Determinants and outcomes associated with decisions to deny intensive care unit admission in Tunisian ICU

Pan Afr Med J. 2018 Mar 26:29:176. doi: 10.11604/pamj.2018.29.176.13099. eCollection 2018.

Abstract

Introduction: intensive care unit (ICU) beds are a scarce resource, and admissions may require prioritization when demand exceeds supply. However, there are few data regarding both outcomes of admitted patients to intensive care unit (ICU) in comparison with outcomes of not admitted patients. The aim of this study was to assess reasons and factors associated to refusal of admission to ICU as well as the impact on mortality at 28 days and patients' outcomes.

Methods: Single-center, cross-sectional descriptive study conducted in 8-bed Medical ICU at a Tunisian University hospital. All consecutive adult patients referred for admission to ICU during 6 months were included. We collected demographic data, ICU admission/refusal reasons, co-morbidity and diagnosis at time of admission, mortality probability model (MPMII0) score, day and time of admission, request for admission and mortality at 28 days.

Results: 327 patients were evaluated for ICU admission and 260 were refused to ICU (79.5%). Patients refused because of unavailability of beds represented 50% and patients considered "too sick to benefit" represented 22%. Multivariate analysis showed that the presence of acute respiratory failure and request by direct contact in the unit were independently associated to admission to ICU (OR: 0.15; 95% CI: 0.07-0.31 and OR: 0.16; 95% CI: 0.08-0.31, respectively). Higher mortality rates were shown in patients "too sick to benefit" (80.7%) and unavailable beds (26.56%).

Conclusion: Refusal of ICU admission was correlated with the severity of acute illness, lack of ICU beds and reasons for admission request. ICU clinicians should evaluate their triage decisions and, if possible, routinely solicit patient preferences during medical emergencies, taking steps to ensure that ICU admission decisions are in line with the goals of the patient. Ultimately, these efforts will help ensure that scarce ICU resources are used most effectively and efficiently.

Keywords: Intensive care unit; mortality; risk factors.

MeSH terms

  • Adult
  • Aged
  • Bed Occupancy / statistics & numerical data
  • Cross-Sectional Studies
  • Decision Making*
  • Female
  • Hospital Mortality
  • Hospitals, University
  • Humans
  • Intensive Care Units / statistics & numerical data*
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Outcome Assessment, Health Care
  • Patient Admission / statistics & numerical data*
  • Time Factors
  • Triage*
  • Tunisia