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Singh H, Spitzmueller C, Petersen NJ, Sawhney MK, Sittig DF. Information Overload and Missed Test Results in Electronic Health Record–Based Settings. JAMA Intern Med. 2013;173(8):702–704. doi:10.1001/2013.jamainternmed.61
Author Affiliations: Houston VA Health Services Research and Development Center of Excellence, Center of Inquiry to Improve Outpatient Safety Through Effective Electronic Communication, Michael E. DeBakey Veterans Affairs Medical Center, Houston, Texas (Drs Singh, Petersen, and Sawhney); Section of Health Services Research, Department of Medicine, Baylor College of Medicine, Houston (Drs Singh, Petersen, and Sawhney); Department of Psychology, University of Houston, Houston (Dr Spitzmueller); and School of Biomedical Informatics and University of Texas–Memorial Hermann Center for Healthcare Quality and Safety, University of Texas Health Science Center at Houston (Dr Sittig).
Electronic health record (EHR)-based alerts are often used to notify practitioners of abnormal test results, but follow-up failures (missed results) continue to occur in outpatient settings.1 In the Department of Veterans Affairs (VA), abnormal test result alerts are generated automatically for prespecified abnormal laboratory values or manually by the interpreting radiologist when an unexpected finding is noted.2-4 Factors such as workflow, user behaviors, and organizational characteristics likely affect EHR-based test result follow-up.1,5 Thus, we examined the “sociotechnical” predictors of missed test results in the setting of EHR-based alerts.
From June 2010 through November 2010, we conducted a cross-sectional survey of VA primary care practitioners (PCPs); trainees and subspecialists were excluded.6 The survey content was informed by an 8-dimensional sociotechnical model7 representing multiple complex facets of EHR-based test result notification. Survey items assessed PCPs' perceptions of technological factors (eg, EHR notification software, its ease of use, content of alerts PCPs received, EHR user interface) and social factors (eg, workflow, people, and organizational policies and procedures) related to alert follow-up. We assessed potential information overload by asking if practitioners received more alerts than they could effectively manage or received too many alerts to focus on the most important ones.
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