What is a measurement system analysis (MSA) primarily concerned with?

• A. Assessing patient satisfaction
• B. Evaluating accuracy and precision of measurement systems (gage repeatability, reproducibility, bias)
• C. Calculating sample size
• D. Evaluating financial impact

Answer: (B)

MSA focuses on the quality of the data itself by examining how well the measurement system performs, not on the process being measured. It asks whether the measurements are accurate and consistent enough to trust for decision making. The main elements are bias (systematic error) and precision, captured through repeatability (same item, same conditions) and reproducibility (different operators or instruments). A common approach is to assess GR&R to quantify how much variability comes from the measurement system versus the process under study. By identifying and addressing bias or excessive measurement variation, you ensure the data truly reflect real process performance rather than measurement noise. This is why it’s different from topics like patient satisfaction, which relates to experiences; sample size, which relates to study design; or financial impact, which relates to cost considerations.