Since inception, the Veterans Affairs (VA) National TeleOncology (NTO) service has monitored clinical operations through data tools produced by the Veterans Health Administration Support Service Center (VSSC). Unfortunately, pertinent data are spread across multiple reports, making it difficult to continually harmonize needed information. Further, the VSSC does not account for NTO’s hub and spoke clinical model, leading to inaccuracies when attempting to analyze unique encounters. To address these challenges, NTO partnered with the VA Salt Lake City Health Care System Informatics, Decision-Enhancement, and Analytic Sciences Center (IDEAS) to develop an informatics architecture and frontend NTO Clinical Operations Dashboard (NCOD). Here, we summarize our dashboard development process and the finalized key reporting components of the NCOD.
The VA Corporate Data Warehouse (CDW) serves as the primary data source for the NCOD. SQL Server Integration Services was used to build the backend data architecture. Data from the CDW were isolated into a staging data mart for reporting purposes using an extract, transform, load (ETL) approach. The frontend user interface was developed using Power BI. We used a participatory approach1 in determining reporting requirements. Stakeholders included the IDEAS dashboard development team and potential end users from NTO, including leadership, program managers, support assistants, and telehealth coordinators.
The NCOD ETL is scheduled to refresh the data nightly to provide end users with a near real-time experience. The NCOD is comprised of the following four data views: clinic availability, team productivity, patient summary, and encounter summary. The clinic availability view summarizes clinic capacity, no shows, overbookings, and percent utilization. Relative value unit- based productivity is summarized in the team productivity view. The patient summary view presents aggregated data for veterans served by NTO, including geographic distribution, with patient-level drill down displaying demographics, cancer characteristics, and treatment history. Lastly, the encounter view displays utilization trends by modality, while accurately accounting for the hub and spoke clinical model.
An informatics architecture and frontend information display that is capable of synthesizing EHR data into a consumable format has been pivotal in obtaining accurate and timely insight into the demand and capacity of services provided by NTO.