As we grapple with provider shortages, the surge in chronic illness and the quality to price (QPR as they say in the wine business) challenge in US healthcare delivery, it’s hard to imagine a future that does not include some sort of guideline or algorithm-driven care. As providers take on more financial risk, one common strategy involves team-based care, and the attendant increase in decision-making and care delivery by non-physician clinicians. If the je ne sais quoi feature of a quintessentially great doctor is clinical judgment and instinct, one of the challenges of this transition to team-based care is how to harness that trait and use it efficiently.
Care decisions that are unassailable at a population level (e.g., women should have regular, routine PAP smears or smoking is bad for your health) or are algorithmic in nature (e.g., titration of treatment for uncomplicated hypertension or therapy for mild to moderate teenage acne) can all be effectively reduced to guidelines. This, in turn, allows a physician to delegate certain therapeutic decisions to non-physician providers while maintaining a high degree of care quality. It is also thought that this type of uniformity of care delivery will improve the QPR too, by decreasing variability.
How do we come up with guidelines? Typically they are based on large-scale, randomized, controlled clinical studies. As is nicely articulated in a recent JAMA opinion piece by Drs. Jeffrey Goldberg and Alfred Buxton (JAMA, June 26, 2013—Vol 309, No. 24, pg 2559), guidelines are formulated based on the inclusion criteria for these trials. This process gives us comfort that guidelines are based on rigorous science — and that is a good thing. The challenge arises when we realize that individuals do not reflect populations exactly. Clinical research is much more complex than wet lab work because people are complex and indeed unique. Every clinician has had the experience of prescribing a therapy to a patient who fit guideline criteria exactly and having the opposite outcome of what the guideline predicts.