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
