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Predictability of Same-Day Discharge Candidacy After Bariatric Surgery with Machine Learning.

Jia-Ling Wu¹, Che-Chen Lin¹, Hsiu-Yin Chiang¹

¹China Medical University, Taichung, Taiwan.

Obesity Surgery

|April 30, 2026

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Same-day discharge (SDD) after bariatric surgery is feasible for many patients. However, current predictive models using Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program (MBSAQIP) data cannot reliably identify suitable candidates for SDD.

Area of Science:

Bariatric Surgery Outcomes
Health Informatics
Predictive Analytics in Healthcare

Background:

Same-day discharge (SDD) after bariatric surgery is underutilized due to patient selection challenges.
The Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program (MBSAQIP) database is a potential source for predicting SDD candidacy.
This study evaluates the predictive capability of MBSAQIP data for SDD in bariatric surgery patients.

Purpose of the Study:

To assess if the MBSAQIP database contains sufficient information to predict same-day discharge (SDD) candidacy after bariatric surgery.
To evaluate the performance of various machine learning models in identifying SDD candidates.

Main Methods:

Retrospective cohort study using the 2023 MBSAQIP database.

Keywords:

Bariatric Surgery Machine Learning Predictive Modeling Same Day Discharge

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Identified average-risk patients undergoing gastric bypass or sleeve gastrectomy.

Defined SDD candidacy by discharge within 24 hours and no 30-day readmission.

Applied five predictive models: logistic regression, random forest, gradient boosting, XGBoost, and light gradient boosting machine.

Main Results:

Out of 47,071 patients, 70.1% of gastric bypass and 80.4% of sleeve gastrectomy patients met SDD criteria.
SDD candidates were more likely to be male with fewer comorbidities.
All five predictive models demonstrated poor performance in identifying SDD candidacy, with the best models achieving only marginal predictive power (AUROC < 0.54).

Conclusions:

Over half of average-risk bariatric surgery patients may be suitable for same-day discharge.
Predictive artificial intelligence models using MBSAQIP data were not reliable for identifying SDD candidacy in 2023.
Further research is needed to develop accurate predictive tools for SDD in bariatric surgery.