An algorithm for matching anonymous hospital discharge records used in occupational disease surveillance: anonymous record matching algorithm.

ABSTRACT

The expense of collecting primary data, coupled with limited authority to mandate reporting, requires alternative methods of implementing an occupational disease registry in Illinois. One alternative data source for surveillance of some occupational diseases is hospital discharge records. Because these records lack personal identifiers, it has been impossible historically to match records belonging to the same individual and obtain reliable case estimates. To circumvent this difficulty, an algorithm has been developed to match anonymous hospital discharge records collected from all Illinois hospitals. The algorithm was based on the assumption that specific combinations of occupational disease code, sex, zip code, and date of birth would identify an individual to whom multiple hospitalizations belong. Matching with the algorithm reduced the 1986 case estimates from 597 to 499 for all cases of coal workers' pneumoconiosis, asbestosis, and silicosis.