Journal of the American College of Surgeons
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An impending surgeon shortage looms in the United States (US) due to increasing demand and stagnant number of surgeons entering practice. We sought to evaluate the state of our surgical workforce by exploring current practice patterns, job satisfaction, and reasons why surgeons consider leaving surgery. ⋯ Reported surgeon job satisfaction was high, but a surprising number of surgeons reported that they were considering leaving surgery. Work time requirements and lack of personal time are leading factors contributing to surgeons leaving practice.
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With inpatient length of stay decreasing, discharge destination after surgery can serve as an important metric for quality of care. Additionally, patients desire information on possible discharge destination. Adequate planning requires a multidisciplinary approach, can reduce healthcare costs and ensure patient needs are met. The Surgical Risk Preoperative Assessment System (SURPAS) is a parsimonious risk assessment tool using 8 predictor variables developed from the American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) dataset. SURPAS is applicable to more than 3,000 operations in adults in 9 surgical specialties, predicts important adverse outcomes, and is incorporated into our electronic health record. We sought to determine whether SURPAS can accurately predict discharge destination. ⋯ The 8-variable SURPAS model preoperatively predicts risk of postoperative discharge to a destination other than home as accurately as the 28 nonlaboratory variable ACS NSQIP full model. Therefore, discharge destination can be integrated into the existing SURPAS tool, providing accurate outcomes to guide decision-making and help prepare patients for their postoperative recovery.
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The American College of Surgeons (ACS) NSQIP Surgical Risk Calculator (SRC) plays an important role in risk prediction and decision-making. We sought to enhance the existing ACS NSQIP SRC with functionality to predict geriatric-specific outcomes and assess the predictive value of geriatric-specific risk factors by comparing performance in outcomes prediction using the traditional ACS NSQIP SRC with models that also included geriatric risk factors. ⋯ The ACS NSQIP SRC can predict 4 unique outcomes germane to geriatric surgical patients, with improvement of predictive capability after accounting for geriatric risk factors. Augmentation of ACS NSQIP SRC can enhance shared decision-making to improve the quality of surgical care in older adults.
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The complexity of retroperitoneal soft tissue sarcoma (RPS) surgery has prompted international recommendations to regionalize it to high-volume hospitals (HVHs). A minimum procedural volume threshold for RPS is not yet defined, hampering effective referral and regionalization in the US. This multihospital study sought to establish an HVH threshold informed by national data and international expert opinion. ⋯ This is the first multicenter analysis to merge data-driven RPS surgery volume thresholds to clinically meaningful sarcoma expert opinions. These findings will help inform national/international consensus recommendations, a practical volume threshold, trial design, and motivate evidence-based hospital referral.
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An optimal method to quantify surgical complexity using patient comorbidities derived from administrative billing data is lacking. We sought to develop a novel, easy-to-use surgical Complexity Score to accurately predict adverse outcomes among patients undergoing elective surgery. ⋯ Compared with the most commonly used comorbidity and surgical risk scores, the novel surgical Complexity Score outperformed the CCI, ECI, and CMS-HCC in predicting postoperative morbidity, 30-day readmission, 90-day readmission, and postoperative super-use.