Informing the design of clinical decision support services for evaluation of children with minor blunt head trauma in the emergency department: A sociotechnical analysis

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• 作者：Barbara Sheehan ; Lise E. Nigrovic ; Peter S. Dayan ; Nathan Kuppermann ; Dustin W. Ballard ; Evaline Aless ; rini ; Lalit Bajaj ; Howard Goldberg ; Jeffrey Hoffman ; Steven R. Offerman ; Dustin G. Mark ; Marguerite Swietlik ; Eric Tham ; Leah Tzimenatos ; David R. Vinson ; Grant S. Jones ; Suzanne Bakken ; for the Pediatric Emergency Care Applied Research Network (PECARN)
• 关键词：CDSS ; clinical decision support services ; CT ; computed tomography ; ED ; emergency department ; TBI ; traumatic brain injury
• 刊名：Journal of Biomedical Informatics
• 出版年：2013
• 出版时间：October, 2013
• 年：2013
• 卷：46
• 期：5
• 页码：905-913
• 全文大小：586 K

文摘

Integration of clinical decision support services (CDSS) into electronic health records (EHRs) may be integral to widespread dissemination and use of clinical prediction rules in the emergency department (ED). However, the best way to design such services to maximize their usefulness in such a complex setting is poorly understood. We conducted a multi-site cross-sectional qualitative study whose aim was to describe the sociotechnical environment in the ED to inform the design of a CDSS intervention to implement the Pediatric Emergency Care Applied Research Network (PECARN) clinical prediction rules for children with minor blunt head trauma. Informed by a sociotechnical model consisting of eight dimensions, we conducted focus groups, individual interviews and workflow observations in 11 EDs, of which 5 were located in academic medical centers and 6 were in community hospitals. A total of 126 ED clinicians, information technology specialists, and administrators participated. We clustered data into 19 categories of sociotechnical factors through a process of thematic analysis and subsequently organized the categories into a sociotechnical matrix consisting of three high-level sociotechnical dimensions (workflow and communication, organizational factors, human factors) and three themes (interdisciplinary assessment processes, clinical practices related to prediction rules, EHR as a decision support tool). Design challenges that emerged from the analysis included the need to use structured data fields to support data capture and re-use while maintaining efficient care processes, supporting interdisciplinary communication, and facilitating family-clinician interaction for decision-making.