Predictors of transfer from rehabilitation to acute care in burn injuries

J Trauma Acute Care Surg. 2012 Dec;73(6):1596-601. doi: 10.1097/TA.0b013e318270d73d.

Abstract

Background: Transfer to acute care from rehabilitation represents an interruption in a patient's recovery and a potential deficiency in quality of care. The objective of this study was to examine predictors of transfer to acute care in the inpatient burn rehabilitation population.

Methods: Data are obtained from Uniform Data System for Medical Rehabilitation from 2002 to 2010 for patients with a primary diagnosis of burn injury. Predictor variables include demographic, medical, and facility data. Descriptive statistics are calculated for acute and nonacute transfer patients. Logistic regression analysis is used to determine significant predictors of acute transfer within the first 3 days. A scoring system is developed to determine the risk of acute transfer.

Results: There were 78 acute transfers in the first 3 days of a total of 4,572 burn admissions. Functional level at admission, age, and admission classification are significant predictors of transfer to acute care (p < 0.05). Total body surface area burned and medical comorbidities were not significantly associated with acute transfer risk. A 12-point acute transfer risk scoring system was developed, which demonstrates validity.

Conclusion: Efforts to reduce readmissions to acute care should include greater scrutiny of older, lower-functioning patients with burn injury who are evaluated for admission to inpatient rehabilitation. This acute transfer scoring system may be useful to clinicians, health care institutions, and policymakers to help predict those patients at highest risk for early transfer to the acute hospital from rehabilitation.

Level of evidence: Prognostic/diagnostic study, level II.

MeSH terms

  • Burns / pathology
  • Burns / rehabilitation
  • Burns / therapy*
  • Critical Care / statistics & numerical data
  • Cross-Sectional Studies
  • Female
  • Humans
  • Logistic Models
  • Male
  • Middle Aged
  • Patient Readmission / statistics & numerical data
  • Patient Transfer / statistics & numerical data
  • Retrospective Studies
  • Risk Factors