D Mann1, M Knaus2, L McCullagh2, A Sofianou3, L Rosen2, T McGinn2, J Kannry3. 1. Department of Medicine, Section of Preventive Medicine and Epidemiology, Boston University School of Medicine , Boston, MA, USA. 2. Department of Medicine, Hofstra North Shore-LIJ School of Medicine , Manhasset, NY, USA. 3. Department of Medicine, Division of General Internal Medicine, Mount Sinai School of Medicine , New York, NY, USA.
Abstract
OBJECTIVE: To understand clinician adoption of CDS tools as this may provide important insights for the implementation and dissemination of future CDS tools. MATERIALS AND METHODS: Clinicians (n=168) at a large academic center were randomized into intervention and control arms to assess the impact of strep and pneumonia CDS tools. Intervention arm data were analyzed to examine provider adoption and clinical workflow. Electronic health record data were collected on trigger location, the use of each component and whether an antibiotic, other medication or test was ordered. Frequencies were tabulated and regression analyses were used to determine the association of tool component use and physician orders. RESULTS: The CDS tool was triggered 586 times over the study period. Diagnosis was the most frequent workflow trigger of the CDS tool (57%) as compared to chief complaint (30%) and diagnosis/antibiotic combinations (13%). Conversely, chief complaint was associated with the highest rate (83%) of triggers leading to an initiation of the CDS tool (opening the risk prediction calculator). Similar patterns were noted for initiation of the CDS bundled ordered set and completion of the entire CDS tool pathway. Completion of risk prediction and bundled order set components were associated with lower rates of antibiotic prescribing (OR 0.5; CI 0.2-1.2 and OR 0.5; CI 0.3-0.9, respectively). DISCUSSION: Different CDS trigger points in the clinician user workflow lead to substantial variation in downstream use of the CDS tool components. These variations were important as they were associated with significant differences in antibiotic ordering. CONCLUSIONS: These results highlight the importance of workflow integration and flexibility for CDS success.
RCT Entities:
OBJECTIVE: To understand clinician adoption of CDS tools as this may provide important insights for the implementation and dissemination of future CDS tools. MATERIALS AND METHODS: Clinicians (n=168) at a large academic center were randomized into intervention and control arms to assess the impact of strep and pneumonia CDS tools. Intervention arm data were analyzed to examine provider adoption and clinical workflow. Electronic health record data were collected on trigger location, the use of each component and whether an antibiotic, other medication or test was ordered. Frequencies were tabulated and regression analyses were used to determine the association of tool component use and physician orders. RESULTS: The CDS tool was triggered 586 times over the study period. Diagnosis was the most frequent workflow trigger of the CDS tool (57%) as compared to chief complaint (30%) and diagnosis/antibiotic combinations (13%). Conversely, chief complaint was associated with the highest rate (83%) of triggers leading to an initiation of the CDS tool (opening the risk prediction calculator). Similar patterns were noted for initiation of the CDS bundled ordered set and completion of the entire CDS tool pathway. Completion of risk prediction and bundled order set components were associated with lower rates of antibiotic prescribing (OR 0.5; CI 0.2-1.2 and OR 0.5; CI 0.3-0.9, respectively). DISCUSSION: Different CDS trigger points in the clinician user workflow lead to substantial variation in downstream use of the CDS tool components. These variations were important as they were associated with significant differences in antibiotic ordering. CONCLUSIONS: These results highlight the importance of workflow integration and flexibility for CDS success.
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