Laura P. Ruppert, MHA, Cancer Surveillance Section Director, Indiana State Cancer Registry
(NAACCR Steering Committee Chair)
As a central cancer registry, the Indiana State Cancer Registry (ISCR) is interested in supporting research, capture processes, and finding avenues to identify missing cases. In the surveillance community, we know there is information within electronic health records (EHR), that when linked with our data base, is able to provide a well-rounded picture of a cancer case, thus enhancing research efforts.
In terms of completeness of the ISCR, we like to say, we only know what we know! Over the years, linkages have provided real solutions for identification of missing cases. Some examples include linking with the Indiana Breast and Cervical Program, death data bases, etc. Nevertheless, we are always searching for ways to increase our efforts. A robust and complete ISCR database benefits Indiana and the nation so cancer control efforts can be applied appropriately.
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Abstract
Background: Large automated electronic health records (EHRs), if brought together in a federated data model, have the potential to serve as valuable population-based tools in studying the patterns and effectiveness of treatment. The Indiana Network for Patient Care (INPC) is a unique federated EHR data repository that contains data collected from a large population across various health care settings throughout the state of Indiana. The INPC clinical data environment allows quick access and extraction of information from medical charts. The purpose of this project was to evaluate 2 differ-ent methods of record linkage between the Indiana State Cancer Registry (ISCR) and INPC, determine the match rate for linkage between the ISCR and INPC data for patients diagnosed with cancer, and to assess the completeness of the ISCR based on additional validated cancer cases identified in the INPC EHRs.
Methods: Deterministic and probabilistic algo-rithms were applied to link ISCR cases to the INPC. The linkage results were validated by manual review and the accuracy assessed with positive predictive value (PPV). Medical charts of melanoma and lung cancer cases identified in INPC but not linked to ISCR were manually reviewed to identify true incidence cancers missed by the ISCR, from which the com-pleteness of the ISCR was estimated for each cancer.
Results: Both deterministic and probabilistic approaches to linking ISCR and INPC had extremely high PPV (>99%) for identifying true matches for the overall cohort and each subcohort. The combined match rate for melanoma and lung cancer cases identified in the ISCR that matched to any patient occurrence in INPC (not by disease) was 85.5% for the complete cohort, 94.4% for melanoma, and 84.4% for lung cancer. The estimated completeness of capture by the ISCR was 84% for melanoma and 98% for lung cancer.
Conclusions: Cancer registries can be successfully linked to patients’ EHR data from institutions participating in a regional health information organization (RHIO) with a high match rate. A pragmatic approach to data linkage may apply both deterministic and probabilistic approaches together for the diverse purposes of cancer control research. The RHIO has the potential to add value to the state cancer registry through the identification of additional true incident cases, but more advanced approaches, such as natural language processing, are needed.
Key words: electronic health records, record linkage
The opinions expressed in this article are those of the authors and may not represent the official positions of NAACCR.
