LAUSR

Background Integration of patient information across medical institutions remains a major challenge in American healthcare. In particular, meaningful data compilation, extraction and analysis are impeded by separate information technology systems, thereby limiting collaborative efforts addressing translational and patient-centered outcomes research. Furthermore, incorporating predictive models to ensure favorable patient outcomes are critically needed, especially for high-complexity, high-resource utilizing patient populations like blood and marrow transplant (BMT) recipients. To this end, the Nationwide Children's Hospital (NCH) BMT Smart Forms were created with the ultimate goal of developing an analytics-integrated, EMR (electronic medical record)-based smart form for BMT and cell therapy patients, which would have the potential to improve patient outcomes by assimilating clinical data across transplant and cell therapy centers. Smart Form Design and Functionality Originally created in 2013 at Nationwide Children's Hospital, the pre- and post-BMT Smart Forms (SFs) were designed by a collaborative team including members of the BMT Program, Information Services and Technology, Electronic Data Warehouse, and Research Information Solutions and Innovation (RISI). Specifically, the BMT SFs were designed using the Epic® platform to enable clinical and quality reporting and research data capture (Figure 1). In this regard, the SFs contain minimal free text fields to minimize data entry error and standard data elements (SDEs), which facilitate data mapping and routing. Once completed, the SFs can be transformed into clinical documentation for clinical management purposes. By design and through a data visualization platform (QlikView®), the BMT SFs also facilitate internal and external data reporting for transplant- and cell therapy-related agencies including the CIBMTR (Center of International Blood and Marrow Transplant Research), FACT (Federation for Accreditation of Cellular Therapy), and NMDP (National Marrow Donor Program). Clinical data entered into the BMT SFs route into a database with the capability for automated data transfer from within and outside NCH, thereby creating the potential for a combined, multi-institutional database through which data can be easily queried (Figure 2). Lastly, the database enables predictive analytic modeling for common transplant-related metrics (e.g., engraftment) and complications (e.g., infection). Reiterations of the BMT SFs have occurred over time, reflecting new technologies and approaches to transplant care as well as future steps for on-boarding additional transplant centers.