Autonomy Is Not a Preference — It’s a Clinical Requirement

For eleven years, I operated an independent urgent care center that functioned largely on a cash-pay basis. Many days, I drove my staff crazy. What frustrated them most was that, despite having general protocols for care, I frequently reminded them that every patient is unique and that testing and treatment must be decided on a case-by-case basis. They wanted simplicity and predictability—something closer to conveyor-belt medicine. But primary care does not work that way, and it never has.

Today, bureaucrats, administrators, and third-party intermediaries (you know who you are) are attempting to do something similar to direct primary care (DPC): make it measurable, standardized, and scalable. In doing so, they risk undermining the very foundation that makes DPC work in the first place—autonomy. Thanks to Dutch Rojas for introducing many readers to the work of James C. Scott, a political science professor at Yale University. In his book Seeing Like a State, Scott describes how governments and large institutions attempt to make society “legible”—easy to see, measure, and control from a distance. To accomplish this, complex realities are simplified into maps, categories, metrics, and standardized systems.

While legibility helps large institutions administer systems, it often ignores the messy, local, practical knowledge people rely on in real life. When top-down planners impose simplified models onto complex human systems, Scott argues, they frequently damage or destroy what was already working organically. The result is inefficiency at best and failure at worst.

Scott calls the ideology behind this impulse “high modernism”—the belief that technology, scientific management, and rational design can engineer optimal systems from above. Modern healthcare reflects this thinking clearly. Those in positions of power seek to make primary care legible through data: RVUs, ICD codes, HEDIS measures, quality scores, visit counts, and panel sizes (sound familiar?). Once care is reduced to standardized measurements, it becomes easier to control, compare, and manage. As Rojas summarized the idea: 

what cannot be enumerated cannot be administered. 

what cannot be categorized cannot be controlled. 

what cannot be standardized cannot be scaled.

This mindset has pushed primary care toward the brink for decades, contributing to moral injury among physicians and a gradual erosion of medicine’s foundation. Primary care is not scalable in the way factories are scalable. It is not a product; it is a relationship. Administrators and payers see primary care through metrics and dashboards, but what actually matters is trust, pattern recognition over time, narrative history, intuition, judgment under uncertainty, and knowing this patient—not patients like them. Scott refers to this kind of local, experience-based understanding as metis, or practical knowledge.

The defining strengths of DPC—continuity, flexibility, and individualized care—are inherently non-standard and context dependent. In Scott’s terms, primary care is largely illegible to centralized systems. Traditional healthcare attempts to simplify care into abstractions: a visit becomes a billing code, a patient becomes a risk score, and a physician becomes a throughput unit. DPC rejects this framing. A patient is a human being. Care unfolds over time. Value is contextual.

By removing billing codes, insurance intermediaries, visit quotas, and metric-driven incentives, DPC represents more than a business model change. It is, in many ways, an epistemological rebellion. It restores clinical discretion, temporal flexibility, narrative medicine, and local adaptation—precisely the elements high-modernist systems tend to erase.

Top-down systems assume that experts can design optimal processes, that standardization improves outcomes, and that variation represents inefficiency. Modern healthcare embodies these assumptions through clinical pathways, utilization management, formularies, prior authorization, and population health dashboards. Yet primary care thrives on variation. One patient needs reassurance, another needs confrontation, another needs time, another needs restraint, and another needs trust built slowly over years.

DPC embraces what might be called controlled heterogeneity, which Scott argues is a source of resilience. Variation and local knowledge—the metis of medicine—are not flaws; they are the lifeblood of effective care. In practice, metis means knowing when not to order a test, sensing when a symptom does not fit the story, understanding family dynamics, recognizing early decline before metrics change, and tailoring advice to a patient’s lived reality. These skills cannot be protocolized, scaled without dilution, or taught through checklists alone. They develop through time, autonomy, and experience.

Direct primary care maximizes metis by reducing patient panel sizes, extending visit lengths, removing bureaucratic noise, and preserving physician judgment. Critics often ask how such a model can scale. Scott’s answer would likely be that it should not scale in the conventional sense. Primary care scales horizontally, not vertically—through replication rather than centralization, through local ownership rather than standardization, and by enabling many small systems instead of building one large one.

Just as peasant agriculture often outperformed top-down, state-controlled farms, small, autonomous primary care practices outperform industrial medicine in trust, access, and often outcomes. The truth is that autonomy is not a preference—it is a clinical requirement.

From a Scottian lens, autonomy is not about physician comfort. It is about preserving complexity. It is about protecting adaptive capacity. It is about preventing epistemic collapse. When primary care loses autonomy, it becomes legible—but brittle. When it retains autonomy, it remains messy—but resilient.

DPC chooses resilience. It’s science.