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Emerging approaches to multiple chronic condition assessment.

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|June 14, 2022
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Summary
This summary is machine-generated.

Multiple chronic conditions (MCCs) are common in older adults. Four new models—CART, QCS, MMI, and omics in network medicine—emerged to improve MCC assessment and treatment for the aging population.

Keywords:
measurementmultimorbiditymultiple chronic conditionsolder people

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Area of Science:

  • Gerontology
  • Epidemiology
  • Biomedical Informatics

Background:

  • Older adults frequently have multiple chronic conditions (MCCs).
  • Accurate assessment of MCCs is crucial for healthcare delivery, research, and policy.
  • Understanding MCC patterns in this demographic is essential for targeted interventions.

Purpose of the Study:

  • To describe four emerging approaches for assessing MCCs in older adults.
  • To discuss the potential applications of these models in healthcare, research, and policy.
  • To highlight future research directions for MCC assessment in the aging population.

Main Methods:

  • A panel of experts convened by the National Institutes of Health identified four emerging models in 2018.
  • The identified models include classification and regression tree (CART), qualifying comorbidity sets (QCS), the multimorbidity index (MMI), and omics applied to network medicine.

Main Results:

  • Four distinct models for MCC assessment were identified by the expert panel.
  • These models offer novel ways to analyze and understand the complexity of MCCs.
  • The report details the characteristics and potential utility of each model.

Conclusions:

  • Emerging models like CART, QCS, MMI, and omics in network medicine show promise for improving MCC assessment.
  • Further research into these models can enhance the understanding of MCC epidemiology, diagnosis, and treatment in older adults.
  • These advancements are vital for optimizing healthcare and policy for the aging population.