Using public health data systems to understand and eliminate cancer disparities.
Identifying and eliminating social disparities in cancer depend upon the availability and ready use of public health surveillance data at the national, state and local levels. As an example of advancing a statewide research agenda in cancer disparities, we present descriptive statistics from major public health surveillance data systems in Massachusetts. Disparities highlighted include higher breast cancer mortality rates among African-American women than women of other racial groups, lower rates of colorectal and cervical cancer screening among Asian-American residents, and striking gradients in cancer risk factor prevalence and screening by income and education. Challenges in utilizing public health surveillance data include lack of information in many domains of social inequity beyond race/ethnicity, uneven quality, and lack of stable, reportable data for smaller populations. Opportunities to maximize the usefulness of cancer registry data include application of geographic information systems and linkage with other data systems tracking information on health services outcomes and clinical trial participation. Analyses of surveillance data can spark advances not only in community-based participatory research but also in programs and policies that may ultimately eliminate disparities along the cancer continuum.
Koh
Howard K
HK
Division of Public Health Practice, Harvard School of Public Health, 1552 Tremont Street, Boston, MA 02120, USA. hkoh@hsph.harvard.edu
Judge
Christine M
CM
Ferrer
Barbara
B
Gershman
Susan T
ST
D004493:Education; D040362:Geographic Information Systems; D006296:Health Services / Q000706:statistics & numerical data; D006297:Health Services Accessibility; D006801:Humans; D007182:Income; D007255:Information Services; D008404:Massachusetts / Q000453:epidemiology; D009369:Neoplasms / Q000191:economics* / Q000209:etiology* / Q000401:mortality; D011159:Population Surveillance; D011634:Public Health / Q000706:statistics & numerical data*; D012307:Risk Factors; D012923:Social Class; D013219:State Government