JMIR Publications

ABSTRACT

Describe the lessons learned in the design and implementation of a novel electronic data capture tool (EDCT) with the goal of significantly increasing the nation’s capability to manage real-time data collection and analysis during public health emergencies (PHE). Design The Discovery Critical Care Research Network Program for Resilience and Emergency Preparedness (Discovery PREP) partnered with a third-party technology vendor to design and implement an EDCT that addressed multisite data collection challenges during a PHE. The basis of the work was to design an EDCT and prospectively gather data on usability from bedside clinicians during national health system stress queries, and influenza observational studies. The initial design focused on data collection and evolved into a short assessment on the accuracy of automated data extraction. In addition to user feedback during semi-structured interviews, the System Usability Scale (SUS) questionnaire was used as a basis to evaluate the usability and performance of the system. Participants included Discovery-PREP physicians, their local administrators, and data collectors from tertiary level academic medical centers from 5 different institutions. User feedback indicated that the designed system had an intuitive user interface and could be used to automate study communication tasks making for more efficient management of multisite studies. SUS questionnaire results classified the system as highly usable (SUS score 82.5/100). Automation of 61% of the 28 variables in the influenza observational study was deemed feasible during the exploration of automated versus manual data abstraction. The creation and use of the Project Meridian EDCT identified 6 key design requirements for multisite data collection, including the need for: 1) scalability irrespective of the type of participant; 2) a common data set across sites; 3) automated back-end administrative capability e.g., reminders and a self-service status board; 4) multimedia communication pathways e.g., email, SMS; 5) interoperability and integration with local site information technology infrastructure; 6) natural language processing to extract non-discrete data elements. Discussion Utilization of the EDCT in multiple multisite Discovery PREP clinical studies proved the feasibility of using the novel, cloud-based platform in practice. Lessons learned from this effort can be used to inform the improvement of multisite data collection efforts and transform current manual data abstraction approaches into reliable, real-time, and automated information exchange. Future research is needed to expand the ability to perform automated multisite data extraction during a PHE and beyond.