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Australian Catholic University
Adopting strategies that include funding in the digital era demands the mindset of being risk taking and being flexible. There are various benefits in the funding of the digital healthcare. This includes innovation which includes the goal of optimizing the systems, reducing the human errors, improving patient outcomes through mobile experiences. According to statistics, more than 50% web browsing is done on the mobile devices in the world (Boudreaux, et al., 2014). The strategy of using big data provides various benefits. These includes the lower error rate that is based on the past records, drug prescriptions are given by the software and decreases the medication errors. It facilitates preventive care as big data identifies the people who are having repetitive visits to emergency rooms and then big data provide preventive measure by assuring that the patient doesn’t return. The company is benefited as the predictive analysis is provided by the big data where the estimation of future admissions is predicted. This allows company to allocate staff accordingly and resulting into decreased costs and wait time (Dimitrov, 2016). The virtual reality has supported in the digital healthcare transformation as it has myriad of applications through which the patient’s treatment is changing. The doctors are using the virtual reality for planning complicated surgeries. It is playing the major role in the digital strategy adopted in healthcare funding. The healthcare companies are also funding in the technological devices that are wearable and updated monitoring in the case of high risk patients is determined. In a recent report, it was found that the market of wearable devices will reach to about $27 million in the year 2023 from $8 million in the year 2017 (Marakhimov & Joo, 2017). The most common wearable devices are the exercise trackers, heart rate sensors and the sweat meters, oximeters and others. This personalizes the experience of healthcare as the patients can improve their health themselves and have to pay less insurance premiums. It also provides the opportunity of creating goals to achieve the goals of being healthy by following the diet, exercise and the nutrition plan (Ghosh, Dohan & Veldandi, 2018).
The benefits of the digital health makes the reach to the quality healthcare as anyone can stay connected with the professionals in order to resolve the concerns. The professionals can keep the information and which allows them to make the accurate reports on the progress of the patient’s health and take the clinical decisions easily (Wysham, Abernethy & Cox, 2014). The technology leads to adherence and empowerment of the treatments to the patients as they receive the biofeedback in the real time. An example of this is the ReHub that commits for the digital innovation in health industry. This includes the rehabilitation therapies by which the patients can perform exercises whenever or wherever they want to do which is monitored by the professionals (Rose, Nam & Chen, 2018).
Except the benefits that digital healthcare is providing, there are the cons to the strategic decisions on the funding of digital health. This includes the least personal involvement as the investment in the surgery robots is logical. It does not connect with the emotional level of the patient (Hasselberg, 2020). Due to the involvement of AI in the healthcare, the interactions between the patients and doctors decreases which is important in the building of trust. The AI instruments can also function with some errors that can affect the whole treatment (Khan, 2020). The introduction of digitalization will also impact the employment rate as AI is included on a vast scale in the healthcare. There are various activities that is replacing humans and adopting the robots. The mental health help is now provided by the chatbots that analyzes the situation of the patient’s health and the problems are foreseen by these technologies like the sepsis, cardiac arrest, seizures and many others which leads to the decrease in the jobs of the people to a great extent (Chakraborty & Bhojwani, 2018). For the accurate diagnosis of a particular disease, that depends on the large collection of data that is the funding in the big data strategy of collecting data but the data considers the people who have the experience of the similar conditions but this is where it can lack in the proper information of the individual patient as the background of the people differs and this results into the inappropriate diagnosis. For example in US about 200,000 patients died due to digital medical errors and the loss was $20 billion (Bottles, Begoli & Worley, 2014). Also, the suggestions given to the people may not be suitable for them as the machines cannot understand the background of people. The AI algorithm can recommend the nursing facility that may not be afforded by the particular person but the doctors provides the suitable treatment based on the income level of the person.
There are also some barriers in the digital health that are the threatened behaviour of the health professionals because of the new technologies. The digital technology is seen as the replacement of the human from the healthcare. There are only about 3 from 10 public hospitals that adapt the digital instruments and only 6 from 10 private hospitals that adopt the technologies. In the present, the funding in the digital health is 1% and one of the barriers in the digital health strategy is the cost that is involved in the research and development which the healthcares are not always willing to pay and the costing is high both for the health providers and the patients (Lim & Anderson, 2016).
Bottles, K., Begoli, E., & Worley, B. (2014). Understanding the pros and cons of big data analytics. Physician executive, 40(4), 6-12.
Boudreaux, E. D., Waring, M. E., Hayes, R. B., Sadasivam, R. S., Mullen, S., & Pagoto, S. (2014). Evaluating and selecting mobile health apps: strategies for healthcare providers and healthcare organizations. Translational behavioral medicine, 4(4), 363-371.
Chakraborty, S., & Bhojwani, R. (2018). Artificial intelligence and human rights: are they convergent or parallel to each other?. Novum Jus: Revista Especializada en Sociología Jurídica y Política; Vol. 12, no. 2 (jul.-dic. 2018); p. 13-38.
Dimitrov, D. V. (2016). Medical internet of things and big data in healthcare. Healthcare informatics research, 22(3), 156.
Ghosh, K., Dohan, M., & Veldandi, H. (2018). Digital transformation strategies for healthcare providers: perspectives from senior leadership.
Hasselberg, M. J. (2020). The digital revolution in behavioral health. Journal of the American Psychiatric Nurses Association, 26(1), 102-111.
Khan, S. H. (2020). ARTIFICIAL INTELLIGENCE IN HEALTHCARE SETUPS: PROS AND CONS AND WAY FOR WARD TO MANAGE. Pakistan Armed Forces Medical Journal, 70(2), 634-38.
Lim, S. Y., & Anderson, E. G. (2016, January). Institutional Barriers against Innovation Diffusion: From the perspective of digital health startups. In 2016 49th Hawaii International Conference on System Sciences (HICSS) (pp. 3328-3337). IEEE.
Marakhimov, A., & Joo, J. (2017). Consumer adaptation and infusion of wearable devices for healthcare. Computers in Human Behavior, 76, 135-148.
Rose, T., Nam, C. S., & Chen, K. B. (2018). Immersion of virtual reality for rehabilitation-Review. Applied ergonomics, 69, 153-161.
Wysham, N. G., Abernethy, A. P., & Cox, C. E. (2014). Setting the vision: Applied patient reported outcomes and smart, connected digital healthcare systems to improve patient-centered outcomes prediction in critical illness. Current opinion in critical care, 20(5), 566.
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