For the past few years, ambient AI tools have received a largely warm reception in healthcare settings. As the technology was designed to passively listen to physician-patient conversations and automatically generate a draft clinical note, it has slowly proved itself in both increasing operational efficiency and helping doctors mitigate “pajama time,” a term that is colloquially used by physicians in reference to the time spent drafting notes and finishing clinical documentation after hours. A paper published in JMIR earlier this year confirmed this sentiment: “ambient AI scribe use was associated with a statistically significant reduction in on-shift documentation time (P<.001), equivalent to approximately 24 minutes per 8-hour shift if used across 20 encounters.”
However, hospital systems are now moving away from the initial pilot phase of these and other AI systems and are now shifting towards full-scale deployment, meaning that they are increasingly encountering new hurdles and aspects that have to be addressed by leadership. For ambient scribing tools, governance structures matter, as questions are increasingly arising regarding the value vs. concerns regarding an “invisible listener” during encounters and what it means for an exam room to be a continuous data stream. A paper published in the JMIR Medical Informatics Journal explains that significant potential governance issues may arise from widespread ambient scribe incorporation, ranging from consent and trust issues by patients to cognitive deskilling for physicians. While it does elaborate that patients may view excessive AI use as potentially negative, the converse is definitely valid as well: patients certainly do not feel good when they feel that their physicians are not paying attention to the conversation and have to document real time during the encounter. The problem is that physician workloads do not accommodate for the extensive documentation needs that are often required; appointment times are already typically truncated and schedules are often running late. Therefore, ambient devices do have some positive benefits and have helped quell many practical issues.
In fact, experts have opined that these benefits are not just intangible impacts, but have real effects on the workforce. Authors of a paper in the journal Cardiovascular Diagnosis & Therapy explain that ambient AI tools significantly reduce cognitive burdens for physicians, improve job satisfaction, and even help efficiency at the practice level, which could lead to measurable increases in access to care. The paper does call out some key issues that are persistent with these devices, however: “studies also report frequent documentation omissions and occasional clinically significant hallucinations. Implementation remains a sociotechnical challenge involving workflow redesign, medico-legal considerations, and preservation of the patient-clinician relationship. In [certain subspecialties], where documentation requires precise, time-sensitive detail, AI-related errors may carry greater risk, underscoring the need for specialty-specific validation.”
Therefore, widespread adoption and scaling of these technologies will not be an easy feat. While pilot projects can be launched with some degree of ease in healthcare settings, implementation of large programs across patient care sites requires significant attention to detail, massive change-management programs and strict thresholds to judge performance. Especially as this technology is clinically embedded, developers and leaders must keep a low threshold to pause implementation and roll-out should patient safety or physician workflows ever be impacted negatively.
