The proper care for patients’ delays requires the use of clear decision logic and tools. Simulation and optimization methods can support business decisions to minimize the risk of the evaluation complex process by analyzing and assessing various patient flow control strategies. The patient scheduling problem is defined as integer programming models, and the Tabu search strategy and L-shaped algorithm solve the significant aspects of the complex scheduling problem.

To minimize patient waiting time, the introduction of the patient triage process in the emergency room, the use of a critical care physician for a medical condition, and the organizing of diagnostic tests in the early stages of the process, as well as a specialist laboratory for emergency patients, are recommended to speed up the hospital process, according to the findings obtained. To balance the advantages of clinic and patient satisfaction while considering patient preference and service fairness simultaneously, a sequential appointment scheduling strategy should be proposed. In regard to recognizing the concept of complexity in business and work strategies, organizations encounter significant obstacles. The complexity theory is investigated in this topic in connection to the effectiveness of healthcare and scheduling services. Healthcare metrics should be used to assess organizational performance.

The goal of this Special Issue is to see if complex thinking influences scheduling efficacy. The findings may aid healthcare leaders and decision-makers overcome obstacles in their jobs and improve the efficiency of healthcare services. There is no such research in this field that we are aware of it. There is a need for more empirical studies on the effectiveness of scheduling on various levels of healthcare functions. Furthermore, this topic aims to show how managed scheduling functions can be used to improve health care. The purpose of this topic, more specifically, was to develop a suitable resolution to the conundrum of inequalities in scheduling efficacy of healthcare services based on complexity theory. We welcome original studies and review articles on this subject.

Potential topics include but are not limited to the following:

• Chase and complexity in scheduling systems in healthcare
• Extended complexity theory in healthcare waiting time network
• Business decisions for diminishing the risk of the evaluation process
• Statistical models to reduce patients' waiting times
• Patient scheduling problems with novel models
• Sequential appointment scheduling strategies
• Machine learning models for scheduling problems in healthcare
• Metaheuristic optimization models to design sensitive scheduling networks
• Complexity of health care systems in the care of financial, learning, and quality problems