A Probabilistic Patient Scheduling Model with Time Variable Slots.

Area of Science:

• Operations Research
• Healthcare Management
• Health Informatics

Background:

• Patient no-shows are a significant challenge for health centers, leading to service underutilization, reduced income, and extended patient access times.
• Existing appointment scheduling systems are evolving with electronic health records, incorporating no-show prediction, but personalized variable time slots remain under-analyzed.

Purpose of the Study:

• To propose and analyze a novel appointment scheduling system that integrates patient no-show probabilities with personalized, variable time slots and dynamic priority allocation.
• To maximize clinic profits by optimizing appointment scheduling for both first and follow-up visits.

Main Methods:

• Development of a scheduling system based on a mixed-integer programming model.
• Incorporation of patient no-show probabilities and variable time slot allocation.
• Validation through an extensive simulation study using real data from a Spanish hospital.

Main Results:

• The proposed system demonstrates significant potential benefits for clinic operations.
• Implementation of the model led to a projected increase in annual accumulated profit exceeding 50%.
• The system also achieved a 30% reduction in the waiting list and a 50% decrease in waiting times.

Conclusions:

• The proposed appointment scheduling system, incorporating variable time slots and no-show probabilities, offers substantial improvements over traditional methods.
• This approach effectively enhances clinic profitability while simultaneously improving patient access and reducing wait times.