1. Rosemary D. Cress, DrPH Research Program Director Collection and Use of Industry and Occupation Data II: Overview and Goals NAACCR: June 19-25, 2010 Quebec City

2. Introduction The California Cancer Registry has collected information about cases of cancer diagnosed among all California residents since 1988. In 2008, more than 145,000 Californians were diagnosed with cancer.

3. Introduction Information collected for each patient includes:  Patient characteristics (age, sex, race, address, etc)  Tumor characteristics (site, histology, extent of disease)  First course of treatment (surgery, chemotherapy, radiation)

4. Introduction Information on industry and occupation is collected in text fields. The CCR began manually coding narrative I&O in 1995, then developed an autocoding program Autocoding stopped in 2002 when the CCR moved to a new data management system due to lack of resources

5. Introduction In 2007, the Centers for Disease Control funded the National Institute for Occupational Safety and Health (NIOSH) to work with the California Cancer Registry (CCR) on a pilot study to explore the feasibility of coding industry and occupation (I&O) information contained in CCR records.

6. Goals Goals of the project: Develop an autocoding program to assign codes to I&O text fields in registry records Use these data to calculate incidence rates and standardized rate ratios for major cancer sites for various construction occupations Demonstrate the usefulness of this coding to other state cancer registries

7. Methods During the first year, NIOSH staff translated the older CCR autocoding program to SAS. The program utilizes a “look-up” table with I/O codes and text CCR staff used the program to evaluate completeness of I/O coding in the CCR database and to identify uncoded text strings

8. Methods (continued) Uncoded I/O text strings were prioritized by frequency CCR staff provided I&O text strings to NIOSH for coding USC and NIOSH staff coded text strings to the Bureau of the Census 1990 I/O codes These new codes and text strings were added to the SAS program, and the process was repeated

9. Results At the beginning of the study 49.3% of the records in the CCR database had I&O coded. As of April 2010, 78.4 % of nearly three million records (diagnosed 1988-2007) were coded.

10. Industry Information on CCR cases, 1988-2007 (n=2,989,888)

11. Results Over 75,000 cancer patients with a construction occupation have been identified. Over 490,000 patients are coded as “retired,” and over 800,000 as “unemployed or unknown” making their records unusable for I/O research Over 600,000 remain uncoded

12. Results The remaining uncoded cases have unique text strings that will likely take several years to code. Eventually nearly half of CCR cases will be assigned valid I&O codes (excluding retired)

13. Conclusions This study has demonstrated that it is feasible to code I/O text fields for use in research into occupational risk factors for cancer It also demonstrated a relatively low cost way to obtain I/O information for a large number of cancer patients

14. Conclusions However, incomplete information recorded for I/O in the medical record remains a barrier

15. Future Plans In the next year we will be working to incorporate the coded I&O data into our research dataset. We also are exploring how to incorporate I&O information from death certificates into the CCR database.

16. Acknowledgements CDC/NIOSH Geoffrey Calvert Sara Luckhaupt Pamela Schumacher Rui Shen California Cancer Registry, Sacramento Katrina Bauer Mark Allen Los Angeles Cancer Surveillance Program, USC Dennis Deapen Shirley Miyashiro