Phenodrift

Clinical cohorts and quality measures are often implemented as warehouse queries that can drift when schemas, vocabularies or source policies change. Phenodrift proposes a regression monitor that stores the reviewed policy beside the deployed query, replays versioned synthetic cases and reports which records change classification, which clause is implicated and what modeled operational impact follows. The supplied research confirms policy-to-query generation and synthetic clinical data, while finding no continuous deployed-query drift monitor.

Passing synthetic tests does not establish clinical correctness, patient safety or measure validity. Source policy, qualified interpretation, query version, schema version, terminology mapping, synthetic case, expected classification, replay result, drift candidate, clinical or measure-owner finding, deployment approval, production observation and patient outcome must remain separate. Real patient data should remain inside the customer's governed environment.

The compounding asset is a reviewed golden-case library and drift history, but those cases can encode outdated assumptions and synthetic coverage gaps. Two referenced interfaces remain unverified. Modeled cost is a scenario, not a realized financial or care outcome, and a signed drift report proves bounded provenance rather than clinical truth.

A clinical analytics, quality-measure, data-platform or governance leader responsible for deployed cohort definitions in a healthcare data environment.