Notes on the Perfidy of Dashboards
I spent the past four years working as a data scientist for a healthcare company on population health initiatives, and started building out a body of research around how to engage clinicians using data (among other things, through dashboards). That&#x27;s a bit different than the article, but one of my key learnings was that dashboards are often incredibly ineffective and only promulgated by well-intentioned engineers, based on what they would want to see if they were a clinician.<p>I worked with a behavioral economist, and we started running RCTs looking at different approaches to sharing data, and found that dashboards led to less engagement, when there was engagement it was more likely to drive ineffective interventions, and generally our dashboard groups had worse patient outcomes. Non-dashboard approaches had 20x better engagement and anywhere from 20-100% better patient outcomes (depending on the condition).<p>Unfortunately, both of us left the company when a bunch of engineers moved in, scoffed at our work, and immediately said &quot;doctors need to be able to slice and dice their data&quot; -- which, by every measure we had tested, is simply not true. But the &quot;mission control&quot; style thinking, where you have tons of dials and numbers flashing on a screen, pervaded because it &quot;feels&quot; like the right answer despite being the objectively wrong one.