Abstract
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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 905-913 |
| Number of pages | 9 |
| Journal | Journal of Biomedical Informatics |
| Volume | 46 |
| Issue number | 5 |
| DOIs | |
| State | Published - Oct 2013 |
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Keywords
- Clinical decision support
- Emergency department
- Pediatrics
- Prediction rules
- Traumatic brain injury
ASJC Scopus subject areas
- Computer Science Applications
- Health Informatics
Cite this
Informing the design of clinical decision support services for evaluation of children with minor blunt head trauma in the emergency department : A sociotechnical analysis. / Sheehan, Barbara; Nigrovic, Lise E.; Dayan, Peter S.; Kuppermann, Nathan; Ballard, Dustin W.; Alessandrini, Evaline; Bajaj, Lalit; Goldberg, Howard; Hoffman, Jeffrey; Offerman, Steven R.; Mark, Dustin G.; Swietlik, Marguerite; Tham, Eric; Tzimenatos, Leah S; Vinson, David R.; Jones, Grant S.; Bakken, Suzanne.
In: Journal of Biomedical Informatics, Vol. 46, No. 5, 10.2013, p. 905-913.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Informing the design of clinical decision support services for evaluation of children with minor blunt head trauma in the emergency department
T2 - A sociotechnical analysis
AU - Sheehan, Barbara
AU - Nigrovic, Lise E.
AU - Dayan, Peter S.
AU - Kuppermann, Nathan
AU - Ballard, Dustin W.
AU - Alessandrini, Evaline
AU - Bajaj, Lalit
AU - Goldberg, Howard
AU - Hoffman, Jeffrey
AU - Offerman, Steven R.
AU - Mark, Dustin G.
AU - Swietlik, Marguerite
AU - Tham, Eric
AU - Tzimenatos, Leah S
AU - Vinson, David R.
AU - Jones, Grant S.
AU - Bakken, Suzanne
PY - 2013/10
Y1 - 2013/10
N2 - 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.
AB - 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.
KW - Clinical decision support
KW - Emergency department
KW - Pediatrics
KW - Prediction rules
KW - Traumatic brain injury
UR - http://www.scopus.com/inward/record.url?scp=84883825012&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84883825012&partnerID=8YFLogxK
U2 - 10.1016/j.jbi.2013.07.005
DO - 10.1016/j.jbi.2013.07.005
M3 - Article
C2 - 23892207
AN - SCOPUS:84883825012
VL - 46
SP - 905
EP - 913
JO - Journal of Biomedical Informatics
JF - Journal of Biomedical Informatics
SN - 1532-0464
IS - 5
ER -