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Future of Healthcare Q1 2023

How treatment-outcome data can unlock the door to better healthcare

Chris May

Founding Director, Mayden

Measuring treatment outcomes systematically has the potential to optimise and personalise healthcare for future patient journeys.

The healthcare system is facing a perfect storm: an ageing population and a historical lack of funding and resources. In times like these, its inefficiencies become all too glaring. “A major problem is that the system is fragmented,” insists Chris May, Founding Director of Mayden, a company that creates technology to support healthcare services. “Patient information isn’t thorough, consistent or joined up — technology and data sit at the heart of that.” 

Optimising the use of healthcare data 

One way of achieving this is with ‘outcomes-focused, data-driven healthcare,’ says May. This means using information about how past patients responded to treatment to inform and optimise treatment for present ones. Yet, it’s an idea which doesn’t often happen in practice. 

“Currently, a clinician will build up a profile of a new patient by asking them various questions, run tests, then use their clinical experience to work out the most beneficial treatment pathway,” explains May. “What the clinician can’t do, however, is find all patients in their database with similar profiles, look at the treatment pathways those people took and the outcomes they obtained. They could then use that data to inform the best treatment pathway for their new patient.” 

Data-driven healthcare is an inevitability.

Measuring outcomes to transform healthcare  

Why don’t clinicians work this way? Well, there are a few reasons, notes May. The most fundamental one is that — and this frequently surprises people, he admits — healthcare service often don’t measure outcomes consistently. If they did, it would prove transformative. 

Today’s digital Electronic Health Records (EHR) will include data about the type of treatment a person has received or is receiving. “For example, it will note that someone has had a hip replacement,” explains May.  

“But a hip replacement isn’t an outcome. It’s an input. What we really need to know is: ‘After that hip replacement, was the patient able to walk without pain?”  

Standardise to personalise 

“And what was the journey they took to get to that outcome? What happened in the run-up to surgery, what did the recovery period look like? When did rehabilitation start and what form did it take?’ Unfortunately, that kind of information rarely gets recorded systematically.”  

If it was, May argues that it could be used to design standardised treatment pathways tailored specifically to the needs of individual patients. That optimises healthcare — and personalises it. “It can seem counter-intuitive,” he admits. “But what might sound like a data-driven sausage machine is actually the opposite. It’s a very patient-centred way of working.” It could also identify potential problems early and be more cost-efficient. 

Giving patients more control  

Mayden has developed an EHR for the NHS’s talking therapies services, which includes the care pathway data and outcome measurements for 8 million patients. 

“That’s 8 million patient journeys that can tell us what works and what doesn’t for different patient cohorts.” 

It should also be possible to put this power into the hands of patients to level up patient-clinician relationships. 

“In many cases, the patient can feel subordinate to the clinician,” says May. “We already allow patients to book and manage their own appointments and input their own outcome measurements. Why not give them the data to make informed choices as well? Then they will feel more in control of their healthcare.” 

Personalised data is used to tailor the customer experience in other sectors such as banking and retail, so May believes that data-driven healthcare is an inevitability. “It’s going to happen — it’s just a question of when. Using data in a more productive and efficient way will improve the patient experience.” 

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