Dataset Information

Integration of Cancer Registry Data into the Text Information Extraction System: Leveraging the Structured Data Import Tool.

ABSTRACT:

Introduction/background

Cancer registries in the US collect timely and systematic data on new cancer cases, extent of disease, staging, biomarker status, treatment, survival, and mortality of cancer cases. Existing methodologies for accessing local cancer registry data for research are time-consuming and often rely on the manual merging of data by staff registrars. In addition, existing registries do not provide direct access to these data nor do they routinely provide linkage to discrete electronic health record (EHR) data, reports, or imaging data. Automation of such linkage can provide an impressive data resource and make valuable data available for translational cancer research.

Methods

The UPMC Network Cancer Registry collects highly structured, longitudinal data on all reportable cancer patients, from the point of the diagnosis throughout treatment and follow-up/outcomes. Using commercial registry software, we collect data in compliance with standards governed by the North American Association of Central Cancer Registries. This standardization ensures that the data are highly structured with standard coding and collection methods, which support data exchange among central cancer registries and the Centers for Disease Control and Prevention.

Results

At the UPMC Hillman Cancer Center and University of Pittsburgh, we explored the feasibility of linking this well-curated, structured cancer registry data with unstructured text (i.e., pathology and radiology reports), using the Text Information Extraction System (TIES). We used the TIES platform to integrate breast cancer cases from the UPMC Network Cancer Registry system and then combine these data with other EHR data as a pilot use case that can be replicated for other cancers.

Conclusions

As a result of this integration, we now have a single searchable repository of information for breast cancer patients from the UPMC registry, combined with their pathology and radiology reports. The system that we developed is easily scalable to other health systems and cancer centers.

SUBMITTER: Linkov F

PROVIDER: S-EPMC6319041 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Integration of Cancer Registry Data into the Text Information Extraction System: Leveraging the Structured Data Import Tool.

Linkov Faina F Silverstein Jonathan C JC Davis Michael M Crocker Brenda B Hao Degan D Schneider Althea A Schwenk Melissa M Winters Sharon S Zelnis Joyce J Lee Adrian V AV Becich Michael J MJ

Journal of pathology informatics 20181224

<h4>Introduction/background</h4>Cancer registries in the US collect timely and systematic data on new cancer cases, extent of disease, staging, biomarker status, treatment, survival, and mortality of cancer cases. Existing methodologies for accessing local cancer registry data for research are time-consuming and often rely on the manual merging of data by staff registrars. In addition, existing registries do not provide direct access to these data nor do they routinely provide linkage to discret ...[more]

PMID: 30662793

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Dataset Information

Integration of Cancer Registry Data into the Text Information Extraction System: Leveraging the Structured Data Import Tool.

Introduction/background

Methods

Results

Conclusions

Publications

Integration of Cancer Registry Data into the Text Information Extraction System: Leveraging the Structured Data Import Tool.

Similar Datasets

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