The thrill round synthetic intelligence (AI) use instances in healthcare – particularly these involving generative AI and ChatGPT – is palpable, with consultants predicting that generative AI may ship $1 trillion in healthcare financial savings. Nevertheless, the AI ​​resolution that has the best potential to strengthen healthcare outcomes and healthcare fairness will not be the one which healthcare leaders consider first.

As a substitute, the present worth may come from extractive AI. It’s a instrument that enables organizations to show even handwritten textual content despatched by way of photographs or PDF by way of digital fax right into a structured knowledge sport. It’s also a sensible resolution to advertise knowledge interoperability with out the necessity for a heavy expertise raise to incorporate healthcare's digital have-nots, similar to post-acute care amenities and well being clinics.

A strong lever for enhancing well being fairness

A healthcare group's skill to assist whole care, particularly for our nation's most weak affected person populations, is dependent upon entry to knowledge that allows a 360-degree view of affected person medical historical past and the elements that affect well being , together with social determinants of well being (SDoH). .

However based on a current research from the Nationwide Institutes of Well being, 80% of healthcare knowledge is unstructured knowledge: knowledge that isn’t captured or saved in a standardized format, similar to handwritten notes despatched by digital fax. When suppliers don't have the flexibility to intelligently extract this knowledge and make it available inside doctor workflows, they lose the facility to make use of this knowledge to reinforce care. Within the present workflow, this could require guide knowledge entry, which slows down care and is typically carried out by scientific employees who ought to be treating sufferers. Moreover, this will increase strain on suppliers because it turns into troublesome to seek out the knowledge they want, once they want it. It additionally dampens efforts to offer customized, empathetic care by placing a holistic perspective of the affected person simply out of attain.

These are challenges that every one healthcare organizations face, however their impression is felt most intensely in organizations that don’t have a licensed EHR, similar to post-acute care amenities and well being clinics in underserved markets, which have restricted assets for sharing and receiving affected person knowledge in an well timed method.

“What we’ve seen throughout Covid is the necessity to make extra knowledge obtainable [around health inequities] quicker,” stated Dr. Claudia Fegan, chief medical officer of Prepare dinner County Well being, throughout a HIMSS 2023 panel titled “Persevering with the Journey to Well being Fairness.” “We’ve to make data-driven selections. And till we collect that info, we are able to't take motion on it.”

Clever knowledge extraction ranges the taking part in area between digital “haves” and “have-nots” in healthcare, by enabling smaller organizations to share and obtain affected person knowledge in a well timed method – and in ways in which allow physicians to behave shortly . Simply as importantly, it may well assist these objectives with out draw back danger by leveraging a instrument these organizations depend on most: a digital cloud fax resolution.

That is the way it works:

• Unstructured knowledge, similar to knowledge associated to doctor referrals or hospital discharges, is shipped to a facility by way of digital fax. At this time, seven in ten hospitals nonetheless depend on fax to share affected person info with different suppliers.
• By making use of pure language processing (NLP) and AI to faxed paperwork, handwritten or textual content knowledge is reworked right into a construction that may be simply utilized by any system. This places helpful info within the arms of healthcare suppliers on the level of care. The impression: higher knowledgeable care selections and higher coordination between healthcare suppliers.
• Healthcare suppliers acquire perception not solely into the affected person's medical historical past and rapid care wants, but in addition into the SDoH elements that impression total well being and long-term outcomes, similar to issue understanding discharge directions, issue accessing nutritious meals or transportation, or the stress that comes with it. with residing in an unsafe surroundings. With this info in hand, physicians can develop a plan to mitigate these dangers earlier than a affected person is discharged, lowering the prospect of issues and readmission after the affected person returns dwelling.

Taking digital faxing to the subsequent stage with NLP and AI bridges the hole between healthcare's digital 'haves' and 'have-nots' by enabling organizations to obtain crucial info the place and when it’s wanted, regardless the place it comes from or in what kind. It’s an inexpensive, sensible resolution that’s vital for healthcare fairness and addressing SDoH.

Convert unstructured knowledge into usable info

If we need to understand AI's full potential to enhance well being outcomes and healthcare fairness at decrease prices and fewer burden on the organizations that ship care, we should apply it in a means that gives a 360-degree expertise for all healthcare stakeholders in actual time. diploma picture of a affected person. . By selecting clever knowledge extraction utilizing a instrument that’s nonetheless closely relied upon in healthcare (digital fax), we are able to make sure that physicians don’t miss beneficial alternatives to make a deeper impression, one affected person at a time.

Picture: Filograph, Getty Pictures