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Joachim Werr, HN - AI Guided Case-Finding | LSI Europe '22

Speakers

Joachim Werr

Joachim Werr

Founder & Executive Chair, HN
Read Biography
The company's HN Predict is a software solution designed to help clinicians identify patients at risk of adverse and preventable events by analyzing routinely collected healthcare data and transforming it into actionable data that enables predictive and reactive healthcare.

Transcription

Joachim Werr  0:10  

My name is Joachim. I'm the founder of HN Health Navigator. Something as unusual as a profit making growing digital health company founded in London and having business across the UK and in Ireland, and we're here to attract investors to join our journey as the first external investors to take our products further scale into the US. Any of you remember this late afternoon wallet Bernd Montag said this morning around the key challenge that healthcare is facing. He couldn't decide for one, but he mentioned three. But the first one he mentioned was the lack of skilled clinical staff, which is actually costing lives in the system. I don't know how many of you are from UK. But those of you who aren't. These is the challenge we're facing the NHS in the healthcare system every day, almost 7 million individuals are waiting for care in the UK 400,000 of them have been waiting for more than one year 40% of those who attend a&e Any day we'll need to wait more than four hours. And you'll know what there are plenty of studies out there demonstrating that it costs live to not get access to unplanned care. At the same time, there is a staff shortage in the NHS of around 1 million, including social care 1 million people missing every 11% of GDP are on staff. We can't staff those we don't have more staff, we need to change the model. And that's where a chunk comes in, we believe we can predict and prevent care instead of delivering more. HN was founded in 2015. In the UK, we started with a large randomized controlled trial. We do use routinely collected healthcare data that is available in a hospital or in social care and process that through our AI NML in order to generate risk scores that identify individuals who will crash into the A and D who will get stranded in the hospital and who might be prevented and we have demonstrated clinical efficacy in a large clinical trial. I have a clinical background PhD from the Colin's can Stockholm and the founder, Mark England our CEO has a software background he ran one of the first integrated care systems in the NHS. And his last position in the agent service was Deputy National Director of origin and emergency care. He joined NH three years ago, we own the company together. Here's the problem statement. 50% of all non elective bed days are occupied by 1% of the population. I think that's generally known. But What is less known that this group of high consumers has a turnover of 90% per year. So 90% of those individuals who consume most care on you the next year. What we have done is we have built a data engineering solution and algorithms that can identify those who will become the super users of care. And we can do that agnostic of the diagnosis because most of these patients will have several diagnosis, of course, congestive heart failure, COPD, atrial fibrillation, hypertension, diabetes mellitus, without complications, etc, etc. But these individuals are not defined by a single diagnosis. They are defined by a multimorbid problem and challenge. And we have demonstrated not only we can find them, but we can support them in a scalable, effective way. Our core product is HN Predict. It's a SaaS platform that harvests data from different sources. And we can adopt the model to the sources and the data available. We process those data obviously in an IG compliant, fair way. We apply AI and ML on those data to identify those individuals that have certain risks, clinical crisis, readmissions, unplanned admissions, a serious falls, etc. And we push that data and that, that information back to the clinicians or our own staff. We do not only have HN predict we also have a case management platform and can wrap around those digital services with advanced population health analytics. Our customers either contract our SAS or they contract an end to end service, which both has the SAS confidence but also the clinical staffing. Back to burn contacts point is not only about technology, it's also about stuff. In 2015, we started a large randomized control trial ethically approved by the HRA NIHR adopted, that trial came to an end which due to 2000 individuals in a trust, here are the outcomes. They are partly published, they are partly about to be published. And part of this is also under patent application. I won't go into the details, but I want to show you one slide that I'm particularly proud of. And we didn't expect this. After the trial was closed, we saw an unexpected reduction in mortality in the entire group of those who received the intervention compared to those just receiving NHS standard treatment. When we controlled for age and gender, we found that the impact was almost entirely related to elderly males. And you see in this Kaplan Meier curve, that we could reduce the mortality in these elderly males with 48%, statistically significant, and right now impressed. The hypothesis, of course, is that these elderly males are poor at engaging with primary care. They have their diseases, but they don't show up in any type of preventive care before they crash into the a&e, and sometimes do that too late. We have a GP on our advisory board. He said when he saw these data, he said, Yeah, I know that elderly males do not come to the GP unless their wifes forced them to do so. So obviously, not all of them have wifes that forced them to go to the GP. We're probably quite proud around these results that were unexpected. We have customers around 20 in the NHS in England and Scotland, and they also live in Ireland. And they the revenue streams are coming from different products from the NBN solution to SAS and the wraparound services. Obviously, we are growing and the market is not defined by a finite value. It's defined by the NHS and the health system just starting to adopt and use predictive algorithms to better recruit patients into care rather than have them referred into care. 4 billion of preventable a&e attendances and admissions in the NHS. That's the NHS own assumptions. The US market, obviously, much bigger, much more complicated. We realize that, but also a clear incentive because in the in the US markets, there's always an owner of the per patient cost in the European systems. There is normally not a clear own over per patient cost. It's rather the prosple or per GP office cost. Why are we here? We brought the company to a 3 million turnover. We had a half a million profit last year, we are here to raise 5 million to take the company to the next level, invest in technology, and marketing and sales. All the sales you see here are generated by Mike and myself. And we want to have an investor who shares our belief that we can transform care into predictive and preventive and joy and join our journey going forward. Thank you very much.

 

 

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