Clinical Decision Support with a Comprehensive in-EHR Patient Tracking System Improves Genetic Testing Follow Up

Abstract

Objective We sought to develop and evaluate an electronic health record (EHR) genetic testing tracking system to address the barriers and limitations of existing spreadsheet-based workarounds. Materials and Methods We evaluated the spreadsheet-based system using mixed effects logistic regression to identify factors associated with delayed follow up. These factors informed the design of an EHR-integrated genetic testing tracking system. After deployment we assessed the system in two ways. We analyzed EHR access logs and note data to assess patient outcomes and performed semi-structured interviews with system users to identify impact of the new system on work. Results We found that patient-reported race was a significant predictor of documented genetic testing follow up, indicating a possible inequity in care. We implemented a CDS system including a patient data capture form and management dashboard to facilitate important care tasks. The system significantly speeded review of results and significantly increased documentation of follow-up recommendations. Interviews with system users identified key team members ensuring success and revealed that the system addresses a number of sociotechnical factors that collectively result in safer and more efficient care. Discussion Our new tracking system ended decades of workarounds for identifying and communicating test results and improved clinical workflows. Interview participants related that the system decreased cognitive and time burden which allowed them to focus on direct patient interaction. Conclusion By assembling a multidisciplinary team, we designed a novel patient tracking system that improves genetic testing follow up. Similar approaches may be effective in other clinical settings.