Joshua Herb1,2, Rachael Wolff3, Philip McDaniel3, Mark Holmes4,5, Jennifer Lund4, Karyn Stitzenberg6. 1. Department of Surgery, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. Joshua.herb@unchealth.unc.edu. 2. Cecil G. Sheps Center for Health Services Research, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA. Joshua.herb@unchealth.unc.edu. 3. University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. 4. Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. 5. Cecil G. Sheps Center for Health Services Research, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA. 6. Department of Surgery, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Abstract
PURPOSE: SEER data are widely used to study rural-urban disparities in cancer. However, no studies have directly assessed how well the rural areas covered by SEER represent the broader rural United States. METHODS: Public data sources were used to calculate county level measures of sociodemographics, health behaviors, health access and all cause cancer incidence. Driving time from each census tract to nearest Commission on Cancer certified facility was calculated and analyzed in rural SEER and non-SEER areas. RESULTS: Rural SEER and non-SEER counties were similar with respect to the distribution of age, race, sex, poverty, health behaviors, provider density, and cancer screening. Overall cancer incidence was similar in rural SEER vs non-SEER counties. However, incidence for White, Hispanic, and Asian patients was higher in rural SEER vs non-SEER counties. Unadjusted median travel time was 53 min (IQR 34-82) in rural SEER tracts and 54 min (IQR 35-82) in rural non-SEER census tracts. Linear modeling showed shorter travel times across all levels of rurality in SEER vs non-SEER census tracts when controlling for region (Large Rural: 13.4 min shorter in SEER areas 95% CI 9.1;17.6; Small Rural: 16.3 min shorter 95% CI 9.1;23.6; Isolated Rural: 15.7 min shorter 95% CI 9.9;21.6). CONCLUSIONS: The rural population covered by SEER data is comparable to the rural population in non-SEER areas. However, patients in rural SEER regions have shorter travel times to care than rural patients in non-SEER regions. This needs to be considered when using SEER-Medicare to study access to cancer care.
PURPOSE: SEER data are widely used to study rural-urban disparities in cancer. However, no studies have directly assessed how well the rural areas covered by SEER represent the broader rural United States. METHODS: Public data sources were used to calculate county level measures of sociodemographics, health behaviors, health access and all cause cancer incidence. Driving time from each census tract to nearest Commission on Cancer certified facility was calculated and analyzed in rural SEER and non-SEER areas. RESULTS: Rural SEER and non-SEER counties were similar with respect to the distribution of age, race, sex, poverty, health behaviors, provider density, and cancer screening. Overall cancer incidence was similar in rural SEER vs non-SEER counties. However, incidence for White, Hispanic, and Asian patients was higher in rural SEER vs non-SEER counties. Unadjusted median travel time was 53 min (IQR 34-82) in rural SEER tracts and 54 min (IQR 35-82) in rural non-SEER census tracts. Linear modeling showed shorter travel times across all levels of rurality in SEER vs non-SEER census tracts when controlling for region (Large Rural: 13.4 min shorter in SEER areas 95% CI 9.1;17.6; Small Rural: 16.3 min shorter 95% CI 9.1;23.6; Isolated Rural: 15.7 min shorter 95% CI 9.9;21.6). CONCLUSIONS: The rural population covered by SEER data is comparable to the rural population in non-SEER areas. However, patients in rural SEER regions have shorter travel times to care than rural patients in non-SEER regions. This needs to be considered when using SEER-Medicare to study access to cancer care.
Authors: Laura-Mae Baldwin; Yong Cai; Eric H Larson; Sharon A Dobie; George E Wright; David C Goodman; Barbara Matthews; L Gary Hart Journal: J Rural Health Date: 2008 Impact factor: 4.333
Authors: Amy M Berkman; Clark R Andersen; Vidya Puthenpura; J A Livingston; Sairah Ahmed; Branko Cuglievan; Michelle A T Hildebrandt; Michael E Roth Journal: Cancer Epidemiol Date: 2021-09-28 Impact factor: 2.984
Authors: Ugonna Ihenacho; Ann S Hamilton; Wendy J Mack; Anna H Wu; Jennifer B Unger; Dorothy R Pathak; Kelly A Hirko; Richard T Houang; Michael F Press; Kendra L Schwartz; Lydia R Marcus; Ellen M Velie Journal: Breast Cancer Res Treat Date: 2022-08-04 Impact factor: 4.624