Literature DB >> 29924657

Predicting the Ideal Patient for Ambulatory Cleft Lip Repair.

Victor Chang1,2, Brendan O'Donnell1,2, William J Bruce2, Uma Maduekwe1,3,4, Max Drescher1,2, Bernandino M Mendez5, Anai N Kothari1,4, Parit A Patel1,6.   

Abstract

BACKGROUND: The utilization of ambulatory surgical centers (ASCs) for cleft lip repair is increasing to reduce costs. This study better defines the patient population appropriate for ambulatory cleft repair with uplift modeling, a predictive analytics technique.
METHODS: Pediatric patients who underwent cleft lip repair were identified in the 2007 to 2011 California Healthcare Cost and Utilization Project State Inpatient Database and State Ambulatory Surgery and Services Database. The 2-model uplift approach was utilized using multivariate logistic regressions fit to assess the effect of ASCs, age, comorbidities, and procedure type on mortality or 30-day readmission.
RESULTS: Of the pediatric cleft lip repairs in California between 2007 and 2011, 2383 (83%) were conducted in inpatient facilities and 498 (17%) in ASCs. The 30-day readmission rates were 2.01% and 1.93% for ASC repairs and inpatient repairs, respectively ( P = .909). Uplift modeling predicts that of the 2881 patients, approximately 40% of patients would have benefit from an ASC repair and an ASC repair would have had no effect on the remaining 60%. Patients likely to benefit from an ASC repair were more likely younger than 1 year old, nonsyndromic, not to have a respiratory or neurologic diagnosis, have less number of procedures, and to have undergone an isolated cleft lip repair.
CONCLUSION: Uplift modeling predicts that approximately 40% of patients would benefit from an ASC cleft lip repair. Targeting patients younger than 1 year old, nonsyndromic, with no respiratory or neurologic diagnosis for ASC cleft lip repair, may be a safe and cost-saving endeavor.

Entities:  

Keywords:  ambulatory cleft lip repair; cleft lip; patient safety; uplift modeling

Year:  2018        PMID: 29924657     DOI: 10.1177/1055665618779980

Source DB:  PubMed          Journal:  Cleft Palate Craniofac J        ISSN: 1055-6656


  1 in total

1.  Application of data mining for predicting hemodynamics instability during pheochromocytoma surgery.

Authors:  Yueyang Zhao; Li Fang; Lei Cui; Song Bai
Journal:  BMC Med Inform Decis Mak       Date:  2020-07-20       Impact factor: 2.796

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.