Promoting Data Use for Program Planning
Mississippi Cancer Registry
In September 2007, Susan G. Komen for the Cure published information regarding Madison County, Mississippi having the highest breast cancer mortality rate in the country. While the information was factual, it failed to provide a context for the high rate—namely, that Madison County is small and contains the only inpatient hospice for central Mississippi. The Mississippi State Department of Health's Office of Vital Statistics and the Mississippi Cancer Registry conducted a joint project using mortality data to show that the majority of Madison County breast cancer deaths during the time period of interest occurred at the hospice. Further, we used incidence data to show that the majority of those who died at the hospice were not residents of Madison County at the time of diagnosis. This gave us an opportunity to dialogue with Susan G. Komen for the Cure and encourage the use of registry data. These data provided the means to examine the state, locate areas where intervention is most needed, and use local expertise to help interpret that data.
The issue of Madison County is still brought up frequently today. We can calm fears and thwart efforts to spend an inordinate amount of time and resources on research and intervention in Madison County where it is not needed. This also has provided an opportunity to point out the importance of using data and interpreting that data correctly when planning and implementing new programs.
An example of correct data use occurred in July 2010. In 2010, the REACH US coalition was formed to address disparities in breast and cervical cancer, and the Director of the Mississippi Cancer Registry was invited to join the coalition. From the beginning, the coalition examined incidence rates, stage of disease at diagnosis, and other data to determine where interventions were needed most.
This is a change in Mississippi. Previously, groups did not think to look at data sources until they needed to evaluate a program. We now see a shift to examining the data to make the best use of limited resources.