How CAREFUL works with AI and machine learning to improve patient outcomes

Ai And Machine Learning

How CAREFUL coordination works with machine learning and AI to help practitioners anywhere communicate securely and easily and improve patient outcomes.

AI is now ubiquitous; going by the challenges healthcare practitioners face every day in and across care settings the world over, care coordination is not.

AI* (i.e. pitting ChatGPT against Gemini) says care coordination is “the deliberate organization of healthcare activities and information sharing among all those involved in a patient’s care…essentially ensuring that different healthcare providers (doctors, nurses, specialists) work together seamlessly to deliver a cohesive and effective treatment plan for the patient”. We could take a poll, but the expectation is that seamless and cohesive is a future state that we are all still striving for.

AI says, “Effective communication between all healthcare providers involved is crucial”. It is indeed, which is why we think that because there’s a gap within legacy systems, the ‘effective’ communication happens via informal and unsecure means – WhatsApp (>95% of doctors use it to exchange patient information), email, phone calls, corridor conversations, paper…even FAX! What? AI for fax?

AI says this accounts for over 30% of patient data that is lost – or rather actioned outside of the legacy system and therefore unrecorded in said system.

And AI says a care coordination platform (such as CAREFUL) could help.

When quick decision-making by teams, or forward planning for groups of patients is required, practitioners exchange actions on WhatsApp, email, whiteboards, phone calls, bits of paper, spreadsheets, verbal instructions given on the fly and memory to move actions forward.

We think the first step is capturing all these actions – the millions of bits of data pointing to what needs to be done now, next, by whom and by when. Ripe for analysis by those who have been part of the exchanging, and for those who have identified the risks – to then be able to do something about gaps/blind spots/delays/errors.

That’s where machine learning comes in – taking the vast, unstructured bits of text, images, times and more and making sense of it all, producing insights for practitioners and help to ease the immense pressure and workload.

Next? AI**, the type that starts to think ahead based on all that it has already witnessed, suggesting next steps to help reduce the pressure a little bit more.

But we need a single source of truth, say individual providers – we say put this into your EHR. CAREFUL, machine learning and AI can, together, help improve the way we care.

CAREFUL captures an otherwise lost data set to create a new, competitive and rich moat for machine learning and AI … that can be used to improve efficiency and outcomes for the care provider and the patient.

The platform acts as a neutral hub, enabling secure exchange of patient actions (not just data) across different healthcare organisations, regardless of their existing electronic health record (EHR) systems. This provides a holistic, action-focused view of the patient’s health journey and better continuity of care.