Which Healthcare Specialist can be Replaced by AI?
AI in healthcare has the potential to automate many tasks currently performed by healthcare professionals, leading to concerns about job displacement. While AI is not expected to replace healthcare professionals completely, it may change specific job categories' roles and responsibilities.
AI-powered diagnostic tools may significantly reduce the workload of radiologists and pathologists, who must review increasing medical images and laboratory results yearly. This could lead to faster diagnoses and treatment plans for patients and give healthcare professionals more time to focus on other important tasks. Furthermore, as AI technology in healthcare continues to grow, it has the potential to revolutionize the way medical professionals work, making their jobs more accessible and more efficient.
Radiologist
I have been working in healthcare for over 20 years and have seen a lot of incorrect diagnoses due to inaccurate imaging reports. For example, reading a CAT Scan report that indicates a liver mass but cannot determine whether it is a hemangioma or malignant can be frustrating and upsetting. Similarly, ultrasound reports showing gallbladder stones vs. polyps can leave physicians and patients uncertain. While I understand that medical imaging technology has come a long way, it's clear that there is still significant room for improvement.
That's why AI has the potential to revolutionize medical imaging. While human eyes can make mistakes and miss important details, AI can process information quickly and accurately. This means patients can receive more accurate diagnoses and avoid unnecessary radiation or other consequences of incorrect diagnoses. With AI, we can take healthcare to the next level and provide patients with better care and outcomes.
When I worked as an ER physician assistant, I often found myself in a predicament where I was required to read x-ray films after 7 pm due to the absence of an in-house radiologist. In such cases, the radiologists' group, located in Australia and operating in a different time zone, would be responsible for evaluating the scans. Despite the convenience of having them available at night, it still took some time to transmit data for them to read a CT scan result, as they did not read X-rays. I had received some training in reading X-rays, but I could not guarantee that I was 100% accurate all the time. As a result, we had to wait until 9 am the following day for the in-house radiologist to review the scans and provide a final verdict.
Pathologist
The field of pathology is notorious for its lack of standardization, which can lead to different results from different facilities, even when analyzing the same tissue samples. The problem is that pathologists often rely on their subjective observations to determine whether or not a selection contains malignant cells. Additionally, many pathologists may be working with outdated or incomplete records, which can complicate accurately diagnosing a patient. To improve the consistency and reliability of pathology results, it may be necessary to implement more standardized protocols and procedures and invest in more advanced technology for analyzing tissue samples. By doing so, we can ensure that patients receive the most accurate and effective diagnoses possible.
As a medical professional, it can be frustrating to have to reschedule patients for an endoscopic ultrasound with fine needle biopsy to rule out pancreatic cancer, especially when no pathologists are available, or they are on vacation. Many hospital policies require a pathologist to review frozen sections at the bedside to give a preliminary result, which can create difficulties when unavailable.
However, there are concerns about the potential loss of jobs and the ethical implications of relying too heavily on AI in healthcare decision-making. While AI can provide accurate and efficient diagnoses, it can only partially replace the human touch and empathy that is often necessary for healthcare (by the way, radiologists and pathologists do not need to touch humans).
Despite these concerns, I remain optimistic about the potential of AI in healthcare. With the proper development and implementation, AI can improve patient outcomes and reduce the workload of healthcare professionals, ultimately leading to a better healthcare system for all.
