Using health insurance reimbursement data to identify incident cancer cases.

OBJECTIVES

The objective of this study was to establish an optimal population-level follow-up strategy for identifying incident cancers using health insurance reimbursement data in rural China.

STUDY DESIGN AND SETTING

We compared active follow-up and passive linkage with claims data for identification of incident cancer cases. Claims data were derived from the New Rural Cooperative Medical Scheme (NCMS). Follow-up data from subject enrollment to December 31, 2016, regarding 33,948 subjects in a large-scale randomized controlled trial were used in this study.

RESULTS

The overall sensitivity of passive linkage with NCMS claims data was significantly higher than that of active follow-up (95.6% vs. 54.9%, P < 0.001). Of 12 cases missed by the NCMS data set, seven were treated on an outpatient basis and there were therefore no records in the NCMS system, and five were diagnosed at primary (township-level) health facilities and excluded from the quality control process. Of the 123 cases missed by active follow-up, 54 were reported as negative, 69 were reported as positive but had inaccurate information regarding the site of cancer, or exceeded the 6-month limitation from the date of diagnosis.

CONCLUSION

Passive linkage with NCMS claims data is an efficient approach for identifying incident cancers in areas without cancer registries in rural China.