Art & Science in medicine: Qual vs Quant

Today I want to talk about the blend of art and science in medicine. Medical research by nature has to operate at the population level; understanding how disease or pathologies present and progress *generally* allows clinicians to take these findings and, ideally, fit them to anyone who walks into their clinic. Unfortunately, human variability throws a wrench into this idealized flow of research -> findings -> knowledge that applies to everyone. Physical therapy and musculoskeletal rehabilitation is particularly difficult, because 1.) we all have differences in the shape and construction of our skeleton and soft tissue, and 2.) as I’ve mentioned in prior Tech Corners, we each adapt differently to our environments. This innate human variability makes applying generalized findings challenging (especially when much of the research is on limited population samples). Physical therapists joke that their practice is part science and part art. They run tests on their patients, but they’re not as quantitative as, say, a blood panel. New tech is bringing quantitative metrics into PT, sports medicine, and orthopaedic clinics through motion capture systems, pressure pads, force plates, and high-tech treadmills, but you still need the clinician’s training and years of seeing human variation to give this data context and prescribe actions in response. One crucial piece of context a clinician relies on is a patient’s self-reporting. Understanding what happens or what a patient does before they present symptoms and their health history, in other words, their personal context, is key information. The clinician is the algorithm! Their outputs are only as good as the data and context they receive. This is one of the reasons why health tracking outside of the clinic is only continuing to expand. Healthcare only advances when tools work for both clinicians and patients 🧠