What Should Podiatrists Know About Artificial Intelligence?

In the past few months, national news media has been focused on artificial intelligence (AI) and even Congress has started to look into issues raised by the proliferation of AI in every facet of our lives.

The head of the artificial intelligence company behind ChatGPT testified before Congress last month that government intervention "will be critical to mitigate the risks of increasingly powerful" AI systems. "As this technology advances, we understand that people are anxious about how it could change the way we live. We are too," said OpenAI CEO Sam Altman at the recent Senate hearing.¹ Mr. Altman’s San Francisco-based start-up company launched ChatGPT, a free chatbot tool, late last year.¹

Teachers noted initial concerns about students potentially using this technology to cheat on homework assignments. But now the debate is even wider, bringing up transparency, copyright, and job security.¹ I recall news reports in the business community that shared that AI has generated life-like “robots” to take orders at restaurants and in Japan, AI companions in a hospital-like setting can keep patients company, listen to their concerns, and assist in daily activities.

In my observation, the United States not yet adopted AI as vigorously as in some other countries—but I do see potential to engage more often in the near future, possibly reducing cost and supporting “small business” during these uncertain financial times.

One of the major issues private practitioners encountered during the pandemic years is that of staffing shortages. At first, small practices were most impacted but it is clear that even large hospital systems are facing difficulties in recruiting employees. AI may be able to ease these challenges as we employ technologies that can help improve workflow. AI could automate administrative tasks, such as appointment scheduling, medical record documentation, and billing, reducing the burden on podiatrists (and practitioners of all specialties), allowing them to focus more on patient care. Natural language processing (NLP) techniques can be used to extract relevant information from unstructured clinical notes, allowing for efficient retrieval of patient data.²

Currently I have implemented patient self-scheduling software that asks patients relevant questions, allowing them to schedule their own appointments through our website. After they schedule, they will be sent reminders and links to complete their medical history in the portal, and the information then goes into their medical chart. Patients also complete their own registration and payments through the same portal. The patient no longer needs to arrive 30 or 60 minutes prior to their appointment to complete these tasks. I have only to review their information, confirm and append pertinent data, complete my exam, and document my findings and treatment. NPL techniques may also be used to extract information to translate into ICD-10 and CPT codes so that once your documentation is complete, generating and submitting claim(s) in real time. I see that as the next iteration of electronic medical records and practice management systems. With this new process in my practice, I can almost reassign a staff member to other tasks, or potentially even reconsider how many staff my practice needs.

Based on conversations I’ve had with esteemed colleagues, other potential areas where I believe AI will likely be of benefit to podiatric physicians (and all other clinicians) are:

1)     Diagnosis and treatment support: AI can analyze larger quantities of medical data, including patient histories, imaging results, and research articles. Then, in the right format, AI algorithms could identify patterns, recognize abnormalities, and suggest potential diagnoses or treatment options, helping podiatrists make more accurate and efficient decisions.

2)     Medical imaging interpretation: By training algorithms on large datasets of labeled images, AI might be able to identify specific foot and ankle conditions, detect fractures, tumors, or other abnormalities, and provide quantitative assessments of the severity or progression of a disease. I can see where this might improve accuracy, speed up the diagnosis process, and reduce treatment delays.

3)     Virtual consultations and remote monitoring: Most of us had to quickly adopt these practices during the COVID-19 pandemic. Now AI-powered chatbots or virtual assistants can enable remote consultations. AI can provide initial recommendations or determine if further evaluation is necessary. Moreover, wearable devices and sensors can track patient data remotely, such as for gait analysis, pressure distribution, or wound healing progress, and transmit it to AI systems for analysis. We already have some of these devices, but at this time I note that monitoring is the responsibility of medical staff or nurses who review the information and then contact the physician and the patient to alert or change behavior. AI may then enable continuous monitoring and early detection of potential complications with little human involvement; potentially affecting change in real time.

4)     Personalized treatment plans: By analyzing vast amounts of data and considering individual variations, AI algorithms can suggest tailored interventions, such as customized orthotics, exercise routines, or footwear recommendations, to optimize treatment outcomes. AI can leverage patient-specific data, not just medical history, but lifestyle factors and genetic information, to develop personalized treatment plans.

5)     Research and drug discovery: AI may accelerate research efforts in medicine as a whole, by analyzing large volumes of scientific literature and identifying relevant findings or potential connections between various foot and ankle conditions or disease processes. AI algorithms may also aid in drug discovery by analyzing molecular structures, simulating drug interactions, and predicting efficacy or side effects without actually involving patients in a clinical trial to see its effects and outcomes. This can lead to the development of novel therapies or more targeted treatment approaches for many medical conditions. I am excited about this potential in the wound care arena, where developing personalized medications, skin substitutes, dressing products, and treatment protocols may be of greater benefit in targeting what is missing in that particular wound.

I do see that certain job markets will likely require less staffing. In my estimation, medical assistants, billers and coders, and maybe even radiologists or pathologists may see a tighter market. With the tight labor market and rising costs, all industries are looking at ways to manage their overall financial resources and continue to deliver optimal or better service while preserving their bottom lines. You may be thinking at this point that I would be happy with replacing myself with AI—but I am not. While I believe AI has significant potential in podiatric medicine (and in medicine and business as a whole), it should not replace human expertise and judgment. Rather, it should be seen as a complementary tool that can enhance decision-making, improve patient outcomes, and increase efficiency in podiatric medical practice or in the business world with ethical considerations, privacy protection, and regulatory guidelines carefully addressing the responsible and safe integration of AI into health care and all settings.

Dr. Aung is Chief of the Podiatry Section of the Tenet Health System/St. Joseph’s Hospital in Tucson, Ariz. She is a member of the APMA Coding Committee, the APMA MACRA/MIPS Task Force and is on the Exam Committee of the American Board of Wound Management. Dr. Aung is also on the Editorial Review Board for Wound Management and Prevention. Her website is www.healthy-feet.com.

References
1.     O’Brien M. ChatGPT chief says artificial intelligence should be regulated by a U.S. or global agency. Philadelphia Inquirer. Available at: https://www.inquirer.com/business/technology/chatgpt-artificial-intelligence-regulation-20230516.html . Published May 16, 2023. Accessed May 22, 2023.
2.     Sheikhalishahi S, Miotto R, Dudley JT, Lavelli A, Rinaldi F, Osmani V. Natural language processing of clinical notes on chronic diseases: systematic review. JMIR Med Inform. 2019 Apr 27;7(2):e12239.

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