How much measurement is needed for quality improvement is a Goldilocks problem, as this article points out. Too little and you miss critical information needed to guide decisions. Too much and you risk analysis paralysis and/or high respondent burden. Need some help getting started? With our friends Health Quality BC, we've put together quick tips on the foundations QI for long-term care and retirement homes, including measurement, here: https://lnkd.in/eT4TKFBK
“Without data, you don’t know if you have a problem, you don't know if you’re making any headway in solving that problem, and you don't know whether the interventions that you’re trying to test or implement are holding," said Michael Posencheg, MD, Associate Chief for Clinical Affairs at the Children's Hospital of Philadelphia. For teams who may feel intimidated by the prospect of measurement, Posencheg offers a helpful concept: “just enough” data. “Teams sometimes feel like they need to have all of the data to make a decision about something,” he said in a recent interview. “I think many teams get into this ‘analysis paralysis,’ where all they want to do is look at all the available data before making a change.” The impulse to be comprehensive, while understandable, can needlessly stall progress. https://lnkd.in/eznbeJyk
Member at West Toronto Ontario Health Team
2wGoldilocks can be averted by testing a "theory of performance" for a program... why do I think it works effectively. Data will not just follow a bunch of widgets, it will point to strength/ weakness in optimal performance. Refinement happens fast then.