Setting up Waiting Time Targets for Out Patients using Fuzzy Linear Programming

Abstract

Objective: To introduce fuzzy linear programming to find the patients' waiting time by satisfying some defined satisfaction targets of patients at out-patient department (OPD) of a healthcare unit. Method: The concept of tolerance limit has been used for obtaining fuzzy linear programming formulation. Fuzzy linear programming is transformed into its equivalent crisp linear programming. The software TORA 3.0 is then used to solve the obtained crisp linear programming. Findings: Waiting times for patients at their different satisfaction targets have been obtained by solving equivalent crisp linear programming. The solution of the present model suggests that At least 95.30 % patients should be checked-up within half an hour of their appointment and all of them should be checked up within 45 minutes for punctual patients and at least 26.51 % of them should be checked up within half an hour of their arrival and all of them should be checked up within 45 minutes for late patients. Due to assumption of tolerance limit, patients' satisfaction targets regarding waiting time are relaxed up to predefined limits. Consequently the efficiency of healthcare unit increases in the proportion of relaxed limits. Novelty: Patients' waiting time with satisfying targets have already been obtained using statistical analyses and classical linear programming. In this article we introduce the fuzzy linear programming to get waiting time for patients by fuzzifying the patients' satisfaction constraints which are indeed novel idea in setting patients' waiting time. Furthermore, some crisp constraints are also included to make the waiting time standards consistent for patients.

Generalized Fuzzy Technique and Its Consistent Assessment in Multi-criteria Decision Making of Medical Decisions

“…In the sequence, Gupta et al reviewed fuzzy logic based systems in the medical diagnosis [13]. Kumar and Pandey modeled the waiting time targets for out-patients for healthcare units using fuzzy linear programming [22]. In 2023, Hosseinzadeh et al describe the determination of fuzzy weights in multi-criteria decision making [15].…”