Social, organizational, and contextual characteristics of clinical decision support systems for intensive insulin therapy: a literature review and case study.
BACKGROUND
Evaluations of computerized clinical decision support systems (CDSS) typically focus on clinical performance changes and do not include social, organizational, and contextual characteristics explaining use and effectiveness. Studies of CDSS for intensive insulin therapy (IIT) are no exception, and the literature lacks an understanding of effective computer-based IIT implementation and operation.


RESULTS
This paper presents (1) a literature review of computer-based IIT evaluations through the lens of institutional theory, a discipline from sociology and organization studies, to demonstrate the inconsistent reporting of workflow and care process execution and (2) a single-site case study to illustrate how computer-based IIT requires substantial organizational change and creates additional complexity with unintended consequences including error.


CONCLUSIONS
Computer-based IIT requires organizational commitment and attention to site-specific technology, workflow, and care processes to achieve intensive insulin therapy goals. The complex interaction between clinicians, blood glucose testing devices, and CDSS may contribute to workflow inefficiency and error. Evaluations rarely focus on the perspective of nurses, the primary users of computer-based IIT whose knowledge can potentially lead to process and care improvements.


CONCLUSIONS
This paper addresses a gap in the literature concerning the social, organizational, and contextual characteristics of CDSS in general and for intensive insulin therapy specifically. Additionally, this paper identifies areas for future research to define optimal computer-based IIT process execution: the frequency and effect of manual data entry error of blood glucose values, the frequency and effect of nurse overrides of CDSS insulin dosing recommendations, and comprehensive ethnographic study of CDSS for IIT.
Campion
Thomas R
TR
Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN, USA. thomas.campion@vanderbilt.edu
Waitman
Lemuel R
LR
May
Addison K
AK
Ozdas
Asli
A
Lorenzi
Nancy M
NM
Gadd
Cynthia S
CS
D000465:Algorithms; D001292:Attitude to Computers; D003659:Decision Making, Organizational; D020000:Decision Support Systems, Clinical; D006785:Hospitals, University; D006801:Humans; D007004:Hypoglycemic Agents / Q000008:administration & dosage*; D007328:Insulin / Q000008:administration & dosage*; D007362:Intensive Care Units; D007400:Interprofessional Relations; D019982:Organizational Case Studies; D009936:Organizational Innovation; D013714:Tennessee; D014584:User-Computer Interface
D007004:Hypoglycemic Agents; D007328:Insulin