Understanding Disparities in Persons with Multiple Chronic Conditions: Research Approaches and Datasets. 8.2.3 Data sources and analysis


Needed analyses:

  • Most prior studies on MCC disparities have only examined MCC and disparities at a crude level. There is still a need for basic research using large datasets to examine disparities for the most common combinations of health conditions.
  • Disparities related to socioeconomic factors such as income, occupation/employment, wealth/poverty, place of birth/geography, housing and disability have not yet been explored, and little is known about disparities in cost and utilization patterns.
  • Research is needed to examine how well the health needs of different MCC populations are being served by the health care system, and how this contributes to or mitigates disparities.
  • Data analysis could also help to identify disparities “hot spots” to be targeted for intervention, i.e. population subsets that have worse trajectories and cause lower performance or higher cost for a health plan.

Promising datasets for analysis:

  • Some of the more reliable HCUP datasets may be useful to explore MCC disparities by race, ethnicity and socio-economic factors. To identify states that provide high-quality data, researchers can rank states based on the extent of missing/incomplete data on key variables of interest, and use data from states with the least amount of missing data.
  • It may also be useful to conduct analyses on disparities in care affecting the Medicare-eligible population under age 65. This population is eligible for Medicare because of disabilities. Disability is both a chronic condition and a stratifying variable for disparities analysis. Research could focus on challenges experienced by persons with disabilities to receive care for any conditions other than their main disability.

Analytic methods:

  • Publications are needed to describe what types of statistical models and advanced multivariate techniques can provide insights into the drivers of disparities for the MCC population
  • In developing analytic methods, researchers should be aware that certain types of analyses can increase risks for communities of color. For example, employers may discriminate against employees or potential employees based on information that is reported to them about the MCC risks and costs experienced by various populations. One way to minimize this risk is to focus analyses on how well various populations are being served by the health care system. Such analyses are less likely to perpetuate disparities compared to research examining disparities in the prevalence and incidence of MCC in various populations.

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