The AI Instrument that Issues Most for Medical Care Isn’t ChatGPT

The joy for synthetic intelligence (AI) use instances in healthcare—particularly these involving generative AI and ChatGPT—is palpable, with specialists predicting generative AI may assist unlock $1 trillion in healthcare financial savings. Nonetheless the AI answer that holds the strongest potential to strengthen care outcomes and well being fairness isn’t the one healthcare leaders consider first.

As a substitute, right-now worth may come from extractive AI. It’s a instrument that offers organizations the facility to place even handwritten textual content despatched by way of photographs or PDF by digital fax right into a structured knowledge play. It’s additionally a sensible answer for advancing knowledge interoperability and not using a heavy know-how carry to incorporate healthcare’s “digital have-nots,” like post-acute care amenities and well being clinics.

A strong lever for enhancing well being fairness

A healthcare group’s potential to assist complete care, particularly for our nation’s most susceptible affected person populations, relies on entry to knowledge that allows a 360-degree view of the affected person’s medical historical past and the elements that affect well being, together with social determinants of well being (SDoH).

But in accordance with a current Nationwide Institutes of Well being examine, 80% of healthcare knowledge is unstructured knowledge: knowledge that isn’t captured or saved in a standardized format, like handwritten notes despatched by digital fax. When suppliers don’t have the flexibility to intelligently extract this knowledge and make it obtainable instantly inside clinicians’ workflows, they lose the facility to place this knowledge to make use of in strengthening care. In at present’s workflow, this may require guide knowledge entry, which slows down care and is typically accomplished by medical employees who ought to be treating sufferers. Moreover, this will increase strain on suppliers by making it tough to search out the data they want, after they want it. It additionally dampens efforts to supply customized, empathetic care by placing a whole-person view of the affected person simply out of attain.

These are challenges all healthcare organizations face, however their impression is most intensely felt in organizations that don’t personal an authorized  EHR—like post-acute care amenities and well being clinics in underserved markets, which have restricted assets for sharing and receiving affected person knowledge in a 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, Prepare dinner County Well being, shared throughout a HIMSS 2023 panel named, ‘Persevering with the Journey to Well being Fairness.’ “We have now to make data-driven choices. And till we accumulate that info, we will’t start to behave on it.”

Clever knowledge extraction ranges the taking part in subject between digital haves and have-nots in healthcare by positioning smaller organizations to share and obtain affected person knowledge in a well timed method—and in ways in which allow clinicians to behave shortly. Simply as necessary, it could actually assist these objectives with no draw back danger by leveraging a instrument these organizations depend on most: a digital cloud fax answer.

Right here’s the way it works:

• Unstructured knowledge, comparable to knowledge associated to doctor referrals or hospital discharge, is transmitted to a facility by way of digital fax. At present, 7 out of 10 hospitals nonetheless depend on fax to share affected person info with different suppliers.
• Making use of pure language processing (NLP) and AI to faxed paperwork transforms handwritten or textual content knowledge right into a construction that may be simply consumed by any system. This places actionable intelligence within the palms of suppliers on the level of care. The impression: extra knowledgeable care decision-making and higher coordination throughout suppliers.
• Suppliers not solely achieve perception into the affected person’s medical historical past and quick care wants, but in addition the SDoH elements that have an effect on total well being and long-term outcomes, comparable to issue understanding discharge directions, struggles to entry nutritious meals or transportation, or the stress that comes with residing in an unsafe setting. With this info in hand, clinicians can develop a plan to mitigate these dangers earlier than a affected person is discharged, decreasing the potential for problems and readmission after the affected person returns house.

Upleveling digital fax with NLP and AI bridges the hole between healthcare’s digital haves and have-nots by enabling organizations to obtain essential info when and the place it’s wanted, regardless of the place it originates or in what kind. It’s an reasonably priced, sensible answer that issues for well being fairness and in addressing SDoH.

Turning unstructured knowledge into actionable intelligence

If we’re to realize AI’s full potential to enhance well being outcomes and well being fairness at decreased value and decreased pressure for the organizations that present care, we should apply it in ways in which give all healthcare stakeholders a 360-degree view of a affected person in actual time. By leaning into clever knowledge extraction utilizing a instrument that continues to be closely relied upon in healthcare—digital fax—we will guarantee clinicians don’t miss useful alternatives to make a deeper impression, one affected person at a time.

Photograph: Filograph, Getty Photos