Understanding Disparities in Persons with Multiple Chronic Conditions: Research Approaches and Datasets. 2. Introduction


Adults with multiple chronic conditions (MCC) represent a growing percentage of the population as well as a large percentage of health care services utilization and cost. To date, however, most research on chronic conditions focuses on individual conditions, in isolation from chronic comorbidities. Consequently, research results often are not applicable to the population of persons with MCC. Research on the unique challenges facing individuals with multiple chronic conditions (MCC) is an emerging field of study supported by the Department of Health and Human Services (HHS). In 2008 HHS formed the Interagency Workgroup on Multiple Chronic Conditions which developed a strategic framework for improving health care for people with multiple chronic  conditions and created an inventory of HHS activities focused on MCC (HHS 2010 & 2011).

As part of its MCC strategic framework, HHS specified a goal related to research gaps with a sub goal (objective) and strategies related to addressing disparities:

  • “Goal 4: Facilitate research to fill knowledge gaps about, and interventions and systems to benefit, individuals with multiple chronic conditions.
    • Objective D: Address disparities in multiple chronic conditions populations.
      • Strategy 4.D.1: Stimulate research to more clearly elucidate differences between and opportunities for prevention and intervention in MCC among various sociodemographic groups.
      • Strategy 4.D.2: Use research findings on group-specific indicators for MCC risk and intervention options to leverage HHS disparities programs and initiatives to address the MCC population.”

This white paper advances HHS’s Goal 4 by describing health disparities research challenges, accomplishments, and opportunities in the MCC field.

The standard challenges of studying disparities are compounded by similar research challenges relating to MCC. These challenges include:

  • Sample size: Only a limited number of administrative and epidemiological datasets provide a sufficiently large sample size to study MCC, let alone detect disparities in persons with MCC. (For a full discussion of issues related to studying MCC see Understanding the High Prevalence of Low- Prevalence Chronic Disease Combinations: Databases and Methods for Research. Rezaee M. et al. September 2013, available at: http://aspe.hhs.gov/.
  • Data quality: Of the datasets that are large enough to study the numerous unique combinations of MCC, many have data quality issues that result in the misclassification of persons into (or out of) groups burdened by disparities.
  • Data capture: Datasets developed through healthcare provider and insurance systems only capture people with MCC who utilize the health care system.
  • Lack of standard definitions: The concepts of disparities and MCC are defined differently by different researchers, making it difficult for researchers in the field to build on each other’s findings.
  • Constantly evolving methods: Methods used to study both MCC and disparities are continually evolving, complicating disparities-sensitive measures of health care quality for patients with MCC.
  • Limited information: The factors that drive differences in MCC prevalence and healthcare utilization/cost in race/ethnic groups may include genetics, circumstances (e.g. health immigrant effect), inaccurate data collection procedures, patient access to healthcare (sampling issues), etc. When interpreting the research on racial/ethnic disparities it is important to understand the potential limitations of the data.

Despite these methodological challenges, the body of knowledge on MCC disparities is growing as discussed later in the report.

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