How automated chronic disease management can help scale care
A recent study from the Brigham and Women’s Hospital demonstrates exciting possibilities. Medicine is reaching a problem of epic proportions: without any changes to how primary care is delivered, in 2030 there will be a projected deficit of 14,800 to 49,300 (25th to 75th percentile) primary care physicians (PCPs). Chronic diseases (such as heart failure, hypertension, diabetes) are managed by PCPs and take up a majority of healthcare spending that accounts for 17% of the United States GDP. The problem is a supply and demand mismatch: too many patients, too few physicians. Historically, other industries have overcome this problem by utilizing structured “algorithms” to make product development more scalable, efficient, and with minimized variation in quality. Can medicine undergo its own “Industrial Revolution” to make patient care more algorithmic, scalable, cost-effective, while optimizing patient outcomes and reducing its variability?