Automated electronic reminders to prevent miscommunication among primary medical, surgical and anaesthesia providers: a root cause analysis

Department of Anesthesiology, 1H247 Box 0048, University of Michigan Hospital, 1500 East Medical Center Drive, Ann Arbor, MI 48109, USA
BMJ quality & safety (Impact Factor: 3.99). 07/2012; 21(10):850-4. DOI: 10.1136/bmjqs-2011-000666
Source: PubMed


In this case report, the authors present an adverse event possibly caused by miscommunication among three separate medical teams at their hospital. The authors then discuss the hospital's root cause analysis and its proposed solutions, focusing on the subsequent hospital-wide implementation of an automated electronic reminder for abnormal laboratory values that may have helped to prevent similar medical errors.

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    ABSTRACT: Study Objective To perform a frequency analysis of start minute digits (SMD) and end minute digits (EMD) taken from the electronic, computer-assisted, and manual anesthesia billing-record systems. Design Retrospective cross-sectional review. Setting University medical center. Measurements This cross-sectional review was conducted on billing records from a single healthcare institution over a 15-month period. A total of 30,738 cases were analyzed. For each record, the start time and end time were recorded. Distributions of SMD and EMD were tested against the null hypothesis of a frequency distribution equivalently spread between zero and nine. Main Results SMD and EMD aggregate distributions each differed from equivalency (P < 0.0001). When stratified by type of anesthetic record, no differences were found between the recorded and expected equivalent distribution patterns for electronic anesthesia records for start minute (P < 0.98) or end minute (P < 0.55). Manual and computer-assisted records maintained nonequivalent distribution patterns for SMD and EMD (P < 0.0001 for each comparison). Comparison of cumulative distributions between SMD and EMD distributions suggested a significant difference between the two patterns (P < 0.0001). Conclusion An electronic anesthesia record system, with automated time capture of events verified by the user, produces a more unified distribution of billing times than do more traditional methods of entering billing times.
    Journal of Clinical Anesthesia 06/2014; 26(4). DOI:10.1016/j.jclinane.2013.10.016 · 1.19 Impact Factor

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