Episode 63 — Sampling Design for r2
Show notes
Sampling under r2 involves structured statistical or judgment-based methods to validate control operation across representative populations. Candidates must understand that HITRUST expects sampling to be risk-based, with rationale documented for how items are selected and how results generalize to the full environment. The process ensures testing efficiency without sacrificing assurance quality. Assessors use sampling to evaluate repeatable control performance—such as access reviews, change approvals, or vulnerability scans—while balancing operational feasibility.
In practice, strong sampling design includes defining populations accurately, applying stratified or random selection, and retaining detailed sampling logs. For exam readiness, candidates should know how sample size, control frequency, and population size affect testing scope. HITRUST QA often reviews sampling logic closely to confirm statistical validity and traceability. Mastery of sampling design reflects analytical discipline and helps organizations demonstrate that control effectiveness is consistent and scalable across complex systems and business units.
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