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How Clinical Ambient Intelligence Can Address Clinician Burnout

While clinical ambient intelligence could mitigate clinician burnout, organizations must leverage an implementation strategy that promotes interconnectivity, according to a Forrester analyst.

Clinical ambient intelligence solutions could be healthcare's fix to its clinician burnout problem.

The tools have hit the market with the goal of helping providers spend less time staring at a screen and more time delivering patient-centered care. Current estimates put providers spending up to six hours a day on clinical documentation, a driving force behind clinician burnout.

That figure is out of control, according to Shannon Germain Farraher, a senior analyst at Forrester.

"Technology that automates and augments clinician tasks is front and center right now and is one of the few ways to effectively mitigate burnout," she told EHRIntelligence in an interview. "Everyone is being asked for more from all sides. The shortage and burnout is just a vicious cycle."

"On top of that, there are medical deserts across the United States in rural and urban areas," Germain Farraher added. "We're at a pivotal moment when health systems are either going to sink or swim."

She likened ambient intelligence solutions to smart medical scribes.

Traditional medical scribes work alongside physicians to confidentially document patient encounters virtually or in person. Current estimates suggest that there could be as many as 100,000 medical scribes employed in the United States. While these professionals can help cut down on clinician documentation time, they are costly to train and have high turnover.

On the other hand, ambient clinical documentation technology uses automatic speech recognition (ASR) and natural language processing (NLP) to document patient-provider conversations in the EHR.

Generally, ambient intelligence refers to physical spaces that are sensitive and responsive to the presence of humans, according to the National Center for Biotechnology Information (NCBI). The technology hinges on data collected by contactless sensors embedded into everyday objects and utilizes machine learning algorithms for data analytics.

For example, devices that automatically respond to a person's voice, such as Amazon's Alexa, use ambient intelligence. In healthcare, popular ambient intelligence solutions include but aren't limited to DeepScribe, eClinicalWorks Scribe, and Nuance's DAX Copilot.

"What is so special about ambient intelligence solutions is that it will only digest and filter what is most important and insert that into the medical note," Germain Farraher said.

For instance, if a physician begins or ends an encounter with small talk or other pleasantries, the AI medical scribe does not document those parts of the conversation.

She explained that since these solutions leverage machine learning, they get smarter and more accurate with time, which includes picking up on different clinicians' note structure styles.

"Basically, the physician is able to dictate how they want the note to be formatted and structured," Germain Farraher noted. "It's not just letting the technology interpret the structure. It takes into consideration the physician and how he or she wants to structure the medical note and what he or she wants to include."

"That's where the machine learning and natural language processes are being refined over time, and the more exposure, the smarter the tech gets," she pointed out.

Additionally, while the note turnaround time for traditional medical scribes can be up to 24 hours, AI medical scribes can produce clinical notes in minutes. From there, the physician can make any edits or changes before saving the note and locking it into the patient's record.

A 2023 study found that the implementation of ambient voice technology cut down clinician documentation time by over 28 percent per primary care encounter.

The clinical ambient intelligence market is booming, with projections of almost $60 billion slated by 2026 in inpatient and home settings, Germain Farraher said.

However, for ambient intelligence solutions to support the clinician and patient experience, healthcare organizations must leverage an implementation strategy that supports interconnectivity.

"Health systems, health plans, and other healthcare organizations haven't really nailed down how to make an impact that is widespread," she said. "For example, they will implement a certain technology in a certain department, but not throughout the entire health system."

This can foremost create an inconsistent clinician experience. For example, if a clinician is working on one unit and goes somewhere else in the hospital that does not have the same capabilities for documentation automation, they have an inconsistent experience. Alternatively, certain units may use the same technology in different capacities.

On the other hand, inconsistent adoption of documentation automation tools impacts the patient experience.

"Patients will see glimpses of how artificial intelligence and ambient intelligence solutions can revolutionize their experience because they have a great interaction with a provider on one floor, but then they go somewhere else in the health system and do not get that same experience," Germain Farraher explained.

As the digital health transformation progresses, striving for consistent adoption of AI documentation tools across healthcare organizations will be crucial to driving both the patient and clinician experience.

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