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Medical AI Inquiry: You was designed to assist in medical decision-making based on the provided user questions. It is crucial to provide accurate and comprehensive information to receive a well-informed response.  Labels: BACKGROUND, METHODS, RESULTS. Meshes: Adult, Age Distribution, Biomechanical Phenomena, Critical Care, Female, Glasgow Coma Scale, Health Services Research, Humans, Injury Severity Score, Length of Stay, Logistic Models, Los Angeles, Male, Medical Staff, Hospital, Middle Aged, Multiple Trauma, Patient Admission, Predictive Value of Tests, Registries, Surgery Department, Hospital, Survival Analysis, Trauma Centers, Treatment Outcome, Workload.
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Does patient volume per surgeon predict survival in adult level I trauma centers? Context: The 1999 American College of Surgeons resources for optimal care document added the requirement that Level I trauma centers admit over 240 patients with Injury Severity Score (ISS) > 15 per year or that trauma surgeons care for at least 35 patients per year. The purpose of this study was to test the hypothesis that high volume of patients with ISS > 15 per individual trauma surgeon is associated with improved outcome. Data were obtained from the trauma registry of the five American College of Surgeons-verified adult Level I trauma centers in our mature trauma system between January 1, 1998, and March 31, 1999. Data abstracted included age, sex, Glasgow Coma Scale (GCS) score, intensive care unit length of stay, hospital length of stay, probability of survival (Ps), mechanism of injury, number of patients per each trauma surgeon and institution, and mortality. Multiple logistic regression was performed to select independent variables for modeling of survival. From the five Level I centers there were 11,932 trauma patients in this time interval; of these, 1,754 patients (14.7%) with ISS > 15 were identified and used for analysis. Patients with ISS > 15 varied from 173 to 625 per institution; trauma surgeons varied from 8 to 25 per institution; per-surgeon patient volume varied from 0.8 to 96 per year. Logistic regression analysis revealed that the best independent predictors of survival were Ps, GCS score, age, mechanism of injury, and institutional volume (p < 0.01). Age and institutional volume correlated negatively with survival. Analysis of per-surgeon patient caseload added no additional predictive value (p = 0.44).
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The significant independent predictors of survival in severely injured trauma patients are Ps, GCS score, age, mechanism of injury, and institutional volume. We found no statistically meaningful contribution to the prediction of survival on the basis of per-surgeon patient volume. Since this volume criterion for surgeon enpanelment and trauma center designation would not be expected to improve outcome, such a requirement should be justified by other measures or abandoned. Final Decision: no