Objective: Tokyo Sakurajyuji group has established executive health checkup courses to encourage business owners to undergo medical checkups, as they have fewer opportunities to undergo medical checkups. A dedicated concierge takes care of the executive health checkup examinees from booking to follow-up after the checkup. The number of users was 15 in 2017, but has continued to increase, reaching 166 in 2022 through referrals. Business owners have sometimes brought their family members, especially their wives who have even fewer chances to receive health checkups. Additionally, requests for employee health checkups have increased. In the present study, we conducted a satisfaction survey of executive health checkup examinees.
Methods: Thirty-seven people who underwent executive health checkups at Tokyo Sakurajyuji clinics between January 2022 and January 2023 were included in the analysis. The degree of satisfaction was evaluated using a self-administered questionnaire and individual interviews. The items of the survey included physical aspects (hardware) of the facility environment, as well as human aspects (software), such as customer services and hospitality.
Results: Regarding the hardware aspects, 35 subjects (95%) rated the comfort of the facilities as good, followed by 32 subjects (86%) who rated the private room environment as good. However, air conditioning was rated lower, with only 22 subjects (52%) rating it as good. Regarding the software aspects, 36 subjects (97%) reported that the doctors' explanation of the results were good. Thirty-four subjects (92%) rated the coordination from reservation to confirmation and the examination items in the executive health checkup as good.
Conclusion: The hospitality services provided by doctors, paramedical staff, and concierge were confirmed to be important for increasing visit and repeat rates of executive health checkups. Busy businesspeople may require "timesaving" services. Thus, our one-stop, one-operation service in which the concierge acts as a liaison was recognized to be effective.
【Method】 Activity period: April 1, 2023 ~ March 31, 2024. Target persons: Health class participants, salon participants in school districts, all staff in the preventive medicine center, health checkup recipients, people outside the community, and related parties.
Activities Offered:
(1) Hold a 10-minute lecture to help prevent dementia. twice a month, before the start of Health classes,
(2) Designing a double task that leads to the prevention of dementia in Medimesse's original gymnastics
(3) Creation and display of posters to raise awareness of dementia for staff
(4) Light up the perforated metal wall in front of the center entrance in orange.
(5) Visiting local salons for the elderly to give lectures on dementia prevention and awareness-raising
(6) Presentation at the 52nd Annual Meeting of the Japan Society of Comprehensive Health Examination Medicine
【Result】 The autor was able to communicate the existence of dementia technologists and the author's the technologists. In addition, by promoting the acutivity in a multidisciplinary collaboration team, the autor was able to expand the possibilities and learn a lot, and was able to find issues that will lead to future activities.
【Dscussion】 The initiative that made use of the qualifications of a certified dementia laboratory technician was a good opportunity to let people know about the ideas and existence. In particular, by giving lectures at health classes and local salon activities, which serve as a point of contact with the community, authors were able to gain a correct understanding of dementia and raise awareness of dementia prevention. In addition, the author felt that by collaborating with multiple professions, the understanding and knowledge of dementia in other occupations will be deepened, and it will expand further in the future.
【Conclusion】 The authors will continue to promote activities related to preventive medicine and aim to extend the healthy life expectancy of as many people as possible, and will disseminate what the authors can do now here at Medimesse Sakura Cross
Dementia prevention is essential for maintaining a sustainable community. Prevention should include primary, secondary, and tertiary prevention in a seamless manner. It is recommended that scientific evidence-based methods be used when practicing dementia prevention. The most important target population for dementia prevention is mild cognitive impairment (MCI), which should be detected early and preventive interventions should be implemented. Since olfactory impairment precedes memory impairment in dementia of Alzheimer type, an olfactory screening kit should be used as a method for early detection. Aromatherapy is recommended as an approach to early detection of olfactory abnormalities. The anti-amyloid-β antibody drugs: Leqembi® and Kisunla® can now be prescribed, and the treatment of dementia has entered a new stage. Early diagnosis of MCI, which had not been previously treated, is now required. Those who are eligible for treatment with anti-amyloid-β antibody drugs must be given the drugs appropriately, while those who are not eligible for treatment must receive appropriate advice on dementia prevention.
Gastric cancer is one of the major cancers in Japan, and screening for its prevention and early detection is important. Traditionally, barium X-ray contrast examination was the mainstream method of gastric cancer screening, but in recent years, the usefulness of endoscopic examination has been widely recognized. In Japan, endoscopic examination was finally introduced as a preventive screening in 2015, but its penetration rate varies by municipality. Compared to neighboring South Korea, the penetration of endoscopic examination in Japan is currently lagging behind. In this review, we provide an overview of the past and present of gastric cancer screening, discuss the transition of gastric cancer incidence rate with the decline in H. pylori infection rate, the usefulness of endoscopic examination, and the progress of imaging diagnostic technology using artificial intelligence (AI). Furthermore, we discuss the significance of H. pylori eradication as a primary prevention of gastric cancer. As a future outlook, further evolution of endoscopic diagnostic technology, especially AI endoscope, is expected.
For the past 25 years, Japan has followed outdated guidelines for mammography screening, with no proven reduction in breast cancer mortality. This is due to extrapolating Western evidence, which is directly applicable to Japanese women with different breast densities. Japanese women have a higher rate of dense breasts, and the sensitivity of mammography alone for women in their 40s is only 47%. The J-START study, the only RCT (randomized controlled trial) for Japanese women, proves that adding ultrasonography improves sensitivity. Though J-START hasn't shown reduced mortality, it is more relevant than Western RCTs.
Breast cancer screening funded by insurers should aim to reduce personal mortality risk, promote more early detection and treatment, and prevent workforce loss. It requires more accurate screening methods. Japan lacks an accurate system to track mammography sensitivity and participation rates, contributing to inefficacy. Current guidelines are based on outdated combined mammography and clinical breast examination screening data and do not reflect screening mammography alone data.
Next-generation breast cancer screening should focus on equitable screening, ensuring all women, especially those with dense breasts, achieve the best outcomes, such as avoiding breast cancer deaths.
Gastrointestinal cancers are a leading cause of cancer-related deaths worldwide, and early detection significantly improves survival rates. In Japan, adding endoscopic screening to the gastric cancer program since 2016 has increased the workload for endoscopists. Recent advancements in AI have introduced diagnostic systems to support endoscopic examinations, potentially improving accuracy and reducing missed diagnoses. AI's effectiveness in detecting gastric tumors and colorectal adenomas has been shown in trials, and its clinical adoption is expected to grow. In 2017, the authors established AI Medical Service Inc. (AIM), developing the gastroAI™ model-G2, which helps detect areas within the images suspicious for early gastric cancer and adenomas. AIM also provides gastroBASE screening to support Japan's population-based screening using upper gastrointestinal endoscopy. Although challenges remain in the societal implementation of endoscopic AI, AIM, in partnership with the Council for AI Medical Devices, has recommended policies on insurance reimbursement and AI development subsidies. This article explores the current state and future prospects of endoscopic AI.
In recent years, the adoption of AI technology in the medical field has progressed rapidly, particularly in diagnostic imaging, where significant transformations are occurring. AI plays a crucial role in the early detection of abnormalities and improving diagnostic accuracy. Deep learning (DL)-based AI systems are expected to enhance diagnostic efficiency.
This paper first outlines the fundamentals of AI technology, explaining the basic mechanisms of convolutional neural networks (CNNs) and vision transformers (ViTs) and their applications in medical imaging.
Lung cancer remains the leading cause of cancer-related deaths, and early detection significantly impacts prognosis. The NLST and NELSON trials have demonstrated the effectiveness of low-dose CT (LDCT) screening for heavy smokers. However, issues such as false positives and overdiagnosis require further investigation. Moreover, there is a trade-off between radiation dose reduction and image quality, making noise reduction in LDCT images a critical challenge. Advances in AI for noise reduction and lung nodule detection have improved the diagnostic performance of chest X-rays and CT scans. This paper discusses these advancements through specific clinical cases.
The diagnostic performance of AI has already been reported to match or exceed that of radiologists. However, AI also influences human diagnostic capabilities, and the process of AI decision-making remains a black box. The development of explainable AI (XAI) is crucial. Considering the future of AI, including generative models like ChatGPT, AI should be leveraged as a powerful partner to enhance diagnostic accuracy and streamline workflows. This paper aims to provide a structured overview of AI in respiratory medicine and serve as a useful resource for clinical and research applications.