Confirming mortality in a longitudinal exposure cohort: optimizing National Death Index search result processing

Abstract

Purpose: The National Death Index (NDI) is an important resource for mortality ascertainment. Methods selected to process NDI search results are rarely described in studies using linked data and can have an impact on resources and mortality ascertainment. We evaluate methods to process NDI search results among a 9/11-exposed cohort-the World Trade Center Health Registry (Registry).

Methods: We describe three approaches to process search results (NDI-recommended cutoff points [NDIc]; National Program of Cancer Registries [NPCR] algorithm, and modified National Institute of Occupational Safety and Health algorithm [mNIOSH]). We calculate percent agreement, positive predictive value, sensitivity, specificity, and quantify the burden of manual review to compare the approaches.

Results: Of 51,158 Registry enrollees submitted for linkage, 9449 enrollee-level and 17,909 record-level matches were identified. NPCR and mNIOSH were highly concordant (97.1%); more record pairs required manual review for mNIOSH (mNIOSH: 2.7% and NPCR: 1.8%). NDIc sensitivity was 82.9%, with differences observed by race and ethnicity (Asian: 74.4% and White: 86.1%).

Conclusions: NPCR algorithm minimized false matches and reduced the manual review burden. NDIc had nonrandom distribution of missed matches and low sensitivity. NDI search processing methods have important implications for resulting linked data; measures of linkage quality should be available to data users.

Keywords: Algorithms; Mortality; National Death Index; Process linkage output; Vital statistics.