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Digital health, which includes digital care programs, is the convergence of digital technologies with health, healthcare, living, and society to enhance the efficiency of healthcare delivery and make medicine more personalized and precise. The discipline involves the use of information and communication technologies to help address the health problems and challenges faced by people under treatment. These technologies include both hardware and software solutions and services, including telemedicine, web-based analysis, email, mobile phones and applications, text messages, wearable devices, and clinic or remote monitoring sensors. Generally, digital health is concerned about the development of interconnected health systems to improve the use of computational technologies, smart devices, computational analysis techniques, and communication media to aid healthcare professionals and their clients manage illnesses and health risks, as well as promote health and wellbeing. Although digital health platforms hold a number of possible benefits, 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. 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.

Technologies
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.

Telemedicine
Telemedicine is one 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 has proven to be very successful. 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
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.

Others
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.

The ownership of health data issue
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.

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.

Institutional Ageism
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.

Exacerbated Existing Social Inequalities or Lack of Digital Literacy
19 million people in the US do not have reliable connectivity access. Worldwide, the UN estimates that 3.8 billion people are offline. Those in rural communities and with lower levels of education lack significant barriers, like lack of reliable broadband and 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

Unintended Rise of Bio-Surveillance State
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. In South Korea for instance, the government strictly tracks the smartphone location of those who have been infected to make sure they obey quarantine guidelines. Programs like this are being implemented across the world in countries such as Italy, China , Poland, and more. Although beneficial in combating spread, critics worry about the potential loss of civil liberties associated with individuals handing over their private health data to government entities, and whether these “reduced regulations” will stay in place in a post-pandemic world.

Lack of Existing Regulation
The COVID-19 Pandemic has brought to light the lack of existing regulation that exists in the digital health space. When looking at Electronic Health Record platforms (EHR), the Health Insurance Portability and Accountability Act (HIPPA) of 1996 was the first comprehensive framework that aimed to protect the personal data of patients. It was recently amended in 2009 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 HIPPA. 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 HIPPA 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.