Explainable AI for Public Health: Client Linkage and Deduplication

Tue, 03 Feb 2026 00:00:00 -0500

Public health data is messy in very human ways. Families share phones and email addresses. Clinics rely on placeholder dates so work can keep moving. Organizations sometimes appear where people should. Any patient deduplication approach that ignores these realities will struggle to produce results teams can trust.

Probabilistic deduplication and linkage is a key public health AI use case that supports responsible stewardship of personal health information. Using machine learning, it estimates match likelihood across records that are often incomplete, transcription-heavy, and not consistently validated against authoritative sources. We treat it as governed, explainable decision support aligned with our responsibilities as a health information custodian (HIC), with equity considerations and routine human review.

Probabilistic Client Linkage & Deduplication Consultations

Thu, 25 Jan 2024 00:00:00 -0500

Explainable AI on phiz

Explainable AI for Public Health: Client Linkage and Deduplication

Probabilistic Client Linkage & Deduplication Consultations