Multi-Criteria Decision Analysis to prioritize hospital admission of patients affected by COVID-19 in low-resource settings with hospital-bed shortage

Int J Infect Dis. 2020 Sep:98:494-500. doi: 10.1016/j.ijid.2020.06.082. Epub 2020 Jun 30.

Abstract

Objective: To use Multi-Criteria Decision Analysis (MCDA) to determine weights for eleven criteria in order to prioritize COVID-19 non-critical patients for admission to hospital in healthcare settings with limited resources.

Methods: The MCDA was applied in two main steps: specification of criteria for prioritizing COVID-19 patients (and levels within each criterion); and determination of weights for the criteria based on experts' knowledge and experience in managing COVID-19 patients, via an online survey. Criteria were selected based on available COVID-19 evidence with a focus on low- and middle-income countries (LMICs).

Results: The most important criteria (mean weights, summing to 100%) are: PaO2 (16.3%); peripheral O2 saturation (15.9%); chest X-ray (14.1%); Modified Early Warning Score-MEWS (11.4%); respiratory rate (9.5%); comorbidities (6.5%); living with vulnerable people (6.4%); body mass index (5.6%); duration of symptoms before hospital evaluation (5.4%); CRP (5.1%); and age (3.8%).

Conclusions: At the beginning of a new pandemic, when evidence for disease predictors is limited or unavailable and effective national contingency plans are difficult to establish, the MCDA prioritization model could play a pivotal role in improving the response of health systems.

Keywords: COVID-19; Multi-Criteria Decision Analysis; Pandemic; SARS CoV-2.

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • Betacoronavirus / genetics
  • Betacoronavirus / physiology*
  • COVID-19
  • Coronavirus Infections / diagnosis
  • Coronavirus Infections / therapy*
  • Coronavirus Infections / virology
  • Decision Support Techniques
  • Female
  • Hospital Bed Capacity / statistics & numerical data*
  • Hospitalization / statistics & numerical data
  • Humans
  • Male
  • Middle Aged
  • Pandemics
  • Patient Admission / statistics & numerical data*
  • Pneumonia, Viral / diagnosis
  • Pneumonia, Viral / therapy*
  • Pneumonia, Viral / virology
  • SARS-CoV-2
  • Young Adult