Related Experiment Video
Updated: Feb 18, 2026
Author Spotlight: Recent Advancements in Reoperative Foregut Surgery
Published on: September 22, 2023
Incidence and predictors of 30-day postoperative readmission in children
Daniel Vo1, David Zurakowski1, David Faraoni2
1Department of Anesthesiology, Perioperative and Pain Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
Insights
Pediatric postsurgical readmissions occur in 4.8% of children. High-risk factors include congenital heart disease, inpatient status, and postoperative complications, informing a new predictive algorithm.
Area of Science:
- Pediatric Surgery
- Health Services Research
- Quality Improvement
Background:
- Hospital readmissions are increasingly utilized as a quality metric for reimbursement.
- Understanding factors predicting pediatric readmissions is crucial for quality assessment.
- Current knowledge on pediatric postsurgical readmission predictors is limited.
Purpose of the Study:
- To determine the incidence of 30-day postsurgical readmissions in pediatric patients.
- To identify key predictors associated with these readmissions.
- To develop a predictive algorithm for identifying high-risk children.
Main Methods:
- Analysis of the 2012-2014 American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) Pediatric database.
- Utilized univariable and multivariable logistic regression to identify predictors.
- Developed and validated a predictive algorithm for 30-day readmissions.
Main Results:
- The study analyzed 182,589 pediatric cases, with a 4.8% readmission rate within 30 days.
- Significant predictors identified: American Society of Anesthesiologists physical status ≥ 3, congenital heart disease, inpatient status at surgery, and postoperative complications.
- The predictive algorithm demonstrated good discrimination (AUC 0.747) and calibration (Brier score 0.044).
Conclusions:
- Children with congenital heart disease, higher ASA physical status, inpatient surgical status, and postoperative complications face elevated readmission risk.
- A validated algorithm is available to quantify this risk.
- The algorithm aims to reduce readmissions, enhance care for complex pediatric patients, and lower healthcare costs.
Background:
Hospital readmissions are being used as a quality metric for hospital reimbursement without a clear understanding of the factors that contribute to readmission.
Objective:
The objective of this study was to report the incidence of 30-day postsurgical readmission in children, identify the predictors for readmission, and create an algorithm to identify high-risk children.
Methods:
Data from the 2012-2014 Pediatric database of the American College of Surgeons National Surgical Quality Improvement Program were analyzed using univariable and multivariable logistical regression analysis.
Results:
Among 182 589 children included in the 2012-2014 American College of Surgeons National Surgical Quality Improvement Program Pediatric database, 4.8% (8815/182 589) experienced a readmission within 30 days. Four significant predictors were retained in the multivariable logistic regression model: American Society of Anesthesiologists physical status ≥ 3 (OR: 1.9, 95% CI: 1.8-2.0), presence of congenital heart disease (OR: 1.66, 95% CI: 1.31-2.11), inpatient status at time of surgery (OR: 3.5, 95% CI: 3.3-3.7), and at least 1 postoperative complication (neurologic, renal, wound, cardiac, bleeding, or pulmonary) (OR: 3.14, 95% CI: 2.92-3.34). The multivariable logistic regression model showed reasonably good discrimination in predicting 30-day readmissions with receiver operating characteristic area under the curve of 0.747 (95% CI: 0.73-0.75) and good calibration (Brier score: 0.044). We created a predictive algorithm of 30-day readmission based on the 4 significant predictors.
Conclusion:
Children with congenital heart disease, high American Society of Anesthesiologist physical class, inpatient status, and at least 1 postoperative complication of any kind are at high risk for postsurgical readmissions. We provide an algorithm for quantifying this risk with the goal of reducing the number of readmissions, improving the care of patients with complex chronic illnesses, and reducing hospital costs.
More Related Videos
Related Concept Videos
01:29Appendicitis-II: Diagnostic Studies and Management
Diagnosing Appendicitis
It requires a multifaceted approach, starting with a detailed physical examination to pinpoint the location and nature of the pain and identify any associated symptoms. Laboratory tests play a crucial role. A complete Blood Count (CBC) typically reveals leukocytosis (an increased number of...
01:28Cardiomyopathy VII: Pre and Post Operative Nursing Management
01:26Endoscopic Procedures IV: Sigmoidoscopy and Laproscopy
Sigmoidoscopy
Sigmoidoscopy is a diagnostic procedure that uses a flexible sigmoidoscope equipped with a light source and camera to examine the rectum and sigmoid colon. The procedure involves inserting the tube through the anus...
01:23Peripheral Artery Disease V: Postoperative Nursing Management
01:16Kidney Transplant III: Nursing Management
01:22Aneurysm IV: Nursing Management