Article Figures & Data
Tables
- Table 1
Differences in Processes and Outcomes Between Care Isolated to a Single Disease and Primary Care
Construct Isolated Single Disease with Linear Mechanical Processes Primary Care Nonlinear Adaptive Processes Care process Process complexity Few variables to be measured and controlled
Example: central line bundlesNumerous variables that make accurate measurement problematic
Example: patients with multiple medications, comorbidities, and socioeconomic challengesProcess standardization Standard processes use consistent raw materials
Example: antibiotics administered just before the incision is made in elective surgeriesVariable 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 fibromyalgiaProcess controls Machines 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 appliedThe 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 teamOutcome goals Goal clarity: multimorbidity All team members and machines work toward one clear goal
Example: titanium artificial hip placed in the appropriate positionThere 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 careGoal clarity: unique patient priorities Patients and caregivers agree on clear outcome
Example: minimum days intubated on mechanical ventilationPatients 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 auntGoal timing Standard processes have fixed expectations of the timing of interventions
Example: daily trials of endotracheal tube extubationThe 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 mentionedInadequate summative quality scorecards Poor risk-adjustment tools Coexisting patient complexities rarely affect process metrics
Example: postoperative thrombosis prophylaxisCoexisting patient complexities often affect patient outcomes
Example: any number of social determinant factors affect disease- and patient-oriented outcomesGoal target number Six Sigma-level outcomes
Example: 0% infection rate or 100% vaccination uptakeOutcomes 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 incentivizedScorecard comprehensiveness List of metrics for a physician represents most of the work performed
Example: an overall rating for an orthopedist who only replaces hips and kneesFew 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 Shared-decision reporting Target ranges without absolute goals Measure when physicians do not order tests or treatments Measure other aspects of primary care capacity associated with better outcomes Comprehensiveness of services offered at the primary care center Physician-patient continuity Smaller practice size Rate of generic prescription writing Increased office visit time for complex patients Access to local clinic professionals 24/7 Careful selection of referral specialists De-emphasize measures of patient satisfaction Measure outcomes more important to patients Peer-led qualitative reviews of patterns of care
Additional Files
The Article in Brief
The Challenges of Measuring, Improving, and Reporting Quality in Primary Care
Richard A. Young , and colleagues
Background This essay asserts that traditional quality improvement processes used for linear mechanical systems, such as isolated single-disease care, are inappropriate for complex adaptive systems such as primary care.
What This Study Found A new set of priorities for quality management in primary care that better reflects the discipline's complexity and value is needed. Proposed priorities include patient-centered reporting; quality goals not based on rigid targets; metrics that capture avoidance of excessive testing or treatment; attributes of primary care associated with better outcomes and lower costs; less emphasis on patient satisfaction scores; patient-centered outcomes, such as days of avoidable disability; and peer-led qualitative reviews of patterns of care, practice infrastructure, and intrapractice relationships.
Implications
- The authors conclude that the inappropriate application of traditional quality improvement strategies and misaligned metrics undermine primary care and, in turn, all patient care.
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