Guideline-Based Decision Support Systems for Prevention and Management of Chronic Diseases

Abstract

One of the greatest challenges in today’s health care is closing the gap between scientific evidence and medical practice. Keeping up with information in health care has never been easy, but with 500,000 clinical trials currently listed in the Cochrane Controlled Trials Register, and 75 clinical trials and 11 systematic reviews published daily (Bastian, 2010), physicians face unmanageable information processing tasks. It has been estimated that clinicians would have to read 20 papers a day to keep abreast of advances in biomedical knowledge (Shaneyfelt, 2001), and that it may take up to 20 years before findings from scientific studies are implemented in medical practice (Institute of Medicine [IOM], 2001). Medicine is not reaping the full benefits of research efforts, and much of the knowledge that is acquired in scientific studies is lost in translation. The lack of success in translating research findings into medical practice is particularly prevalent in the prevention and management of chronic diseases (Lenfant, 2003). For instance, the protective benefits of beta-blockers for patients who are recovering from myocardial infarction were established in 1981 (β-Blocker Heart Attack Study Group, 1981), and confirmed by several later studies. Yet in 1996, beta-blockers were being prescribed for only 62.5 percent of patients who had had a myocardial infarction in the U.S. (National Committee for Quality Assurance, 1997). Similarly, in 1983 it was shown that aspirin is a highly effective therapy in patients with acute myocardial infarction and unstable angina, and as long-term, secondary preventive therapy in patients with established cardiovascular disease (Awtry & Loscalzo, 2000). Nonetheless, in the year 2000 aspirin was being prescribed for at most one third of patients with coronary artery disease for whom there were no contraindications to its use (Stafford & Radley, 2003). Clinical practice guidelines are considered essential instruments to increase the application of scientific evidence to routine care (IOM, 2001). Guidelines summarize the available evidence for specific medical conditions, and provide cut-and-dried recommendations for common medical tasks such as screening, diagnosis, triage, treatment selection, and longterm management of patients. However, guidelines are often not followed in clinical practice. Implementing clinical practice guidelines in routine care has proved to be a challenging problem of its own. Computerised decision support is an effective means to solve this problem, as computers can provide, concurrent with care, reminders and advice