Clinicians have been on the receiving end of some pretty terrible practices when it comes to information technology. Instead of informed and shared decision making, clinicians experience an assault of mandates, metrics, buzzwords, and acronyms without clear explanation or expectations. Not surprisingly, the pages of THCB and beyond contain frustrated denunciations of EMRs, dares for Dr. Watson to replace them, and dismissals of “big data.” This whole “technologists are from mars, clinicians are from venus” vibe is understandable, but it isn’t productive.
Data is the building block of measurement and now that it’s finding its way into healthcare systematic use of it to measure, improve, and provision care isn’t likely to be dropped off the formulary any time soon. It would be helpful then to have a shared language to allow clinicians and technicians alike to cut through the fog of jargon and focus on using data productively.
Developed through trial and error (mostly error) is a simple heuristic that I have found useful for establishing a shared understanding around using data in healthcare. I’ll call it Data Thinking, if only to keep with the tech tradition of stealing working names from other products (in this case, Design Thinking).
Data Thinking is a simple way of coming to consensus, explaining the jobs to be done, and mapping buzzwords to function. Regardless of vendor, technology, or buzzword, making data useful falls into a few basic steps:
Access – getting your hands on the data
Structure – getting it to “apples to apples” so you can do the math
Analysis – learning what matters
Interaction – putting it to use: right place, time, people, presentation
We all know Luddites. They proudly pronounce their rejection of Facebook and feign disgust about how they finally “broke down” and bought that awesome Motorola Razor they still carry. Maybe you are a Luddite or pretend to be because you can’t make Gmail work on your phone. So who was this Ludd and why is he the timeless symbol of rage against the machine?
My guess was that the original Ludd was probably some horse breeder that bet the farm against the future of the automobile. As it turns out, the Ludd story is not at all what you’d expect.
Legend has it that in 1779, a fed up British factory worker named Ned Ludd took his aggression out against the knitting machines he was employed to operate, smashing two of them to pieces with a hammer. In this one brazen act of defiance, he became the symbol of man’s rebellion against automation, technological displacement, the death of artisanship, and the worsening conditions of the working class.
Not long after, as the Industrial Revolution gained steam (terrible, I know) young Ned became the poster boy, quite literally, for factory worker uprisings each of which was punctuated with the destruction of machines.
The Luddites met in secret and their operations ranged from sabotage to all out warfare, including a battle with the British Army. They became so fearsome that industrialists had secret chambers constructed in their factories in which they could hide should the Luddites come knocking. Fearing that the name “Ned” lacked gravitas, his PR team apparently took to branding him King Ludd or General Ludd.
It’s 8:15 on Friday evening. I’m almost through editing the job description for a user interface engineer after sending off an introductory slide deck to a potential client. Today I met with a business development prospect, held calls with a potential advisor, a potential client, and finally made those changes to the website. There’s not time to write this but when will there be? I’m part of a growing trend of academics, programmers, and clinicians taking the startup path to try to make healthcare a better place. In fact, record breaking amounts of venture funding are pouring into healthcare with 2014 seeing $4.13 billion in digital health venture funding and 2015 showing no signs of slowing. Established tech companies not typically associated with healthcare including Apple, Samsung, Google, and IBM are getting in on the act with substantial investments. It seems that nearly every hospital and insurer is launching its own incubator or innovation fund.
The real question is why, after decades of lagging behind nearly all other industries in the adoption and use of information technology, does healthcare seem to suddenly be such a hotbed of activity?
The answer: data matters like never before in healthcare.