CholGate: Computerized clinical decision support for primary and secondary prevention of cardiovascular disease

The aim of this research was to study the effect of two methods used in providing clinical decision support (CDSS) in primary care, on demand/order entry or alerting/critiquing. Within the overall objective we investigated the impact of a computer-based intervention that supports the general practitioner in performing primary and secondary prevention of CVD. To achieve this objective we analyzed the practice guidelines of the Dutch College of General Practitioners with respect to recommendations for primary and secondary prevention of CVD, analysed current practises of Dutch general practitioners with regards to primary and secondary prevention of CVD, designed the decision support system CholGate, and conducted a randomized trial to assess which method of decision support yields most effect on GP compliance to the recommendations of the DCGP guidelines. This study shows that both the On-demand and Alerting version of CholGate greatly improve screening perf! ormance for dyslipidaemia. In addition, although CholGate On-demand seemed to improve treatment performance, only CholGate Alerting significantly improve treatment performance for dyslipidaemia by general practitioners

Cholgate - a randomized controlled trial comparing the effect of automated and on-demand decision support on the management of cardiovascular disease factors in primary care

Automated and on-demand decision support systems integrated into an electronic medical record have proven to be an effective implementation strategy for guidelines. Cholgate is a randomized controlled trial comparing the effect of automated and on-demand decision support on the management of cardiovascular disease factors in primary care

Electronic alerts versus on-demand decision support to improve dyslipidemia treatment: A cluster randomized controlled trial

BACKGROUND - Indirect evidence shows that alerting users with clinical decision support systems seems to change behavior more than requiring users to actively initiate the system. However, randomized trials comparing these methods in a clinical setting are lacking. We studied the effect of both alerting and on-demand decision support with respect to screening and treatment of dyslipidemia based on the guidelines of the Dutch College of General Practitioners. METHODS AND RESULTS - In a clustered randomized trial design, 38 Dutch general practices (77 physicians) and 87 886 of their patients (39 433 men 18 to 70 years of age and 48 453 women 18 to 75 years of age) who used the ELIAS electronic health record participated. Each practice was assigned to receive alerts, on-demand support, or no intervention. We measured the percentage of patients screened and treated after 12 months of follow-up. In the alerting group, 65% of the patients requiring screening were screened (relative risk versus control=1.76; 95% confidence interval, 1.41 to 2.20) compared with 35% of patients in the on-demand group (relative risk versus control=1.28; 95% confidence interval, 0.98 to 1.68) and 25% of patients in the control group. In the alerting group, 66% of patients requiring treatment were treated (relative risk versus control=1.40; 95% confidence interval, 1.15 to 1.70) compared with 40% of patients (relative risk versus control=1.19; 95% confidence interval, 0.94 to 1.50) in the on-demand group and 36% of patients in the control group. CONCLUSION - The alerting version of the clinical decision support systems significantly improved screening and treatment performance for dyslipidemia by general practitioners