The Health Disparities Calculator (HD*Calc) uses SEER Data or other population based health data (e.g., National Health Interview Survey, California Health Interview SurveyExternal Web Site Policy, Tobacco Use Supplement to the Current Population Survey, and National Health and Nutrition Examination Survey) to calculate two types of disparity measures and two pair comparison measures:

  1. Absolute Disparity, which includes Range Difference (RD), Between Group Variance (BGV), Absolute Concentration Index (ACI), and Slope Index of Inequality (SII)
  2. Relative Disparity, which includes Range Ratio (RR), Index of Disparity (IDisp), Mean Log Deviation (MLD), Relative Concentration Index (RCI), Theil Index (T), Kunst Mackenbach Relative Index (KMI), Relative Index of Inequality (RII).
  3. Pair Comparison Measures, which includes Pair Difference (PD) and Pair Ratio (PR).

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.

This application extends the work published in the National Cancer Institute Surveillance Monograph Series entitled Methods for Measuring Cancer DisparitiesIcon indicating linked file is archived content., 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 (PDF, 1.4 MB)Icon indicating linked file is archived content..

A second monograph, Selected Comparisons of Measures of Health Disparities: A Review Using Databases Relevant to Healthy People 2010 Cancer-Related Objectives, uses case studies to analyze the performance and appropriateness of various 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 have been published in statistical journals.