At HIMSS20, Cerner will be talking AI-powered voice technology

Its message to attendees will revolve around clinical documentation and how it is using AI, machine learning, NLP and more to ease physician workloads and enhance patient experiences.
By Bill Siwicki
11:35 AM
At HIMSS20, Cerner will be talking AI-powered voice technology

Update: HIMSS20 has been canceled due to the coronavirus. Read more here.

EHR kingpin Cerner at HIMSS20 will be showcasing technologies aimed at improving clinical documentation through the use of artificial intelligence and machine learning. These technologies will include, but are not limited to, voice-assisted tools to help clinicians complete and fill in gaps in documentation.

There will always be a need for clinical documentation, so Cerner is focused on how to lessen the burden on the care team, said Dr. Tanuj Gupta, vice president and physician executive, Cerner Intelligence, at Cerner.

Continuity of care and reimbursement

“Clinical documentation today is mostly human-driven with the physician and care team spending a significant amount of their time manually entering data based on patient encounters,” Gupta said. “On top of this, reimbursement and quality requirements heighten the need for robust documentation. Clinical documentation serves as a necessary communication tool, ensuring continuity of care for the patient between venues and informing financial reimbursement and care quality for reporting purposes.”

Cerner is finding ways to improve and automate clinical documentation through AI and machine learning so that it can be extended to serve larger purposes like informing public health and research, as well as identifying new patterns in clinical care, he added.

"With the addition of in-room devices and sensors, there is potential for the healthcare industry to one day see the cognitive load of data entry be entirely shifted from humans to AI."

Dr. Tanuj Gupta, Cerner

A necessary part of clinical documentation is medical chart review – going back into the data for reimbursement, research or quality improvement purposes. While this process is almost completely human-driven today, Cerner is uncovering ways to make it more efficient through intelligence, Gupta said.

“Cerner is using our own natural language processing engine to completely automate medical chart reviews,” he explained. “Called Chart Assist, this solution evaluates EHR data using industry standardized terminologies and identifies opportunities to improve and validate documentation. Presenting this information at the time of a patient’s visit proactively improves the provider’s documentation, helping reduce the provider’s workload and number of post-discharge queries.”

The algorithms used in Chart Assist are configurable and transparent so that the AI is open, he explained.

“At all times, the medical decision-making belongs to the physician,” he asserted. “Chart Assist simply assists the clinician by automating the chart review for clinical validation in near real time and across all inpatient encounters. By doing so, a necessary but time-consuming process is completed, giving valuable time back to clinicians. In the future, an automated chart review tool like Chart Assist could be used to search for patient safety indicators, hospital acquired conditions or even patients that match to new clinical trials.”

Filling in gaps in documentation

The first step to achieving high-quality clinical documentation is data entry. The more data that can be provided on a patient during an encounter, the more clinicians can see the benefits of tools like clinical decision support, NLP, AI and machine learning to assist in creating documentation and closing gaps in care, Gupta contended.

Voice recognition can help reduce or eliminate the burden of data entry from the care team, he stated.

“For a long time, there has been predominantly only one use-case for voice-assisted technology in healthcare – medical dictation,” he said. “In this case, a physician uses a microphone for two or three minutes to dictate a structured clinical note. The burden of data entry is squarely placed on the physician, whether through voice or through a mouse and keyboard.”

The new approach of conversational voice, or ambient voice as some call it, brings the promise of getting the same data from a natural interaction with a patient and does not require data entry from the care team, he said.

“With the addition of in-room devices and sensors, there is potential for the healthcare industry to one day see the cognitive load of data entry be entirely shifted from humans to AI,” he predicted. “Medical decision-making will still belong to clinicians, but the cumbersome work of data entry will be handled by machines.”

Cerner wants to bring the best and most useful voice experience it can to its clients, Gupta said. The vendor has had success with its medical dictation partners, he added.

“We are excited to see the new innovation coming to healthcare through leaders in consumer voice technology and are evaluating ways to work with the right partners through our open and interoperable platforms,” he said. “Cerner is embracing an open philosophy to integrate innovative voice-assisted technology from third-party developers that supports our clients’ needs. In this way, we can collaborate across the industry to bring value to our clients and help them improve care delivery.”

Cerner’s overall message at HIMSS20

Gupta said that at HIMSS20, Cerner wants to make it clear to attendees that the company is working to make data more actionable for healthcare, while at the same time reducing the cognitive load on care teams.

“AI and machine learning play a big role in this process, with the potential to ease data entry and analysis for clients,” he said. “This is part of our strategy to improve care team and patient experiences through AI-infused workflows and standardization.”

Cerner has had success structuring and compiling data through its decades of work on the EHR.

“Now we are capitalizing on innovative technologies like voice recognition and NLP to make capturing clinical data easier to give time back to clinicians for direct patient care,” he said. “Through technologies that use AI machine learning at scale, we can help providers gain more actionable insights from their data to direct and improve patient care and health system operations.”

Cerner, he concluded, is using innovations like these to transform, optimize and simplify care delivery for both patients and clinicians to create intelligent, seamless experiences.

Cerner will be in Booths 2933, 2941, 400-76, 8300-42, at HIMSS20 in March.

Twitter: @SiwickiHealthIT
Email the writer: bill.siwicki@himssmedia.com
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