Deep Learning amid Increased Physician Administrative Workload

4 min read

The Epitome of the Trojan Horse to duplicate Physician Clinical Judgment and conquer the Medical Industry

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Photo by Michael Dziedzic on Unsplash

The administrative workload is one of many burdens experienced by most physicians of our period. Doctors, particularly those practicing independently, have to work ten times harder for the same level of per-patient reimbursement than they did ten years ago. At least part of this trend concerning inappropriately validated and designed electronic health record systems (EHR) is an increasing bureaucracy that involves single patient care. To stay focused, I do not intend to cover the “why and how” of such a rising physician practice burden. However, most readers of this piece who are familiar with today’s medical practice system would concede that physician burnout is a significant healthcare problem.

To overcome physician burnout and limit their administrative workload, various agencies and business entities have stipulated multitudes of solutions, many of which, as of today, have failed to yield anything promising.

The cause of physician burnout is multifaceted, and Undertaking to alleviate administrative pressure requires a medley of shared responsibility from physicians and organizations as well as central and locally implemented programs. Reaching such a task is not an easy one, as it requires addressing a multitude of determinants along the way. The physician professional lifestyle’s complexity is the upshot of later phenomena, whereas such manifestation is not always a coincidence. Imagine an insurance company making it so complicated for physicians to claim a patient visit or procedure. Even a penny in a dollar worth mistake by physicians can translate into billions overall for the reimbursing corporation.

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Photo by Jonathan Borba from Pexels

Now, imagine an insurance company or any profit-driven corporation tries to come up with a solution for a physician burden caused by their complicated billing paperwork.

One of the most prominent solutions is implementing an automated smart practice management solution software to lessen the burden they have caused, to begin with; this includes government administration.

Today various medical practice solutions using artificial intelligence (AI) and deep learning (DL) technologies are becoming extremely popular and handy. Among many uses AI has in the healthcare arena, one currently being contemplated is around its utility towards reducing administrative burden, thus physician burnout.

Artificial Intelligence and Deep learning require access to daily, raw, yet valuable physician activities and patient data. Then utilizing sets of prewritten DL algorithms designed for a particular purpose, the system adapts a set of functions or tasks that would otherwise be carried out by the physician. Using this process, the engineers hope to alleviate the physician burden.


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The concept of automating certain medical practice activities is revolutionary and extremely useful; nonetheless, the use of AI does not always stop there. Also, some are contemplating creating the so-called Dr. Robot to replace a physician. For Dr. Robot to Deep learn clinical skills also necessitates its particular algorithms. The current algorithms are not entirely transparent, therefore carrying the best opportunity for in-depth learning of the physician’s clinical judgment and abilities. Just imagine Dr. Robots having access to billions of terabytes of clinical practice Data at no additional cost to the owner of the Artificial intelligence technology and the EHR system. Meaning, while trying to solve Physician burnout, it also learns how to think, diagnose, and treat like a doctor.

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Becoming a medical doctor takes years of hard work and dedication. A person has to learn, practice, and be mentored to reach a professional stage to treat a patient. They even have to pay to attend school.

Today Dr. Robot is going to medical school with the aid of its corporate executives. But those corporations don’t pay physicians for mentoring the Dr. Robot, and nobody is asking why!

Artificial Intelligence is gaining a degree in Medicine, but Dr. Robot needs as much knowledge and data as it can get. So, what is a better opportunity than using physician burnout as a primary excuse? While doing so, collect big data and apply deep learning on how physicians reach a clinical judgment?

Dr. Robots need physician clinical judgment and diagnostics skills for deep learning. There is no better source of gaining clinical skills for a robot than already produced medical records in an electronic health record system that is monopolized to benefit the system’s owner. So, shouldn’t corporations, at the very least, pay for using such data? Maybe if a physician isn’t aware of what they are losing, then it must be ok!?

Access to free clinical judgment besides raw clinical Data is what Dr. Robot needs to become a medic. And physician burnout and administrative mandates serve as their own fabricated “Trojan horse”. Only this time, the invader hides the AI algorithms to conquer lifelong physician knowledge instead of the city. And In this scenario, the solution for physician burnout is the horse. (Metaphorically)

Most physicians aren’t aware that the better EHR may be using a not so-called perfect algorithm.


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Let us be clear; Artificial intelligence and Deep learning are useful tools but only for transparent and honest users. Other than what said, Dr robot is still a physician without human touch. Furthermore, Patient information is precious, and the corporate cartel is after such clinical data.

Physicians, clinical judgment, or the thought process (clinical reasoning) that enables physicians to reach a conclusion or clinical decision-making based on objective and subjective information about a patient is valuable Data. And that valuable commodity is being snatched for free and used against doctors under the excuse of helping them with administrative burden.

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Photo by Photos Hobby on Unsplash

The physicians should not have faced a burden, to begin with, and since they do, they should then get paid for those clinical decision strategies. But regardless of the only way to protect patients, we must ensure transparency and accountability of all algorithms utilized and return the ownership of data to its owners. Most of all, hold the government responsible for dictating and letting the entities such as the insurance industry command patient care criteria when all needed is to empower patients, reduce mandates on physicians, and ensure a decentralized data management system.

Adam Tabriz, MD Dr. Adam Tabriz is an Executive level physician, writer, personalized healthcare system advocate, and entrepreneur with 15+ years of success performing surgery, treating patients, and creating innovative solutions for independent healthcare providers. He provides critically needed remote care access to underserved populations in the Healthcare Beyond Borders initiative. His mission is to create a highly effective business model that alleviates the economic and legislative burden of independent practitioners, empowers patients, and creates ease of access to medical services for everyone. He believes in Achieving performance excellence by leveraging medical expertise and modern-day technology.

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