Reaching big goals with simple automation

Sometimes the way to achieve the really clever, complicated stuff is to actually do one very simple thing first.

This principle is how we were able to set our client on the way to an AI enabled, completely digital system for patient record keeping. With one small change to how they processed patient records, a whole world of new possibilities for data-driven patient care opened up.

We redesigned basic wound-care record forms, and used Optical Character Recognition (OCR) to automate getting data off the form, and into a data warehouse. This allowed not just faster processing of patient records, but also a way of consolidating and collating patient data. The more data you have, the more you can analyse, report, and ultimately, learn.

By first improving this simple process of data extraction, we set the groundwork in place for our client to achieve their bigger, longer term goal to do more with their data.

The challenge

Keeping records of wound care had been problematic. The issue was that without a central data warehouse, it was difficult to collate the various different data points gathered about a patient in order to use them in a meaningful way; for example, images, diagnostic records, treatment plans and outcomes.

The current clinical reporting form could not easily be automatically scanned, which meant patient data would have to be manually transcribed in order to run reports on outcomes. It involved a combination of tick boxes and free text inputs, filled out by hand, by clinicians. Have you ever managed to read a doctor’s handwriting? Us neither. Imagine getting a computer to do it – could be tricky, right?

Well, luckily there are lots of pre-configured tools available to do just that. But with so many different AI systems available for automating data extraction, which would be the right one to use?

The solution

We knew that we could very quickly build a working prototype to scan documents, extract the information, and store it in a data warehouse. We initially used Google Cloud Vision to demonstrate how this would work, and act as proof of concept for our client, allowing the project to move ahead quickly.

However, we also knew that - for this particular scenario - Google Cloud Vision was an unwieldy beast, and probably wouldn’t allow the degree of fine tuning and flexibility we’d need in the system.

The solution we actually delivered to automate data extraction was built with a much more custom approach. Using Tesseract OCR, we were able to build a system which could process each input field independently. Having this degree of control was important, but there were other benefits too. It was important that the solution was cost effective, and in this instance, Tesseract OCR had the edge. Forms were not only read faster, but also – crucially! – accurately too. It meant that all the information could be stored in a consistent format, error-free, and much faster than would be possible manually.

Interesting. So now what?

So just imagine how much more suddenly becomes possible when all your data is available at your fingertips like this. For our client, what this looks like in practice is being one step closer to a fully integrated system of data-driven patient care. It means they’re able to collate all the relevant information about patients in one place. It means being able to run timelines of care and treatment plans versus outcomes, run deeper reporting, access better insights and just generally start to make better use of the technology which is already out there. It’s a wise move. Because you can bet that if even you don’t do this, your competitors will be doing. And if you’re not moving forwards, eventually you’ll get left behind.

Sometimes, to unlock huge possibilities, you’ve just got to start small. If the future of healthcare is big data, then automating the first steps is just the start.

Perhaps you’ve got some big goals to reach, and don’t know where to begin? Good news - we can talk about AI and this stuff all day long. We’d love to help you get one step closer to what you want to achieve, with the right tech. Drop us a line if that sounds good.

All this data allowed for much more meaningful reporting on patient outcomes. With complete and standardised records of wounds and wound care, users could now more accurately compare treatments, and predict the time it should take a patient to heal.

With this knowledge, you also become much better able to predict supply and demand of wound care products, and forecast more effectively. All round? It means a tighter grasp of how patient outcomes impact commercial decisions, for both users and suppliers of medical technology.

Our system opens up a whole new set of possibilities for our client, to offer data-driven and AI enabled benefits to their own customers, setting them ahead of the competition.

We know this is how it all starts, and when we say ‘all’, what we mean is the future of healthcare and medical tech. Taking the leap into AI to solve your short-term problem is the first step on the way to innovating in ways you’ve not even thought of yet.

Maybe we should talk about what AI could look like in your business?

Our other case studies:

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