Automating Radiation Therapy Scheduling for Better Patient Care

Radiation Therapy (RT) is a common treatment for cancer, especially as more people receive a cancer diagnosis each year. With an increasing number of patients, hospitals face challenges in Scheduling RT efficiently. Manually organizing patient appointments can take a lot of time and effort, leading to longer waiting times for treatments. Long waits can make treatment less effective and add stress for both patients and staff.

To address these issues, hospitals are turning to automated systems that can help schedule appointments. These systems use mathematical methods to create schedules that meet both the needs of patients and the constraints of the hospital’s resources.

#Importance of Efficient Scheduling

When patients need RT, they often must visit the hospital multiple times over several weeks. Many patients prefer to receive their treatments at specific times or locations, which can make scheduling even more complicated. Additionally, some patients require urgent care, making it crucial to reserve time slots for them.

Long waiting times for RT can lead to several problems, including:

• Tumor growth, which can make treatment less effective.
• Increased chances of local recurrence, meaning the cancer can return after treatment.
• Longer patient discomfort and psychological stress.
• Stress on RT staff, which could affect the quality of care.

To improve patient care, hospitals must focus on timely treatment. Good scheduling can greatly enhance patient experience and involvement in their care.

#The RT Workflow

The RT process begins with a consultation where the patient's condition is evaluated. After the consultation, patients need to book time for CT simulations, which help tailor the treatment plan based on their specific needs. This planning period is crucial, as it considers the characteristics of the tumor and the intended treatment.

Most patients receive RT as outpatients. This means they come to the hospital for treatment during weekdays. However, some schedules may include weekly or every-other-day treatments. Each session typically lasts between 10 and 30 minutes, which adds to the complexity of scheduling.

With patients arriving at different times, creating efficient schedules manually becomes challenging. Automated scheduling algorithms can help hospitals maximize their resources while providing better services.

#The Role of Operations Research

Operations research (OR) is a field that uses mathematical and statistical methods to solve complex problems, including those in healthcare. OR has been employed in various healthcare settings, but its use in RT scheduling is relatively new.

Studies have shown that OR can improve scheduling efficiency. However, many models have relied on simulated data rather than real-world clinic schedules. This gap makes it difficult to assess how well these models would work in practice.

One notable example of using an OR model for RT scheduling showed positive results for a short evaluation period. However, it only assessed the schedule for one week, which does not provide a complete picture since treatment schedules can change significantly over time.

#Automating RT Scheduling

Recent developments aim to automate RT scheduling using OR methods based on real clinical data. The main goal is to create schedules that closely align with the hospital's objectives while adhering to medical and technical requirements.

This system can allow a hospital to schedule treatments in a way that reduces waiting times for patients by making use of existing data. This includes factors related to patient arrivals and Machine Availability.

#Scheduling at Iridium Netwerk

At Iridium Netwerk, a large RT center in Belgium, ten linear accelerators (machines that deliver RT) are used to treat thousands of patients each year. Scheduling treatments requires careful planning due to machine availability, Patient Preferences, and treatment protocols.

Each treatment protocol has specific instructions, including the type of machine needed, the length of each session, and the minimum number of sessions per week. Staff members often reserve time slots for urgent patients based on historical arrival data.

In 2020, over half of the patients scheduled were deemed urgent. This urgency adds another layer of complexity to scheduling workflows. As treatment protocols vary, scheduling staff must determine the best options for each patient based on their needs.

#Gathering Patient Data

To make the scheduling process more effective, staff at Iridium Netwerk collect detailed patient data. Information about treatments is recorded in the hospital's oncology information system, ensuring that data is organized and ready for analysis.

Patient preferences, such as preferred treatment times or locations, are important factors that influence scheduling decisions. However, since this data is not always recorded during the patient’s visit, staff may estimate preferences based on the patient's home location.

The data also includes planned machine downtime for maintenance and any unplanned outages due to equipment failure. Understanding this information allows for better scheduling and patient management.

#How Automatic Scheduling Works

The automated scheduling process involves creating a schedule that considers patient needs and machine availability. The OR model generates schedules at the end of each day, taking into account all the new patients and any changes from previous days.

By utilizing all the available information, the automated system can minimize waiting times and ensure an efficient use of resources. The algorithm is designed to handle uncertainties and prioritize urgent patients, allowing hospitals to improve patient care.

#Daily Scheduling Practices

Each day, the automatic scheduling system reviews patient arrivals and develops a schedule that covers the next three months. The algorithm considers all previously scheduled patients and prioritizes urgent cases first.

In the hospital, patients receive notifications about their treatment schedules soon after their initial visit. It is important to keep patients informed, as most prefer to have a clear understanding of when their treatments will occur.

#Addressing Machine Failures

Machine breakdowns can disrupt the treatment schedule. The automated system anticipates possible failures and adjusts the schedule accordingly. If a machine fails, the algorithm can quickly reschedule affected patients to other available machines. This capability is crucial for ensuring that patients do not experience delays in treatment.

#Evaluation of Scheduling Quality

To assess the effectiveness of the automated scheduling system, various metrics are developed to evaluate the quality of generated schedules. These include measures of waiting times, appointment consistency, and machine usage.

Automated schedules are compared to manually created schedules from the same time period. This comparison helps identify areas where improvements can be made.

#Results of Automatic Scheduling

In practice, the automated scheduling process has shown significant benefits:

• Average patient waiting time decreased by about 80% compared to manual scheduling.
• The consistency of appointment times improved by 80%.
• The number of treatments scheduled on preferred machines increased by over 90%.

These results indicate that using automated methods can greatly enhance the scheduling process in RT centers and provide better service to patients.

#Understanding Patient Experiences

Waiting times directly affect patient experiences. By using the automated system, hospitals can ensure that patients receive care more quickly, leading to a more positive overall experience. Quick treatment can alleviate patient stress and improve the chances of successful outcomes.

#Challenges to Implementation

While the automated scheduling system shows promise, several challenges remain for its full implementation in clinical practice.

One of the most significant barriers is the need for a user-friendly interface that can integrate with existing hospital systems. This integration would facilitate easier access to patient data and machine availability.

Additionally, collecting comprehensive patient preferences and treatment protocols is essential for the system to work effectively. Hospitals must ensure that patients’ wishes are recorded accurately to improve the scheduling process.

#Conclusion

As the number of cancer cases continues to rise, hospitals must find efficient ways to schedule treatments to meet growing demand. Automated scheduling systems present a viable solution to help manage the complexities involved in RT scheduling.

The use of OR methods in clinical practice can lead to shorter waiting times, better use of resources, and improved patient satisfaction. With continued development and integration into healthcare systems, automated scheduling has the potential to significantly enhance the quality of care for patients undergoing radiation therapy.