Recently, digital health has gained the attention of physicians, patients, and healthcare industries. Digital health, a broad umbrella term, can be defined as an emerging health area that uses brand new digital or medical technologies involving genomics, big data, wearables, mobile applications, and artificial intelligence. Digital health has been highlighted as a way of realizing precision medicine, and in addition is expected to become synonymous with health itself with the rapid digitization of all health-related data. In this article, we first define digital health by reviewing the diverse range of definitions among academia and government agencies. Based on these definitions, we then review the current status of digital health, mainly in Korea, suggest points that are missing from the discussion or ought to be added, and provide future directions of digital health in clinical practice by pointing out certain key points.
Artificial Intelligence ; Genomics ; Government Agencies ; Government Regulation ; Health Care Sector ; Humans ; Korea ; Mobile Applications ; Precision Medicine ; Telemedicine

The first hospice care center in Korea dates back to the East West Infirmaries (Dongseodaebiwon in the Korean language) of the Goryeo period in the early 11th century. It has been 50 years since hospice care was introduced in Korea. Initially hospice care was provided in the private sector, including those with a religious background, and its development was slow. In the 1990s, related religious organizations and academic associations were established, and then, a full-swing growth phase was ushered in as the Korean government institutionalized hospice care in the early 2000s. As a result, enhanced quality of hospice care service could be provided, which meant better pain management and higher quality of life for late stage cancer patients and their families. Still, the nation lacked a realistic reimbursement system which was needed to for financial stability of the affected patients. However, the national health insurance scheme began to cover hospice palliative expenses in 2015. In 2016, the Act on Decisions on Life-Sustaining Treatment for Patients in Hospice and Palliative Care or at the End of Life was legislated, allowing terminally-ill patients to refuse meaningless life-sustaining treatments. As the range of diseases subject to hospice palliative care was expanded, more challenges and issues need to be addressed by the service providers.
Hospice Care ; Hospices ; Humans ; Korea ; National Health Programs ; Pain Management ; Palliative Care ; Private Sector ; Quality of Life

OBJECTIVE: Enhanced technology in computer and internet has driven scale and quality of data to be improved in various areas including healthcare sectors. Machine Learning (ML) has played a pivotal role in efficiently analyzing those big data, but a general misunderstanding of ML algorithms still exists in applying them (e.g., ML techniques can settle a problem of small sample size, or deep learning is the ML algorithm). This paper reviewed the research of diagnosing mental illness using ML algorithm and suggests how ML techniques can be employed and worked in practice. METHODS: Researches about mental illness diagnostic using ML techniques were carefully reviewed. Five traditional ML algorithms-Support Vector Machines (SVM), Gradient Boosting Machine (GBM), Random Forest, Naïve Bayes, and K-Nearest Neighborhood (KNN)-frequently used for mental health area researches were systematically organized and summarized. RESULTS: Based on literature review, it turned out that Support Vector Machines (SVM), Gradient Boosting Machine (GBM), Random Forest, Naïve Bayes, and K-Nearest Neighborhood (KNN) were frequently employed in mental health area, but many researchers did not clarify the reason for using their ML algorithm though every ML algorithm has its own advantages. In addition, there were several studies to apply ML algorithms without fully understanding the data characteristics. CONCLUSION: Researchers using ML algorithms should be aware of the properties of their ML algorithms and the limitation of the results they obtained under restricted data conditions. This paper provides useful information of the properties and limitation of each ML algorithm in the practice of mental health.
Bays ; Forests ; Health Care Sector ; Internet ; Learning ; Machine Learning ; Mental Health ; Residence Characteristics ; Sample Size ; Support Vector Machine

OBJECTIVES: Conventional radiological processes have been replaced by digital images and information technology systems within South Africa and other developing countries. Picture Archiving and Communication Systems (PACS) technology offers many benefits to institutions, medical personnel and patients; however, the implementation of such systems can be a challenging task. It has been documented that South Africa has been using PACS for more than a decade in public hospitals with moderate success. The aim of this study was to identify and describe the PACS challenges endured by PACS vendors during implementation in the South African public healthcare sector. METHODS: This was achieved by engaging in a methodological approach that was qualitative in nature collecting data through semi structured interviews from 10 PACS experts/participants which were later analysed qualitatively. RESULTS: The findings show that PACS vendors have countless challenges, some of which include space, insufficient infrastructure, image storage capacity, system maturity and vendor related concerns. It was clear that the PACS experts readily offered contextually appropriate descriptions of their encounters during PACS implementations in South African public healthcare institutions. CONCLUSIONS: PACS vendors anticipate these challenges when facing a public healthcare institution and it is recommended that the hospital management and potential PACS stakeholders be made aware of these challenges to mitigate their effects and aid in a successful implementation.
Commerce ; Delivery of Health Care ; Developing Countries ; Health Care Sector ; Hospitals, Public ; Humans ; Information Storage and Retrieval ; Medical Informatics ; Medical Informatics Computing ; Radiography ; Radiology Information Systems ; South Africa

With China's implementing big data strategy, health care becomes one of the key areas in which the national big data strategy is highly promoted. However, as the health care big data industry grows rapidly, the security risk is increasingly prominent and the internet plus medical care makes the protection of health care big data more complicated. By analyzing the current situation of health care big data security protection, the article proposes the viewpoint of relative security and suggests the strategies and key issues of health care big data protection. From the aspects of legal supervision, talents cultivation, publicity and education, and key data protection, it is necessary to build the prevention and control system for health care big data security, so that the security risk can be reduced and the data utility can be maximized.
Big Data ; China ; Computer Security ; standards ; Health Care Sector ; standards ; Internet

Blockchain is at the center of attention recently and it is expected to have a huge impact on healthcare industry including dentistry as well. Blockchain is a fundamental technology behind Bitcoin and itis all about decentralization, security, reliability, and transparency. These characteristics of the technology empower it to disrupt the current healthcare industry in innumerable practices such as supply chain management in pharmaceuticals to prevent the counterfeited medicine, clinical trials to guarantee transparency, healthcare information exchanges or personal health record systems to ensure data integrity and interoperability, etc. It will surely revolutionize the way the current healthcare system works; from provider-oriented to patient-centered. Hence, it is time to seriously consider how we could be a part of this blockchain revolution in dentistry.
Clinical Medicine ; Delivery of Health Care ; Dentistry ; Health Care Sector ; Health Records, Personal ; Information Systems ; Politics

BACKGROUND: This study aims to conduct curriculum analysis on health management schools focusing on relationship with licence and certification in Republic of Korea. METHODS: Possible employment field, licence and certification as well as curriculum were collected from the home page of 30 health management schools. The subjects and credits of curriculum were analyzed using descriptive statistics. Main subjects by areas were drew using categorization and ranking within qualitative methods. Comparative analysis was conducted for checking relationship between main subject and possible employment field, licence and certification. RESULTS: First, major employment fields after graduation were public health officer, general hospital and clinic, and National Health Insurance Service. Possible licence and certificate were hospital administrator, medical recorder, health education specialist, and medical insurance specialist. Second, total graduate credits were 133.9 including 79.0 for major education, 30.5 for of general education, and 30.5 for elective courses. Third, main subjects were reviewed by areas including basic medicine, health management, hospital business & management, medical records & information, insurance billing & assessment, healthcare marketing & tourism, and health education. There were highest number of subjects on health education area among 8 categories. By subjects, many health management schools open health law, medical terminology, introduction to public health, and biostatistics. Relationship between main subjects and possible employment field, licence and certification in health management schools was strong. CONCLUSION: It is necessary to review curriculum and for improving educational quality in health management schools. Also, development of curriculum standards for courses in health administration and introduction of accreditation system can be considered.
Accreditation ; Biostatistics ; Certification ; Commerce ; Curriculum ; Education ; Employment ; Health Care Sector ; Health Education ; Hospital Administrators ; Hospitals, General ; Humans ; Insurance ; Jurisprudence ; Medical Records ; National Health Programs ; Public Health ; Republic of Korea ; Specialization

In 1994 Korea government began to develop the healthcare industry, since then the government has tried to create opportunities to promote the industry through various political efforts and policies. The biggest achievement was attracting foreign patients from 2009 to 2016 with a cumulative 1.56 million and total revenue of 3 trillion won. But Korea still loses the opportunity to become a global leader in the health care industry due to regulations and various ideological disputes. Accordingly, it is necessary to facilitate policy understanding and present a practical road map so that Korea's healthcare industry become a new growth engine that will lead the trend of global market in the future. It also suggests a national economic development paradigm, the health economy as health and economic value are rotated through a shift in view of health care. At this point, 20 years after the beginning of the healthcare industry development, it is necessary to evaluate the related policies and discuss effective future directions. In this sense, the purpose of this study is to examine the policies and limitations of the healthcare industry by each government division, and based on it, to propose political tasks for the future.
Delivery of Health Care ; Dissent and Disputes ; Economic Development ; Health Care Sector ; Humans ; Internationality ; Korea ; Social Control, Formal

BACKGROUND: Numerous studies have shown that healthcare professionals are exposed to psychological distress. However, since most of these studies assessed psychological distress using self-reporting questionnaires, the magnitude of the problem is largely unknown. We evaluated the risks of mood disorders, anxiety disorders, sleep disorders, and any psychiatric disorders in workers in healthcare industry using Korea National Health Insurance (NHI) claims data from 2014, which are based on actual diagnoses instead of self-evaluation. METHODS: We used Korea 2014 NHI claims data and classified employees as workers in the healthcare industry, based on companies in the NHI database that were registered with hospitals, clinics, public healthcare, and other medical services. To estimate the standardized prevalence of the selected mental health disorders, we calculated the prevalence of diseases in each age group and sex using the age distribution of the Korea population. To compare the risk of selected mental disorders among workers in the healthcare industry with those in other industries, we considered age, sex, and income quartile characteristics and conducted propensity scored matching. RESULTS: In the matching study, workers in healthcare industry had higher odds ratios for mood disorders (1.13, 95% CI: 1.11–1.15), anxiety disorders (1.15, 95% CI: 1.13–1.17), sleep disorders (2.21, 95% CI: 2.18–2.24), and any psychiatric disorders (1.44, 95% CI: 1.43–1.46) than the reference group did. Among workers in healthcare industry, females had higher prevalence of psychiatric disorders than males, but the odds ratios for psychiatric disorders, compared to the reference group, were higher in male workers in healthcare industry than in females. CONCLUSIONS: The prevalence of mood disorders, anxiety disorders, sleep disorders, and all psychiatric disorders for workers in the healthcare industry was higher than that of other Korean workers. The strikingly high prevalence of sleep disorders could be related to the frequent night-shifts in these professions. The high prevalence of mental health problems among workers in healthcare industry is alarming and requires prompt action to protect the health of the “protectors.”
Age Distribution ; Anxiety Disorders ; Delivery of Health Care ; Diagnosis ; Diagnostic Self Evaluation ; Female ; Health Care Sector ; Humans ; Korea ; Male ; Mental Disorders ; Mental Health ; Mood Disorders ; National Health Programs ; Odds Ratio ; Prevalence ; Sleep Wake Disorders

The Korean society is rapidly aging and the health care needs for aged people are increasing. In this context, some physicians claim to establish new medical specialty board (MSB) for geriatric medical experts but also MSB for primary medical care specialists, clinical pharmacologists, and public health experts. In Korea, basic concept for the specialty board system is still under debates and the legal support for the system is poor. At present, doctors with MSBs in private sectors supply 92.4% of primary medical care but the National Health Care System requires more primary care physicians than specialists in Korea. Therefore, the government must invest in the education of doctors more to improve the public health care system. The proposal of the new MSB for geriatric medicine must be gradually developed according to the national long-term health plan, social needs, and national budget for the public benefit. Please stop discussing unprepared new MSBs.
Aging ; Budgets ; Delivery of Health Care ; Education ; Humans ; Korea ; Physicians, Primary Care ; Private Sector ; Public Health ; Specialization ; Specialty Boards*