@article {Geere000813, author = {Lupita I Geer and Sonya Kagele and Scot Townshend and Brooke Watson and Elaine F Reed and Michelle J Hickey}, title = {Design of a state of the art reporting system and process improvement for reporting of high complexity single antigen bead data for transplant patients to the electronic medical record}, volume = {9}, number = {1}, elocation-id = {e000813}, year = {2020}, doi = {10.1136/bmjoq-2019-000813}, publisher = {BMJ Open Quality}, abstract = {The UCLA Immunogenetics Center is an Immunogenetics and Histocompatibility laboratory that performs testing for multiple transplant programmes within and outside of UCLA. The single antigen bead (SAB) test is a high complexity luminex bead test used to assess pretransplant and post-transplant patients for the presence of pathogenic human leucocyte antigen donor-specific antibody associated with allograft rejection. Efficient reporting of the SAB test has been difficult as data analysis and reports are generated in the laboratory information system (LIS) and uploaded to the electronic medical record (EMR) as PDFs. To solve this, we recently developed a state of the art reporting workflow allowing discrete reporting of SAB data (antibody specificity, mean fluorescent intensity and interpretative comments) from the LIS HistoTrac to UCLA Health System{\textquoteright}s EMR EPIC:CareConnect. However, a proportion of tests did not report to the EMR appropriately. Baseline system performance data evaluated over a 10-week period showed that ~4.5/100 tests resulted in EPIC as {\textquoteleft}preliminary result{\textquoteright} or {\textquoteleft}in process{\textquoteright} instead of {\textquoteleft}final result{\textquoteright} with only common cause variation. Quality improvement methods were employed to improve the process with the SMART Aim of reporting 100\% of tests as {\textquoteleft}final result{\textquoteright}. Pareto analysis identified two errors accounting for 79\% of common system-level failures{\textemdash}status errors and interface errors. We hypothesised that addressing the status error would reduce or eliminate the interface errors. We used the Model For Improvement to test a reprogramming intervention. Status and interface errors were completely resolved through the process improvement. Continuous monitoring revealed a system-level shift with only ~1.9/100 tests resulting inappropriately. Through the audit process, the remaining common system-level failures were identified and resolved. Therefore, 100\% of tests result to EPIC as {\textquoteleft}final result{\textquoteright}. The study demonstrates that high complexity SAB bead data can be efficiently reported EPIC:CareConnect from HistoTrac as discrete data.}, URL = {https://bmjopenquality.bmj.com/content/9/1/e000813}, eprint = {https://bmjopenquality.bmj.com/content/9/1/e000813.full.pdf}, journal = {BMJ Open Quality} }