on measuring clinicians' 'time expenditures' among different clinical activities rather than inspecting clinical 'workflow' from the true 'flow of the work' perspective. In this paper, we present a set of new analytical methods consisting of workflow fragmentation assessments, pattern recognition, and data visualization, which are accordingly designed to uncover hidden regularities embedded in the flow of the work. Through an empirical study, we demonstrate the potential value of these new methods in enriching workflow analysis in clinical settings. |
DOI | 10.1136/jamia.2010.004440 |
Alternate Journal | J Am Med Inform Assoc |
PubMed ID | 20595314 |
PubMed Central ID | PMC2995654 |
Grant List | UL1RR024986 / RR / NCRR NIH HHS / United States |
Research reported in this publication was supported by the National Cancer Institutes of
Health under Award Number P30CA046592. The content is solely the responsibility
of the authors and does not necessarily represent the official views of the
National Institutes of Health.
Research reported in this publication was supported by the National Cancer Institutes of
Health under Award Number P30CA046592 by the use of the following Cancer Center
Shared Resource(s): Biostatistics, Analytics & Bioinformatics; Flow Cytometry;
Transgenic Animal Models; Tissue and Molecular Pathology; Structure & Drug
Screening; Cell & Tissue Imaging; Experimental Irradiation; Preclinical
Imaging & Computational Analysis; Health Communications; Immune Monitoring;
Pharmacokinetics)
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