Effective communication between physician and patient is critical in healthcare delivery to ensure correct diagnosis, subsequent course of treatment, and billing/reimbursement. Both parties must be able to understand what the other is saying and later remember the details on the exchange.
Recent research has shown how incomplete medical records “pose a serious challenge to the health care of patients” and that “the biggest reasons for missing health information are communication and education.”
The completeness of information captured during physician/patient encounters varies broadly – whether it is an in-person visit that takes place in a brick-and-mortar building or a telehealth appointment facilitated by technology.
The University of Central Florida (UCF) and CirrusMD partnered on a National Science Foundation (NSF) funded research project to characterize the data completeness of chat-based episodes of care on the CirrusMD Physician-first Care & Guidance virtual care platform. They also identified a correlation between high data completeness and positive patient experience and outcomes.
This paper presents the outcomes of this research and opportunities to apply artificial intelligence (AI) and machine learning (ML) algorithms to 100% accurate chat-based data sets for greater physician empowerment and episode of care efficiency.
UCF NSF-funded research on AI in telehealth
University of Central Florida (UCF), a research leader in engineering, computer science and healthcare, secured a National Science Foundation (NSF) grant for a federally funded research project on how to best implement AI in telehealth by observing doctor/patient communication during telehealth encounters.
Roger Azevedo, the project’s principal investigator and a professor in UCF’s School of Modeling Simulation and Training, described the aim of the research:
“As technology advances in healthcare, it can facilitate ease of use, reduced travel time and more. But there’s also new problems that arise, including the potential for medical errors. We want to use AI to enhance the patient experience, so they get the care they need, and improve the doctor’s experience by facilitating diagnostic reasoning.”
The project’s co-principal investigators were Varadraj Gurupur, an associate professor in UCF’s School of Global Health Management and Informatics; Mark Neider, a professor in and the associate chair of UCF’s Department of Psychology; Mindy Shoss, an associate professor in UCF’s Department of Psychology; and Dario Torre, a professor of medicine and director of Programs Assessment in UCF’s College of Medicine.
Azevedo and team designed a study that would leverage a Telehealth-Neural Network (THNN) model comprised of Natural Language Processing (NLP) and AI-enabled systems to determine the true sentiments of patients and providers and measure data completeness during telehealth encounters.
Communication effectiveness in chat-first care
Through CirrusMD’s chat-first platform, a patient connects with a physician in 60 seconds or less and the chat between the physician and patient is stored verbatim in their natural language. If either party failed to document any detail of their encounter, they can refer to the chat text to review what was discussed.
Patient and physician can reconnect during a 7-day window to address additional care needs or concerns that may arise. If a patient has a follow up question, forgot to mention something during the original encounter, or their condition has changed and they need additional support, the physician is only a chat away. The physician can also follow up with the patient to check on progress, treatment results, and adjust as needed.
Supporting the physician is CirrusMD AI which continuously surveys the chat recommending resources and information to the physician that are relevant to the patient’s needs. This takes place in real-time during the care encounter and all recommendations are fully captured, so the patient can easily refer back to them, helping increase the likelihood that referrals are acted upon.
To close the loop, CirrusMD can assign a health coach to help the patient follow through with their treatment plan.
While not part of the formal study, the patients from the chat dataset provided to the UCF researchers gave CirrusMD a 100% positive patient satisfaction rating and went on to rate the company’s physicians 5 out of 5 in scoring.
Furthermore, the inclusion of text-first colloquial speech, such as emojis, correlates with positive patient feedback CirrusMD has received around physician emoji use. Patients have told the company that the use of emojis makes the conversation feel more human, trustworthy and natural.
“Between the positive sentiment behind our patients’ communication and how they rate their experience, we know our patients have a very positive experience,” said Chris Leone, Manager, Data and Analytics, CirrusMD. “Beyond their positive experience, our patients are also receiving a higher quality of care when you factor in our high data completeness.”
CirrusMD chat exchanges feature:
• Excellent data completeness
• Thorough physician documentation
• Clear communication between
• Positive patient sentiment
Patients in the data set:
• Gave CirrusMD a 100% positive
• Rated CirrusMD doctors 5 out of 5
• Feel physician emoji use makes
chat encounters feel more human,
trustworthy and natural