Especially in healthcare. Although truthfully, if-you-build-it-they-will-come has rarely worked well for any company, Apple being one of a handful of exceptions.
But, according to John Brownstein from Boston Children’s and Adam Landman from Brigham and Women’s it definitely doesn’t work in healthcare. These two fine gentlemen put the record straight on that in a recent Rock Health podcast.
John and Adam are each responsible for innovation centers at their respective hospitals, so they’ve seen their fair share of pitches. So, what really counts…? Well, anyone who’s been around healthcare for very long will have heard of the quadruple aim. Building on the IHI’s triple aim, the quadruple aim looks to:
- Improve population health
- Increase patient satisfaction
- Reduce per-capita healthcare spend
- Improve care-giver satisfaction
And the quadruple aim is a must-have for start-ups looking to impress both men. As John states, “We want to understand how that product meets the IHI’s triple aim, and I would extend that to the quadruple aim.”
So what does that mean in practice for would-be healthcare entrepreneurs?
- Your product should address a sizable population, not just a handful of patients.
- It’s got to fit seamlessly into a patients lifestyle.
- It has to be more cost effective than existing approaches.
- Finally, at the very least it can’t increase the workload on clinicians. And trust me, in my experience, if you can reduce the burden on caregivers, you’re golden.
I used Tableau Public to compare the performance of acute care hospitals using the JCAHO core measures. The Centers for Medicare and Medicaid publishes performance data periodically. Essentially, the core measures show how frequently hospitals perform certain basic care functions – such as heart attack patients given aspirin on arrival at hospital, or surgery patients being given the right type of antibiotics at the right time.
My visualization shows 2012 performance compared to 2010 (you can switch between the two data sets using the tabs at the top left). The size of each box shows the number of procedures, the bluer the box the better providers are at complying with the guidelines. The data is there to go down to the individual provider level, but I have not taken it that far yet. So, on the face of it, hospitals are improving care quality because the 2012 treemap is bluer than the 2010 treemap.
That’s great – but not the whole story. Arguably, the biggest challenge for care quality right now is managing the transitions between care providers and settings. For example, the IHI estimates that 50% of medication errors occur because of poor communication during transitions. Technology can help with that – but for now, we’ll take the improvement in core measures….
I have college-age kids just around the corner. It’s a scary time – not least because I was fortunate enough to get my undergraduate degree in the UK at a time when the government paid for it! Oh happy days…
In the US – and even the UK now – people pay for college out of their own pocket. But, that doesn’t always mean you get what you pay for. As I’ve researched colleges with my eldest, it’s been very hard to make a meaningful like-for-like comparison. Even using so-called college comparison websites. For example, common measure like the 6 year graduation rate are close to worthless. So I was excited to see the federal government step in and reveal its own comparison site recently. I’m sure it will attract criticism, especially from those that are heavily invested in the status quo.
But, now we need the same for healthcare. We need this for healthcare because without transparency into healthcare there will be no change. Without change, the US healthcare system is unsustainable. And that should scare healthcare providers as much as citizens. Here’s a scenario – imagine I need a total knee replacement. (I don’t, but those knees have seen a lot of soccer…). Here’s the problem:
- How do I chose a knee specialist to perform the surgery? Where’s the public data – yes, actual data – to help me as a consumer sort the best, from the good, from the mediocre? It doesn’t exist.
- Where is the public data to help me compare costs – the cost of the surgeon, and the cost of the hospital or facility for a start? It doesn’t exist.
Caleb Stowell, MD and Christina Akerman, MD are of course right when they say that better value will come from improving outcomes. But, as a consumer, I need visibility into both outcomes and costs to make wise decisions about my healthcare. Sadly, the governments Hospital Compare website doesn’t even come close to providing what we need. Without such visibility, there is no real consumer choice, no competition among providers. Without competition, healthcare costs will continue to spiral out of control. That’s bad for us, but it’s worse for our children.
Managing unplanned re-admissions is a persistent and enduring problem for healthcare providers. Analysis of Medicare claims from over a decade ago showed that over 19% of beneficiaries were re-admitted within 30 days. Attention on this measure increased when the Affordable Care Act introduced penalties for excessive re-admits. However, many hospitals – including those in South Florida and Texas – are losing millions in revenue because of their inability to meet performance targets.
Carolinas HealthCare System has applied predictive analytics to the problem, using Predixion Software and Premier Inc. Essentially, by using patient and population data, Carolinas is able to calculate a more timely, more accurate assessment of the re-admit risk. The hospital can then put in place a post-acute care plan to try and minimize the risk of re-admission. You can find a brief ten minute webinar presented by the hospital here. But, from an analytics, information management and decision making perspective, here are the key points:
- The risk assessment for readmission is now done before the patient examination, not after it. Making that assessment early means there is more time to plan for the most appropriate care after discharge.
- The risk assessment is now more precise, accurate, and consistent. In the past, the hospital just categorized patients into two buckets – high risk and low risk. There are now four bands of risk so the care team can make a more nuanced assessment of risk and plan accordingly. Further, the use of Predixion’s predictive analytics software means that far more variables can be considered to make the determination of risk. Us puny human’s can only realistically work with a few variables well to make a decision. Predictive analytics allowed more than 40 data points from the EMR, ED etc. to be used to make a more accurate assessment of risk. Finally, calculating the risk using software meant that Carolinas could avoid any variability introduced by case managers with different experience and skills.
- The risk assessment is constantly updated. In practice, the re-admission risk for any individual patient is going to change throughout the care process in the hospital. So, a patients re-admission risk is now recalculated and updated hourly – not just once at the time of admission which was situation in the past.
- The overall accuracy of risk assessment gets better over time. A software-centered approach means that suggested intervention plans can be built in – so again reducing variability in the quality of care. But, the data-centric approach means that the efficacy of treatment plans can also be easily measured and adjusted over the long-term.
Overall, this data-driven approach to care is a win-win. It results in higher care quality and better outcomes for the patient. And Carolinas HealthCare System improves its financial performance too. This is all possible because more of the risk assessment is now based on hard data, not intuition.