Multi-Criteria Decision Analysis to Prioritise Hospital Admission of Patients Affected by COVID-19 in Settings with Hospital-Bed Shortage

Background: The COVID-19 pandemic has resulted in many health systems worldwide facing an imbalance between patients’ need and available resources. No previous studies have developed explicit recommendations for selecting patients most likely to benefit from hospitalisation in settings with an unsolvable hospital-bed shortage. Methods: Multi-Criteria Decision Analysis (MCDA) was used to determine weights for criteria to prioritise COVID-19 patients for admission to hospital. The MCDA was applied in two main steps: specification of criteria for prioritising 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 healthcare settings with limited resources. Findings: Eleven criteria for prioritising patients were specified, and 103 MDs caring for COVID-19 patients completed the survey to determine the criteria’s weights. The 11 criteria (and levels), in decreasing order of importance [mean weights, summing to 100%], are: PaO2 (>80, 70-80, and 96%, 92-96%, and 20 breaths/min) [9∙5%]; comorbidities (diabetes, respiratory/cardiovascular diseases, and onco-haematological diseases) [6.5%]; living with vulnerable people (people with comorbidities, pregnant women, and immunosuppressed patients) [6∙4%]; body mass index ( 40) [5∙6%]; duration of symptoms before hospital evaluation ( 7 days) [5∙4%]; CRP (normal / high based on local cut off) [5∙1%]; and age (18-50, 50-70, and >70) [3∙8%]. Interpretation: MCDA can be used for prioritising patients for hospitalisation when prioritisation is necessary and evidence for disease predictors is limited or unavailable. MCDA is likely to be especially useful in low- and middle-income countries where effective national contingency plans are difficult to establish. Funding Statement: This project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 820755. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA and bioMerieux SA, Janssen Pharmaceutica NV, Accelerate Diagnostics S.L., Abbott, Bio-Rad Laboratories, BD Switzerland Sarl, and The Wellcome Trust Limited. Declaration of Interests: The authors declare no competing interests. Ethics Approval Statement: There were no humans participating in the research project. Briefly, in the study a list of variables/criteria W ere selected from the scientific literature and the Multi-Criteria Decision Analysis (based on PAPRIKA method) was applied in order to give a weight/score (total 100%) to each criterion. For this reason, the study was exempted from ethical review/clearance.