In economic evaluations, how does data source quality influence results?

• A. Quality of data sources affects results and uncertainty.
• B. Quality of data sources has no impact on results.
• C. Only the sample size matters.
• D. Quality of data sources affects results and uncertainty.

Answer: (D)

Data source quality directly shapes both the estimated costs and effects in an economic evaluation and the precision of those estimates. When data come from high-quality sources—well-designed trials or robust observational studies with proper control for confounding, complete follow-up, validated measures, and representative populations—the parameter estimates are closer to true values and the associated uncertainty is smaller. This yields more credible point estimates and tighter uncertainty around them in analyses like probabilistic sensitivity analysis.

If the data are of lower quality—biased, incomplete, poorly measured, or not representative—the estimated costs and effects can be distorted, and the uncertainty around those estimates grows. That means the results may be less reliable and more sensitive to modeling assumptions, making it harder to draw solid conclusions about cost-effectiveness.

While larger sample sizes do improve precision, they cannot fully compensate for biased or unrepresentative data. High-quality data improve both accuracy and confidence in the results, whereas poor data quality undermines them.