Understanding Disparities in Persons with Multiple Chronic Conditions: Research Approaches and Datasets. 5. Challenges in Disparities Research


The quality of demographic variables, especially race and ethnicity, has suffered from inconsistencies and challenges in data collection for all types of data, not just health data. The same conditions that compromise disparities data in general, compromise disparities research on groups with MCC. Currently national surveys and databases lack standardization among the demographic variables collected, observer bias and inadequate and insensitive response categories can prevent minority populations from being accurately represented in data capture efforts. Analytical challenges also complicate disparities research in general (and therefore MCC research.) The challenges are described below.

Fortunately, as discussed later, a broad range of efforts are being put into place to standardize and improve data collection methods, and improve the overall quality of demographic data. The Affordable Care Act, for instance, called for the creation and use of uniform demographic variables in national surveys. While improved data collection methodologies will help researchers create a more accurate picture of the health challenges facing specific racial and ethnic groups in our nation, it is important to note the potential risks of improving coding of small subgroups of the population, and to ensure that as the methods for identifying and analyzing ever smaller populations improves, safeguards will be put in place to preserve the privacy of these individuals and shield them from potential discrimination.

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