Quality Management and Performance Improvement
Frameworks to know
Donabedian's triad - structure, process, outcome - is the backbone of quality measurement: structure is resources and organization, process is what is done, outcome is the result for the patient. Quality assurance is retrospective inspection against standards; quality improvement is prospective, data-driven redesign. Tools include PDSA rapid cycles, Six Sigma DMAIC, Lean, benchmarking against best performers, and the Model for Improvement's three questions plus plan-do-study-act.
Measurement and variation
Indicators may be process measures (handwashing compliance, specimen rejection rate) or outcome measures (corrected reports, transfusion reactions). Run charts and control charts distinguish common-cause variation (stable, inherent) from special-cause variation (a point beyond control limits, a run of points on one side of the centerline, a trend). Reacting to common cause as if it were special - tampering - worsens the process. Pareto charts separate the vital few contributors from the trivial many; fishbone diagrams and 5 Whys organize cause hypotheses.
Prospective versus reactive
FMEA is proactive: score severity, occurrence, and detection from 1 to 10 and multiply to get the risk priority number (RPN); high RPN items get action first. Root cause analysis is reactive, triggered by a sentinel event or serious occurrence. CAPA closes the loop with documented corrective and preventive action and effectiveness checks.
Worked example
An FMEA team scores a mislabeled-specimen failure mode at severity 7, occurrence 4, detection 3. RPN = 7 × 4 × 3 = 84. If the team's action threshold is 100, they monitor; if it were 75, they would act - commonly by adding barcode verification, which lowers occurrence and detection scores.