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Page 49 Talwar et al. Art Int Surg. 2025;5:46-52 https://dx.doi.org/10.20517/ais.2024.81

[11]
modern PRO measures . To this end, NLP systems should help us better understand patients and their
goals. Ambient transcription systems will be able to identify important themes within a consultation and
highlight what the patient perceives as important. For example, if a patient consistently expresses concerns
about scarring, the surgeon can address this issue more thoroughly during and after the consultation.

NLP systems may also complete a PRO questionnaire during the consultation, alleviating the burden on
patients. Having a preoperative BREAST-Q or Michigan Hand Questionnaire, for example, would help
surgeons understand a patient’s well-being in a more objective way. This would also facilitate postoperative
patient tracking to measure a patient’s progress using the same PRO instruments.

Translation and health literacy
LLMs should also assist in translating clinical materials, both in conversation and clinical documents. This
would allow non-English speakers to more readily access care. This is particularly useful in plastic surgery,
where a surgeon may need to communicate surgical details to a patient who is more comfortable with
another language. Beyond language translation, LLMs can also address varying levels of health literacy
within the same language. Studies have found translating clinical documents for geriatric patients may
[12]
improve patient-provider interaction . More generally, translating plastic surgery jargon like “NAC” and
“IMF” into more familiar terms will aid patient understanding. For example, NLP can analyze the
complexity of the language used in consent forms and provide suggestions for simplifying the text to match
the patient’s comprehension. Furthermore, NLP can be used to generate personalized educational materials
tailored to the patient.

Chatbot
While NLP systems can facilitate conversations between plastic surgeons and patients, they may also
conduct their own conversations to provide patients with real-time support and information. “Question
answering” is a discipline in NLP involving systems that answer questions posed by humans, using a
relevant context and in a natural language. Several foundation models, including GPT-4 and Med-PaLM 2,
have shown promise in the medical question answering space [13,14] .

Question answering chatbots will enable patients to access care on demand 24/7. After a consultation,
patients can use a chatbot to answer common questions (i.e., about postoperative showering or dressings),
provide reminders for medication or follow-up appointments, and even alert the surgeon if the patient
reports any concerning symptoms. These systems can help optimize patients’ conditions before and after
their surgery, such as by advising on food and activities.

Still, recent otolaryngology and neurosurgery literature suggests we should temper our expectations. A
study by Gajjar et al. compared versions of GPT in answering neurosurgery-specific patient questions. They
found that, while factually accurate, the responses lacked readability and were not rated as highly
beneficial . Another study by Karimov et al. found ChatGPT was inferior to UpToDate in answering
[15]
[16]
several otolaryngology-specific patient questions . However, both these studies used untrained versions of
GPT. Future investigations should attempt to train plastic surgery-specific chatbots to improve
performance.

ETHICAL CONSIDERATIONS, LIMITATIONS, AND CHALLENGES
While the applications of NLP in plastic surgery consultations offer numerous benefits in both
documentation and communication, there are also ethical considerations, limitations, and challenges that
must be addressed. One major concern is the privacy and security of patient data. NLP systems rely on large