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

2. 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

3. 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?

4. Methods
Analysis included all cases of invasive cancer diagnosed from 2003 to 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 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)

5. 77,992
cases of invasive cancer among Montana residents from
77,948
had been geocoded
77,936
had known GIS coordinate quality
Results

6. 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.

7. 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.

8. Results: By County

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

10. Results: By Census Tract

11. 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.

12. Cancer Incidence Analysis in Butte

13. Let’s take another look at Butte

14. Another Example

15. 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

16. 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