Challenges encountered in linking community health centers' electronic health record data to a web-based clinical decision support tool [abstract] Abstract uri icon

abstract

  • Background: Clinical decision support (CDS) tools, which process patient data via algorithms based on up-to-date evidence, can help disseminate care guidelines by keeping providers abreast of current recommendations. However, such CDS tools are often available only in the delivery system or electronic health record (EHR) where they were developed, necessitating reprogramming at multiple sites when care guidelines change. This inefficiency could be addressed if data from any EHR could be sent to a website with regularly updated CDS algorithms. We are currently testing the effectiveness of CV Wizard© ─ a web-based CDS tool run by HealthPartners ─ in 68 community health centers (CHCs) that share an EHR through OCHIN. Methods: Between March 2017 and April 2018, OCHIN and HealthPartners collaborated to establish a data exchange between OCHIN’s Epic EHR and the CV Wizard CDS website. Needed EHR data (eg, demographics, diagnoses, labs, allergies, vitals) were sent to CV Wizard, which then sent CDS suggestions back to the EHR. Results: Numerous challenges in establishing this data exchange were identified and resolved. These included determining: who maintains records of data sent/responses sent back; what legal agreements were required for needed data retention; the method for sending CDS results back to the EHR; whether to send all available medication/laboratory/allergy/diagnosis data to the CDS or just data points currently needed by the algorithm; how to manage security concerns related to the transmission of real-time patient data; whether the CDS’ cache routine could be modified to improve performance/sustainability; how OCHIN’s unique structure (a collaborative of many independent organizations) necessitated rethinking managing data from more than 60 lab interfaces; how to generate data on CDS use rates; and how to modify the CDS tool’s “feedback” function for consistency with OCHIN’s usual support practices. Barriers to customizing the cardiovascular disease risk cut-point that triggered the CDS tool also were identified. Conclusion: Inefficiencies are inherent when new care guidelines must be programmed in myriad CDS systems. We demonstrated that multiple EHRs can successfully plug into a single CDS algorithm, after resolution of multiple data exchange challenges.

publication date

  • 2019