This article needs additional citations for verification. (December 2017)
Digital health is a discipline that includes digital care programs, technologies with health, healthcare, living, and society to enhance the efficiency of healthcare delivery and to make medicine more personalized and precise. It uses information and communication technologies to facilitate understanding of health problems and challenges faced by people receiving medical treatment and social prescribing in more personalised and precise ways. The definitions of digital health and its remits overlap in many ways with those of health and medical informatics.
Worldwide adoption of electronic medical records has been on the rise since 1990 and is closely correlated with the existence of universal health care. Digital health is a multi-disciplinary domain involving many stakeholders, including clinicians, researchers and scientists with a wide range of expertise in healthcare, engineering, social sciences, public health, health economics and data management.
Digital health technologies include both hardware and software solutions and services, including telemedicine, wearable devices, augmented reality, and virtual reality. Generally, digital health interconnects health systems to improve the use of computational technologies, smart devices, computational analysis techniques, and communication media to aid healthcare professionals and their patients manage illnesses and health risks, as well as promote health and wellbeing.
Although digital health platforms enable rapid and inexpensive communications, critics warn against potential privacy violations of personal health data and the role digital health could play in increasing the health and digital divide between social majority and minority groups, possibly leading to mistrust and hesitancy to use digital health systems.
The prominence of Digital health in the past century has culminated for the emergence of three reasons, stated by both Professor John Powell and Professor Theodoros N Arvanitis "the development of new technologies... and also trends towards smart, wearable and pervasive technologies; the need for health services to find new approaches to addressing the demands of an ageing population... and the role of the empowered patient and the shift in models of health service delivery towards patient-centred care, and patient-led care." These three points have directed and motivated the rise in the elements that play a crucial role in the creation of Digital health care services.
Primary Care Services
The first group of these services is known as primary care services in the domain of digital health. These services include wireless medical devices that utilize technology such as Wi-Fi or Bluetooth, as well as applications on mobile devices that encourage the betterment of an individual's health as well as applications that promote overall general wellness. For example, researchers developed a digital service to help elderly people with balance disorder and risk of falling. As prominent sociologist Deborah Lupton states, "Health promoters have experimented with using text messages, social media sites and apps to disseminate information about preventive health, collect data about people's health-related behaviours and attempt to ‘nudge’ members of target groups to change their behaviour in the interests of their health." In other words, Lupton states that various media technologies that can be found on mobile devices are being utilized to try and better certain groups' behaviors in concern with digital health.
Acute Care Services
The second group of these services is known as acute care in the digital health domain. These services include telemedicine which is defined as handling patients over some sort of streaming device and is targeted towards areas where the population is more widely scattered, medical devices that incorporate different aspects of software otherwise known as SaMD, and examples of these devices are pacemakers. The final example of acute care services is the 'interoperability' of 'Health IT, Cybersecurity, and Medical Devices', Health IT is how the electronic database stores, processes, and analyses personal health information and how this information can be utilized by medical personnel and organizations around the world of easier access of information, Cybersecurity which then plays into the storing of personal health information in how this information is secured and protected in the interest of personal safety of the individuals who's information is being stored, and Medical Devices that are able to communicate within each other to better care for a patient by transmitting what needs to be done on one machine to another. Sociologist Deborah Lupton states "However, members of some social groups are currently excluded from full participation in the digital health ecosystem. Mechanisms for facilitating further consultation between the various stakeholders involved in digital health, including patients and carers, need to be established. The rights and responsibilities of the different stakeholders involved in connected digital health also need to be better identified and highlighted. At the same time, personal data privacy and security need protection." Lupton concludes that despite the innovation of various elements in this digital health area, there are still multiple issues that need to be organized and dealt with for the continuation of the revolution of Digital Health.
Other Digital Health Elements
The rest of the elements of Digital health that do not fall so squarely into acute or primary care services are listed as the transmission of medical education and information between practitioners and researchers through the utilization of digital technologies and applications that can be employed by doctors for risk-assessment regarding patients. Devices that can be utilized for the improvement and management of bodily purposes as well as the encouragement of the education of digital health to the public. There are also patient-based applications that can be utilized to share information by individual patients as well as encourage the usage of drug trials. The tracking of outbreaks of disease by the use of mass media that social media has developed has also come about through Digital Health. Finally the recording of the environment around sensor devices that are being utilized for the betterment of the community.
This section needs additional citations for verification. (March 2019)
Digital health technologies come in many different forms and extend into various parts of healthcare. As new technologies develop, digital health, as a field, respectively transforms. The three most popular domains of digital health technologies include telemedicine, wearable technologies, and augmented and virtual reality. Telemedicine is how physicians treat patients remotely and the different technologies needed to make the process more efficient and faster. The other main side of digital health is data collection and how to provide on-demand medical information for patients, which gave rise to wearables. Wearable technologies hold the promise of bringing personalized data and health-related tracking to all users. In terms of digitized treatment, augmented and virtual reality can create personalized regimens for patients that can be repeated and tailored to treat many conditions.
In fact some of these technologies are being propelled by the startup space, which has been followed via Internet or online media sources such as podcasts on digital health entrepreneurs. The National Institute for Health and Care Research (NIHR) has published a review of research on how digital health technologies can help manage health conditions.
Telemedicine is one of the broadest areas of digital health. It encompasses the digitization of medical records, remote care, appointment booking, self-symptom checkers, patient outcome reporting, and many others. Digital and remote clinics are commonly used to provide quick, nonurgent consultations that save both the patients and doctors time. Especially with the COVID-19 pandemic, this type of treatment has become the primary way doctors are seeing their patients and may be as effective as face to face appointments. This type of digital treatment keeps both parties safe and is a reliable method that physicians plan to use for routine checks even after the pandemic ends.
Telemedicine also covers online health records, where both patients and doctors have access to the relevant information at all times. All this digital information means that patient data is accessible to healthcare professions and can be analyzed to create better and smarter treatment plans. This paves the path for a more personalized healthcare system, which can help patients better understand their conditions and could result in more positive outcomes.
Wearable technology comes in many forms, including smartwatches and on-body sensors. Smartwatches were one of the first wearable devices that promoted self-monitoring and were typically associated with fitness tracking. Many record health-related data, such as "body mass index, calories burnt, heart rate, physical activity patterns". Beyond smartwatches, researchers are developing smart-related bodywear, like patches, clothes, and accessories, to administer "on-demand drug release". This technology can expand into smart implants for both severe and non-severe medical cases, where doctors will be able to create better, dynamic treatment protocols that would not have been possible without such mobile technology.
These technologies are used to gather data on patients at all times during the day. Since doctors no longer need to have their patients come into the office to collect the necessary data, the data can lead to better treatment plans and patient monitoring. Doctors will have better knowledge into how well a certain medication is performing. They will also be able to continuously learn from this data and improve upon their original treatment plans to intervene when needed.
Augmented and virtual reality
In digital health, augmented reality technology enhances real-world experiences with computerized sensory information and is used to build smart devices for healthcare professionals. Since the majority of patient-related information now comes from hand-held devices, smart glasses provide a new, hands-free augmented way for a doctor to view their patient's medical history. The applications of this technology can extend into data-driven diagnosis, augmented patient documentation, or even enhanced treatment plans, all by wearing a pair of smart glasses when treating a patient.
Another similar technology space is virtual reality, which creates interactive simulations that mimic real-life scenarios and can be tailored for personalized treatments. Many stroke victims lose range of motion and under standard treatment protocols; 55% to 75% of patients have long-term upper muscular dysfunction, as the lower body is primarily targeted during therapy. Repeated actions and the length of therapy are the two main factors that show positive progress towards recovery. Virtual reality technologies can create various 3D environments that are difficult to replace in real-life but are necessary to help patients retrain their motor movements. These simulations can not only target specific body parts, but can also increase in intensity as the patient improves and requires more challenging tasks.
Some other technologies include Assistive technologies, rehabilitation robotics, and unobtrusive monitoring sensors that can help people with disabilities perform their daily tasks independently. Computational simulations, modeling, and machine learning (e.g. FG-AI4H) approaches can model health-related outcomes. These advanced simulations are able to be repeated, replicated, and tailored to any research area. In medical imaging, the applications for this technology helps healthcare professionals visualize genes, brain structures, and many other components of human anatomy. The flexibility in this technology also allows for more positive and accurate results. Mobile health (or mhealth) is the practice of medicine and public health supported by mobile devices.
Health systems engineering is another subset of digital health that leverages other engineering industries to improve upon applications include knowledge discovery, decision making, optimization, human factors engineering, quality engineering, and information technology and communication. Speech and hearing systems for natural language processing, speech recognition techniques, and medical devices can aid in speech and hearing (e.g. cochlear implants). Digital hearing aids use various algorithms to reduce background noises and improve perceptual performance, which is a significant improvement from regular hearing implants.
National electronic health record (EHR) systems National digital programs exist to support healthcare, form meaningful indicators, and facilitate population-based studies by providing clinically procured data in an open-source and standardized digital format. These can inform public health decisions, which are especially crucial in low-resource settings. The World Health Organization's Global Observatory for eHealth (GOe) conducts and reports a worldwide survey of its 194 member nations on their progress towards EHR implementation as well as universal healthcare coverage. In their latest issue in 2015, 73 Members (58%) responded with having some eHealth strategy in place, a count that has increased since 1990. Within this cohort, high-income countries are overrepresented, as well as the majority are countries with universal health care (UHC).
National digital programs exist to support healthcare, such as those of Canada Health Infoway built on core systems of patient and provider registries, clinical and diagnostic imaging systems, clinical reports and immunizations. By 2014, 75% of Canadian physicians were using electronic medical records.
In Uganda and Mozambique, partnerships between patients with cell phones, local and regional governments, technologists, non-governmental organizations, academia, and industry have enabled mHealth solutions.
In the United Kingdom, the National Health Service (NHS) has commissioned a report on how to integrate digital healthcare technologies into the next generation of medicine. The "Topol Review" recommended an expansion of education for both patients and providers of next-generation technologies such as Whole Genome Sequencing, and has also created Digital Fellowships for health professionals. The United States has also embarked on a nationwide health study known as 'All of Us" to bring together a variety of health indicators in a digital format for researchers around the world.
On the other hand, the implementation of these innovations has also brought to light societal risks and regulatory needs, which are certainly challenging the current governance structures in the health sector.
The innovation process for digital health is an iterative cycle for technological solutions that can be classified into five main activity processes from the identification of the healthcare problem, research, digital solution, and evaluating the solution, to implementation in working clinical practices. Digital health may incorporate methods and tools adopted by software engineering, such as design thinking and agile software development. These commonly follow a user-centered approach to design, which are evaluated by subject-matter experts in their daily life using real-world data.
U.S. Food and Drug Administration
In 2019, the FDA published a Digital Health Innovation Action Plan that would reduce inefficiencies for physicians in an effort to cut overhead costs, improve access, increase quality of service, and make medicine more easily adapted for each person. Topics within the innovation plan are wireless devices, telemedicine, software, and cybersecurity, among others. According to FDA guidelines, if you release an app designed to help someone with a medical condition then that is considered a medical device. The FDA cannot regulate all healthcare apps, so they use "enforcement discretion", and up until 2020, have chosen not to regulate all digital care programs and apps. However, programs that use the word treatment, seek to diagnose or treat a condition, or are deemed unsafe, are and will be regulated by the FDA. During the COVID-19 pandemic, regulations and enforcement of digital psychiatry apps were relaxed to facilitate use and reduce in-person contact.
At an intergovernmental level, the World Health Organization is the United Nations Specialized Agency for health, and the International Telecommunication Union is the UN Specialized Agency for ICTs, the Agencies collaborate in their work on digital health, such as the H.870 standard on safe listening, as well as the ITU-WHO Focus Group on Artificial Intelligence for Health, a subsidiary of the ITU-T Study Group 16.
In traditional healthcare, doctors conducted medical practices with a limited number of tools, and got more experienced over time. Since becoming a doctor required experience and knowledge, very few took up the profession. The lack of communication between people in different places caused new technology to spread slowly. Since doctors were seen as experts in their fields, patients would have very little decision on how they were treated. Although there's been an extensive change in technology, the current health care system doesn't reflect on the changes in treatments. During the 2010s, healthcare knowledge continued to grow rapidly, and patients began to get frustrated due to the vast knowledge out there that physicians didn't know or use. The number of and the cost to treat chronic illnesses increased, and the World Health Organization estimated that there was a worldwide shortage of 4.3 million healthcare workers. During the transition from traditional healthcare to digital health, the amount of access to high quality health technology and medical records and studies increased. The transition also gave patients the option of self-care because not only did it change the technology accessible to patients, but also the patients' ability to choose their way of treatment. Although this new way of treatment has given patients a role in treatment, it has led to difficulty with patients choosing the best treatment options. According to the article, Digital Health is a Cultural Transformation of Traditional Healthcare from the National Library of Medicine, "The success of providing care depends on collaboration, empathy and shared decision making. What is needed for this is a newly defined co-operation between patients and their caregivers." In this quote, health care experts explain that they need to collaborate with patients and respect their decisions in choosing treatment options for them. The article then explains how a strong relationship between physicians and patients help influence what treatment options they choose, and how empathy is an important characteristic for physicians to have.
In May 2018, the World Health Organization passed a global strategy for digital health. There were four major goals for the strategy. The first goal was for nations and companies to collaborate more in making new treatments and technology. Two other main goals for the strategy were to increase the implementation of national strategies towards digital health, and to increase authority over digital health from global to national levels. The World Health Organization also made guidelines in regulating certifying digital health medical devices similar to how medicine and vaccines are tested. The strategy was also made to list health data as a public health good, and made an outline for how research and data are shared, and how Artificial Intelligence is used. It even endorsed people-centered health systems that used digital health. While the World Health Organization was pushing their strategy, other groups are also developing strategies to make digital health more available in communities that don't have it.
Before this strategy was published, the World Health Organization made a plan around the beginning of 2015 to use digital health to end Tuberculosis. The following reasons why this strategy was passed included how health care managers didn't have the resources for prevention of Tuberculosis. There was a need for a step to step plan to include digital health for the End TB Strategy. The plan would also give opportunity to improve health care technology and increase efficiency and sustainability of efforts. The plan focused on treating and preventing tuberculosis, and giving treatment options for patients suffering from Tuberculosis from national to international levels. the following steps included functional laboratory information included using digital technologies to diagnose patients, providing secure data transmission and storage, and using data to store patients' results. Some of the technologies used in the campaign were Video Treatment Support, and eHealth Portal.
Digital healthcare presents a wide range of complex and sometimes novel regulatory challenges, including questions about how to balance public interest concerns against an individual's right to privacy as well as the risks of 'pseudo-experts' providing medical advice. Meanwhile, the explosion in the number of uses and applications seen during the COVID-19 pandemic has also brought to light the limitations of existing legislation and other regulatory tools to grapple with these concerns (or, in some cases, been enabled by changes in legislation that groups such as the Varieties of Democracy have argued have produced a 'pandemic backslide' in human rights protections).
Ownership of health data
At a global level, the implementation of digital health solutions depends on large data sets, ranging from simple statistics that record every birth and death to more sophisticated metrics that track diseases, outbreaks, and chronic conditions. These systems record data such as patient records, blood test results, EKGs, MRIs, billing records, drug prescriptions, and other private medical information. Medical professionals can use this data to make more data-driven decisions about patient care and consumers themselves can utilize it to make informed choices about their own health. Given the personal nature of the data being collected, a crucial debate has arisen amongst stake-holders about one of the challenges induced by digital health solutions: the ownership of health data. In most cases, governments and big data and technology companies are storing citizens' medical information, leaving many concerned with how their data is being used and/or who has access to it. This is further compounded by the fact that the details that answer these questions is oftentimes hidden in complex terms & conditions that are rarely read. A notable example of a data privacy breach in the digital health space took place in 2016. Google faced a major lawsuit over a data-sharing agreement that gave its artificial intelligence arm, DeepMind, access to the personal health data of 1.6 million British patients. Google failed to secure patient consent and guarantee the anonymity of the patients. Another concept is that data is considered as a form of public good. Researchers from Stanford University proposed the use of such a framework, to think about data and the development of AI; they were thinking about radiology data specifically. They concluded that clinical data should be a form of public good, used for the benefit of future patients and that the data should be widely available for the development of knowledge and tools to benefit future patients. From this, they drew three main conclusions. Firstly, if the clinical data is really not owned by anyone, those who interact with it then have an obligation to ensure that the data is used for the benefit of future patients in societies. Secondly, this data should be widely shared for research and development, and all the individuals and entities with access to that data, then essentially become stewards of that data and become responsible to carefully safeguard the privacy and to ensure that the data is used for developing knowledge and tools for the good. Thirdly, patient consent wouldn’t necessarily be required before the data is used for secondary purposes, such as AI development and training and testing, as long as there are mechanisms in place to ensure that ethical standards are being followed. According to this proposed framework, the authors propose that it would be unethical to sell data to the third parties by granting exclusive access in exchange for monetary or any kind of payments that exceed costs.
Misinterpretation of data
Although the data and information provided by personalized health platforms may give reassurance to users, they might simultaneously induce increased anxiety and obsessive behavior. As seen with platforms like WebMD, the misinterpretation of data can further contribute to patient hysteria: having increased access to information on oneself is not always positive. In an extreme scenario, patients might feel a misplaced sense of security knowing that they have this access, meaning that they won't seek medical advice or help from professionals, even if it may be needed.
Ageism is defined as the process of systemic discrimination against the elderly. As digital health becomes more prevalent in our society, those who lack strong digital skills and the technical know-how needed to navigate these platforms will be put at a disadvantage. This doesn't just apply to current seniors. New digital technologies become popularized every year rendering older technology obsolete. This means that this digital divide will always be present, unless health companies actively work to try to minimize this gap. Not to mention, seniors are more prone to chronic health issues, meaning that they are one of the groups that has the greatest need for a digital health platform. They represent an untapped user group.
Worldwide, the UN estimates that 3.8 billion people are offline and even in the US, 19 million people do not have reliable connectivity access. Other barriers to access include a lack of basic digital literacy required to use many digital health platforms. As a result, the already existing health gap between low-income and high-income populations may become further exacerbated by up and coming health technologies. To be effective, digital health solutions must foster the development of health literacy skills amongst platform users to make sure that the technology is used as intended
In the age of the COVID-19 pandemic, the use of digital health platforms as a means to contain the spread of the disease has been accelerated worldwide. Governments in many economies, including South Korea, Taiwan, India, Italy, Poland, and China, have implemented strict digital track and trace systems to both identify those infected with COVID-19 and to ensure that they obey quarantine guidelines.
Although some studies (such as one by the Asian Development Bank) have suggests that such programs have been beneficial in combating spread, some critics worry have continued to express strong concerns about the potential loss of civil liberties associated with individuals handing over their private health data to government entities; this includes whether new or emergency regulations will stay in place in a post-pandemic world.
Additional Legal and Regulatory Issues
In the United States, the Health Insurance Portability and Accountability Act (HIPAA) of 1996 was the first comprehensive framework that aimed to protect the personal data of patients. In 2009, it was amended with the Health Information Technology for Economic and Clinical Health (HITECH) Act which seeks to examine personal health data privacy laws through the lens of the private sector and increase enforcement of HIPAA. Critics of these acts claim that they don't go far enough as there are still around 600,000 types of businesses that can access patient data without explicit consent. Not to mention, there are extensive reports proving that HIPAA regulations are constantly violated, making some wonder whether the government even has the capacity to enforce the laws that they put in place. With major companies like Facebook and Apple moving into digital health, critics question whether existing regulations are comprehensive enough.
Electronic Medical Records (EMRs)
Technology has also started to become involved in the medical field. One of the most used E-health applications worldwide is electronic medical records (EMRs). Electronic medical records have multiple functions in the medical field. Some of the functions include but are not limited to documentation, communication, and management of patient data. Electronic medical records are the technological replacement for paper-based documentation, which is not only labor intensive but also repetitive, inaccurate at times, and can consume a lot of time. Electronic health records (EHRs) are another E-health application used by physicians. However, despite the many similarities in both health applications, they are not the same. The main difference between the two is that EHRs have an additional feature which includes the ability to share the data for multiple authorized physicians.
Due to the initial gap between the expectations and performances of electronic medical records, they are frowned upon by clinicians. The initial failures have shaped physicians' perceptions of EMR. Therefore before considering adopting the EMRs in the medical field, the quality of the information system has to be accounted for. Physicians that use the EMRs have a different view of how effective this new technology is and most of this has to do with age. Younger primary care physicians (PCP) find the technology easier to use as they have more knowledge about technology, therefore were inclined to use EMRs than older physicians with less knowledge of technology. Electronic medical records still have positive and negative implications for the medical field. Some of the positives of the EMRs in the medical field include the accuracy of results by both minimalizing the errors that used to occur as well as having more complete records. This leads to having a better quality of healthcare for patients because the guidelines are better followed. Not only that, but the efficiency of the work also increases because not only can the data be shared more readily, but also the time required to work on the medical records is less. However, there is contrary information which is that when it comes to data management and communication function, EMRs are less effective. Another positive is that there is better privacy for the records as they are harder to access by non-authoritative personnel. However, all these benefits are debatable because there is no tangible evidence that there has been an improvement in the quality of the work being performed by primary care physicians.
There are also negative consequences of using electronic medical records. Firstly, the place where the EMRs are being implemented would have to be financially capable as there is a very high cost of implementation. Additionally, the systems that are being used at the location would have to be modified so that the EMRs would be relevant and useful to the location. This implementation of EMRs would not be possible at locations that lack the resources to instruct physicians in charge of using the new E-health applications, especially in smaller or solo clinics. Not only that, but EMRs also are unable to factor in the social and psychological aspects of a patient into the record. To better understand how EMRs would compare with paper-based records in a hospital setting, a study was conducted between two hospitals and each of the hospitals adopted one of the methods. The results were that the quality of healthcare service in the hospital that had adopted the usage of EMRs was better than the other hospital. The quality of health care services is defined by how health results are improved. Multiple factors play a role in quality enhancement. Some factors are regarding the interaction between the patient and physician. For example, whether the patient gets assurance from the responses given by the physician.
Burden on healthcare providers' well-being
The integration of digital health has brought about considerable challenges for healthcare providers, and some physicians are highly critical of the utility of EMRs for patient care, and point to their rising use as a significant component in physician burnout.  Other negative experiences and challenges encompass frustrations stemming from communication problems, reduced physician-patient interaction, inadequate resources, increased workloads, system complexity, difficulties in accessing information within Electronic Health Records (EHRs), and limited access to web-based information stored in digital systems. Additionally, clinicians often find themselves overwhelmed by the sheer volume of data and alerts generated by digital tools, which can hinder patient-centered care. In this digital healthcare landscape, emerging fears are prevalent, including the fear of change and potential job replacement, the fear of forgetting crucial patient information, and the fear of misinterpreting patient data. These fears contribute to increased stress and anxiety when new technologies are adopted. Furthermore, a sense of confusion is reported by some clinicians, stemming from a conflict between digital tools and their professional identity. This conflict revolves around concerns related to work visibility and perceived threats to professional autonomy. 
- Fadahunsi KP, O'Connor S, Akinlua JT, Wark PA, Gallagher J, Carroll C, et al. (May 2021). "Information Quality Frameworks for Digital Health Technologies: Systematic Review". Journal of Medical Internet Research. 23 (5): e23479. doi:10.2196/23479. PMC 8167621. PMID 33835034.
- Fadahunsi KP, Akinlua JT, O'Connor S, Wark PA, Gallagher J, Carroll C, et al. (March 2019). "Protocol for a systematic review and qualitative synthesis of information quality frameworks in eHealth". BMJ Open. 9 (3): e024722. doi:10.1136/bmjopen-2018-024722. PMC 6429947. PMID 30842114.
- Chen CE, Harrington RA, Desai SA, Mahaffey KW, Turakhia MP (June 2019). "Characteristics of Digital Health Studies Registered in ClinicalTrials.gov". JAMA Internal Medicine. 179 (6): 838–840. doi:10.1001/jamainternmed.2018.7235. PMC 6547144. PMID 30801617.
- Bhavnani SP, Narula J, Sengupta PP (May 2016). "Mobile technology and the digitization of healthcare". European Heart Journal. 37 (18): 1428–38. doi:10.1093/eurheartj/ehv770. PMC 4914890. PMID 26873093.
- "WHO | Global diffusion of eHealth: Making universal health coverage achievable". WHO. Archived from the original on 29 December 2016. Retrieved 5 November 2020.
- O'Donoghue J, Herbert J (1 October 2012). "Data Management within mHealth Environments: Patient Sensors, Mobile Devices, and Databases". Journal of Data and Information Quality. 4 (1): 1–20. doi:10.1145/2378016.2378021. S2CID 2318649.
- Widmer RJ, Collins NM, Collins CS, West CP, Lerman LO, Lerman A (April 2015). "Digital health interventions for the prevention of cardiovascular disease: a systematic review and meta-analysis". Mayo Clinic Proceedings. 90 (4): 469–80. doi:10.1016/j.mayocp.2014.12.026. PMC 4551455. PMID 25841251.
- "Digital health". US Food and Drug Administration. 19 July 2019. Retrieved 23 September 2019.
- Mclaughlin M, Delaney T, Hall A, Byaruhanga J, Mackie P, Grady A, et al. (February 2021). "Associations Between Digital Health Intervention Engagement, Physical Activity, and Sedentary Behavior: Systematic Review and Meta-analysis". Journal of Medical Internet Research. 23 (2): e23180. doi:10.2196/23180. PMC 8011420. PMID 33605897.
- Donkin L, Christensen H, Naismith SL, Neal B, Hickie IB, Glozier N (August 2011). "A systematic review of the impact of adherence on the effectiveness of e-therapies". Journal of Medical Internet Research. 13 (3): e52. doi:10.2196/jmir.1772. PMC 3222162. PMID 21821503.
- "What is digital health technology and what can it do for me?". NIHR Evidence. 2022. doi:10.3310/nihrevidence_53447. S2CID 252584020.
- Powell J, Arvanitis TN (1 January 2015). "Welcome to the Digital Health revolution". Digital Health. 1: 2055207614561571. doi:10.1177/2055207614561571. PMC 5999059. PMID 29942537.
- "Essential Components of an Effective Digital Health Initiative". Northeastern University Graduate Programs. 4 September 2018. Retrieved 17 October 2022.
- Gaspar AG, Lapão LV (February 2022). "A Digital Health Service for Elderly People with Balance Disorders and Risk of Falling: A Design Science Approach". International Journal of Environmental Research and Public Health. 19 (3): 1855. doi:10.3390/ijerph19031855. PMC 8835704. PMID 35162877.
- Lupton D (4 December 2014). "Critical Perspectives on Digital Health Technologies: Digital Health Technologies". Sociology Compass. 8 (12): 1344–1359. doi:10.1111/soc4.12226.
- Lupton D (9 November 2017). "Digital health now and in the future: Findings from a participatory design stakeholder workshop". Digital Health. 3: 2055207617740018. doi:10.1177/2055207617740018. PMC 6001191. PMID 29942616.
- El-Miedany Y (1 January 2017). "Telehealth and telemedicine: how the digital era is changing standard health care". Smart Homecare Technology and TeleHealth. 4: 43–52. doi:10.2147/SHTT.S116009.
- Amft O (January 2018). "How Wearable Computing Is Shaping Digital Health". IEEE Pervasive Computing. 17 (1): 92–98. doi:10.1109/MPRV.2018.011591067. ISSN 1558-2590. S2CID 3921043.
- Merians AS, Jack D, Boian R, Tremaine M, Burdea GC, Adamovich SV, et al. (September 2002). "Virtual reality-augmented rehabilitation for patients following stroke". Physical Therapy. 82 (9): 898–915. doi:10.1093/ptj/82.9.898. PMID 12201804.
- Monaghesh E, Hajizadeh A (August 2020). "The role of telehealth during COVID-19 outbreak: a systematic review based on current evidence". BMC Public Health. 20 (1): 1193. doi:10.1186/s12889-020-09301-4. PMC 7395209. PMID 32738884.
- Byaruhanga J, Atorkey P, McLaughlin M, Brown A, Byrnes E, Paul C, et al. (September 2020). "Effectiveness of Individual Real-Time Video Counseling on Smoking, Nutrition, Alcohol, Physical Activity, and Obesity Health Risks: Systematic Review". Journal of Medical Internet Research. 22 (9): e18621. doi:10.2196/18621. PMC 7519427. PMID 32915156.
- Rich E, Miah A (2 January 2017). "Mobile, wearable and ingestible health technologies: towards a critical research agenda" (PDF). Health Sociology Review. 26 (1): 84–97. doi:10.1080/14461242.2016.1211486. ISSN 1446-1242. S2CID 151558809.
- Klinker K, Wiesche M, Krcmar H (25 June 2019). "Digital Transformation in Health Care: Augmented Reality for Hands-Free Service Innovation". Information Systems Frontiers. 22 (6): 1419–1431. doi:10.1007/s10796-019-09937-7. ISSN 1572-9419. S2CID 195330313.
- Chang V (November 2017). "Computational Intelligence for Medical Imaging Simulations". Journal of Medical Systems. 42 (1): 10. doi:10.1007/s10916-017-0861-x. PMID 29177790. S2CID 13049464.
- Silva BM, Rodrigues JJ, de la Torre Díez I, López-Coronado M, Saleem K (August 2015). "Mobile-health: A review of current state in 2015". Journal of Biomedical Informatics. 56: 265–72. doi:10.1016/j.jbi.2015.06.003. PMID 26071682.
- Jiang T, Liang R, Wang Q, Bao Y (March 2018). "Speech Noise Reduction Algorithm in Digital Hearing Aids Based on an Improved Sub-band SNR Estimation". Circuits, Systems and Signal Processing. 37 (3): 1243–1267. doi:10.1007/s00034-017-0605-7. ISSN 0278-081X. S2CID 3484142.
- Fritz F, Tilahun B, Dugas M (March 2015). "Success criteria for electronic medical record implementations in low-resource settings: a systematic review". Journal of the American Medical Informatics Association. 22 (2): 479–88. doi:10.1093/jamia/ocu038. PMID 25769683.
- "Progress in Canada". Canada Health Infoway. 2016. Archived from the original on 12 November 2016. Retrieved 11 November 2016.
- Collier R (January 2015). "National Physician Survey: EMR use at 75%". CMAJ. 187 (1): E17–E18. doi:10.1503/cmaj.109-4957. PMC 4284187. PMID 25487665.
- Källander K, Tibenderana JK, Akpogheneta OJ, Strachan DL, Hill Z, ten Asbroek AH, et al. (January 2013). "Mobile health (mHealth) approaches and lessons for increased performance and retention of community health workers in low- and middle-income countries: a review". Journal of Medical Internet Research. 15 (1): e17. doi:10.2196/jmir.2130. PMC 3636306. PMID 23353680.
- "Topol review". Health Education England. 21 February 2018. Retrieved 8 March 2020.
- "The Topol Review". The Topol Review – NHS Health Education England. Retrieved 8 March 2020.
- "National Institutes of Health (NIH)". National Institutes of Health (NIH) — All of Us. 1 June 2020. Retrieved 12 May 2021.
- Plattner H, Schapranow MP, eds. (2013). High-Performance In-Memory Genome Data Analysis. Springer.
- Benjamin K, Potts HW (27 February 2018). "Digital transformation in government: Lessons for digital health?". Digital Health. 4: 2055207618759168. doi:10.1177/2055207618759168. PMC 6005404. PMID 29942624.
- FDA (26 September 2019). "Examples of Software Functions for Which the FDA Will Exercise Enforcement Discretion". U.S. Food and Drug Administration. Retrieved 8 June 2020.
- Center for Devices and Radiological Health (16 April 2020). "Enforcement Policy for Digital Health Devices For Treating Psychiatric Disorders During the Coronavirus Disease 2019 (COVID-19) Public Health Emergency". U.S. Food and Drug Administration. Retrieved 30 July 2020.
- Meskó B, Drobni Z, Bényei É, Gergely B, Győrffy Z (September 2017). "Digital health is a cultural transformation of traditional healthcare". mHealth. 3: 38. doi:10.21037/mhealth.2017.08.07. PMC 5682364. PMID 29184890.
- Mariano B (April 2020). "Towards a global strategy on digital health". Bulletin of the World Health Organization. 98 (4): 231–231A. doi:10.2471/blt.20.253955. PMC 7133480. PMID 32284641. S2CID 215746281.
- "Digital health for the end TB strategy: an agenda for action". World Health Organization & European Respiratory Society. Geneva: World Health Organization. 2015. hdl:10665/205222.
- Solove DJ (April 2013). "HIPAA turns 10". Journal of AHIMA. 84 (4): 22–8, quiz 29. PMID 23781600. SSRN 2245022.
- Edgell A, Lachapelle J, Lührmann A, Maerz SF, Grahn S, et al. (2020). "Pandemic Backsliding: Democracy During Covid-19 (PanDem), Version 6". Varieties of Democracy (V-Dem) Institute. University of Gothenburg. Archived from the original on 29 April 2020.
- Center for Devices and Radiological Health (22 September 2020). "What is Digital Health?". FDA.
- Torous J, Roberts LW (May 2017). "Needed Innovation in Digital Health and Smartphone Applications for Mental Health: Transparency and Trust". JAMA Psychiatry. 74 (5): 437–438. doi:10.1001/jamapsychiatry.2017.0262. PMID 28384700. S2CID 205144235.
- Sharon T (1 July 2018). "When digital health meets digital capitalism, how many common goods are at stake?". Big Data & Society. 5 (2): 2053951718819032. doi:10.1177/2053951718819032. ISSN 2053-9517. S2CID 150255521.
- Larson DB, Magnus DC, Lungren MP, Shah NH, Langlotz CP (June 2020). "Ethics of Using and Sharing Clinical Imaging Data for Artificial Intelligence: A Proposed Framework". Radiology. 295 (3): 675–682. doi:10.1148/radiol.2020192536. PMID 32208097. S2CID 214643087.
- Lupton D (2014). "Critical Perspectives on Digital Health Technologies". Sociology Compass. 8 (12): 1344–1359. doi:10.1111/soc4.12226. ISSN 1751-9020.
- Becker S, Miron-Shatz T, Schumacher N, Krocza J, Diamantidis C, Albrecht UV (May 2014). "mHealth 2.0: Experiences, Possibilities, and Perspectives". JMIR mHealth and uHealth. 2 (2): e24. doi:10.2196/mhealth.3328. PMC 4114478. PMID 25099752.
- Lloyd-Sherlock PG, Ebrahim S, McKee M, Prince MJ (August 2016). "Institutional ageism in global health policy". BMJ. 354: i4514. doi:10.1136/bmj.i4514. PMID 27582131. S2CID 41312322.
- "The Effect of Ageism on the Digital Divide Among Older Adults". heraldopenaccess.us. Retrieved 3 November 2020.
- Loader BD (13 January 2009). Loader B, Hardey M, Keeble L (eds.). Digital Welfare for the Third Age. doi:10.4324/9780203886533. ISBN 9780203886533.
- "Press Release". www.itu.int. Retrieved 3 November 2020.
- "Eighth Broadband Progress Report". Federal Communications Commission. 21 August 2012. Retrieved 3 November 2020.
- Dunn P, Hazzard E (October 2019). "Technology approaches to digital health literacy". International Journal of Cardiology. 293: 294–296. doi:10.1016/j.ijcard.2019.06.039. PMID 31350037. S2CID 196519877.
- "The rise of the bio-surveillance state". www.newstatesman.com. 25 March 2020. Retrieved 3 November 2020.
- "Coronavirus bio-surveillance around the globe". Big Think. 27 March 2020. Retrieved 3 November 2020.
- Gillispie, Clara. "How Can South Korea Teach, Lead, and Better Engage with the Asia-Pacific in Shaping Data Governance for the 5G Era?." Asia Policy 28.4 (2021): 143-166.
- Assessment of Covid-19 response in the republic of Korea (PDF). Manila, Philippines: Asian Development Bank. 2021. ISBN 978-92-9262-791-1.
- Gillispie C. South Korea's Digital Healthcare Conundrum. The Next Digital Decade (PDF). Konrad Adenauer Stiftung Singapore and Digital Asia Hub Hong Kong. ISBN 978-981-18-3493-6.]
- Miron-Scahtz T, Elwyn G (30 June 2011). "To serve and protect? Electronic health records pose challenges for privacy, autonomy and person-centered medicine". International Journal of Person Centered Medicine. 1 (2): 405–409. doi:10.5750/ijpcm.v1i2.84.
- Sharon T (July 2020). "Blind-sided by privacy? Digital contact tracing, the Apple/Google API and big tech's newfound role as global health policy makers". Ethics and Information Technology. 23 (Suppl 1): 45–57. doi:10.1007/s10676-020-09547-x. PMC 7368642. PMID 32837287.
- Ayaad, Omar; Alloubani, Aladeen; ALhajaa, Eyad Abu; Farhan, Mohammad; Abuseif, Sami; Al Hroub, Ahmad; Akhu-Zaheya, Laila (1 July 2019). "The role of electronic medical records in improving the quality of health care services: Comparative study". International Journal of Medical Informatics. 127: 63–67. doi:10.1016/j.ijmedinf.2019.04.014. ISSN 1386-5056. PMID 31128833. S2CID 145999064.
- "EHR vs. EMR: What's the Difference?". SimplePractice. Retrieved 14 March 2023.
- O’Donnell, Amy; Kaner, Eileen; Shaw, Caroline; Haighton, Catherine (13 November 2018). "Primary care physicians' attitudes to the adoption of electronic medical records: a systematic review and evidence synthesis using the clinical adoption framework". BMC Medical Informatics and Decision Making. 18 (1): 101. doi:10.1186/s12911-018-0703-x. ISSN 1472-6947. PMC 6234586. PMID 30424758.
- Daniel Essin MA (6 February 2012). "Improve EHR Systems by Rethinking Medical Billing". Physicians Practice. Retrieved 8 March 2020.
- Wosny M (17 October 2023). "Experience of Health Care Professionals Using Digital Tools in the Hospital: Qualitative Systematic Review". Journal of Medical Internet Research Human Factors. Retrieved 19 October 2023.