For all the ways that technology has visibly transformed our lives as consumers over the last decade, it has seemed like just a matter of time before the excitement of big data, social, local, mobile, process automation, artificial intelligence, and blockchain (nb. use of buzzwords intentional) will make their way into helping us meet the aims of precision medicine and population health. Though I am quite convinced that health care as an industry can be one of the most rapidly changing, I think it is fair to say that the health care consumer (ie patient) experience has remained fundamentally unchanged during this period. It feels, if anything, that the gap is only getting wider. What’s taking so long?
Doctors are overwhelmed with data. They spend 12% of their time looking up clinical data when they could be seeing patients and still information gets missed. In fact, the IOM has identified untimely access to clinical data as a leading contributor to the 3rd leading cause of death in the US: medical errors. Existing information systems and electronic medical records are better optimized for billing and documentation than they
are for making care safer. There has to be a better way.
In aggregate, community health centers account for the care of about 20 million people in the US. Over half of these patients represent racial or ethnic minorities and over a fifth (22%) prefer to speak Spanish rather than English.
Most CHC revenue comes from fee-for-service reimbursement paid by Medicaid (40%), private payers (7%), and Medicare (6%). This has led CHCs to pursue many of the strategies for maintaining solvency as other care centers across the US, including increasing patient visit volume and improving operational efficiency.
One problem all clinic sites face is the incidence of no-shows, patients for which an appointment is scheduled but that do not show up. It is estimated that no-shows account for 5-30% of appointments scheduled across the US and it is typically higher at CHCs. No-shows risk failing to deliver appropriate care to patients for whom they are scheduled in a timely or continuous manner, reduce access to scarce healthcare resources for those waiting for appointments, and represent up to 15% of lost revenue for the clinic.
Testing design assumptions with users is a critical ingredient in user-centered design. In Symcat’s early stages (ca 2012), we thought, for better or worse, that we would identify some eligible test users through Craigslist NYC. We were surprised by just how many people were willing to participate and collected some pretty interesting data in the process. I just stumbled upon it and I suspect much of it is still relevant, so I thought I would share. Get ready for some graphs.
If you’re like me, you’re extremely excited about the potential for design to reshape health care. I’m not talking health care system redesign (ACOs and such–though that’s great too), I’m talking about the type of design you see on Dribbble: the focus of a recent (awesome) HHS-sponsored competition.
One of the promising upstarts of health care re-design was a 2-year-old-or-so startup called Massive Health founded by ex-Mozillite Aza Raskin. Though I tend towards the skeptical, there was a part of me that thought that not only were they on to something, but they clearly had managed to aggregate real design talent. And in health care, no less! Apparently, I was not the only one as they convinced a number of investors to throw $2.25 million in to test out what they could do.
Continue reading What Does the Massive Health Acquisition Really Mean? on the Symcat blog.
As exciting as the digital health space is right now, there is still little guidance or validated path to getting off the ground. As part of an effort to help aspiring health care entrepreneurs, I’ll be writing a series of posts explaining some of the decisions we made for Symcat. It hasn’t been a year since we’ve started, but my hope is that our few months of experience can help those who are just getting started themselves.
One of the questions I’m most frequently asked is if our time at Blueprint Health, a health start-up accelerator, was worth it. To participate, the program requires 3 months of relocation to the NYC offices in SoHo and the forfeiture of a nearly 6% equity stake in the company. The program basically offers $20k, mentorship from its network, and office space. A few other health start-up accelerators (ie Rock Health, Healthbox) have some variations but basically the same theme. They are all very selective accepting 3-5% of applicants. While it’s nice to be accepted, there’s still the important matter of deciding if it is right for you.
Continue reading Blueprint Health Startup Accelerator: Was it Worth it? on the Symcat blog.
When people get sick, they have several options for obtaining health care. These include going to the emergency room, urgent care center, or calling a doctor or nurse. However, 80% of people experiencing symptoms start with an Internet search. Unfortunately, searching on Google offers spotty results and frequently leads to undue concern. For example, one is 1000x more likely to encounter “brain tumor” in web search results for “headache” than they are to ever have the disease. Undue concern is a contributor to the 40% of emergency room visits and 70% of physician visits that are considered to be inappropriate.
Though in some ways replaced by ultrasound technology, cardiac auscultation–using a stethoscope to listen to a patient’s heart–remains an important screening modality for recognizing heart disease. Auscultation serves as a cost-effective screening tool for heart disease and is of particular importance in several clinical scenarios. Less emphasis has been placed on training US clinicians in auscultation, however, making this something of a “lost art.” This may delay a patient’s diagnosis of heart disease. Continue reading