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JapaneseGiving back time to the front lines – AI and business automation supporting work style reform for doctors
In April 2024, regulations limiting overtime work were also applied to hospital doctors. With staffing levels limited, yet medical care cannot be stopped – the challenge under these severe constraints is to redesign work processes to reclaim time for tasks that only humans can perform.
The number of people supporting healthcare is not increasing. Yet, the quality of medical care must be maintained – many healthcare institutions are currently caught between these two demands.
From April 2024, overtime work for hospital doctors is now subject to upper limits. The general rule is less than 960 hours per year and 100 hours per month (Level A). Even in exceptional cases where it is unavoidable, such as securing regional medical care, the upper limit is 1,860 hours per year (Ministry of Health, Labour and Welfare). For workplaces that have relied on long working hours, this change forces a fundamental review of how things are done.
First, let’s look at the number of times when we say “I don’t have time.”
960 hours per year
The principle limit on overtime work (Level A) that came into effect in April 2024.
1,860 hours per year
1,860 hours per year The upper limit of the special standards (B and C levels) applicable to specific tasks such as emergency medical services.
39%
The percentage of medical institutions that responded that they "generally have a grasp of" the working hours of doctors, including those with side jobs or second jobs. 24% of university hospitals reported this figure.
Regulations have begun. However, only 40% of facilities can accurately track working hours in the first place. You can’t reduce what you can’t see. The first step in work style reform is to make the reality of work visible.
Where does the doctor’s time go?
Task 1
The burden of record-keeping and document creation
Medical records, referral letters, various summaries, and consent forms – these tasks, essential for the quality of medical care, yet consuming a significant amount of a doctor’s time, fill up the gaps between consultations.
Task 2
Focusing on tasks that can be done even by non-specialists
Tasks that should ideally be entrusted to other professions or systems continue to be conventionally concentrated on doctors. While task shifting is being institutionalized, its implementation in practice is not keeping pace.
Task 3
Fragmented systems and manual labor
The systems, separated by department, are manually linked by people. This “manual linking” is a breeding ground for unseen overtime.
Automate repetitive tasks with AI, and make decisions with humans.
What’s needed isn’t to make doctors work faster, but to automate tasks that don’t necessarily require a doctor’s expertise. The areas where AI and automation can contribute are clear.
Automatic drafting of records
The consultation conversation is transcribed using speech recognition, and AI summarizes and structures it to generate a draft of the medical record. The doctor’s role shifts from writing from scratch to reviewing and approving it.
Automation of administrative tasks and data entry
Automate data transfer between systems, reservation and inquiry handling, and creation of standardized documents. Connect fragmented systems and reduce manual work.
Support for access to knowledge
An AI assistant that provides interactive access to information buried in manuals and the tacit knowledge of veterans. It compensates for differences in experience and reduces the burden of handling inquiries.
Visualization of working hours
We will capture actual work conditions as data to identify biases and bottlenecks. This will enable reforms to be implemented as practical actions rather than just empty rhetoric.
Figure: Flowchart of automated drafting of medical records. The “Human-in-the-loop” design, where AI handles transcription, summarization, and structuring, with final confirmation and approval always performed by a physician, is a prerequisite for trust in healthcare.
“The goal of automation is not to take jobs away from doctors. It is to return time to the front lines – time to face patients, time to think, time to rest”.
The perspective of “AI that can be used in the field”
Although in a different industry, Cubastion has a track record of building AI assistants in the automotive sector to support mechanics’ access to technical information. With multilingual support and 24/7 operation, it significantly reduced the burden of handling inquiries and the time required to respond. The idea of ”supporting professionals’ access to knowledge with AI” is also applicable to the medical field.
Note: The above is an example from the automotive sector and does not represent implementation results in the medical field. It is presented solely as a reference for the concept of “designing AI that can be used in the field.”
How to protect healthcare in an era where increasing the population is not feasible
Work-style reform is not a compromise that will lower the quality of medical care. It is a design issue to protect sustainable medical care with limited personnel. Next time, as a typical example of this “limited number of specialized personnel,” we will look at the reality of radiology, which has the world’s highest number of examinations but whose image interpretation system cannot keep up, and the possibilities of AI image diagnosis.
