Accepted for/Published in: JMIR Formative Research
Date Submitted: Aug 25, 2023
Date Accepted: May 3, 2024
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Applying the principles of lean thinking and Toyota’s methods to leverage surgery-related big data is an effective approach for developing a new informative surgical scheduling system that meets users’ needs without incurring additional costs
ABSTRACT
Background:
Surgical scheduling is pivotal because it determines the daily sequence of patient surgeries. Patients typically desire early surgeries due to the physical and emotional strain of waiting. Efficient scheduling impacts hospital resources, especially considering the high cost linked to operating rooms, roughly $36 per minute. Existing literature indicates that there is no globally accepted method for surgical scheduling. The primary challenge is predicting the time each surgeon requires for various surgeries on patients with different conditions. Therefore, we have applied principles from the Toyota Production System in clinical operations, finding its problem-solving approach valuable. In their book, "Lean Thinking," Womack and Jones identify five principles of the Toyota Production System and state that any service that "does not meet customer needs" is waste. In a hospital, waste can lead to patient safety and medical quality issues, which are critical to address.
Objective:
Our aim is to apply lean thinking and the Toyota method to enhance our surgical scheduling system.
Methods:
The five principles include specifying value and pinpointing the value stream, flow, pull, and perfection. The customer’s needs represent value, emphasizing the importance of a scheduling system that aligns with these needs. Our hospital's surgical system has two subsystems: one for presurgery patient data and another for during/after surgery data. The former was found to be inefficient, prompting us to create a value stream map for the surgical process. We used the Visual Basic for Applications programming language to write a macro, calculating the average surgery time using data from the during/after surgery data. Another Excel macro was devised for time estimation and concise, visually pleasing schedule report generation using data from the presurgery patient data. We tested our new system by comparing the time taken by nurses using the old and new value stream maps.
Results:
The new system reduced the scheduling time from 301 to 261 seconds (P=.016). In the revised process areas, the time declined from 99 to 62 seconds (P<.001). However, 21% of nurses favored the old method due to familiarity. The Excel macro, respecting data privacy, disseminated schedules via a LINE group. Ensuring 'flow,' the macro functioned efficiently and was capable of anytime execution; it has been in daily use for over three years, monitoring surgeries and operation durations. The 'pull' principle became evident when a software disruption led to quick user-driven repairs, and the 'perfection' principle spurred continuous improvement. The only unimproved step is confirming patient details before surgery, a crucial aspect for patient safety.
Conclusions:
Lean principles and Toyota’s methods, combined with computer programming, can revitalize surgical scheduling processes. They offer effective solutions for surgical scheduling challenges and enable the creation of a novel surgical scheduling system without incurring additional costs.
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