Risk-based decision making framework for prioritizing patients' access to healthcare services by considering uncertainties

Because of insufficient capacity of hospitals, all patients on waiting lists can't be treated immediately. Then, patients must be prioritized for treatment based on variety of factors. But, current decisions regarding patients' prioritization have been criticized as being highly subjective and inadequate to assess urgency and case-mix of patients. This study presents a new risk based prioritization framework using fuzzy soft sets, in an attempt to overcome the limitations of current approaches. The proposed framework can aid hospitals' decision makers to evaluate and select the high-risk patients in uncertain and complex environments. In order to show the effectiveness of the proposed framework, a numerical study for surgical patients' prioritization is considered. The numerical study suggests that the proposed framework not only considers various perspectives and risks in determining patients' priorities, but also remains noticeably robust as shown by sensitivity analysis. This framework can increases patients' safety, quality of care, and decrease uncertainties and total risks that threaten patients on waiting lists. Besides it can have significant impact on both the medical community and the public's faith in justice and equity.