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Factors Associated With Exceeding Predicted Hospital Stays in Pediatric Trauma Patients
Michelle C Coughlin1, Elika Ridelman1, Lydia J Donoghue1
1Department of Surgery, Division of Pediatric Surgery, Children's Hospital of Michigan, Wayne State University, Detroit, MI, USA.
Pediatric trauma patients with higher Injury Severity Scores, non-accidental trauma, and complex injuries often exceed predicted hospital stays. Identifying these factors can improve length of stay (LOS) predictions and reduce actual LOS for better reimbursement.
Area of Science:
- Trauma Surgery
- Pediatric Critical Care
- Health Services Research
Background:
- The Center for Medicare and Medicaid Services (CMS) uses predicted length of stay (LOS) for reimbursement.
- Injury Severity Score (ISS) and non-accidental trauma (NAT) are linked to longer hospital stays in pediatric trauma patients.
- Factors impacting CMS-predicted LOS in pediatric trauma are not fully understood.
Purpose of the Study:
- Identify factors influencing CMS-predicted LOS in pediatric trauma patients.
- Determine if practice changes can reduce actual LOS.
- Inform strategies for improving LOS predictions and reducing actual LOS.
Main Methods:
- Retrospective chart review of 1005 pediatric trauma patients (January 2018 - December 2020).
- Analysis of patient data, including demographics, injury characteristics, and hospital course.
- Statistical analysis with significance set at P < .05.
Main Results:
- 17.6% of patients exceeded their CMS-predicted LOS.
- Excessive LOS associated with higher ISS, confirmed NAT, child protective services involvement, ICU admissions, intubations, ventilator days, transfusions, and inpatient rehabilitation discharges.
- Etiologies like motor-vehicle crashes and suspected abuse, along with brain and internal organ injuries, correlated with longer stays.
- Increased imaging studies, surgical procedures, and longer operative times were noted in patients with excessive LOS.
Conclusions:
- A significant proportion of pediatric trauma patients exceed CMS-predicted LOS, impacting hospital reimbursement.
- Factors related to patient demographics, trauma etiology, and inpatient care influence excessive LOS.
- Addressing identified factors can improve LOS predictions and potentially reduce actual LOS.
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