TY - JOUR
T1 - Grand challenges in clinical decision support
AU - Sittig, Dean F.
AU - Wright, Adam
AU - Osheroff, Jerome A.
AU - Middleton, Blackford
AU - Teich, Jonathan M.
AU - Ash, Joan S.
AU - Campbell, Emily
AU - Bates, David W.
N1 - Funding Information:
This research was supported by a Grant LM06942 from the National Library of Medicine, National Institutes of Health, titled Overcoming the Unintended Consequences of Computerized Physician Order Entry Implementation. Emily Campbell and Adam Wright were also supported by National Library of Medicine training Grant ASMMI0031.
PY - 2008/4
Y1 - 2008/4
N2 - There is a pressing need for high-quality, effective means of designing, developing, presenting, implementing, evaluating, and maintaining all types of clinical decision support capabilities for clinicians, patients and consumers. Using an iterative, consensus-building process we identified a rank-ordered list of the top 10 grand challenges in clinical decision support. This list was created to educate and inspire researchers, developers, funders, and policy-makers. The list of challenges in order of importance that they be solved if patients and organizations are to begin realizing the fullest benefits possible of these systems consists of: improve the human-computer interface; disseminate best practices in CDS design, development, and implementation; summarize patient-level information; prioritize and filter recommendations to the user; create an architecture for sharing executable CDS modules and services; combine recommendations for patients with co-morbidities; prioritize CDS content development and implementation; create internet-accessible clinical decision support repositories; use freetext information to drive clinical decision support; mine large clinical databases to create new CDS. Identification of solutions to these challenges is critical if clinical decision support is to achieve its potential and improve the quality, safety and efficiency of healthcare.
AB - There is a pressing need for high-quality, effective means of designing, developing, presenting, implementing, evaluating, and maintaining all types of clinical decision support capabilities for clinicians, patients and consumers. Using an iterative, consensus-building process we identified a rank-ordered list of the top 10 grand challenges in clinical decision support. This list was created to educate and inspire researchers, developers, funders, and policy-makers. The list of challenges in order of importance that they be solved if patients and organizations are to begin realizing the fullest benefits possible of these systems consists of: improve the human-computer interface; disseminate best practices in CDS design, development, and implementation; summarize patient-level information; prioritize and filter recommendations to the user; create an architecture for sharing executable CDS modules and services; combine recommendations for patients with co-morbidities; prioritize CDS content development and implementation; create internet-accessible clinical decision support repositories; use freetext information to drive clinical decision support; mine large clinical databases to create new CDS. Identification of solutions to these challenges is critical if clinical decision support is to achieve its potential and improve the quality, safety and efficiency of healthcare.
KW - Clinical decision support
KW - Clinical information systems
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U2 - 10.1016/j.jbi.2007.09.003
DO - 10.1016/j.jbi.2007.09.003
M3 - Article
C2 - 18029232
AN - SCOPUS:40049093057
SN - 1532-0464
VL - 41
SP - 387
EP - 392
JO - Journal of Biomedical Informatics
JF - Journal of Biomedical Informatics
IS - 2
ER -