Evaluation of Geocoding Quality in Montana Considerations for Sub-county analysis Heather Zimmerman

Background Montana Central Tumor Registry (MCTR) routinely geocodes address at diagnosis using the NAACCR geocoder 16% of cases have only PO Box reported 2.5% have incomplete or incorrect physical address

Evaluation Questions What areas of Montana have the highest proportion of cases with PO box only? What areas have the highest potential of census tract misclassification?

Methods Analysis included all cases of invasive cancer diagnosed from 2003 to 2016 among Montana residents. GIS coordinate Quality (item #366) grouped into 3 categories Street level or better: codes 00-05 Zip code or city centroid: codes 06-09 and 11 PO box zip centroid: code 10 Cases with codes 98 “Unknown” (only 12 cases) were excluded from analysis There were no cases with codes 12 “County centroid” or 99 “Unmatchable” Looked at the proportion of cases in each of these categories by year of diagnosis, geocoded county, and 2010 census tract (for years 12 to16)

77,992 cases of invasive cancer among Montana residents from 2003-2016 77,948 had been geocoded 77,936 had known GIS coordinate quality Results

Results: Year of Diagnosis There was an increase in proportion of cases geocoded to the street level or better from 2003 to 2016 and a corresponding decrease in cases coded to the zip or city centroid. Proportion of cases with PO Box only also decreased until about 2009 and has stayed about the same since then.

Results: By County Percent of cases geocoded to the street level or better varies widely between counties 95.1% in Yellowstone 26% in Prairie Median is 69.5% For geographic analysis I only used cases diagnosed from 2012 to 2016.

Results: By County

Results: By Census Tract There is even more variation at the census tract level 0% to 96.5% for census tracts

Results: By Census Tract

Results: By Census Tract 58 census tracts have 100% of cases geocoded to the street level, i.e. all cases geocoded to the centroid cannot be assigned to these tracts because the centroid is not located in these tracts.

Cancer Incidence Analysis in Butte

Let’s take another look at Butte

Another Example

Conclusions Our most rural areas have the highest proportion of cases with PO box only Urban areas have the highest potential for census tract misclassification

Next Steps Reduce the number of cases with PO box only Working with Montana Cancer Registrar’s Association to identify quality improvement projects to get physical address for residents with a PO Box Use ZCTA for sub-county analysis when timeframe is limited to available population data Carefully assess GIS coordinate quality before doing analysis at the census tract level