Clinical Benefits of an Embedded Decision Support System in Anticoagulant Control

Computer-based decision support (CDSS) systems can deliver real patient care and increase chances of long-term survival in areas of chronic disease management prone to poor control. One such CDSS, for the management of warfarin, is described in this paper and the outcomes shown. Data is derived from the running system and show a performance consistently around 20% better than the applicable guidelines. Keywords—“Decision Support”, “Anticoagulant Control”

[1]  Patrice Degoulet,et al.  An overview of the effect of computer-assisted management of anticoagulant therapy on the quality of anticoagulation , 1998, Int. J. Medical Informatics.

[2]  M Stefanelli,et al.  A specialized framework for medical diagnostic knowledge-based systems. , 1992, Computers and biomedical research, an international journal.

[3]  M S Leaning,et al.  Validation of an algorithm for oral anticoagulant dosing and appointment scheduling. , 1995, Clinical and laboratory haematology.

[4]  M J Buxton,et al.  Anti-coagulant monitoring service delivery: a comparison of costs of hospital and community outreach clinics. , 2000, Clinical and laboratory haematology.

[5]  M Bryans,et al.  Decision support software for dementia diagnosis and management in primary care: Relevance and potential , 2003, Aging & mental health.

[6]  Jonathan M. Teich,et al.  The impact of computerized physician order entry on medication error prevention. , 1999, Journal of the American Medical Informatics Association : JAMIA.

[7]  Jochen R. Möhr.  A Quantitative Perspective on the Virtual Patient Record (VPR) and its Realization , 1998, MedInfo.

[8]  M. Leaning,et al.  Evaluation of a decision support system for initiation and control of oral anticoagulation in a randomised trial , 1997, BMJ.

[9]  Paul Wallace,et al.  Embedding guidelines into direct physician order entry: simple methods, powerful results , 1999, AMIA.

[10]  Patrice Degoulet,et al.  Computer-Adjusted Dosage of Anticoagulant Therapy Improves the Quality of Anticoagulation , 1998, MedInfo.

[11]  T Austin.  The Development and Comparative Evaluation of Middleware and Database Architectures for the Implementation of an Electronic Healthcare Record , 2004 .

[12]  Dipak Kalra,et al.  Synapses in Use: Supporting Cardiac Care at the Whittington Hospital , 1998 .

[13]  D. Bates,et al.  Improving response to critical laboratory results with automation: results of a randomized controlled trial. , 1999, Journal of the American Medical Informatics Association : JAMIA.

[14]  M. Leaning,et al.  Comparison of oral anticoagulant control by a nurse-practitioner using a computer decision-support system with that by clinicians. , 1997, Clinical and laboratory haematology.

[15]  M. Modell,et al.  A prototype computer decision support system for the management of asthma , 1996, Journal of Medical Systems.

[16]  Guidelines on oral anticoagulation: third edition , 1998 .

[17]  E. Balas,et al.  Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success , 2005, BMJ : British Medical Journal.

[18]  D M Rind,et al.  Designing studies of computer-based alerts and reminders. , 1995, M.D. computing : computers in medical practice.