Introduction of a Mobile Adverse Event Reporting System Is Associated With Participation in Adverse Event Reporting.

Physicians underutilize adverse event reporting systems. Web-based platforms have increased participation; thus, it was hypothesized that a mobile application would increase adverse event reporting. The authors developed a mobile reporting application for iOS and Android operating systems and performed a retrospective review on reporting rates by clinicians in the Department of Anesthesia and Critical Care. Monthly reporting rates were calculated for the intervention year and for the 2 prior years (2013-2016). The Wilcoxon rank sum test and χ2 test were used to evaluate significance. Overall monthly reporting rates for all clinicians were 15.3 ± 7 for the first time period, 17.3 ± 6 for the second time period, and 27.9 ± 7 for the third time period ( P = .0035). The majority of reports in the third time period were submitted using the mobile application (193/337, 57%, P = .026). Deployment of a mobile application reduced barriers to adverse event reporting and increased monthly reporting rates for all clinicians.

The limited value of sequencing cases based on their probability of cancellation.

BACKGROUND: Case cancellations on the day of surgery reduce operating room (OR) and anesthesia group productivity. One strategy to reduce the impact of case cancellations on productivity is to assign high-risk cases to start last in the OR workday. To evaluate the utility of this intervention, we used a database of canceled cases to model the process of identifying high-risk cases and resequencing them to be the surgeons' last cases of the day. METHODS: Descriptive information was prospectively collected on 1 year of canceled cases. A comparison group of completed cases served as controls. Predictors of case cancellation were identified and used to calculate the number of cases that would require resequencing for 1 cancellation to occur at the end of the day. The proportion of total OR hours relevant to each predictor was assessed. To assess the desirability of this strategy, surgeons were surveyed regarding their scheduling preferences for patients at high risk for cancellation. RESULTS: During the study period, 946 of 12,253 cases were canceled. Strong predictors of cancellation included percentage of missed clinic appointments (number of cases requiring resequencing = 5.27) and insurance status (number of cases requiring resequencing = 8.87 for Medicaid). The predictor accounting for the most scheduled time was residence in Chicago (5.1% of total hours). No predictor both required the resequencing of 5 or fewer cases to prevent 1 cancellation in the middle of the day and accounted for >4% of scheduled time. Survey results demonstrated that in addition to cancellation probability, factors such as case complexity also influenced surgeons' sequencing preferences. CONCLUSION: Highly sensitive predictors of case cancellation are impractical for sequencing purposes because they account for too few hours of scheduled OR time. Effort invested in identifying and resequencing cases at high risk for cancellation likely has limited value.