Hacking Healthcare: How Technology Can Upend Fee-For-Service Care
A conversation with Steve Daniels, C0-Founder and President at Able Health
Despite all of the noise and innovation in the healthtech world, we’re at a crossroads. Software is eating the world, as Marc Andreessen noted years ago, but healthcare is still lagging behind: expensive legacy systems are costly to maintain, the regulatory environment is difficult to navigate, and, as we all know, people don’t always do what’s best for them.
At BaseHealth, we believe that the developers and engineers behind today’s most promising technology will forge the road ahead, invent new solutions to legacy problems, improve the overall healthcare experience, and, ultimately, create a healthier future.
That’s why we’ve started this series — to recognize and celebrate the people whose behind-the-scenes innovations are driving healthcare toward a brighter future.
In our eighth edition of Hacking Healthcare, we interview Steve Daniels, Co-founder and President of Able Health. Able Health’s platform aggregates patient data from one or more EHR systems, claims databases, and other sources to ensure organizations get credit for every diagnosis, encounter, and clinical activity. Steve uses human-centered design to deliver products that care for their users. Previously at IBM, he designed and built enterprise healthcare applications, including a patented Watson-based clinical decision support tool, a mobile patient engagement app in partnership with Apple, and advanced population health management for IBM Research. He has founded three ongoing social enterprises. Steve holds a BA from Brown University and has spoken at TED and Pop!Tech. You can follow him on Twitter at @steveddaniels or on Medium @Steve Daniels.
What are you working on right now and how will it impact healthcare world?
I’m building a platform that gets doctors paid for quality care. The old way of paying doctors — fee-for-service — encouraged provider organizations to perform way more tests and procedures than were necessary. Now the US has the most expensive healthcare system in the world, yet it also performs poorly in quality. A new model called pay for performance rewards providers for meeting quality and cost metrics.
Pay for performance has been accelerated by the Affordable Care Act, but it imposes a massive administrative burden. Able Health pulls data from EHRs, claims, and other sources to simplify reporting, compensation, and care coordination.
Other healthcare startups should know that pay-for-performance metrics will be a major driver for providers to purchase solutions that help them improve in certain categories of conditions and care coordination. We’d love to refer underperforming providers to the best solutions in every category.
What is Able’s Health’s most difficult technical challenge?
Measure development is a deceiving challenge. A lot of people who have worked in population health ask, “What’s so hard about a numerator and a denominator?” But calculating a reimbursable measure is different. A measure specification might require calculating the percentage of patients with diabetes who have controlled lab results or what percentage of those in a certain age range have received immunizations. You need to know a patient’s encounters, diagnoses, procedures, lab results, insurance status, medications, and demographics, and you need to check every encounter to make sure these elements meet the nuanced clinical and administrative qualifications of each component of the measure. This becomes even more challenging when dealing with huge volumes of data from EHRs and claims. Our engineering team is brilliant, and they’re challenged every day with some of the hardest problems of their careers.
Describe your development environment. How is it unique?
We embrace Extreme Programming, which is a great fit for measure development. One component is Test-Driven Development (TDD), writing test cases (in our case, test patients), followed by the minimum amount of code to make the tests pass. Our measures need to be 100% accurate, and TDD bakes validation into the development process. Another component is pair programming, which ensures that everyone is aligned and up to speed on the complexities of the domain and codebase. I don’t think any other company that develops measures is writing them at our level of quality, and that matters when patients’ lives and doctors’ reimbursements are on the line.
From a technical standpoint, our stack is Rails, JavaScript, and Postgres. Because we use so much SQL to calculate measures, we make extensive use of Arel, which simplifies the generation of complex queries.
Is regulation limiting healthcare IT’s impact?
It actually benefits startups to embrace regulation, which is an important driver for customers’ purchasing decisions. The most successful digital- health companies are deeply driven by the requirements and incentives of government policies and programs, and now there are now lots of resources to accelerate HIPAA compliance — we love Aptible.
The real problem in healthcare is access to data, especially clinical data in EHRs. Vendors don’t have the motivation to offer modern and complete access to their customers’ data, so much more could be done for providers and patients if access were simpler.
What is the most promising sign in healthcare today?
I’m encouraged by the wave of startups racing to aggregate the data layer of healthcare into easy-to-use platforms for applications. These include Fleet Health, Akido Labs, Human API, Mana Health, and Catalyze. It’s too early to tell how this layer will evolve and whether a standard data model will emerge through either competition or regulation. We like Fleet in particular because they’ve embraced the open FHIR data standard.
How did you get your start in the industry? What drives you?
My first digital-health project was leading front-end for IBM Watson in clinical decision support. The team consisted primarily of computer science PhDs, so my role spanned both front-end development and UX and visual design. As cool as Watson’s technology was, I was more fascinated with how doctors were going to use it to diagnose and treat patients. I went on to fill similar roles while working on patient engagement and population health applications at IBM.
At the same time, I began to develop my own chronic condition, gut dysbiosis. It has taken me all over the healthcare system, and I’ve seen it at its best and worst. This solidified a lifelong commitment to digital health; in particular, to delivering experiences that aid professionals in doing their best work. There’s way too much shitty software that doctors and administrators have to deal with. When we make their jobs easier, we improve patient experiences.
