Abstract
PURPOSE: Incident learning in large, multi-site hospital systems faces challenges from resource constraints, diverse site cultures, and deviations from system-wide policies. This study introduces a novel, resource-efficient hybrid approach to facilitate cross-site learning and proactive risk management, ultimately enhancing patient safety. METHODS: A hybrid approach, integrating statistical, and root cause analyses was used to analyze safety events recorded from 2023 to 2024 at five sites. Events were categorized by time, site, type, and harm score with statistics tracking the event frequency per category. Failure modes (FMs) were identified with summative keywords. The frequency and cross-site correlation of keywords were innovatively displayed by word clouds. The hybrid approach was exemplified at a high-throughput satellite clinic, where treatments and incidents were tracked quarterly. A proactive model was also employed to predict the number of potentially affected patients at this site. RESULTS: An analysis of 228 reported events revealed that most incidents occurred within the treatment planning category, where the keywords "carepath" and "contour" were identified as the top two frequently reported FMs, repeated 13 and 10 times respectively. The keywords "contour" and "documentation" appeared across four sites, followed by "carepath" and "couch" which appeared across three sites. At the featured satellite clinic, a total of 18 FMs were identified from yearly 8,714 treatments. The proactive model showed an average risk priority number decreased from 106 to 77, and the estimated number of affected patients decreased from 27 to 20 at this site. CONCLUSIONS: We developed a comprehensive, system-wide approach that enhanced efficiency in incident learning across multi-site clinics. Site-specific shifts in safety culture were effectively benchmarked and cross-site learning was facilitated through measurable endpoints. A novel word cloud analysis was developed, enhancing visualization of cross-site root causes. Additionally, a proactive model was adopted to increase system-wide preparedness and improve patient safety outcomes.