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10 key takeaways from Health Datapalooza 2014

Early June is Health Datapalooza time, and this year’s event was again a whirlwind of energy, […]

Early June is Health Datapalooza time, and this year’s event was again a whirlwind of energy, insights, and over 2,000 very motivated and passionate health data enthusiasts (health datapaloozers doesn’t sound right). The hallway conversations provided tons of of pragmatic, productive and engaging conversations, inspired by keynotes and presentations from Todd Park, Bryan Sivak, Jeremy Hunt, Atul Gawande, Steve Case, Jerry Levin, Vinod Khosla, Kathleen Seblius, Dwayne Spradlin, Francis Collins, Fred Trotter, and many more (if you haven’t heard of some of them, look them up, it’s worth your time).

  • Data liberation! US CTO Todd Park’s famous battle cry still holds true. We need to turn more data from “passive into active data” (US Secretary of Health Sebelius) and make them more broadly available and used. Here is some advice if you ask for or open up data: it’s key to be clear on what you want to use the data for, indicate who will benefit from this work, work with the data owner/hoarder in a collaborative fashion, and be transparent via open source. You can also use FOIA (freedom of information act).
  • Silos: I knew silos were a problem in US healthcare. But health data are are spread across more places that I had imagined. As an example, Athena Health had to create connections to 110,000 (!) other systems for the 50M patients that they provide EHRs for.
  • New data sources: more and more data collected outside the health system, contributing to #2: quantified self, social media, purchasing, location data. There are smaller sensors, cheaper devices, and a plethora of apps to help anyone track their health and lifestyle. There are few efforts to let individuals bring these data together in central platforms, and healthcare professionals typically don’t (want to?) use this information.
  • Patient in charge: patients can increasingly be in charge if they want to: they have better access to their data (150M Americans now have access to their health data via Blue Button), technology supports tracking of vital health information (see #3), and there are platforms that let patients bring (some of) it in one place, enabling them to analyze and evaluate what works and doesn’t work for them. UK Secretary of Health Jeremy Hunt put it best: the transparency of data reverses the relationship with the physician and puts the patient in charge.
  • Services in the background: we are now in phase 3 of the Internet (says Steve Case); after building the internet (phase 1) and building apps and services on top of the internet (phase 2), the internet is currently being integrated into everyday life, enabling much more seamless experiences that incorporate data from apps, devices, health information etc. But this is still very much in its infancy. See #8 for a potential approach.
  • 20% doctor included: Machine learning is key for the future of medicine. Cognitive limitations and an overload of information mean that physician diagnoses and treatment recommendations are not overly consistent. However, machine + doc will be the winning combination; a decent chess computer with a decent (human) chess player will outperform the best chess computer. Make sure to read Vinod Khosla’s paper 20% doctor included.
  • We heard of fabulous utopias where all data on an individual are in one place, enabling smart machine-learning algorithms to monitor vital signals, predict health risks and enable and encourage prevention. There are different options to get there (more on that in a future post), but none of them is a shoo-in.
  • Walled gardens: the announcement of Apple’s HealthKit created additional fodder for discussion about walled (healthdata) gardens; their collaboration with (walled) electronic health record provider EPIC makes that garden potentially bigger but not more open. However, there will be more opportunities to have health data from iOS apps contribute to the same central system, likely in a very user friendly way.
  • It’s the sickest patients who are driving cost. Our health and data collection systems are currently not designed for them, and new services like Patientslikeme are not integrated into healthcare delivery.
  • Getting to the roots: the app demos and start-up showcase showed amazing progress we have made. While a flurry of apps at past events sometimes looked a bit gimmicky, this time there were several efforts that address issues at the health system level (have a look at some of the start-ups here).
  • A huge thank you to the Health Data Consortium and CEO Dwayne Spradlin for a fabulous conference. Looking forward to Health Datapalooza 2015, 5/31-6/3 in DC.
    And if you missed it, we launched our new white paper on Communicating Data for Impact at the conference and got quite a bit of nice feedback. Enjoy the read!


    Peter Speyer

    Peter is the Chief Data & Technology Officer at the Institute for Health Metrics and Evaluation (IHME) at the University of Washington. He is responsible for in global and public health with data from governments and organizations around the world, keeping data at the institute organized and secure, providing the computational infrastructure to run complex analyses, and sharing results via interactive data visualizations.

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