Contributors to the length-of-stay trajectory in burn-injured patients

Burns. 2018 Dec;44(8):2011-2017. doi: 10.1016/j.burns.2018.07.004. Epub 2018 Aug 10.

Abstract

Objectives: Burn patients have a highly variable length-of-stay (LOS) due to the complexity of the injury itself. The LOS for burn patients is estimated as one day per percent total body surface area (TBSA) burn. To focus care expectation and prognosis we aimed to identify key factors that contribute to prolonged LOS.

Methods: This was a retrospective cohort-study (2006-2016) in an adult burn-centre that included patients with ≥10% TBSA burn. Patients were stratified into expected-LOS (<2 days LOS/%TBSA) and longer-than-expected-LOS (≥2 days LOS/%TBSA). We assessed demographics, comorbidities, and in-hospital complications. Logistic regression and propensity matching was utilized.

Results: Of the 583 total patients, 477 had an expected-LOS whereas 106 a longer-than-expected-LOS. Non-modifiable factors such as age, 3rd degree TBSA%, inhalation injuries and comorbidities were greater in the exceeded LOS patients. Subsequent matched analysis revealed factors like number of procedures performed, days ventilated and in-hospital complications (bacteremia, pneumonia, sepsis, graft loss, and respiratory failure) were significantly increased in the longer-than-expected-LOS group.

Conclusions: Progress has been made to update the conventional one day/%TBSA to better aid health care providers in giving appropriate outcomes for patients and their families and to supply intensive care units with valuable data to assess quality of care and to improve patient prognosis.

Keywords: Burns; Comorbidities; In-hospital complications; Length of stay.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Adult
  • Aged
  • Bacteremia / epidemiology
  • Body Surface Area
  • Burn Units
  • Burns / epidemiology
  • Burns / therapy*
  • Cohort Studies
  • Comorbidity
  • Female
  • Humans
  • Intensive Care Units
  • Length of Stay / statistics & numerical data*
  • Logistic Models
  • Male
  • Middle Aged
  • Pneumonia / epidemiology
  • Propensity Score
  • Quality Indicators, Health Care*
  • Recovery of Function
  • Respiration, Artificial / statistics & numerical data
  • Respiratory Distress Syndrome / epidemiology
  • Respiratory Insufficiency / epidemiology
  • Retrospective Studies
  • Risk Factors
  • Sepsis / epidemiology
  • Skin Transplantation
  • Smoke Inhalation Injury / epidemiology
  • Survivors