At the recent Health 2.0 Code-a-thon in Mountain View, CA, developers and healthcare futurists from across Silicon Valley gathered to conjure meaning from new oceans of data. Held on the Google campus, the San Francisco Bay Area Code-a-thon is only the first in a series of events aiming to mine resources freed as part of the White House’s Open Government Initiative. With mountains of new datasets from data.gov come new opportunities for new applications to bring information transparency to healthcare. And the need to extract meaning from these data is greater than ever. Again and again, the theme arose over the course of the Code-a-thon that better tools are needed for interpreting this healthcare data glut if information is to be relied upon by providers, policy makers and patients to make healthcare in America work.
After introductions by the Health 2.0 production gurus and their partners at Google, a pitchfest was held that gave airtime to innovation. The beauty of pitchfests is that especially when certain groups get together, application developers and health policy pundits, for example, there is never a shortage of intriguing ideas. Application suggestions included automated personal health record data entry by applying character recognition technology to digital pictures, a T9-like system enabling deaf and blind children to better communicate with special technology-integrated gloves, and the rapid intelligent search from brainscanr.com enabling semantic mapping of PubMed literature. Other organizations pitching included Engage with Grace, which advocated provider education for end-of-life decision-making, and the Lucille Packard Foundation, a sponsor of the event, which envisioned information portals enabling school health records that increase safety and reduce absenteeism of children with chronic conditions. The HHS Office of the Assistant Secretary for Preparedness and Response called for a Facebook application to stimulate micro-communities of lifelines “decompressing care systems and increasing community resilience” during disaster response. Qpid.Me was there too, offering SMS-based confirmation of sexual health to facilitate safe decision-making before lucky nights get too hot and heavy. There was even a patient with an implantable defibrillator looking to hack into the data that the device collected, such as indicators of atrial fibrillation, arrhythmic events and chest impedance; despite benefits that real-time risk factors tracking could have, it seemed manufacturer systems lacked flexibility to perform even simple export functions connecting defibrillator patients with their own data.
Once the pitchfest concluded, the Code-a-thoners were off to the races with a suite of powerful tools. Public datasets through the CDC and data.gov, plus private data from Practice Fusion, Microsoft, Engage with Grace, the Lucille Packard Foundation and First DataBank, plus an open-source API with unique identifiers for every U.S. provider, plus a consolidated hospital dataset courtesy of Google Fusion Tables, plus best practices from Frog Design for applying the art of storytelling, equaled an expansive toolkit with which to build and communicate the value of new health information applications. The instant analytics and user meaning enabled by these resources were impressive, such as when Google’s Dr. Roni Zeiger demonstrated a map of hospitals conforming to user-determined criteria around cardiology health outcomes. Indeed, the possibilities for information transparency seemed endless.
Still, my fellow students and I from UC Berkeley’s Haas Healthcare Association could not help but notice that there was a conspicuous lack of data presented at the Code-a-thon around the cost of healthcare. With U.S. health expenditure climbing toward 20% of GDP, transforming the delivery system through information transparency necessitates a focus on value. Value is often defined as utility divided by cost, and only transparency in both the numerator and denominator will encourage the popular will to reduce waste from our system and re-orient our health system around efficiency. There are signs that data transparency around cost is improving with glacial inevitability, with Healthcare.gov providing one of the first neutral comparisons of insurance purchase options, as well as the raw data for independent analyses. Still, the recent lawsuit by Dow Jones & Company to overturn the injunction against public access to records of tax revenues paid to providers shows just how much of our health information treasury remains obscured.
If there was one takeaway from the Code-a-thon, it is that this trend of user-originated healthcare meaning is just beginning. “2014 starts today,” the ubiquitous health reform mantra says. As the health insurance exchange infrastructure takes form and we are all legally required to purchase coverage, ordinary folk technophilic enough to bank, chat and share content online will likely demand — and build — better tools to manage their personal health expenses and optimize the efficiency of their own care. As personal genetic profile, access to services and the cost of insurance coverage become increasingly intertwined, information transparency will become central to the ability for people to assume a more active role in their own health. By creating simple tools illuminating both the quality and cost of service providers, developers like those at the Health 2.0 Code-a-thon will enable small but critical steps towards the realization of personalized healthcare.
Stuart Kamin
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