Leveraging Linkage of Cohort Studies With Administrative Claims Data to Identify Individuals With Cancer.

ABSTRACT:

Background

In an effort to overcome quality and cost constraints inherent in population-based research, diverse data sources are increasingly being combined. In this paper, we describe the performance of a Medicare claims-based incident cancer identification algorithm in comparison with observational cohort data from the Nurses' Health Study (NHS).

Methods

NHS-Medicare linked participants' claims data were analyzed using 4 versions of a cancer identification algorithm across 3 cancer sites (breast, colorectal, and lung). The algorithms evaluated included an update of the original Setoguchi algorithm, and 3 other versions that differed in the data used for prevalent cancer exclusions.

Results

The algorithm that yielded the highest positive predictive value (PPV) (0.52-

SUBMITTER: Bronson MR 

PROVIDER: S-EPMC6043405 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature