Patient record matching

Probabilistic record linkage, the
Fellegi-Sunter way.

A pair of records only gets compared if they share a blocking key (exact match on name+DOB, or on SSN alone). Each shared field then contributes a Bayes factor — how much more likely a true match is to agree this way than two random people are — multiplied against a prior to get a match probability. Pairs scoring ≥ 0.70 auto-link, 0.50–0.70 go to a review queue, below that they're dismissed.

Uses the real blocking rules and trained comparison weights (m/u probabilities) from an actual open-source Splink-based record-linkage model, not invented weights — including its real limitation: first/last name similarity is plain string similarity, with no nickname dictionary. Runs entirely in JavaScript — no model download.