Healthcare Interoperability & GenAI

The Oxford Dictionary provides the following two definitions for interoperability:?

The ability of computer systems or software to exchange and make use of information. "interoperability between devices made by different manufacturers"

The ability of military equipment or groups to operate in conjunction with each other. "staff believe interoperability between forces is crucial to effectiveness"

For years now, we have spoken of the importance of interoperability to the healthcare sector and how it will serve to deal with a number of issues such as:?

• Disjointed patient journeys?
• Continuity of care?
• Reduce risk of errors in treatment?
• Clinician enablement
• Accurate records?
• Serve a big data approach?

To deliver interoperability, several standards and protocols have been developed over a few decades and many are still at play for good reasons today:?

• XML?
• SOAP?
• HL7 (ADT, ORM, ORU, MDM, DFT, SIU, BAR)?
• FHIR?
• DICOM

This is just to name a few of these protocols that serve different purposes and sometimes compliment each other and are often necessary.?

I believe that Interoperability is a key ingredient to a successful and ultimate GenAI journey. GenAI relies on data and data in healthcare is more often than not stored in a fragmented way. Your family doctor will hold some data about you, your exercise family physician, Cardiologist, Obstetrician and Gynaecologist or psychologist will all hold a different set of data.? Interoperability is an important process for how we get to a model of a more comprehensive data set that we can use to build and train GenAI models.?The goal is to use the outcomes of analysing this data for both personalised care (You) and population health (community).

Inarguably the uptake of technology in healthcare has added value to the sector, there has been many learnings, a journey of surprises, and often pain. Now more than ever, we are seeing real benefits arising from the digital health journey; GenAI promises to change the world we live in from basic conversations to biomedical and drug research. Check this out after you finish reading this blog: “Daphne Koller on drug discovery and AI.”? ??

With the hype and the promise of GenAI, we often hear the term “Hallucination.” Hallucinations happen when a GenAI algorithm does not have the proper data, training, proper oversight, inaccurate or incomplete data; the system then makes assumptions in order to generate an answer.? The scary part is that the GenAI’s “Hallucination” is often an answer that is a? “Believable Real Response” for the reader.?

Whether you are an advocate, supporter or critic of GenAI, it is here to stay and one of the most important ways of “it” getting better is increased access to high-quality data. Let’s now bring the relevance of this to the healthcare sector.?

GenAI is only as good as the data we provide it and how we help it consume and understand this data. However,? Due to its ability to consume and digest such large amounts of data, it is going to be able to detect patterns and outcomes that are, if not beyond human comprehension, definitely identified much faster than humans can.?

“Data” is the constant that is required to achieve better results with GenAI every which way we view it. However, data in healthcare, more than most other industries, is fragmented to the point that I am sure some data today remains handwritten on paper or sitting on a fax machine somewhere, or better still both.?

?

Why is GenAI important?

We all get a warm and fuzzy feeling inside when we hear that scientists are advancing in their battle against one of the deadliest diseases in the world “Cancer.” GenAI is enabling researchers and research organisations to compute and analyse more data, faster than what was previously possible. We now hope that science and scientists can use these new tools to be more effective than the diseases that have taken so many lives and continue to.?

On the horizon for all of us in many areas and especially in healthcare, GenAI holds a lot of uncertainty but also a lot of promise. The promise of greater access to care by enabling clinicians, scientists and many front liners to achieve more with less and give them a wider and longer reach.?

The data journey in Healthcare, especially as it relates to GenAI, is only just beginning in my opinion and the challenges are real, from privacy and security to ethics and best use cases. Every one of us contributes data and I hope that we continue this journey in a constructive and effective approach and continue to use GenAI and other tools to find ways to continue to? improve the healthcare systems and ultimately care for every individual.?

Why Clinovera??

We are a team of digital health nerds at Clinovera who are in the trenches on these topics and have delivered and continue to deliver many projects globally. If you have use cases of Interoperability or GenAI give us a shout.?