This chapter is a practical guide to the tools, techniques, and models that power quality management in healthcare. It distinguishes quality models (frameworks for organizing improvement, e.g., PDSA/PDCA, Lean, Six Sigma, Baldrige) from tools and techniques (methods applied at the frontline to diagnose, redesign, and control processes). Readers learn when to use which tool, with do’s and don’ts and hospital-based examples. Core content includes: root cause analysis in depth (5 Whys, fishbone, fault tree, Pareto, change analysis) and how to avoid hindsight bias; risk management end-to-end from hazard identification (FMEA, checklists), mitigation and controls (standard work, hard stops, forcing functions), risk quantification and financial tools, compliance/governance and decision-support tools, and effective risk communication. We cover Safety-I and Safety-II as complementary lenses and introduce Success Cause Analysis to learn from favorable outcomes, not just failures. Data methods such as stratification, SPC/run charts, dashboards, and meaningful performance indicators, show how to detect variation, equity gaps, and unintended effects. Clinical vignettes link each method to real decisions at the bedside, pharmacy, laboratory, and operating room. The aim is to enable teams to select the right model, apply the right tool, and convert measurement into reliable, patient-centred improvement.