Incidence and predictors of case cancellation within 24 h in patients scheduled for elective surgical procedures.

OBJECTIVE: Avoidable case cancellations within 24 h reduce operating room (OR) efficiency, add unnecessary costs, and may have physical and emotional consequences for patients and their families. We developed and validated a prediction tool that can be used to guide same day case cancellation reduction initiatives. DESIGN: Retrospective hospital registry study. SETTING: University-affiliated hospitals network (NY, USA). PATIENTS: 246,612 (1/2016-6/2021) and 58,662 (7/2021-6/2022) scheduled elective procedures were included in the development and validation cohort. MEASUREMENTS: Case cancellation within 24 h was defined as cancelling a surgical procedure within 24 h of the scheduled date and time. Our candidate predictors were defined a priori and included patient-, procedural-, and appointment-related factors. We created a prediction tool using backward stepwise logistic regression to predict case cancellation within 24 h. The model was subsequently recalibrated and validated in a cohort of patients who were recently scheduled for surgery. MAIN RESULTS: 8.6% and 8.7% scheduled procedures were cancelled within 24 h of the intended procedure in the development and validation cohort, respectively. The final weighted score contains 29 predictors. A cutoff value of 15 score points predicted a 10.3% case cancellation rate with a negative predictive value of 0.96, and a positive predictive value of 0.21. The prediction model showed good discrimination in the development and validation cohort with an area under the receiver operating characteristic curve (AUC) of 0.79 (95% confidence interval 0.79-0. 80) and an AUC of 0.73 (95% confidence interval 0.72-0.73), respectively. CONCLUSIONS: We present a validated preoperative prediction tool for case cancellation within 24 h of surgery. We utilize the instrument in our institution to identify patients with high risk of case cancellation. We describe a process for recalibration such that other institutions can also use the score to guide same day case cancellation reduction initiatives.

Promoting Organizational Change: A Urology Department-wide Wellness Program to Reduce Burnout.

INTRODUCTION: We developed a comprehensive wellness initiative to address burnout with specific interventions targeted at faculty, residents, nurses, administrators, coordinators, and other departmental personnel. METHODS: A department-wide wellness initiative was implemented in October 2020. General interventions included monthly holiday-themed lunches, weekly pizza lunches, employee recognition events, and initiation of a virtual networking board. Urology residents received financial education workshops, weekly lunches, peer support sessions, and exercise equipment. Faculty were offered personal wellness days to use at their discretion at no penalty to their calculated productivity. Administrative and clinical staff were given weekly lunches and professional development sessions. Pre- and post-intervention surveys included a validated single-item burnout instrument and the Stanford Professional Fulfillment Index. Outcomes were compared using Wilcoxon rank-sum tests and multivariable ordinal logistic regression. RESULTS: Among 96 department members, 66 (70%) and 53 (55%) participants completed the pre- and post-intervention surveys, respectively. Burnout scores were significantly improved after the wellness initiative (mean 2.06 vs 2.42, mean difference -0.36, P = .012). An improvement was also observed in the sense of community (mean 4.04 vs 3.36, mean difference 0.68, P < .001). Adjusting for role group and gender, completion of the curriculum was associated with decreased burnout (OR 0.44, P = .025), increased professional fulfillment (OR 2.05, P = .038), and increased sense of community (OR 3.97, P < .001). The highest-rated components were monthly gatherings (64%), sponsored lunches (58%), and employee of the month (53%). CONCLUSIONS: A department-wide wellness initiative with group-specific interventions can help reduce burnout and may improve professional fulfillment and workplace community.

Development of Imminent Mortality Predictor for Advanced Cancer (IMPAC), a Tool to Predict Short-Term Mortality in Hospitalized Patients With Advanced Cancer.

PURPOSE: End-of-life care for patients with advanced cancer is aggressive and costly. Oncologists inconsistently estimate life expectancy and address goals of care. Currently available prognostication tools are based on subjective clinical assessment. An objective prognostic tool could help oncologists and patients decide on a realistic plan for end-of-life care. We developed a predictive model (Imminent Mortality Predictor in Advanced Cancer [IMPAC]) for short-term mortality in hospitalized patients with advanced cancer. METHODS: Electronic health record data from 669 patients with advanced cancer who were discharged from Yale Cancer Center/Smilow Cancer Hospital were extracted. Statistical learning techniques were used to develop a tool to estimate survival probabilities. Patients were randomly split into training (70%) and validation (30%) sets 20 times. We tested the predictive properties of IMPAC for mortality at 30, 60, 90, and 180 days past the day of admission. RESULTS: For mortality within 90 days at a 40% sensitivity level, IMPAC has close to 60% positive predictive value. Patients estimated to have a greater than 50% chance of death within 90 days had a median survival time of 47 days. Patients estimated to have a less than 50% chance of death had a median survival of 290 days. Area under the receiver operating characteristic curve for IMPAC averaged greater than .70 for all time horizons tested. Estimated potential cost savings per patient was $15,413 (95% CI, $9,162 to $21,665) in 2014 constant dollars. CONCLUSION: IMPAC, a novel prognostic tool, can generate life expectancy probabilities in real time and support oncologists in counseling patients about end-of-life care. Potentially avoidable costs are significant.

Preparing for Value-Based Payment: A Stepwise Approach for Cancer Centers.

Most cancer centers are ill-equipped to pursue value-based payment (VBP) because of limited information on their population's cost of care. Herein, we outline the stepwise approach used by Smilow Cancer Hospital at Yale-New Haven in our pursuit of better value care. First, we addressed institutional barriers. A move toward value required demonstration to Yale-New Haven Health System leadership that OCM would improve patient care, fund new infrastructure, and provide the opportunity to gain experience with VBP without a major threat to the financial stability of the health system. We evaluated patterns of care and found that of patients presenting to the emergency department (ED), 88% were admitted, 62% arrived during the workday, and 50% could have been stabilized with urgent care services. Within 30 days of death, 27% were admitted to the intensive care unit, 38% presented to the ED, and 52% were admitted. To quantify total cost of care, we accessed the 5% Medicare Limited Data Set to map out total cost of care for patients receiving chemotherapy at Smilow Cancer Hospital. Costs increased as patients moved through 6-month episodes, used the ED (patients with two or more visits were twice as expensive as those with one or fewer), or died during an episode (costs were twice as high as episodes in which the patient lived). To determine strategic interventions to improve value, we targeted investments in urgent care to reduce ED utilization, care management to prevent hospital admissions, and referral to palliative care for clarification of goals of care and avoidance of costly futile treatment. Developing internal metrics to evaluate success will require monitoring our interventions by having utilization measures for each site of care and individual provider.