Data Science BuFoL16 Nuno Almeida

The Untapped Potential of Data Science in Social and Health Care

Both the social and health care sectors have been under a lot of pressure recently, as they face a perfect storm of: cuts, capacity shortage, strict regulatory requirements and pressure to take part in informed conversations about further integration between health and social care.

Those of you who know Nourish will know that we are strongly opinionated about how to deal with this complexity. We feel that by designing all of your processes and organisational requirements focused around the people receiving care is the best way to deliver on the concept concept. As a result everything concerned will slot into place. However, you can only take full advantage of this decision if you use digital tools for care planning, recording and reporting, traditional paper recording methods won’t be able to handle the requirements.

By adopting this approach, we’ve found that care managers feel reassured about quality of care and experience less burden from non-care related tasks, time spent providing face-to-face care increased by as much as 40%, and providers found significant savings in non care related overheads.

As a result, we are demonstrating that by using technology in the right way, social and health care can become more efficient, but become more and most importantly human, while improving service safety and focusing on outcomes for those who receive care.

The advantages are obvious, but at Nourish, we believe that we are just scratching the surface of what’s possible with social and health care 

During a Data Science Workshop held at Bournemouth University as part of their Global Festival of Learning (#BuFoL16) held simultaneously in both the UK and Malaysia, our CEO Nuno Almeida talked about some of the data science applications that we are currently working on in Nourish. 

Our research and development team are structuring our first rules-based decision engine. Rules are a family of very safe and proven algorithms that allow us to automate various aspects of verification of quality of care, based on care records. 

These processes deliver a very powerful impact. Applications are vast, but some health care specific examples include detecting mobility trends from tele-care or wearable devices, and automatically triggering reviews of mobility care plans. This can even be extended to detecting whether people receiving care who are skipping meals are doing so due to mismatches in food preference, or if meal refusal is related to a specific care provider.

What are the impacts?

The impacts of these applications of basic data science are already noticeable within our current client base. One residential care client has stated that having the Nourish system in place feels like “having an additional carer in every shift” when it comes to the amount of help and information available. 

The Nourish research team is focused on evolving our state-of-the-art product to take our support to care teams to the next level. They are the ones ensuring care providers have all the information they need to have, when they need to have it, enabling those who care to focus on what really matters: dignified high quality care, delivered with empathy in a way that respects the wishes of each individual person.

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