Growth in the understanding of many diseases and the increasing complexity of treatments are now so rapid that it has become “humanly impossible” for unaided healthcare professionals to deliver consistent, high-quality patient care with the efficacy, safety and efficiency that modern medical research makes possible. National and international efforts to disseminate up-to-date knowledge of evidence-based practice (e.g. the international Cochrane collaboration and the NHS NICE clinical guidelines programme) are widely seen as key to translating the results of clinical research into clinical practice. However the impacts of such efforts on actual clinician behaviour are “mixed” at best (Chidgey et al 2007; Fox et al, 2009).

Three recent systematic reviews indicate that clinical decision support (CDS) systems have considerable promise for helping clinicians use and comply with best practice as expressed in clinical guidelines to improve quality and safety in patient care (Garg et al 2005; Kawamoto et al 2005; Chaudrhy et al, 2006). Garg et al report that 70% of published trials of clinical decision support applications show significant improvements in clinical decision-making and, if key criteria are met, this rises to more than 95%. It is increasingly accepted worldwide that CDS and other advanced information technologies such as workflow services will become a key tool in clinical practice. was created in 2002 to help raise awareness of the benefits of clinical decision support, workflow and other advanced knowledge management technologies in patient care and clinical research. It was established as an open information service on developments in these fields and as a portal for clinicians, technologists, healthcare providers, commercial IT suppliers and others. The OpenClinical user base is conservatively estimated at 25,000 individuals worldwide and attracts more than 150,000 visitors a year.

A major obstacle to the deployment of advanced knowledge based services in medicine is the absence of practical development platforms, delivery infrastructures, and scalable repositories of machine-readable knowledge bases, application services and service components (Greenes, 2007). These will be necessary to carry out the research that is needed to demonstrate clinical value and achieve wide adoption of CDS technology. was set up as an extension to to provide methods and technologies to author, maintain, publish, trial and deploy enactable knowledge applications for healthcare (e.g. formalising medical logic and clinical decisions, modeling and simulating processes of care, and hosting research trials). provides access to Tallis, an experimental suite of tools and services to support the development of decision support applications in clinical practice.


Chaudhry, Basit, et al. “Systematic Review: Impact of Health Information Technology on Quality, Efficiency, and Costs of Medical Care.” Annals of Internal Medicine 144, no. 10 (May 16, 2006): 742–52.
Chidgey J, Leng G, Lacey T. Implementing NICE guidance. J R Soc Med. 2007 Oct;100(10):448-52.
Fox J, Patkar V, Chronakis I, Begent R. From practice guidelines to clinical decision support: closing the loop. J R Soc Med 2009; 102 (11):464-473.
Garg AX, Adhikari NK, McDonald H et al. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. JAMA. 2005 Mar 9;293(10):1223-38.
Robert A. Greenes (editor). Clinical decision support systems : the road ahead. Elsevier, 2007.
Kawamoto K, Houlihan CA, Balas EA, Lobach DF. Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success. BMJ. 2005 Apr 2;330(7494):765.
Kawamoto et al British Medical Journal 2005.