Clinical Decision Support for Hyperbilirubinemia Risk Assessment in the Electronic Health Record.

BACKGROUND: Physiologic neonatal hyperbilirubinemia (jaundice) is common and affects most newborn infants. However, there is a risk for permanent neurological damage if the bilirubin levels rise above a certain threshold. The management of neonatal jaundice includes the assessment of bilirubin laboratory values, consideration of patient-specific risk factors, and plotting on a bilirubin nomogram reference to determine risk and guide therapy. When performed manually, the process can be time consuming and error-prone. Therefore, web-based calculators such as BiliTool have been developed to assist in risk assessment. METHODS: To streamline the risk assessment calculation process further within our electronic health record (EHR), we created a "BiliReport" to display patient bilirubin-related data and automate transmission of deidentified patient data to the BiliTool website (https://bilitool.org). After implementation, we evaluated usage data, provider satisfaction, and accuracy of documentation. RESULTS: We demonstrated high provider use of the BiliReport and satisfaction with the workflow. We found a significant improvement in the accuracy of bilirubin risk level documentation, with a reduction in erroneous risk stratification from 4% (15/232) to 0.4% (1/243), P < 0.001. We did not find significant a difference in erroneous documentation of the bilirubin lab value (P = 0.07). CONCLUSIONS: Integrating the neonatal hyperbilirubinemia risk assessment process into the EHR may reduce errors and improve provider documentation and adherence to recommended guidelines.

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.

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'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 'preliminary result' or 'in process' instead of 'final result' with only common cause variation. Quality improvement methods were employed to improve the process with the SMART Aim of reporting 100% of tests as 'final result'. Pareto analysis identified two errors accounting for 79% of common system-level failures-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 'final result'. The study demonstrates that high complexity SAB bead data can be efficiently reported EPIC:CareConnect from HistoTrac as discrete data.