Table 1

Differences in Processes and Outcomes Between Care Isolated to a Single Disease and Primary Care

ConstructIsolated Single Disease with Linear Mechanical ProcessesPrimary Care Nonlinear Adaptive Processes
Care process
Process complexityFew variables to be measured and controlled
Example: central line bundles
Numerous variables that make accurate measurement problematic
Example: patients with multiple medications, comorbidities, and socioeconomic challenges
Process standardizationStandard processes use consistent raw materials
Example: antibiotics administered just before the incision is made in elective surgeries
Variable processes with variable raw materials
Example: a wide range of disease severities and treatment options for the same diagnosis: eg, migraine, chronic low back pain, and fibromyalgia
Process controlsMachines and unconscious patients are largely controlled by their human operators
Example: procedure not started until the pre-surgical checklist is completed and chlorhexidine antiseptic has been applied
The patient “machine” is controlled by a milieu of forces, including caregiver biases, unique patient beliefs, socioeconomic status, and the external environment
Example: medication nonadherence associated with poverty, which is not controllable by the physician or the health care team
Outcome goals
Goal clarity: multimorbidityAll team members and machines work toward one clear goal
Example: titanium artificial hip placed in the appropriate position
There is no one right answer or goal, only an individualized understanding of risks and benefits where ideally the patients chooses the best answer for him or her
Example: another round of chemotherapy for a patient with metastatic cancer vs hospice care
Goal clarity: unique patient prioritiesPatients and caregivers agree on clear outcome
Example: minimum days intubated on mechanical ventilation
Patients have different goals or priorities from their caregivers’ recommendations
Example: a diabetic patient who does not want to start taking insulin to reduce her blood glucose because of concerns about the affordability of the medicine and a belief that insulin killed her aunt
Goal timingStandard processes have fixed expectations of the timing of interventions
Example: daily trials of endotracheal tube extubation
The timing and order of addressing patient concerns are highly variable
Example: the primary care physician and patient may negotiate and agree that a vague symptom be given more time to evolve, with no testing or treatment ordered the first time the concern is mentioned
Inadequate summative quality scorecards
Poor risk-adjustment toolsCoexisting patient complexities rarely affect process metrics
Example: postoperative thrombosis prophylaxis
Coexisting patient complexities often affect patient outcomes
Example: any number of social determinant factors affect disease- and patient-oriented outcomes
Goal target numberSix Sigma-level outcomes
Example: 0% infection rate or 100% vaccination uptake
Outcomes are dependent on a multitude of social and behavioral cofactors
Example: much less than 100% of a population wants colon cancer screening no matter how strongly it is recommended and incentivized
Scorecard comprehensivenessList of metrics for a physician represents most of the work performed
Example: an overall rating for an orthopedist who only replaces hips and knees
Few simplistic quality measures capture only a tiny fraction of the work performed by a primary care physician. The alternative is a long, cumbersome list that is costly and burdensome to maintain and of questionable validity