Do duplicate case references create inconsistent follow-up outcomes?

Research question and evidence scope

Published: September 11, 2026. This protocol examines do duplicate case references create inconsistent follow-up outcomes? It reports no measured effect or promised result.

Methodology: use one cluster sharing an external case reference as the observation unit. Pre-register eligibility, exclusions, fields, missing-data codes, and comparisons.

Scope/population: active records detected by the exact-match rule. Observation window: twelve weekly snapshots plus thirty days. Do not generalize beyond these workflows, dates, and systems.

Operating scenario and evidence

Data collection should preserve pseudonymous IDs, sources, timestamps, queue states, owner decisions, outcomes, exclusions, and missingness.

Analysis should report counts and denominators by workflow, case band, reviewer, action, and outcome. Use intervals only when supported.

Method and review criteria

Inference and causal boundaries: Exact matching misses variants; association does not prove cause. Case mix, source age, staffing, season, scripts, and workflow changes are competing explanations.

Quality control: pilot a codebook, blind a second reviewer, and report agreement, adjudications, exclusions, and rule changes.

Limitations: incomplete audio, late notes, inconsistent timestamps, small groups, selection, and unobserved actions can bias results. Quantify each.

Authority and practical implications

Use findings narrowly to improve a field, queue rule, reviewer guide, or prospective test; never judge an individual from aggregates.

Sources/References: NIST Privacy Framework (https://www.nist.gov/privacy-framework); FTC Telemarketing Sales Rule (https://www.ftc.gov/legal-library/browse/rules/telemarketing-sales-rule); AAPOR Best Practices (https://aapor.org/standards-and-ethics/best-practices/); Philippines National Privacy Commission (https://privacy.gov.ph/data-privacy-act/).

Limitations, conclusion, and sources