As we address the issue of quality in healthcare, there is much to be learned from other industries. I believe our current approach, though, is a dangerous one, one that won’t yield the desired results. Thus far, we’ve approached quality assurance as if healing were an industrial process, a process similar to those that yield cars, air conditioners, or even cheeseburgers.

But in an age where science, technology, and health policy are all changing at an unprecedented pace, we must ask a simple question: How should we assess quality in our industry?

The word “quality” elicits confidence, a sense we are discussing something of great value, something highly desirable and useful. Corporate quality strategies such as Six Sigma, however, can only reassure us that products have been through a predictably similar process, that they contain no deviations from their intended design. And in manufacturing, because they limit unwanted variance, these programs make sense, despite telling us nothing about a product’s intrinsic value or effectiveness, about its suitability for our particular needs, tastes, or budgets.

In healthcare, though, it is often the very variances identified as “defects” by these programs that can improve a patient’s health. Good physicians are not assembly line workers executing repetitive tasks. Patients are not cars, comparatively simple, inanimate machines lacking free will. And identifying “defects,” in the industrial sense, is challenging given our incomplete understanding of human beings’ “intended design.” So directly applying industrial quality principles to medical care is an ill-conceived, albeit well-intentioned, goal.

Healthcare quality programs must limit unwanted variance (e.g. wrong therapy, unnecessary test), while retaining desired variance (e.g. patient preference, physician judgment) and accounting for inherent variance (e.g. genetic or socioeconomic determinants of health). Failing to recognize the need for this new paradigm will lead to problems, big problems, particularly as financial and therapeutic decisions are increasingly tied to quality. In fact, we’ve already witnessed this in other industries under similar pressure to measure and improve.

In education, No Child Left Behind sought to bring quality, accountability, scientifically based research, and standardization to our classrooms. It also fueled discussions about tying teacher compensation to student outcomes. (Sound familiar?) But the legislation has been deemed a failure by many educators. Why? It failed to recognize that every child is unique, that even perfectly healthy, well-adjusted children learn in different ways, that teaching is more than a series of easily reproducible tasks, that standardized test scores do not accurately measure learning.

Our industry’s approach to quality has consisted of a rushed, almost frantic quest for uniformity of process and outcome, an approach not unlike the overly simplistic one used in education. And, not unlike the aforementioned emphasis on standardized testing, it has been dominated by a frenzied search for things easily measured, for data we can use to declare patient encounters “failures” or “successes.” But does that approach help us identify true quality?

If a patient has diabetes, an HbA1C of 7.9 is a failure, right? Can’t decide? Okay, let’s talk prevention. A healthy 61-year-old man hasn’t had a colonoscopy — defect? Not sure? Let’s look at outcomes, then. An 81-year-old woman with advanced dementia dies of a nosocomial infection after being admitted and intubated three weeks earlier following a massive stroke — failure? Where was the “defect”? Was it in the treatment of the dementia or the vascular event? Was it that she acquired a nosocomial infection? Was it that her suffering was extended with admission and intubation?

We can’t assess patient care based on isolated pieces of information or marginally applicable national guidelines, nor should we assume every patient interaction can be evaluated in terms of failure and success. Improving health is primarily a local endeavor that is informed, but not governed, by insights gleaned from global research. And our desire to categorize outcomes, to modify them, must be tempered by realities inherent to the human condition, realities that include free will, suffering, and death. So how should we proceed?

The practice of medicine requires compassion; programs assessing and rating it should be equally compassionate. Compassionate quality programs would strive to understand the nuances that make real patients, even those with similar conditions, unique. They would apply that knowledge to assess, rate, and improve care, not to manipulate data, label patients, or penalize physicians. They would not seek “assurance,” “control,” or “compliance” but rather realization, realization of the full potential in an inherently human system, a system limited in its ability, and in some cases, its right, to modify variables that profoundly impact the very outcomes it seeks to measure and improve.

To properly assess, rate, and improve care, a Compassionate Quality Realization Program ℠ must be:

1. Local

• Address regional variation in genetic, demographic, or socioeconomic determinants of health.
• Account for geographic variation in insurance coverage and the availability / cost of drugs, diagnostic tests, and other interventions.

(Without appropriate context, healthcare quality ratings mask local disparities, often correlating poor outcomes with sound care.)

2. Comprehensive

• Assess care longitudinally.
• Recognize both the multifactorial origins of disease and the equally multifactorial nature of healing.

(Reliance on individual disease markers / isolated outcomes dismisses the complex interrelationships within human beings / local delivery systems that impact health.)

3. Agile

• Develop assessment / rating criteria as part of an ongoing, iterative process.
• Seek consensus amongst all stakeholders, including patients and physicians, not just payors, as to what can and should be measured.

(Programs that aren’t agile evaluate current care using outdated guidelines and inappropriately subordinate the interests of some stakeholders.)

4. Objective

• Evaluate outcomes fairly, without unduly rewarding or penalizing delivery systems solely based on organizational structure, size, or other indirect criteria.
• Be reasonable and transparent with regard to funding.

(Entities assessing and rating quality must be held to the same standard of unbiased transparency as those engaged in the work they seek to assess.)

5. Practical

• Distinguish modifiable elements of patient care from those beyond its scope.
• Weigh scientific evidence, physician judgment, and patient behavior / preferences proportionally.

This paradigm challenges the concept of evidence-based medicine. But the profession has always demanded more than unwavering faith in transient, narrowly applicable guidelines. We must reframe the quality discussion to recognize “evidence-informed decision support” as one part of a “reason-based medicine” approach that also values physician judgment and the nature of the humanity it serves. (Scientific evidence is ephemeral and discrete; the human condition is immutable and universal. Only reason can reconcile the two, and our greatest challenge is achieving consensus in applying it.)

Compassionate Quality Realization ℠ will require hard work, patience, discipline, and significant investment. But if we want to improve outcomes and control costs, if we want quality to have real meaning in healthcare, we need to do this right. In education, we’ve unfairly labeled children “defective” and teachers “failures.” Let’s not do the same with patients and physicians, especially if we aren’t really improving anyone’s health along the way.

Luis Collar is a physician who blogs at Sapphire Equinox. He is the author of A Quiet Death.