Ayasdi started the year off with a bang – winning Accenture’s HealthTech Challenge Final Round in San Francisco during JPMorgan’s Healthcare Week. This award represents a massive endorsement of our clinical variation management application and the technology that underpins it.
The Final Round competition included 10 amazing startups – four from North America, two each from Europe, Asia and ANZ. The judging crew grew as well, to almost 50 judges from the world’s largest pharma companies, the biggest payers in the US and some of the country’s largest hospital systems. In addition, there were representatives from companies like Best Buy, GE Healthcare, and Medtronic.
The story we told was pretty simple but spoke to a complex problem. Here is a summary, including the slides we used:
The pitch started out with the size of the opportunity. Clinical Variation is an $800B+ problem in the United States alone. That number comes from the American Medical Association and generally covers all of those things that we do that does not improve the patient outcome or experience. We arrive at this figure by taking the AMA’s stats, pulling out administrative complexity and adjusting for the current cost of healthcare in the United States ($3T). It is a massive number.
More dramatically, that number has persisted for more than three decades – despite our knowing how to solve for it.
The answer is evidence-based medicine protocols. Evidence-based medicine works. No one in healthcare is debating that. The problem is we have never been able to scale it. The cost, time and effort to produce a care process model manually is extremely high (which is why the refresh cycle is around 4 to 7 years!).
Furthermore, the acceptance of those care process models (what we call adherence) is quite low, diminishing further the utility of the effort.
But advancements in machine intelligence and the availability of data change all that. They don’t eliminate the challenges, but they do make them far more manageable, and in doing so create the opportunity to reshape healthcare.
The challenge of clinical variation management lies in its inherent complexity.
Any healthcare episode can be broken down into component parts. How granular you go is a function of what you are looking for. For the purposes of this post, let’s keep it at a high level:
- Events (every lab, test, order, incision, and suture, done inpatient or outpatient)
- Sequences (you don’t put the new knee in until you have removed the old one)
- Timing (you don’t administer the pain killer the day before the surgery, you do it 1 hour and 40 minutes prior)
When you combine the three it creates a picture of extraordinary complexity where the events, the sequence of those events and the timing of the sequence of events all conspire to confuse even the most competent clinician. Add to that co-morbidities and, most importantly the mission of the organization, and it becomes overwhelming.
What do we mean by the mission? Well, the truth is that while as an industry healthcare serves the patient, how health systems do so differ. Stanford, as a teaching hospital has a different mission than Kaiser, who in turn has a different mission than Sutter – and we haven’t even left the confines of the Bay Area. Mission matters. Payers who use our product have a different reason for doing so than providers. Their mission matters too.
Because the problem is complex our natural instinct is to simplify. The result is providers (and payers as seen here) generally develop something rather general – something high level, often using national literature as a guide. This destroys adoption and adherence. These amorphous care paths don’t reflect the organizational mission or their patient populations – and so clinicians ignore them, adding to the mountain of wasted work.
We then made the problem very clear for the judges (we had 10 groups of 6-7 including Accenture folks):
This data is from 1,315 patients who had total knee replacement at a large midwestern hospital system. The range, for an elective procedure for which complications are minimal, is stunning. And it is not just the range; when you dig deeper into the data you find big cost blocks (15% – 20%) that sit on either side of the average.
It tells a story, that this procedure is being practiced both consistently and unevenly.
So how do we attack the problem?
First, we start with the technology that has earned us two mentions on Fast Company’s World’s Most Innovative Companies list. That technology, topological data analysis, is THE state-of-the-art in unsupervised learning. Using it we can identify groups of patients that had similar treatment paths. By identifying those treatment paths we can present multiple candidate care process models for the clinicians to evaluate – often within seconds. Compare this to 8-10 doctors taking time over nine to twelve months and you start to understand how powerful this is.
Second, we solve the problem end to end. That means everything from ingesting the data using the FHIR standard to automating the creation of candidate carepaths, enabling deep inspection of the results through to publishing and tracking adherence.
Managing clinical variation is a whole organizational effort. The application needs to reflect the need of the data architect, the clinician and the administrator. That’s what our application does.
Finally, we put all the technology, all those features, into an intuitive user interface. Simple, but with tons of features within a click or two. The ability to set time windows and alternatives for adherence measurement. The ability to have user-defined variables. The ability to customize the list of co-morbidities the organization wants to track. The list is pretty amazing.
At that point, we dropped into the demo and then into questions (some of which were really detailed).
To see what we demoed (sans the ETL app) check out this video.
That was it. Altering the trajectory of healthcare in nine minutes.
We used a slightly modified version for our final three minute, on-stage pitch which we included below.
Accenture’s HealthTech Challenge is a big honor and a massive platform from which to tell our story. We really look forward to taking advantage of it.