Keeping an Eye on Safety in the Stem Cell Transplant Ambulatory Environment

Abstract

Background: Blood and marrow transplant (BMT) programs are federally required to report pre-transplant and posttransplant outcomes data to the CIBMTR. Programs employ data managers to review medical records and report this data to the registry. Data staff also collect and compile data for physicians, for insurance payor requests for information (RFIs), and for internal quality assurance needs. Accurate and efficient BMT data collection is essential for outcomes analyses and program administration as well as for meeting external reporting requirements. The University of Iowa Blood and Marrow Transplant Data Team utilizes three new processes to track and greatly improve data accuracy. First, the team makes use of an auditing macro within the program database which automatically tracks additions, deletions, and changes of critical data. This allows the team to monitor areas where multiple changes or potential discrepancies are being made. Next, the team partnered with the Office for Compliance to carry out FACT-required TED accuracy audits. A template was built into the program database which allows the Compliance Specialist to complete data audits on a quarterly basis through a shared front-end of the database via a protected drive on the hospital network. Through this template, the team and Compliance Specialist can communicate findings from audits performed, and results automatically generate graph and summary tables that are shared with the program during the Quarterly Quality Council Meetings. Last, the data management team utilizes the TED accuracy template to track all corrections identified from CIBMTR or through chart review. Conclusion: Performing audits and tracking data accuracy has become efficient and seamless, saving staff time and resources by more than 50%. By utilizing existing software and automating nearly all audit processes, our team is able to view where requests for data changes are coming from, identify areas in need of improvement, and meet the multitude of demands for data while assuring that all data provided is of the highest quality.