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[Examples of AI/DX in the medical and healthcare industry] Improving medical efficiency and correcting regional disparities

About the medical and healthcare industry

In recent years, labor shortages have become a social problem due to changes in the population ratio by generation due to the declining birthrate and aging population. doing.

Moreover, the trend is more pronounced in rural areas. The Ministry of Health, Labor and Welfare’s ” Regional Differences in Medical and Nursing Care by Prefecture  ” raises the issue of regional disparities in medical and nursing care between the Tokyo metropolitan area and rural areas.

In the medical and healthcare industry, these concerns are seen as issues related to people’s safety and security. We use technology to solve problems.

In particular, the technological development of cutting-edge diagnosis and treatment using AI technology, as well as the development of new drugs, has been remarkable, and many successful cases of efficient and high-precision AI technology have been reported, raising expectations for future developments.

In this way, the medical and healthcare industry is making progress in protecting people’s safety, security, and health by using AI and other digital technologies to compensate for the shortage of medical professionals and specialist technicians, as well as the regional disparity in medicine. .

Issues in the medical and healthcare industry

The development of medicine and healthcare that utilizes cutting-edge technologies centered on AI is remarkable, but there are many issues, among which the following two are particularly significant.

1. Regional disparities in medical care due to a decrease in medical facilities and a shortage of on-site medical workers and professional technicians

2. Delay in introduction of cutting-edge technologies such as AI-based medical devices

Regional disparities in medical care due to a decrease in medical facilities and a shortage of on-site medical professionals and specialist technicians

While the decline in the working population is seen as a problem, the medical and healthcare industry is also facing a shortage of hospitals and on-site medical workers and professional engineers.

Looking at the basic statistics released by the Ministry of Health , Labor and Welfare in 2018 , trends in medical facilities and medical workers, the number of doctors and nursing staff is increasing, but the content is the number of qualified people. The reality is that the number of people actually working in hospital facilities is decreasing.

The reason for this is that the number of qualified people who are qualified to work is decreasing due to reasons such as the work environment, work content, and wages are not suitable. This is due to the fact that many of them are working in elderly care facilities.

With the exception of dental clinics and general clinics, the number of hospitals has been declining markedly, peaking at 10,096 in 1990 and continuing to decline.

Delay in introduction of cutting-edge technologies such as AI-based medical devices

The use of cutting-edge medical technology using AI and IoT is expected to fill regional disparities in medical care, but the current problem is that it is not being used much.

Due to the pandemic, telemedicine has become partially possible, and the number of medical facilities that have introduced cutting-edge technology has increased, but it is still limited to some.

This is also connected to the decrease in the number of medical facilities introduced earlier, but due to the decrease in the regional population, mainly in rural areas and depopulated areas, hospitals are being converted to clinics or closed. It’s the actual situation.

For this reason, it is hoped that the introduction of cutting-edge technology will enable the establishment of a system that will enable patients to receive the same level of advanced medical care anywhere in Japan.

Use cases of AI/DX in the medical and healthcare industry

From here, I would like to talk about examples of resolving the above-mentioned “regional disparities in medical care due to the decrease in medical facilities and shortages of on-site medical professionals and specialist technicians” and “delays in introducing cutting-edge technology such as AI-based medical devices.” to introduce.

Improving diagnostic efficiency and accuracy through image analysis

example

Image analysis diagnosis and diagnosis support using AI (deep learning) shortens diagnosis time, prevents diagnosis from being overlooked, increases diagnosis and detection rates, and reduces the burden on medical staff.

Theme

As the population becomes more concentrated, so too do medical facilities, medical workers, and specialist technicians. As a result, human errors such as overwork due to a shortage of medical facilities and medical staff in rural areas and depopulated areas, and oversight of diagnoses due to lack of consultation hours continue to occur.

In addition, there have been cases of bias in the results of diagnostic imaging such as CT scans due to a shortage of specialist pathologists.

solution

From 2020, the Ministry of Health, Labor and Welfare has requested medical device manufacturers, etc., to develop an image diagnosis support program using AI.

In addition, we are actively promoting the introduction of AI diagnosis and diagnosis assistance for areas with medical disparities such as rural areas and depopulated areas.

effect

Hitachi, Ltd. Health Care Business Unit ” AI-based Radiation Imaging Diagnosis Support  “

According to the company, lung cancer CT examinations are regularly performed in the Hitachi district of Ibaraki Prefecture, and the data is used for deep learning and AI analysis to succeed in early detection of lung cancer.

As a result, a time-series study targeting Hitachi City residents confirmed a significant mortality reduction effect.

Development of communication environment and cloud service utilization environment in medical institutions

example

We introduced communication technology to handle the big data necessary for AI (deep learning) and cloud services to safely store and manage data.

Theme

Digital technology has not been introduced to the medical field due to a shortage of engineers and specialists who handle cutting-edge technologies such as AI and cloud, and the inability to develop an environment for handling big data.

solution

We provided one-stop support, from the introduction of a communication environment to the data management environment on the cloud using electronic medical records.

effect

Improvements in communication technology and the cloud technology developed by Hitachi have made it possible to detect illnesses early and know changes in medical conditions quickly through the collection of daily health data using electronic medical records and IoT.

summary

AI technology in the medical and healthcare industry is advancing day by day. It will also boost the growth of the market size of healthcare services and medical equipment industries that utilize AI, and further use of AI is expected in the future.

A major problem is the declining birthrate and aging population, the accompanying medical expenses, and the burden on medical professionals, but it is expected that the introduction of AI will alleviate this.

In the future, AI will play a role in transforming people’s anxieties and worries about medical care, such as disease and prevention, into “safety and security.”

For those looking for a practical DX human resource development course

In promoting DX, in-house DX literacy education is an unavoidable path.

・It is difficult to see the effects of human resource development, and it is difficult to make investment decisions.

・I would like to have them take the course, but the target person is busy and it is difficult to find time to study.

to solve problems such as

We have prepared a “DX Literacy Course” that allows you to complete the course in as little as one day from the start of the course and obtain output based on the content of the course .

 

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