Physicians Are Working Like Robots for Robots
But, Convincingly, Shouldn’t It Be The Other Way Around? — A Near Glimpse At The Contemporary Healthcare Paradox
It is not a surreptitious truth that anyone who pursues a professional life must dedicate part, if not all, of their lifespan to learning the required skills—moreover, pronounced, valid to those seeking the medical profession. Long lore periods, sleepless nights, and stressful days are very well known to every medical doctor. That does not only hold in the United States but is also valid across the globe. That is why the medical profession is considered a lifestyle more than a career. It is the lifetime investment of every physician. It is precisely based on the latter fact that most medical doctors, by omission, only know in what they have invested their lives!
Indeed, some physicians may step out of their comfort zone and pursue alternate avenues to adapt to their ever-changing domain, i.e., the Healthcare industry. However, the majority take a passive stance, particularly regarding the information technology of their industry.
Physicians Working Like Robots
Experts in every industry logically and by virtue have taken control of the leadership within their respective domains. They have harnessed the best technology they can offer to their needs by taking the lead on business requirements, design validation, and quality assurance.
Unfortunately, we cannot say the same for physicians. Health information technology is driving the physician practice route toward an unfamiliar sphere. Information technology and its contributors dictate how physicians must practice and how much they should earn. In other words, the value of their work is not decided between them and the patient but merely determined by data analysts’ algorithms. The 21st-century physicians are the disciples of mathematical algorithms. Working like a Robot is the expected attitude of physicians in developing countries today.
Physicians, by nature, are skilled craft persons. They are pretentious about their capacity to customize the care for each patient. But Peculiarly, they can be reluctant to simplify their efforts or more error-proof if doing so jeopardizes this artistic part. Physicians are also the right analytical sages and use these skills in their regular practice. When an idea for change surfaces, they are adept at what De Bono calls “black hat thinking,” an intellectual style that emphasizes the solution’s criticisms. This style is helpful, but it will smother innovation and change if it governs every meeting.
The Black hat attitude’s ultimate consequence has not worked in their interest. It has created a vacuum for other industry leaders, information, and the insurance industry, significantly disrupting the healthcare domain. Doing so has uttered physicians’ taking a follower stance rather than a leadership role, just as physicians should assume the pre-programmed algorithms.
Physicians Working For Robots
Health information and big data have been the pinnacle of developing healthcare technology. The development is more vertical than the healthcare community can keep up with, establishing a chasm that facilitates makeshift scrutiny and nooks in the healthcare vacuum. Every day, all physicians have the adeptness of deciphering information into the proper diagnosis and furnishing the corresponding treatment alternatives. It implicates huddling the pertinent data for each patient, integrating it with pre-existing knowledge, constructing a clinical judgment, and inciting the most suitable treatment according to the patient’s expectations and needs. The clinical assessment pertains to the decision-making process, likewise called clinical reasoning. It allows clinicians to reach a clinical conclusion on treating a disease in an individual patient contingent on objective findings and collected subjective patient understandings. Today, data industries are contemplating strategies to replace or, at the very least, replicate physician clinical practice.
Artificial Intelligence needs an algorithm to diagnose, just like a physician needs medical knowledge. Developments in modern data analytics and computational leverage grant the recourse to obtain new insight and transport data along with subsidized value to clinical practice in real-time. Such systems are denominated as “Clinical Decision Support” (CDS).
The Computer doesn’t go to Medical School. Still, with the inception of new machine learning facilities, unstructured data is becoming more than ever convenient, particularly with the esteem to shadow learning of physician clinical judgment by the deep learning gadgets. Therefore, amidst physicians opting to be followers, it is essential to realize that they work like robots. Nonetheless, they are working for them as the instrument of in-depth learning education.
Robots Working For Physicians
Healthcare sentiments need to change!
A medical practice requires a meaningful transition from one hundred percent unyielding applied a science-based remedy to the domain of compassion that inundates the fairest of all scientific and technological inventions within the confines of its core integrity. Medical science is about recipes to the patient as individuals and not rectifying a set of query outcomes and procedures. Technological innovations such as Data Analytics, Pharma, imaging, and biotechnologies are complementary scientific grounds to medicine, not vice versa. Medicine is the science schooled between a physician and one patient. That contrasts with something cultivating a cookie-cutter medicine that the traditional population health and overreliance on technology would offer. In the present epoch, technology has become a part of human existence. It can comfort our lives and deliver safety and efficiency to our patients. But we will be leading the way to tragic outcomes if the technology cannot be governed or adapted by the industry professionals. Thus, technology must be expanded under the Oversight of Industry Experts and constructed to simplify life for patients and clinicians. But never should be for any reason diverse.
