JMIR Publications

ABSTRACT

Background:

Generative AI (GenAI) solutions using large language models (LLMs) are transforming healthcare. Specialized ambient GenAI tools, like Nuance Dax, Speke, and Tandem Health, “listen” to consultations and generate clinical notes. General non-clinical chatbots, such as ChatGPT, offer broad AI interactions. Medical-focused models, like Med-PaLM, provide tailored healthcare insights. GenAI's capability to summarize complex data and generate responses in various conversational styles or literacy levels makes it particularly valuable since it has the potential to alleviate the burden of clinical documentation on healthcare professionals (HCPs). While GenAI may prove to be helpful offering novel benefits, it comes with its own set of challenges. The quality of the source data can introduce biases, leading to skewed recommendations or outright false information (so-called ‘hallucinations’). In addition, due to the conversational nature of chatbot responses, users may be susceptible to disinformation, posing risks to both safety and privacy. Therefore, careful implementation and rigorous oversight are essential to ensure accuracy, ethical integrity, and alignment with clinical standards. Despite these advances, currently, no review has investigated HCPs’ experiences and opinions about GenAI in clinical documentation. Such a perspective is crucial if these technologies are to be safely and ethically adopted and implemented in clinical practice.

Objective:

To present the protocol for a scoping review exploring HCPs’ experiences and opinions about GenAI and ambient scribes in clinical documentation.

Methods:

This scoping review will be carried out following the methodological framework by Arksey and O’Malley and the PRISMA-ScR checklist. Relevant papers will be searched for in PubMed, IEEE Xplore, APA PsycInfo, CINAHL, and Web of Science. The review will include studies published between January 2023 and January 2025. Inclusion criteria will be original peer-reviewed work that explores healthcare professionals’ experiences and opinions about the use of GenAI or ambient scribes for clinical documentation. Data extraction will include publication characteristics, sample characteristics, clinical setting, study aim, research question, and key findings. Study quality will be assessed using the Mixed Methods Appraisal Tool (MMAT).

Results:

The results will be presented as a narrative synthesis structured along the key themes of the evidence mapped. Data will be collated and presented in charts and tabular format. Findings will be reported in a peer-reviewed scoping review.

Conclusions:

This will be the first scoping review that considers HCPs’ experiences and opinions about GenAI and ambient scribes in clinical documentation. The results will clarify how HCPs use - or avoid using - GenAI in daily healthcare work. This insight will help address perceived benefits, risks, expectations, and uncertainties. It may also reveal key research gaps in the field.