Quality Improvement
Core concepts
Quality improvement is a systematic, data-guided approach to closing the gap between current and desired performance. Know the difference between QI (improve local processes) and research (generate generalizable knowledge). A strong aim statement is specific, measurable, time-bound, and population-focused. Use process maps, root-cause analysis, fishbone diagrams, and Pareto charts to understand systems. PDSA cycles test small changes. Run charts and control charts distinguish common-cause variation from special-cause variation. Measure baseline, track over time, and include balancing measures. Sustain and spread require standard work, ownership, and feedback.
Traps
Questions often reward blaming an individual rather than examining the system. Other traps: an aim that is too broad, no baseline, measuring many things poorly, and declaring success from one data point. Before-and-after comparisons may reflect secular trends or variation. Do not confuse a QI project with a research study requiring consent, though ethical review may still apply.
Worked example
A clinic wants to reduce missed appointments. Baseline no-show rate is measured, a process map identifies reminder timing, and a PDSA tests text reminders for two weeks. The team plots weekly rates on a run chart, checks access and satisfaction as balancing measures, and standardizes the reminder workflow.
Rule of thumb
Start small, measure over time, and standardize what works. Ask “What system produced this result?” before asking “Who caused it?”