Documentation-based clinical decision support to improve antibiotic prescribing for acute respiratory infections in primary care: a cluster randomised controlled trial

Background and objective Clinical guidelines discourage antibiotic prescribing for many acute respiratory infections (ARIs), especially for non-antibiotic appropriate diagnoses. Electronic health record (EHR)-based clinical decision support has the potential to improve antibiotic prescribing for ARIs. Methods We randomly assigned 27 primary care clinics to receive an EHR-integrated, documentation based clinical decision support system for the care of patients with ARIs - the ARI Smart Form - or to offer usual care. The primary outcome was the antibiotic prescribing rate for ARIs in an intent-to-intervene analysis based on administrative diagnoses. Results During the intervention period, patients made 21 961 ARI visits to study clinics. Intervention clinicians used the ARI Smart Form in 6% of 11 954 ARI visits. The antibiotic prescribing rate in the intervention clinics was 39% versus 43% in the control clinics (odds ratio (OR), 0.8; 95% confidence interval (CI), 0.6_1.2, adjusted for clustering by clinic). For antibiotic appropriate ARI diagnoses, the antibiotic prescribing rate was 54% in the intervention clinics and 59% in the control clinics (OR, 0.8; 95% CI, 0.5_1.3). For non-antibiotic appropriate diagnoses, the antibiotic prescribing rate was 32% in the intervention clinics and 34% in the control clinics (OR, 0.9; 95% CI, 0.6_1.4). When the ARI Smart Form was used, based on diagnoses entered on the form, the antibiotic prescribing rate was 49% overall, 88% for antibiotic appropriate diagnoses and 27% for non-antibiotic appropriate diagnoses. In an as-used analysis, the ARI Smart Form was associated with a lower antibiotic prescribing rate for acute bronchitis (OR, 0.5; 95% CI, 0.3_0.8). Conclusions The ARI Smart Form neither reduced overall antibiotic prescribing nor significantly improved the appropriateness of antibiotic prescribing for ARIs, but it was not widely used. When used, the ARI Smart Form may improve diagnostic accuracy compared to administrative diagnoses and may reduce antibiotic prescribing for certain diagnoses

Lessons Learned from Implementing Service-Oriented Clinical Decision Support at Four Sites: A Qualitative Study

Objective To identify challenges, lessons learned and best practices for service-oriented clinical decision support, based on the results of the Clinical Decision Support Consortium, a multi-site study which developed, implemented and evaluated clinical decision support services in a diverse range of electronic health records. Methods Ethnographic investigation using the rapid assessment process, a procedure for agile qualitative data collection and analysis, including clinical observation, system demonstrations and analysis and 91 interviews. Results We identified challenges and lessons learned in eight dimensions: (1) hardware and software computing infrastructure, (2) clinical content, (3) human-computer interface, (4) people, (5) workflow and communication, (6) internal organizational policies, procedures, environment and culture, (7) external rules, regulations, and pressures and (8) system measurement and monitoring. Key challenges included performance issues (particularly related to data retrieval), differences in terminologies used across sites, workflow variability and the need for a legal framework. Discussion Based on the challenges and lessons learned, we identified eight best practices for developers and implementers of service-oriented clinical decision support: (1) optimize performance, or make asynchronous calls, (2) be liberal in what you accept (particularly for terminology), (3) foster clinical transparency, (4) develop a legal framework, (5) support a flexible front-end, (6) dedicate human resources, (7) support peer-to-peer communication, (8) improve standards. Conclusion The Clinical Decision Support Consortium successfully developed a clinical decision support service and implemented it in four different electronic health records and four diverse clinical sites; however, the process was arduous. The lessons identified by the Consortium may be useful for other developers and implementers of clinical decision support services