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Development and validation of a prediction model for conversion of outpatient to inpatient surgery

  • Adam R. Dyas
    Correspondence
    Reprint requests: Adam R. Dyas, MD, Resident Physician, Department of Surgery, University of Colorado Denver, Anschutz Medical Campus, 12631 E. 17th Avenue, C-310, Aurora, CO 80045.
    Affiliations
    Department of Surgery, University of Colorado School of Medicine, Aurora, CO

    Surgical Outcomes and Applied Research Program, University of Colorado School of Medicine, Aurora, CO
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  • William G. Henderson
    Affiliations
    Surgical Outcomes and Applied Research Program, University of Colorado School of Medicine, Aurora, CO

    Adult and Child Center for Health Outcomes Research and Delivery Science, University of Colorado School of Medicine, Aurora, CO

    Department of Biostatistics and Informatics, Colorado School of Public Health, Aurora, CO
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  • Helen J. Madsen
    Affiliations
    Department of Surgery, University of Colorado School of Medicine, Aurora, CO

    Surgical Outcomes and Applied Research Program, University of Colorado School of Medicine, Aurora, CO
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  • Michael R. Bronsert
    Affiliations
    Surgical Outcomes and Applied Research Program, University of Colorado School of Medicine, Aurora, CO

    Adult and Child Center for Health Outcomes Research and Delivery Science, University of Colorado School of Medicine, Aurora, CO
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  • Kathryn L. Colborn
    Affiliations
    Department of Surgery, University of Colorado School of Medicine, Aurora, CO

    Surgical Outcomes and Applied Research Program, University of Colorado School of Medicine, Aurora, CO

    Department of Biostatistics and Informatics, Colorado School of Public Health, Aurora, CO
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  • Anne Lambert-Kerzner
    Affiliations
    Surgical Outcomes and Applied Research Program, University of Colorado School of Medicine, Aurora, CO

    Department of Biostatistics and Informatics, Colorado School of Public Health, Aurora, CO
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  • Robert C. McIntyre Jr.
    Affiliations
    Department of Surgery, University of Colorado School of Medicine, Aurora, CO

    Surgical Outcomes and Applied Research Program, University of Colorado School of Medicine, Aurora, CO
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  • Robert A. Meguid
    Affiliations
    Department of Surgery, University of Colorado School of Medicine, Aurora, CO

    Surgical Outcomes and Applied Research Program, University of Colorado School of Medicine, Aurora, CO

    Adult and Child Center for Health Outcomes Research and Delivery Science, University of Colorado School of Medicine, Aurora, CO
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Published:February 22, 2022DOI:https://doi.org/10.1016/j.surg.2022.01.025

      Abstract

      Background

      Unplanned hospital admission after intended outpatient surgery is an undesirable outcome. We aimed to develop a prediction model that estimates a patient’s risk of conversion from outpatient surgery to inpatient hospitalization.

      Methods

      This was a retrospective analysis using the American College of Surgeons National Surgical Quality Improvement Program database, 2005 to 2018. Conversion from outpatient to inpatient surgery was defined as having outpatient surgery and >1 day hospital stay. The Surgical Risk Preoperative Assessment System was developed using multiple logistic regression on a training dataset (2005–2016) and compared to a model using the 26 relevant variables in the American College of Surgeons National Surgical Quality Improvement Program. The Surgical Risk Preoperative Assessment System was validated using a testing dataset (2017–2018). Performance statistics and Hosmer-Lemeshow plots were compared. Two high-risk definitions were compared: (1) the maximum Youden index, and (2) the cohort above the tenth decile of risk on the Hosmer-Lemeshow plot. The sensitivities, specificities, positive predictive values, negative predictive values, and accuracies were compared.

      Results

      In all, 2,822,379 patients were included; 3.6% of patients unexpectedly converted to inpatient. The 6-variable Surgical Risk Preoperative Assessment System model performed comparably to the 26-variable American College of Surgeons National Surgical Quality Improvement Program model (c-indices = 0.818 vs. 0.823; Brier scores = 0.0308 vs 0.0306, respectively). The Surgical Risk Preoperative Assessment System performed well on internal validation (c-index = 0.818, Brier score = 0.0341). The tenth decile of risk definition had higher specificity, positive predictive values, and accuracy than the maximum Youden index definition, while having lower sensitivity.

      Conclusion

      The Surgical Risk Preoperative Assessment System accurately predicted a patient’s risk of unplanned outpatient-to-inpatient conversion. Patients at higher risk should be considered for inpatient surgery, while lower risk patients could safely undergo operations at ambulatory surgery centers.
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