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.