How AI medical scribes reclaim provider time, claim denials
An AI medical scribe for clinical documentation is helping Onvida Health prevent claim denials while giving clinicians more face-to-face time with their patients.
Revenue cycle staff and clinicians can sometimes be at odds. The revenue cycle team needs complete and accurate clinical documentation, coding and charge capture to generate clean claims and receive quick reimbursement. However, the administrative burden on clinicians is exacerbating what some call an epidemic in healthcare.
"There is a significant documentation burden on clinicians this day and age, and there's a lot of cognitive burden," explains Marc Chasin, M.D., senior vice president and chief information officer at Onvida Health. "This contributes to a huge physician burnout problem in the country."
Reducing the potential for physician burnout is a top priority for Onvida, a nonprofit hospital system based in Yuma County, Arizona. The system employs nearly 500 providers to manage 430 inpatient beds, 45 outpatient clinics and a free-standing emergency department.
"But we still have so many patients that need to be seen," Chasin said as he elaborated on the burden clinical documentation has on clinicians.
Excessive documentation is a top driver of clinician burnout. The sheer volume of documentation required for each patient encounter can be overwhelming, while the complexity of EHR systems can make documentation less efficient and downright difficult to complete. Still, payers are generally requiring more supporting documentation for claims reimbursement to account for evolving health policy and regulation, an increased focus on compliance and more complex coding and billing practices.
"Being a physician myself and understanding the day-to-day burden of seeing patients and documenting that, then also having a family life of your own, it is very difficult," Chasin explained. "Decreasing the documentation burden outside of work, decreasing the potential of physician burnout was very important to us."
Onvida launched a pilot program with Ambience Healthcare using an AI medical scribe to support clinician workloads while addressing revenue cycle management challenges.
How AI medical scribes streamline clinical documentation
AI medical scribes leverage ambient AI technology to capture conversations in the background and analyze the data. It can largely do this unobtrusively, making it an ideal solution for clinical documentation.
"Essentially, when the doctor walks in, they say: 'Do you mind if I record our visit?' If the patient consents, a phone is turned on and starts recording," Chasin explained. "That recording allows the doctor or provider to have face-to-face contact with the patient, as opposed to what happens in today's encounters, which is a keyboard and a screen between the patient and their provider. This allows the entire visit to be recorded in multiple languages with multiple people in the room."
After the encounter, the AI scribe generates documentation for the patient record. Then, clinicians review and edit the documentation if necessary. Once the clinician signs off, the documentation is filed in the EHR thanks to the technology's data integration capabilities.
At the time TechTarget Editorial spoke to Chasin, only a group of six super users were using the technology. However, Chasin already noticed improvements in provider and patient satisfaction, as well as patient throughput. Onvida has now rolled out the AI scribe technology to 100 clinicians across various specialties.
"Aside from decreasing the cognitive burden, this allows the doctor to really focus on medicine as opposed to administrative tasks," Chasin stated. "But it also leads to more accurate reimbursement for provider services."
Healthcare revenue cycle benefits
In addition to addressing burnout and burden, implementing an AI medical scribe that supported the revenue cycle was a top priority for Onvida.
"Many health systems across the country are making the shift to AI scribes. However, not all AI scribes have the same capabilities," Chasin said. "We wanted to make sure that ours had the ability to support coding and patient summaries, as well as referrals, to ultimately generate compliant documentation that supports the needs of our revenue cycle, compliance and quality teams."
Revenue cycle teams are under more pressure to substantiate medical and billing codes through clinical documentation. Coding errors and lack of medical necessity or supporting documentation are consistently among the top reasons for claim denials.
Many health systems across the country are making the shift to AI scribes. However, not all AI scribes have the same capabilities.
Marc Chasin, M.D., SVP and chief information officer, Onvida Health
To rework and ultimately prevent denials, revenue cycle teams are calling on clinicians to bolster documentation efforts to ensure they capture all relevant information for coding and billing purposes.
"But a doctor isn't necessarily going to know all of these things," Chasin said. "And should they? Doctors should be focusing on seeing and treating patients, building the clinician-patient relationship."
To put the focus back on the face-to-face interaction, Onvida is testing AI scribe technology that incorporates coding and billing capabilities, as well as clinical documentation improvement.
The technology analyzes conversations to identify ICD-10 codes and CPT codes while providing audit trails for revenue cycle teams. It also does this across more than 100 specialties and subspecialties -- another priority for Onvida, which wanted a comprehensive solution for clinicians across the organization.
Allowing clinicians to focus on the clinical side of care has led to fewer denials and less administrative work across the organization, Chasin stated.
Incorporating AI in healthcare
Ambient AI is optimizing clinical documentation and revenue cycle management for Onvida. But the decision to incorporate AI into patient encounters was very deliberate, Chasin emphasized.
"AI is important to a rural hospital, but it has to be an appropriate use case. There's a lot of AI around, but we have to be very thoughtful in what we deploy and how we utilize it to its fullest," Chasin said.
Onvida stood up an AI subcommittee through its IT governance area to evaluate use cases, measure upstream and downstream benefits and identify returns on investment. The latter being a major challenge to determine because cost savings aren't always clear despite widespread evidence the technology is improving "soft" metrics, like clinician burnout rates, patient experience and employee engagement.
"We want to know if the AI is helping them do their jobs, and that can't necessarily be measured," Chasin stated. Still, it is an extremely important aspect to understand when using AI in clinical care, he continued.
Fortunately, employees at Onvida have taken to the AI medical scribe and its suite of AI capabilities.
"It is the first technology in a very long time that clinicians are asking for, and that's a good sign," Chasin stated. "This is opposed to all the other administrative and technical burdens that we've placed on our clinical folks."
Jacqueline LaPointe is a graduate of Brandeis University and King's College London. She has been writing about healthcare finance and revenue cycle management since 2016.
