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Critical Audit Field Quality Initiative

Track: Poster Abstracts
Wednesday, February 26, 2014, 6:45 PM-7:45 PM
Longhorn Hall E (Exhibit Level 1) (Gaylord Texan)
Clara Yoon , Dana-Farber Cancer Institute/Brigham and Women’s Cancer Center, Boston, MA
Marion C Tilearcio , Dana-Farber Cancer Institute/Brigham and Women’s Cancer Center, Boston, MA
Julia Suprunova , Dana-Farber Cancer Institute/Brigham and Women’s Cancer Center, Boston, MA
With a rising volume of transplants performed each year, quality initiatives have become increasingly imperative. In order to maintain a high standard of hematopoietic stem cell transplant (HSCT) data, the Dana-Farber Cancer Institute (DFCI)/Brigham and Women’s Cancer Center (BWCC) Adult HSCT Program has developed a project evaluating the accuracy of data in CIBMTR critical audit fields. Audit guidelines serve to focus the DFCI Program on significant data fields and in turn ensure accuracy. The DFCI Program reports transplant data to the CIBMTR and to an internal repository. Through this project, each critical audit field is systematically examined across the relevant repositories and data collection forms, and differences in the reported data are further investigated. This project leverages several categories of logic in order to reveal discrepancies. In one category, data points are confirmed for consistency when redundantly reported across the internal repository and the CIBMTR repository. For example, graft failures are reported CIBMTR 2450 forms and the analogous internal repository forms. In another category, logic from the CIBMTR Forms Instruction Manual is implemented as data is compared across and within CIBMTR Data Collection Forms. For example, the Karnofsky Score at Transplant is reported on both the Pre-TED form and the 2000 form. The final categories include examining outliers, and reviewing data that does not follow a coherent chronological order. For example, disease diagnosis date should be prior to the date of the first transplant. By identifying discrepancies through these quality initiatives, the necessary corrections can be made and accuracy can be improved in both repositories. This project provides a systematic process to augment data consistency and accuracy on a large scale by targeting priority data fields.
Disclosures:
Nothing To Disclose