Almost 10 years ago, Japan set out the Action Plan of Growth Strategy that declared the initiatives of digitalization for medicine, nursing care, and healthcare to achieve the world’s most advanced medical care. This action promoted a major push for digital health and digital medicine in Japan. Specific plans included the following: (1) construction of a digital infrastructure for medicine, nursing care, and healthcare; (2) utilization of the digital infrastructure; (3) advanced digitalization of on-site operations; and (4) system establishment for utilizing medical and personal information. These initiatives formed the foundation of the Japanese national strategy and have been continuously refined, resulting in the current environment of digital health and digital medicine [1].

In this article, we define digital health-related terminologies. First, “digital health” is a comprehensive concept of the utilization of information and communication technology (ICT) for all medical, nursing care, or healthcare support. ICT includes digital technologies such as medical big data of genomic and electronic health information, artificial intelligence (AI), or extended reality (XR) [2]. This term often implies the use of the latest and state-of-the-art digital technology to solve various problems in healthcare fields as the objective. Digital technology seems well suited in the following fields: patient treatment; health promotion including primary prevention; the conduct and support of clinical research including decentralized clinical trials; medical education; observation and evaluation of the patients’ clinical course; and public health monitoring for the general population or specific disease cohorts. Moreover, “digital medicine” refers to digital health related to medical care and broadly supporting medicine practice.” [3] In digital medicine, the use of digital technology for disease treatment is referred to as “digital therapeutics (DTx)” (Fig. 1) [4].

Correlation diagram among digital health-related terminologies

For years, various studies and clinical applications other than digital technologies have been conducted to solve healthcare issues. However, digital technology has become one of the powerful tools to solve healthcare-related problems in any medical field and has strongly assisted the evolution of digital health, along with the recent leap in ICT development, miniaturization and technical advantages of mobile devices, easy access to vast and organized data and ample computational resources, and establishment of 5th (5 G) or higher-generation mobile communication systems that allow for high-capacity, low-latency, and multiple connections. Typical digital technologies include online medical services, AI and machine learning (AI/ML), Web 3.0 (web3) and blockchain technology, XR including metaverse, electronic health records (EHR) and personal health records (PHR), and mobile health (mHealth).

As for online medical service, the Ministry of Health, Labour, and Welfare (MHLW) in Japan has provided “the guidance for the appropriate implementation of telemedicine.” [5] In this guidance, telehealth refers to health promotion and medically related activities using ICT equipment [5]. It includes not only telemedicine but also online medical advice, remote healthcare communication, and real-time online consultation between physicians, similar in concept to digital health. In particular, telemedicine is strictly defined as real-time examination, diagnosis, explanation of laboratory results, and treatment between the physician and the patient, using remote communication tools installed on mobile devices or computers [5]. Of note, regardless of whether it is an insurance-covered medical treatment or not, telemedicine based on this guidance is required.

Owing to the recent coronavirus disease 2019 (COVID-19) pandemic, telemedicine has rapidly and mandatorily gained recognition in Japan. After the state of emergency was declared in April 2020, the MHLW has permitted the use of telemedicine from the first online consultation [6, 7]. Since then, the proportion of hospitals or clinics that could provide telemedicine increased to 15.2% in April 2021 [8]. The revision for medical service fee [9] in 2022 that raised several telemedicine fees (but still less than the face-to-face outpatient fees) may help accelerate the widespread use of telemedicine [10]. However, the number of conducting telemedicine in Japan remains considerably lower than that in European and North American countries [11]. Thus, the advantages and challenges of telemedicine should be reconsidered to further promote its use.

AI has no single definition. The Japanese Society of Artificial Intelligence defined AI as something aimed to perform advanced inference accurately on a large amount of knowledge data [12]. However, the concept of AI is highly diversified and still under discussion. Thus, when using this term, we need to pay attention to what kind of specific AI technology is referred to [13] Currently, rule-based and ML are frequently used AI technology in medical sciences. In addition, the development of computer resources and easy access to medical big data enable us to utilize ML and its subfield, that is, deep learning, for clinical applications.

One of the primary approaches for medical AI implementation today would be to leverage ML, including deep learning or reinforcement learning, as a tool to obtain the target output [13]. In other words, medical AI aims to maximize the performance of the output as “prediction,” “classification,” or “generation” of diseases or data that are currently required in medicine, and numerous efforts are being made to implement it in society. Recently, a large language model of Generative Pre-trained Transformer 3 (GPT-3) with supervised fine-tuning and reinforcement learning from human feedback as InstructGPT [14] and its dialogue-optimized conversation web-console (ChatGPT) [15] attracts huge attention worldwide. Surprisingly, the ChatGPT has already been scored at or near the passing threshold on the United States Medical Licensing Exam [16]. The products applying these natural language processing models have the potential to rapidly penetrate in every aspect of medical fields soon.

Web3.0 is a next-generation Internet environment utilizing blockchain technology, and the metaverse supports part of this environment. Blockchain technology is a type of database that processes and records transactions using cryptography, directly connecting terminals on information communication networks [17]. It has excellent tamper resistance for efficient monitoring and data management in clinical trials [18]. The term “metaverse” refers to a virtual space where anyone can communicate similar to the real world and engage in economic activities involving money as both fiat currency and cryptocurrency [19]. Metaverse uses cross reality (XR), including virtual reality (VR) as its utilization technology, and XR is becoming noteworthy in the medical field.

VR is a technology that creates a virtual environment through a computer, stimulating the human senses and making such an environment perceived as “reality.” [20] Currently, VR controls the visual and auditory senses, and it was often defined as an environment where the external “real” world is completely shut off by a full immersive head-mounted display (HMD). Similar concepts include Augmented Reality (AR) and Mixed Reality (MR), which mainly refer to real-time overlaying (for AR) or merging (for MR) of the environment and objects onto the actual reality we perceived using a see-through HMD or smartphones [20]. Clearly distinguishing them is difficult; thus, a comprehensive concept of XR (cross reality or extended reality) emerged. In the medical field, XR has already been used for medical equipment-level surgical support system [21], medical education [22], and XR-based rehabilitation system [23].

EHR is a collection of electronic medical records stored in an electronic chart originally intended to use only in each hospital or clinic but made shareable and accessible in a specific region or nationwide [24]. EHR contains sensitive personal information; thus, it has been managed mainly by medical institutions. Conversely, the PHR refers to securely usable online medical, health, care and well-being information collected and managed by the person who is being described in the record [25] In PHR, health-related information can be shared and aggregated at the individual level. Thus, even if people visited multiple clinics, PHR can manage not only their medical records but also their lifelong data obtained by wearable devices during daily life.

The term “mHealth” generally refers to digital health using mobile devices. Currently, the most used mobile devices are smartphones and wearable devices. With the advancement of “smart” devices, mobile devices can now measure and estimate not only steps or pulse rates but also electrocardiograms, skin temperature, blood oxygen levels, stress levels, blood pressure, or plasma glucose levels [26]. The wearable devices can also be linked with smartphones to allow viewing, verifying, and processing of biometric data in detail and sharing of data with healthcare providers as needed.

In mHealth, DTx is attracting attention as a novel third option for disease treatment; it is one of the three core treatment pillars, namely, medical, surgical, and digital therapies. I especially focus on DTx in the following chapters.