INTRODUCTION: 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. DISCUSSION: 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. CONCLUSION: 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. Copyright (c) 2009. Published by Elsevier Ireland Ltd.
INTRODUCTION: 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. DISCUSSION: 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. CONCLUSION: 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. Copyright (c) 2009. Published by Elsevier Ireland Ltd.
Authors: K Yamashita; T Okabayashi; T Yokoyama; T Yatabe; H Maeda; M Manabe; K Hanazaki Journal: Acta Anaesthesiol Scand Date: 2008-10-22 Impact factor: 2.105
Authors: Lesly A Dossett; Hanqing Cao; Nathan T Mowery; Marcus J Dortch; John M Morris; Addison K May Journal: Am Surg Date: 2008-08 Impact factor: 0.688
Authors: Ching-Ping Lin; Thomas H Payne; W Paul Nichol; Patricia J Hoey; Curtis L Anderson; John H Gennari Journal: J Am Med Inform Assoc Date: 2008-06-25 Impact factor: 4.497
Authors: Susan J Logtenberg; Nanne Kleefstra; Ferdinand T Snellen; Klaas H Groenier; Robbert J Slingerland; Arno P Nierich; Henk J Bilo Journal: Diabetes Technol Ther Date: 2009-01 Impact factor: 6.118
Authors: Mathijs Vogelzang; Bert G Loef; Joost G Regtien; Iwan C C van der Horst; Hein van Assen; Felix Zijlstra; Maarten W N Nijsten Journal: Intensive Care Med Date: 2008-04-04 Impact factor: 17.440
Authors: Thomas R Campion; Addison K May; Lemuel R Waitman; Asli Ozdas; Cynthia S Gadd Journal: Intensive Care Med Date: 2010-03-30 Impact factor: 17.440
Authors: Thomas R Campion; Lemuel R Waitman; Nancy M Lorenzi; Addison K May; Cynthia S Gadd Journal: Int J Med Inform Date: 2011-10-21 Impact factor: 4.046
Authors: Meryl Bloomrosen; Justin Starren; Nancy M Lorenzi; Joan S Ash; Vimla L Patel; Edward H Shortliffe Journal: J Am Med Inform Assoc Date: 2011 Jan-Feb Impact factor: 4.497
Authors: Thomas R Campion; Addison K May; Lemuel R Waitman; Asli Ozdas; Nancy M Lorenzi; Cynthia S Gadd Journal: J Am Med Inform Assoc Date: 2011-03-14 Impact factor: 4.497
Authors: Kavishwar B Wagholikar; Kathy L MacLaughlin; Michael R Henry; Robert A Greenes; Ronald A Hankey; Hongfang Liu; Rajeev Chaudhry Journal: J Am Med Inform Assoc Date: 2012-04-29 Impact factor: 4.497
Authors: Ashly D Black; Josip Car; Claudia Pagliari; Chantelle Anandan; Kathrin Cresswell; Tomislav Bokun; Brian McKinstry; Rob Procter; Azeem Majeed; Aziz Sheikh Journal: PLoS Med Date: 2011-01-18 Impact factor: 11.069