POTENTIAL BENEFITS
There are numerous ways in which ChatGPT can assist the movement disorders clinician [
7]. In the author’s opinion, the following are the most relevant and impactful (
Figure 1).
- Expediting administrative work
ChatGPT’s largest potential may lie within its ability to rapidly generate documents that are necessary for routine movement disorders care [
6]. The largest demand for these documents probably relates to letters of medical necessity for specialty medications (now used commonly for the management of patients with Parkinson disease), but many other documents of varying complexity can also be generated. Indeed, clinicians can now instantly obtain letters that, for example, justify the use of botulinum toxin injections for facial dystonia, support the use of the new generation of VMAT-2 inhibitors to treat chorea or explain why a patient with a deep brain stimulator should not walk through a metal detector. This remarkable capability has the potential to reduce both physician burnout and administrative times, ultimately benefitting the patient.
- Generating texts for patient education
Using ChatGPT, movement disorders specialists can now instantly provide their patients either a printed document, a text message or an e-mail that is written in lay terms and in their native tongue and explaining a vast variety of topics, from levodopa titration to interpreting genetic testing results. ChatGPT’s grammatically accurate translating capabilities can be particularly helpful in multiethnic countries or for movement practices that offer telemedicine overseas [
9] Movement specialists can also decide whether to create these documents before the clinic visit or in real-time; regardless, this advancement will probably boost clinic efficiency and patient safety while reducing the amount of post-visit patient inquiries.
- Data synthesis
Like in other medical fields, movement specialists often spend significant time searching online databases before making decisions in unfamiliar situations. ChatGPT can synthesize this information by relevance and within a context provided by the clinician. For instance, a movement specialist could inquire about published treatments on the management of relatively rare conditions, like episodic ataxia, or ask for a comparison of prices among genetic testing companies. Being able to automate these searches could allow them to offer answers to their patients while still facing the patient, which can be particularly helpful for rural practices lacking easy access to subspecialized movement disorders care [
12].
- Expanding the differential diagnosis
Movement specialists may sometimes be able to categorize a patient’s phenomenology while still not being confident on the actual diagnosis. This is especially true in the dynamic field of neurogenetics, given its expanding number of overlapping genotype-phenotype correlations. ChatGPT can help put together a differential diagnosis based on signs and symptoms identified by the specialist. By training the model with data from sites like OMIM (
https://www.omim.org/) and PubMed (
https://pubmed.ncbi.nlm.nih.gov/), ChatGPT can aid this task. It is important, however, that clinicians use the generated document only as a guide and apply sound clinical judgement when interpreting the results.
POTENTIAL PERILS
As enticing as including ChatGPT in movement disorders care may seem, certain caveats must be taken into consideration. The following are some issues to keep in mind:
- Privacy
The potential for data breaches or unauthorized access to protected health information (PHI) is perhaps the largest concern at this time when utilizing this technology for movement disorders care [
13]. Whereas ChatGPT does not store or process PHI, it is plausible this technology could be exploited by third parties with egregious purposes. Examples of sensitive information in movement disorders practice that could be misused are abundant, the following being just a select few:
• Entering the genetic status of a patient harboring a mutation in the Huntingtin gene
• Creating a letter that details a Parkinson patient’s legal or financial struggles secondary to impulse control disorders
• Preparing a dossier for an ataxia patient that is planning on applying for permanent disability
The Health Insurance Portability and Accountability Act (HIPAA) is an American federal law designed to protect the privacy and security of individuals’ PHI. It is possible that HIPAA could be amended with the rise of AI language models [
14], or that healthcare facilities will each establish their own guidelines based on HIPAA’s broad principles [
8]. Until either of these scenarios takes place, it is important that movement specialists utilize their best judgment and consider avoiding entering PHI into ChatGPT.
- Accuracy
ChatGPT’s fallibility stems from the complexity of the field of movement disorders and the limited amount of training data available to the model. If a clinician were to ask the ChatGPT for treatment recommendations for a patient with a relatively unusual condition, it may provide an answer that may be factually correct, but could be incomplete, and not necessarily generalizable. Even for common movement disorders like Parkinson Disease (PD), ChatGPT could generate a list of signs and symptoms, when asked, that is not exhaustive. ChatGPT can also generate incorrect bibliography and clinicians are urged to always assess these for validity and appropriateness [
12].
- Bias
ChatGPT’s responses are only as adequate as the data it is trained on, and it is susceptible to inherent gender, racial or cultural bias within the data. For instance, if the training data contains a disproportionate number of examples related to PD (compared to other movement disorders), the model may be more likely to generate responses related to Parkinson when prompted with a movement disorder-related query. Furthermore, if the training data is biased towards a particular demographic, such as middle-aged white males (who are more likely to be diagnosed with PD), the model may also inaccurately suggest that Parkinson is the most prevalent movement disorder across all age groups. This bias may lead to incorrect conclusions and inappropriate treatment decisions [
4,
13].
- Currency
At the time this manuscript was written, ChatGPT had a September 2021 “cutoff date”. 3 This means that the model only had access to information that was available up until that point in time and couldn’t generate text based on more recent events. This can impact movement disorders practice in relation to other rapidly changing fields, like, again, the field of neurogenetics. If, for example, a clinician wanted to consult the tool on genotype-phenotype correlations for a recently described mutation, the model may not be able to generate this response given its novelty. The model may also not be able to comment on a recently recognized side effect to a medication, or on the results of clinical trials that were published after the “cutoff date”. Clinicians should be aware of this limitation and should be urged to cross reference other search engines whenever trying to make decisions based on very recent data. Hopefully, technology may overcome this limitation in the future, allowing the tool to generate results based on current information.
- Patients’ access to the technology
Could ChatGPT become the new “Dr. Google”? Ever since the popularization of internet search engines in the early 1990s, patients have been able to query for differential diagnoses and treatment recommendations based on their self-identified symptoms. ChatGPT now offers patients the ability to curate and categorize the results from these queries, as well as to pre-specify the complexity of the language of the output text [
15]. Whereas it is likely that the tool will often be correct in its predictions, patients need to be counseled that the tool should not replace medical care, and that there are situations in which the phenomenology is ambiguous (for example, dystonic tremor vs. essential tremor, or early chorea vs. ataxia) and in which the tool is no match for the movement specialist’s trained eye.
LOOKING AHEAD
One can only speculate on the following steps in the exponential growth of this technology, and how it will transform future movement disorders care. In the author’s opinion, the next big step will be the integration of AI with the different electronic medical record (EMR) platforms available. It is difficult to predict all the downstream consequences of this strategic partnership, but it is reasonable to envision a future in which AI-powered EMRs could use voice recognition software to “listen in” to the movement disorders clinic visit, and document the clinic note autonomously. Clinicians could, of course, edit the final product to their liking, particularly since the movement examination will need to be entered manually until reliable, AI-powered video interpretation becomes a reality.
It is also possible an AI-powered EMR could generate diagnostic and/or therapeutic suggestions, based on the data compiled within the clinic note and in the context of all previous encounters, even those at outside institutions. An automated review of a patient’s test results in the context of their medication utilization history could allow the detection of health trends and expedite the introduction of proactive interventions. Furthermore, data from one patient could be compared to aggregated, deidentified data from others within the same movement disorders practice (or other practices), which could help recognize outliers in disease progression and medication response. This could help to discern, for example, patients with early multiple systems atrophy from those with idiopathic PD.
ChatGPT could also revolutionize telemedicine delivery. Telemedicine has become an indispensable tool since its rapid and widespread adoption during the COVID-19 pandemic, and will likely continue to have a role in the post-pandemic era. Movement disorders specialists are particularly sensitive to the need for telemedicine to persist, as many of their patients (like those with advanced parkinsonism, chorea, or ataxia) have gait dysfunction limiting their ability to attend in-person visits. Moreover, many of them are elderly, frail, and immunocompromised, increasing their risk of complications from infectious diseases.
To enhance telemedicine care, ChatGPT could be integrated with remote patient monitoring systems, both wired and wireless, and prompted to periodically inform the movement specialist about any concerning changes in symptoms. ChatGPT’s accurate interpretation of the data from these monitors could also help confirm diagnostic impressions, especially in patients who are exclusively assessed over video, and chart disease progression. ChatGPT could also ask patients about both motor and non-motor symptoms ahead of their telemedicine appointments, remind patients about these appointments and assist them with scheduling issues. Lastly, patients could be granted access to sanctioned chatbots that could be trained to answer simple health-related questions, and to refer the patient to the specialist when appropriate.
One last potential future benefit of this technology could be the automatization of prior authorization and appeal processes. Just like this technology has been found to be capable of passing medical board examinations [
16,
17], it could answer specific questions raised by payers regarding a patient’s comorbidities, prior therapeutic trials, or contraindications, among others. It could also forward the responses back to payers autonomously, or with minimal supervision.
Time will tell whether any of these predictions come to pass. As competitors to ChatGPT come online (like Google’s Bard,
https://bard.google.com/), it is possible that other tools could dominate the market, or, perhaps, some tools will prove to be better suited for some tasks. It also remains to be seen whether these innovations will strengthen the clinician-patient relationship and reduce physician burnout, or whether they will produce medico-legal headaches that will, ultimately, hinder its widespread adoption. In the meantime, the power of text-generating AI tools is undeniable, and, given the mismatch between the pace of technological progress and the implementation of regulation, caution is warranted when employing them to generate documents involved in movement disorders care [
18,
19].