Rationale, aims and objectivesThe United States Preventive Services Task Force recommends a one-time screening for abdominal aortic aneurysm (AAA) with ultrasonography for men aged 65 to 75 years who have ever smoked. However, despite a mortality rate of up to 80% for ruptured AAAs, providers order the screening for a minority of patients. We sought to determine the effect of a Web-based point-of-care clinical decision support system on AAA screening rates in a primary care practice.MethodsWe conducted a retrospective review of medical records of male patients aged 65 to 75 years who were seen at any of our practice sites in 2007 and 2008, before and after implementation of the clinical decision support system.ResultsOverall screening rates were 31.36% in 2007 and 44.09% in 2008 (P-value: <0.001). Of patients who had not had AAA screening prior to the visit, 3.22% completed the screening after the visit in 2007, compared with 18.24% in 2008 when the clinical support system was implemented, 5.36 times improvement (P-value: <0.001).ConclusionsA Web-based clinical decision support for primary care physicians significantly improved delivery of AAA screening of eligible patients. Carefully developed clinical decision support systems can optimize care delivery, ensuring that important preventive services are delivered to eligible patients.

The CBLS is a valid method for stratifying faculty physicians' levels of reflection on adverse patient events. Reflection scores are associated with case generalizability and relevance, indicating that reflection improves with pertinent patient encounters. We anticipate that this instrument will be useful in future research on QI among low versus high-reflecting physicians.

Background: Clinical decision support (CDS) for primary care has been shown to improve delivery of preventive services. However, there is little evidence for efficiency of physicians due to CDS assistance. In this article, we report a pilot study for measuring the impact of CDS on the time spent by physicians for deciding on preventive services and chronic disease management. Methods: We randomly selected 30 patients from a primary care practice, and assigned them to 10 physicians. The physicians were requested to perform chart review to decide on preventive services and chronic disease management for the assigned patients. The patients assignment was done in a randomized crossover design, such that each patient received 2 sets of recommendations—one from a physician with CDS assistance and the other from a different physician without CDS assistance. We compared the physician recommendations made using CDS assistance, with the recommendations made without CDS assistance. Results: The physicians required an average of 1 minute 44 seconds, when they were they had access to the decision support system and 5 minutes when they were unassisted. Hence the CDS assistance resulted in an estimated saving of 3 minutes 16 seconds (65%) of the physicians’ time, which was statistically significant (P < .0001). There was no statistically significant difference in the number of recommendations. Conclusion: Our findings suggest that CDS assistance significantly reduced the time spent by physicians for deciding on preventive services and chronic disease management. The result needs to be confirmed by performing similar studies at other institutions.