Healthcare has become a worldwide concern, with most countries prioritizing its quality and accessibility. With the rise of technology, higher demand for quality healthcare despite the shortage of practitioners, and increased levels of lifestyle and chronic diseases, artificial intelligence (AI) could be the next solution to the healthcare problems ( Hamet & Tremblay, 2017). The healthcare system will need to embrace new ideas; procedures, and take risks to provide high-quality services. Change is met with resistance and sometimes confusion, with staff having trouble delivering the same services using new technology or methodologies. Artificial intelligence will create a paradigm shift in healthcare, which will be a sustainable solution to the shortage of medics that the US is currently experiencing, and projected to rise in the next ten years.
Background
Machine intelligence is the ability of computers to mimic human actions ( Russell & Norvig, 2016) . For instance, in healthcare, robots can be used to assist in surgery. With the introduction of government health cover for all citizens, an aging population, and increased lifestyle and chronic diseases, the demand for medical practitioners is higher. According to Pear (2015), the shortage is a limitation to achieving global health standards. The Association of American Medical Colleges is demanding an increase of intake in medical colleges, but the government is unable to fund for more. Since the 21 st century is an age of technology, artificial intelligence is a ready solution to the dilemma. The US has already started shifting towards the use of technology to reduce the need for human labor, with the introduction of Medicare Access and CHIP Reauthorization Act of 2015 (MACRA). MACRA created payment track for clinicians through the Quality Payment Program ( Hamet & Tremblay, 2017). The program adjusts clinician pay based on their working conditions. Clinicians who work in riskier areas receive automatic bonuses, which reduce after transfers. Instead of having a human resource manager who does this manually, the system updates changes in work location every time a clinician shifts (Deloitte, 2019). This should, however, not be seen as a threat to staff and an avenue to lose jobs. Artificial intelligence helps humans achieve results faster, not eliminate the need for human labor ( Russell, & Norvig, 2016) . The technology saves humans time and leaves more time for them to attend to issues that only humans can do, such as spending time and listening to patients.
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The healthcare industry is shifting away from curing diseases and providing short-term solutions to preventing illness and promoting overall health. Both stakeholder groups agree on the benefits of virtual health according to a survey by Deloitte 2018 Surveys of US Health Care Consumers and Physicians, which is an indication of readiness to digitize healthcare, characterized by artificial intelligence. Artificial Intelligence will transform healthcare by performing clinical procedures with higher speed and accuracy as compared to humans. Machines can also be used to spot disease earlier through monitoring and help physicians make health decisions on behalf of their patients. Various countries, including the United Kingdom, China, Netherlands, Australia, and India have invested heavily in digitizing healthcare, some of which have worked and others are still in the process of implementation, according to a survey done by Deloitte (2019). Artificial intelligence (AI) is an expensive investment, which becomes necessary only when the benefits surpass the cost of installation. For instance, the debate on whether to invest more in robots that medical experts are still debating aid surgery. The robots make surgery less tiresome for doctors, but the cost is too high. Once the experts find out if the AI cost is worth the benefits, robots can fully be adopted to be used in theater rooms. Their accuracy is not in doubt, as humans make more errors than machines. They are expected to lower post-surgery complications and deaths.
Alternatives
For facilities not ready to adopt AI, retraining of staff is the quickest decision they make. These facilities have digitized their operations halfway, such that patient procedures are partially paperless, but most of the patient-oriented work is done by staff. For instance, instead of patients ordering drugs online and having them delivered by drones, as AI would suggest, the patients can order the drugs, but they are delivered by a nurse who explains the dosage and side effects at a personal level, although the same is written in the prescription note. The halfway adoption of technology is believed to cultivate healthcare that is more than treating disease. Among the five competencies of nursing, one of them is creating patient-centered care, which AI does not develop ( Hamet & Tremblay, 2017) . Digitalizing operations by retraining staff to use technology in combination with human effort is not an effective strategy due to frequent transfers among medical practitioners. The hospital will have to keep retraining staff once the trained one is transferred to a different facility.
According to Deloitte (2019), another alternative to AI is virtual reality. Virtual reality started in the gaming and entertainment industry but is being evaluated for use in healthcare. The technology utilizes 3D images created in computers to illustrate the target. For instance, doctors in another room could have a 3D representation of the brain during surgery, and communicate with the doctor in the theater room on what to do. The image is a replica of the brain, such that the participating and non-participating doctors see the same thing. The technology also saves time, as doctors can participate in medical procedures without having to travel to the facility. They can also offer consultation services while away. However, the solution may not be practical in a case where the anatomy of the patient is not the conventional one. In a case where the patient has an alteration, the doctor using virtual reality may misguide the doctor performing the medical procedure. A mistake made in the initial programming of the system also means that the error is propagated by all individuals who utilize it, which could result in more medical errors unless detected early ( Roy, Gordon, & Thrun, (2014) . Although virtual reality is an effective platform to test procedures and drugs before practicing them on patients, it is also an expensive investment.
Proposed Solution
Artificial intelligence is a solution to quality healthcare despite the shortage of doctors and increased lifestyle chronic and lifestyle diseases. The technology does not get rid of human resources, but increases efficiency and reduces workload for hospital staffs. Procedures that are not meant to build practitioner-patient relations can be done by machines, while humans are left to concentrate on activities that can only be done by people. AI also reduces errors and creates consistent results. The 21 st century is characterized by numerous inventions, with human beings trying to make life more comfortable. It is, therefore, reasonable to integrate the same into healthcare. The US has a shortage of neurologist and psychiatrists in the US (Pear, 2015). AI includes neuronal learning and mental assessment, which is an immediate solution. According to Riek, (2016) AI could supplement the need for mental health specialists and shorten the waiting period for patients by performing robot-aided assessments.
Recommendations
AI is, however, expensive to implement. It requires sophisticated and carefully programmed systems to avoid recurrent mistakes. A mistake in the initial programming of robots could replicate the same error in all procedures done by the same robots, and a correction means reprogramming them all over again. AI also needs proper regulation from the science and technology department to ensure unscrupulous scientists do not misuse it, as it poses a danger of jeopardizing human life when abused, especially in healthcare.
References
Delloitte. (2019). 2019 Global health care outlook: Shaping the future. Retrieved from https://www2.deloitte.com/content/dam/Deloitte/global/Documents/Life-Sciences-Health-Care/gx-lshc-hc-outlook-2019.pdf
Hamet, P., & Tremblay, J. (2017). Artificial intelligence in medicine. Metabolism , 69 , S36-S40.
Pear, R. (2015). Shortage of doctors proves an obstacle to Obama goals. New York Times .
Riek, L. D. (2016). Robotics technology in mental health care. In Artificial intelligence in behavioral and mental health care (pp. 185-203). Academic Press.
Roy, N., Gordon, G., & Thrun, S. (2014). Planning under uncertainty for reliable health care robotics. In Field and Service Robotics (pp. 417-426). Springer, Berlin, Heidelberg.
Russell, S. J., & Norvig, P. (2016). Artificial intelligence: a modern approach . Malaysia; Pearson Education Limited.
