How AI transcription, integrated with telehealth tools, can boost care quality

A CEO who specializes in this combination reveals how artificial intelligence has the ability to help analyze and summarize key virtual care consultation points, detect patterns in patient data to deliver more personalized care, and much more.
By Bill Siwicki
12:54 PM

Howard Wu, CEO of Whereby

Photo: Howard Wu

There has been a lot of discussion around the ways in which artificial intelligence can be used in telehealth, balancing the need for efficiency with patient security and privacy.

Howard Wu, CEO of Whereby, vendor of a videoconferencing API for telehealth platforms, knows quite a bit about this niche. His company is implementing AI to enable real-time transcription of patient sessions, freeing practitioners to engage more deeply with patients without the distraction of note-taking.

The goal is to not only improve record accuracy but also ensure critical details are captured. Whereby has more than 800 clients, Wu said.

We interviewed Wu to discuss how AI can help with real-time transcription of patient sessions, how AI transcription has the ability to analyze and summarize key consultation points, how AI transcription offers the ability to detect patterns in patient data to deliver personalized care, and how AI transcription can help provider organizations better understand recent data and usage patterns around telehealth.

Q. How can AI help with real-time transcription of patient sessions, and what are the benefits?

A. AI is really changing the game for real-time transcription in telehealth by making documentation easy and accurate. Imagine having every word in a conversation between doctors and patients captured instantly, without anyone needing to jot down notes manually. This means healthcare providers can pay full attention to their patients instead of worrying about taking notes.

The perks of AI-driven transcription are huge. For starters, it cuts down on mistakes in medical records since it captures everything said during a session, ensuring nothing important slips through the cracks. Plus, it speeds things up – doctors can review and finish up notes right after a session, which makes the whole process more efficient and gets patients the follow-up they need faster.

And let's not forget how this helps with patient care. Having detailed and accurate records ready to go means doctors can make better, quicker decisions. Patients get the full attention of their healthcare providers. This is possible right now, and this is just the start of the possible benefits of AI transcription.

Q. You suggest AI transcription has the ability to analyze and summarize key consultation points, streamlining clinician review and aiding in treatment planning. Please elaborate here.

A. The next step in the AI transcription journey is to use AI to summarize key points from the raw transcripts. AI can capture the most important information from sessions and create clear and concise summaries. This means doctors can quickly review the highlights without sifting through raw detailed notes, saving a lot of time.

These AI-generated summaries make treatment planning a lot easier. Doctors can spot trends and critical details at a glance, which helps in making better decisions and tailoring treatment plans to each patient's needs. It also can help doctors maintain context across multiple sessions with the same patient. Key trends can be spotted over time that might otherwise be missed.

Plus, AI summaries help keep everyone on the healthcare team in the loop. When different team members need to look at a patient's history, they quickly can get up to speed with these summaries. This improves the efficiency of the whole process and ensures patients get consistent, high-quality care from everyone involved.

Q. You also suggest AI transcription offers the ability to detect patterns in patient data to deliver personalized, effective care. How does this work?

A. AI transcription isn't just about capturing and summarizing conversations; it also can spot patterns in patient data to help deliver personalized care. By analyzing multiple sessions, AI can pick up on recurring themes or issues that might not be obvious right away. This helps doctors get a better understanding of a patient's health trends over time, providing deeper insights for better diagnosis and treatment.

For instance, if a patient frequently mentions certain symptoms that could indicate a specific condition, AI can flag these recurring mentions for the doctor. This way, potential health issues can be caught earlier, and treatment plans can be adjusted accordingly. It's like having an extra set of highly analytical eyes on the patient's history, ensuring nothing important is missed.

This ability to detect patterns also means more personalized care for patients. By understanding each person's unique history and health trends, doctors can create treatment plans that are specifically tailored to their needs.

AI helps make sure that care is not just reactive but proactive, addressing potential problems before they become serious and adapting treatments to suit each patient's specific situation. This leads to better outcomes and a more personalized healthcare experience for everyone. It's very exciting.

Q. How can AI transcription help provider organizations better understand recent data and usage patterns around telehealth?

A. By analyzing the transcriptions from various patient sessions, with complete compliance to privacy requirements, AI can highlight common themes and trends. This helps provider organizations see what kinds of issues are being frequently discussed and how often certain conditions or treatments come up. It's like having a detailed, real-time report on what's happening in all those virtual visits.

This kind of insight is super valuable because it allows healthcare providers to spot trends and make data-driven decisions. For example, if there's a spike in patients discussing mental health issues, the organization can respond by offering more resources or training for their providers in that area. It helps in adjusting strategies and improving services based on actual usage patterns and patient needs.

Moreover, AI transcription can help highlight how telehealth services are being used over time. Are patients using telehealth for follow-ups more than initial consultations? Are patients discussing preventive health or seeking specific treatments? Do telehealth visits often refer to in-person follow-ups?

Understanding these patterns can help organizations optimize their scheduling, allocate resources more efficiently, and even predict future trends. This leads to better planning and a more effective telehealth program overall.

Follow Bill's HIT coverage on LinkedIn: Bill Siwicki
Email him: bsiwicki@himss.org
Healthcare IT News is a HIMSS Media publication.

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