Opportunities and Drawbacks of Implementing Digital Technologies for Health
I had uploaded the downloadable documents in the reading list provided in the course (which had also been uploaded), and please make sure to use them and the case studies. Since the number of files had reached the maximum, and some links cannot be uploaded, I will send them to the writer later in the messages.
Please choose one of the following essay topics. The essay should be 2,000 words (excluding the list of references), should employ Harvard referencing and should maintain professional levels of style, spelling and punctuation. For all essay topics you must engage with relevant readings (essential and further readings) provided in the Managing Digital Work module. You can use examples and case studies discussed in lectures and workshops to illustrate your arguments.
Please note the following conditions that lead to automatic fail:
Lack of systematic use of relevant readings provided and discussed in the Managing Digital Work module.
Lack of use of references (lack of in-text citations and reference list in the end of the essay).
Lack of use of academic resources (journals, conference proceedings, books or book chapters).
Essay topics
Assess the opportunities and challenges of virtual project teams (VPTs) and reflect on leadership strategies that fit the virtual project environment.
Drawing upon the concept of open innovation and explain how crowdsourcing platforms can be utilised to facilitate innovation processes.
Provide an understanding of big data and discuss its role and value within business organisations.
Provide an understanding of digital health and discuss the opportunities and drawbacks of implementing digital technologies for health.
Here's a link to one reading in week 1
I attached the rest of the materials, and pasted the link of a reading from week 1, and also example essays.
Week 1 URL (Orlikowski):
https://dspace(dot)mit(dot)edu/bitstream/handle/1721.1/108411/Digital%20Work%20-%20A%20Research%20Agenda.pdf?sequence=1&isAllowed=y
Opportunities and Drawbacks of Implementing Digital Technologies for Health
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Opportunities and Drawbacks of Implementing Digital Technologies for Health
Introduction
While digital health is a rapidly advancing field of research, the underlying business models and data flow has remained poorly understood thus raising significant concerns about the public values at stake (Lupton, 2018a). Therefore, it is critical to investigate how novel ways of knowing through quantification of data and digital connections are implemented in the practice of digital health. Digital health is a collection of sociotechnical practices aimed at enabling access to health information, supporting individuals with chronic infections in self-care practices, facilitating the sharing of disease experiences, and empowering populations to practice healthy lifestyles (Lupton, 2018b). Advances in digital health have witnessed unprecedented growth in eHealth, telemedicine, mHealth, and algorithmic medicine (Marrent & Henwood, 2021). eHealth particularly involves sharing of health information and provides critical platforms where patients exchange disease experiences (Kivits, 2013). Telemedicine is a collection of information communication technologies (ICTs) that support distance care and doctor-to-patient interactions. With the rise of mobile technologies, the birth of mHealth has enabled patients to track their mental and physical activities through smartphone apps and wearables (Sharon, 2017). Another powerful application of digital health is in algorithmic medicine where big data and artificial intelligence (AI) technologies are used to diagnose health risks and diseases (Marent & Henwood, 2021). Using promissory discourse and normative claims, this paper reflects on the discussion that although digital health promises endless opportunities for the growth of the health data economy implementing these technologies presents potential drawbacks such as threats to health data privacy.
Opportunities for Digital Health
Marent and Henwood (2021) have used promissory discourses and normative claims to explain the opportunities and drawbacks of digital health in modern societies. The technological revolution driven by digital health has been applauded by policymakers as an avenue of finding solutions to complex health challenges such as the aging population, increase in economic crisis, and the rise in chronic illnesses. The utilitarian argument supports the mobilization of digital health from the perspective of increasing effectiveness, efficiency, and quality of care while the empowerment claims identify the opportunities created by digital technologies in health for patients and citizens to practice self-care. These technologies ensure patients have a better appreciation of their illnesses and can participate in managing their health. Nevertheless, the promissory discourse has been challenged based on societal implications and socio-technical practices. Using societal level theories, technology is seen as a disruptive societal consequence instead of empowerment of societies. Digital technologies have impacts on power distribution, capitalism, inequalities, and penetration of individual privacy. Four areas of digital health, including telemedicine, eHealth, mHealth, and algorithmic medicine have transformed access and provision of health in modern societies. According to Marrent and Henwood (2021), these areas constitute the modern field of digital health and have negative and positive impact on modern societies.
Telemedicine was born in the 1980s following the convergence of video conferencing technologies and personal computers to support distance healthcare provision. Early practices of telemedicine enabled communication between healthcare professionals in facilitating clinical care among remote patients and in situations where a rare specialist was required but not available locally. In later applications, these technologies supported remote physician-patient consultations and remote monitoring of chronically sick patients while at home. For instance, electrocardiogram (ECG) recorders among patients with heart conditions are often worn at home to enable the diagnosis of irregularities in heart rhythm, and results are remotely monitored by telecare workers (Marrent & Henwood, 2021). Piras and Miele (2019) have described remote monntiring as a highly standardised and tructurd care process. In this respect, telemedicine and telecare are seen as increasing healthcare access for patients in remote areas and supporting patients with chronic diseases to enjoy independence and autonomy.
With the introduction of the Internet in the 1990s, eHealth has facilitated access to health information and created new forums where patients can share their disease experiences. eHealth also serves as a way for patients to negotiate their recommended treatments with physicians or healthcare workers. Websites such as healthline.com and social media sites such as YouTube, Facebook, and Twitter have become important platforms where millions of visitors exchange their health experiences. The Internet is used for accessing and sharing health services and information online.
mHealth is a recent concept in digital health relying on mobile technologies such as geolocation devices and sensors, smart apps, and smart textiles. Such technologies are wearables and are connected to other media and ubiquitous digital devices to allow instant access remotely. Through these properties, mHealth practices allow the monitoring of bodies, analyze of the progression of illness, and promote healthy lifestyles while on the move. Smart apps and personal activity trackers have allowed people to keep personal daily records such as physical activities, sleeping, and nutrition intake and this promotes self-care for illnesses such as diabetes though monitoring blood glucose levels or HIV care such as recording adherence to treatment (Marrent & Henwood, 2021). The collection of biomedical data has been made easier with mHealth, with self-tracking becoming mundane and ordinary. The power of mHealth is in quantification where fitness target and health behaviours are visualized through colors or graphs and benchmarked and cross-references with population groups or peers. Self-tracking helps people discover correlations such as comparing running performance with their sleep through private activities or with others on social media. These activities have transformed how self-care among populations is conducted today.
Powerful computing tools have also seen the emergence of algorithmic medicine in digital health. These technologies are used to produce, store, and share big data, a concept known as the “datafication of health” within the perspective of health (Marrent & Henwod, 2021). The main drivers of algorithmic medicine the technologies can filter, sort, and process data and automate the decision-making process to revolutionize medical p...