Operations research methods improve chemotherapy patient appointment scheduling.

Area of Science:

• Healthcare Operations Research
• Clinical Workflow Optimization
• Patient Scheduling Systems

Background:

• Chemotherapy clinics face challenges with complex scheduling, manual processes, and long patient waitlists.
• Outdated booking systems at a Canadian cancer center led to frequent errors and late appointment notifications.
• A 17-month study aimed to resolve these operational inefficiencies.

Purpose of the Study:

• To redesign and improve the booking and scheduling processes for a chemotherapy clinic.
• To reduce patient wait times and improve the timeliness of appointment notifications.
• To enhance overall patient satisfaction and staff experience.

Main Methods:

• Process mapping, data analysis, and patient satisfaction surveys were used for initial assessment.
• Discrete event simulation and an optimization-based scheduling tool were developed for process improvement.
• Implementation involved change management, with results evaluated via data analysis and follow-up surveys.

Main Results:

• A revised, flexible first-stage scheduling process and an automated second-stage process were implemented.
• Median waitlist size decreased by 83%, and appointment notification lead time improved by 57%.
• Patient satisfaction increased, and staff reported reduced stress levels.

Conclusions:

• Process redesign, when combined with operations research methods, yields substantial operational improvements.
• The study demonstrates the effectiveness of data-driven approaches in enhancing healthcare delivery.
• Optimized scheduling systems can lead to better patient outcomes and more efficient clinic operations.