Reframing the Morbidity and Mortality Conference: The Impact of a Just Culture.

ABSTRACT: Morbidity and mortality (M&M) conferences are prevalent in all fields of medicine. Historically, they arose out a desire to improve medical care. Nevertheless, the goals of M&M conferences are often poorly defined, at odds with one another, and do not support a just culture. We differentiate among the various possible goals of an M&M and review the literature for strategies that have been shown to achieve these goals. Based on the literature, we outline an ideal M&M structure within the context of just culture: The process starts with robust adverse event and near miss reporting, followed by careful case selection, excluding cases solely attributable to individual error. Prior to the M&M, the case should be openly discussed with involved members and should be reviewed using a selected framework. The goal of the M&M should be selected and clearly defined, and the presentation format and rules of conduct should all conform to the selected presentation goal. The audience should ideally be multidisciplinary and multispecialty. The M&M should conclude with concrete tasks and assigned follow-up. The entire process should be conducted in a peer review protected format within an environment promoting psychological safety. We conclude with future directions for M&Ms.

Trends in Response Rate to US News & World Report Best Hospitals Reputation Survey, 2015 to 2023.

Reputation score has been shown to be the strongest predictor of ranking in the US News & World Reports (USNWR) Best Hospitals report. However, the extent to which physicians participate in the underlying USNWR reputation survey is not well-characterized. We conducted a retrospective cross-sectional study of USNWR public methodology reports from 2015 to 2023 to characterize trends in physician response rates by specialty, region, and Doximity membership. Overall response rates declined between 2015 (24.0%) and 2023 (8.9%). In 2023, rates ranged from 4.7% (psychiatry) to 13.9% (otolaryngology). Otolaryngology had the highest response rate among all specialties between 2017 and 2023. Within otolaryngology, both response rates (25.0% to 13.9%) and count (2106 to 1724 physicians) declined between 2015 and 2023. Among Doximity members, response rates were consistently higher for otolaryngologists in the Northeast and Midwest compared to other regions. Though hospital rankings often influence where patients seek care, our findings suggest USNWR reputation scores may not be reliable or representative.

Using Machine Learning to Predict Operating Room Case Duration: A Case Study in Otolaryngology.

OBJECTIVE: Optimizing operating room (OR) efficiency depends on accurate case duration estimates. Machine learning (ML) methods have been used to predict OR case durations in other subspecialties. We hypothesize that ML methods improve projected case lengths over existing non-ML techniques for otolaryngology-head and neck surgery cases. METHODS: Deidentified patient information from otolaryngology surgical cases at 1 academic institution were reviewed from 2016 to 2020. Variables collected included patient, surgeon, procedure, and facility data known preoperatively so as to capture all realistic contributors. Available case data were divided into a training and testing data set. Several ML algorithms were evaluated based on best performance of predicted case duration when compared to actual case duration. Performance of all models was compared by the average root mean squared error and mean absolute error (MAE). RESULTS: In total, 50,888 otolaryngology surgical cases were evaluated with an average case duration of 98.3 ± 86.9 minutes. Most cases were general otolaryngology (n = 16,620). Case features closely associated with OR duration included procedure performed, surgeon, subspecialty of case, and postoperative destination of the patient. The best-performing ML models were CatBoost and XGBoost, which reduced operative time MAE by 9.6 minutes and 8.5 minutes compared to current methods, respectively. DISCUSSION: The incorporation of other easily identifiable features beyond procedure performed and surgeon meaningfully improved our operative duration prediction accuracy. CatBoost provided the best-performing ML model. IMPLICATIONS FOR PRACTICE: ML algorithms to predict OR case time duration in otolaryngology can improve case duration accuracy and result in financial benefit.

Handovers in Perioperative Care.

Handovers around the time of surgery are common, yet complex and error prone. Interventions aimed at improving handovers have shown increased provider satisfaction and teamwork, improved efficiency, and improved communication and have been shown to reduce errors and improve clinical outcomes in some studies. Common recommendations in the literature include a standardized institutional process that allows flexibility among different units and settings, the completion of urgent tasks before information transfer, the presence of all members of the team for the duration of the handover, a structured conversation that uses a cognitive aid, and education in team skills and communication.

Measuring and Improving the Quality of Preprocedural Assessments.

BACKGROUND: Preprocedural assessments are used by anesthesia providers to optimize perioperative care for patients undergoing invasive procedures. When these assessments are performed in advance by providers who are not caring for the patient during the procedure, there is an additional layer of complexity in ensuring that the workup meets the needs of the primary anesthesia care team. In this study, anesthesia providers were asked to rate the quality of preprocedural assessments prepared by other providers to evaluate anesthesia care team satisfaction. METHODS: Quality ratings for preprocedural assessments were collected from anesthesia providers on the day of surgery using an electronic quality assurance tool from January 9, 2014 to October 21, 2014. Users could rate assessments as "exemplary," "satisfactory," or "unsatisfactory." Free text comments could be entered for any of the quality ratings chosen. A reviewer trained in clinical anesthesia categorized all comments as "positive," "constructive," or "neutral" and conducted in-depth chart reviews triggered by 67 "constructive" comments submitted during the first 3 months of data collection to further subcategorize perceived deficiencies in the preprocedural assessments. In May 2014, providers were asked to participate in a midpoint survey and provide general feedback about the preprocedural process and evaluations. RESULTS: 37,611 procedures requiring anesthesia were analyzed. Of the 17,522 (46.6%) cases with a rated preprocedural assessment, anesthesia providers rated 3828 (21.8%) as "exemplary," 13,454 (76.8%) as "satisfactory," and 240 (1.4%) as "unsatisfactory." The monthly proportion of "unsatisfactory" ratings ranged from 3.1% to 0% over the study period, whereas the midpoint survey showed that anesthesia providers estimated that the number of unsatisfactory evaluations was 11.5%. Preprocedural evaluations performed on inpatients received significantly better ratings than evaluations performed on outpatients by the preadmission testing clinic or phone program (P < .0001). The most common reason given for "unsatisfactory" ratings was a perception of "missing information" (49.2%). Chart reviews revealed that inadequate documentation was in reality the most common deficiency in preprocedural evaluations (35 of 67 reviews, 52.2%). CONCLUSIONS: The overwhelming majority of preprocedural assessments performed at our institution were considered satisfactory or exemplary by day-of-surgery anesthesia providers. This was demonstrated by both the case-by-case ratings and midpoint survey. However, the perceived frequency of "unsatisfactory" evaluations was worse when providers were asked to reflect on the quality of preprocedural evaluations generally versus rate them individually. Analysis of comments left by providers allowed us to identify specific and actionable areas for improvement. This method can be used by other institutions to identify systemic deficiencies in the preprocedural evaluation process.