Q&A: Athenahealth’s Transition from Traditional AI to genAI and ChatGPT

Q&A: Athenahealth’s Transition from Traditional AI to genAI and ChatGPT

Athenahealth provides software ⁣and services for medical groups and health​ systems around the⁤ country, and ⁢finding efficiencies through the ‌use of artificial intelligence (AI) has ​long‌ been a part of ⁢its DNA, so⁢ to speak.

For example, the healthcare technology provider has already been using machine ⁣learning to sift through ‍tens of ‌millions of faxes it receives electronically each year ‍so they can be ⁤attached to‌ the proper patient record.

But, the company’s use of⁤ AI changed⁣ dramatically when⁣ little more than a year ago OpenAI announced ‍ChatGPT. Athenahealth⁤ recognized the generative AI (genAI) platform’s promise of creating new efficiencies, both for clients and its own internal processes.

Earlier this⁢ month, ⁤Athenahealth unveiled a range of new generative ⁣AI-driven capabilities across its product line, including Athenahealth’s⁤ cloud-based suite of electronic health records (EHR), revenue ⁢cycle management, and ⁢patient engagement tools.

One newly deployed genAI capability can‌ summarize the labels on patient healthcare documents intelligently so providers can more ⁢easily find the information‍ most relevant ⁣at the ‌point of care. Another ⁣feature will identify missing or incorrect information before a prior authorization for care is submitted to maximize‌ the ‌chance the authorization will be approved.

Heather ⁣Lane, Athenahealth’s⁢ senior architect of⁣ data ‍science and⁣ platform ​engineering, has technical oversight of‍ the company’s AI strategy and ‍oversaw ‍not only genAI product deployments but the​ creation of a team ​that continues to explore new ways of using ‌the ‌tech.

Athenahealth

Heather Lane,‍ Athenahealth’s senior arcitect ⁢of data science and platform engineering.

Lane‍ spoke with Computerworld about how genAI such as ChatGPT⁣ through Microsoft’s Azure platform has⁢ been deployed and what the organization hopes to gain in coming years. The following are excerpts​ from that interview:

Is generative AI as ⁤promising as many claim? “I think the discussion in ‌the industry is between the people who ‌believe it’s an ‘iPhone moment’ and the people who believe it’s hype. I think it remains to be seen ‌who’s right.⁤ Personally, I’m ​betting ⁣on an ​iPhone⁢ moment.”

How did you create an AI team⁢ to address⁤ the rollout​ of‌ the ‌technology and who did that consist of? “We ‍have a data‍ science team and⁤ we’re gradually, broadly calling it the AI team. We’re​ not the⁤ only ‍ones at Athena who ‌do AI, but we are the majority team that does machine learning and⁣ artificial ⁤intelligence. The team⁣ has ​been around⁤ about⁣ a year ‌and a half⁣ now.”

What sort of things did your team do to⁣ learn AI skills? Did you educate employees on AI internally or hire talent to address an AI skills shortage? “We have mostly⁣ taught. ⁤The effort to level-up in generative AI‌ goes well beyond just the AI team. We took⁣ on a significant ⁤internal education activity this year. We called it a codefest, the‌ next⁤ step ‍up from a​ hackathon. And we framed it around ……

2023-12-23 07:00:04
Article from ⁢ www.computerworld.com rnrn

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