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The Health Disparities Calculator (HD*Calc) is a statistical software designed to generate multiple summary measures to evaluate and monitor health disparities (HD). HD*Calc was created as an extension of SEER*Stat that allows the user to import Surveillance, Epidemiology, and End Results (SEER) data or other population based health data, such as National Health Survey sample data from the National Health Interview Survey (NHIS) or the Behavioral Risk Factor Surveillance System (BRFSS). Several of the measures included in HD*Calc are not commonly used to evaluate cancer-related health disparities. An important function of HD*Calc is to facilitate use of a range of HD measures so that researchers can explore their utility in different situations.
Cross sectional and trend data (e.g. cancer rates and survival statistics calculated from SEER; and prevalence of obesity and mammography use from the national survey data) categorized by disparity groups (e.g. area-SES, race / ethnicity, geographic areas) can be used with HD*Calc to generate four absolute and seven relative summary measures of disparity. Associated statistics include: standard errors, confidence intervals, and relative change over time for trends. The output is presented in both tabular and graphic formats; this allows users to specify various conditions and formats. Resulting disparity tables and graphs can be exported from the program. In addition to summary measures, HD*Calc also provides pair wise comparisons that allow the user to explore underlying trends in the data.
This application extends the work published in the National Cancer Institute Surveillance Monograph Series entitled Methods for Measuring Cancer Disparities (available at http://seer.cancer.gov/publications/disparities/ ), which evaluates measures of health disparities included in HD*Calc. The monograph discusses major issues that may affect the choice of summary measures of disparity and systematically reviews methods used in health disparities research. Methods for Measuring Cancer Disparities is recommended for those unfamiliar with the measures available in HD*Calc or interested in a comparative summary of available measures of health disparities.
A second monograph, Selected Comparisons of Measures of Health Disparities: A Review Using Databases Relevant to Healthy People 2010 Cancer-Related Objectives (available at http://seer.cancer.gov/publications/disparities2/ ), uses case studies to analyze the performance and appropriateness of various potential measures of health disparities,), uses case studies to analyze the performance and appropriateness of various potential measures of health disparities.
Statistical properties also affect the choice of measures of health disparities. Different data sources, i.e. registry data or survey data, present distinct challenges in the statistical inferences of these measures. Detailed evaluations of inference methods for measures included in HD*Cal and their usage considerations are published in statistical journals.
National Cancer Institute Surveillance Monograph Series References
Harper S, Lynch J. Methods for Measuring Cancer Disparities: Using Data Relevant to Healthy People 2010 Cancer-Related Objectives. NCI Cancer Surveillance Monograph Series, Number 6. Bethesda, MD: National Cancer Institute, 2005. NIH Publication No. 05-5777.
Harper S, Lynch J. Selected Comparisons of Measures of Health Disparities: A Review Using Databases Relevant to Healthy People 2010 Cancer-Related Objectives. NCI Cancer Surveillance Monograph Series, Number 7. National Cancer Institute. NIH Pub. No. 07-6281, Bethesda, MD, 2007.
Statistical Methods References
Li, Y, Yu, M, Zhang, J. Statistical Inference on Health Disparity Indices for Complex Surveys. Am J Epidemiol. 2018 Nov 1;187(11):2460-2469. [Abstract]
Ahn J, Harper S, Yu M, Feuer EJ, Liu B, Luta G. Variance estimation and confidence intervals for 11 commonly used health disparity measures. JCO Clin Cancer Inform. 2018 Dec;2:1-19. [Abstract]
Yu M, Liu B, Li Y, Zou ZJ, Breen N. Statistical inferences of extended concentration indices for directly standardized rates. Stat Med. 2019 Jan 15;38(1):62-73. [Abstract]
Ahn J, Harper S, Yu M, Feuer EJ, Liu B. Improved Monte Carlo methods for estimating confidence intervals for eleven commonly used health disparity measures. PLos One. 2019 Jul 11;14(7):e0219542. [Abstract]
Yu M, Li Y, Qin M, Statistical Inference of the relative concentration index for complex surveys, Stat Med. 2019 Sep 20; 38(21): 4083-4095. [Abstract]
