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Measuring multimorbidity in older adults: comparing different data sources.

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Summary

Combining self-reported and administrative data provides a more accurate picture of multimorbidity in older adults. Using single data sources may underestimate the prevalence of chronic conditions and multimorbidity in primary care settings.

Keywords:
Agreement between sourcesChronic conditionsData sourcesEpidemiologyHealth administrative dataMultimorbidityOlder adultsPrevalencePrimary health careSelf-report

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Area of Science:

  • Gerontology
  • Epidemiology
  • Health Services Research

Background:

  • Multimorbidity is a significant global health challenge, especially impacting older adults in primary care.
  • Accurate epidemiological data is crucial for identifying and addressing the healthcare needs of this demographic.
  • This study addresses the need for comprehensive data on chronic conditions and multimorbidity in older adults.

Purpose of the Study:

  • To compare the prevalence of chronic conditions and multimorbidity using self-reported (SR) data only, administrative (Adm) data only, and combined data sources.
  • To investigate the association between sociodemographic/behavioral factors and multimorbidity across different data sources.
  • To highlight the impact of data source selection on the estimation of multimorbidity prevalence.

Main Methods:

  • Secondary analysis of linked survey and administrative health data from the Longitudinal Survey on Senior's Health and Health Services Use.
  • Inclusion of 1625 community-dwelling older adults (≥65 years) from primary health clinics in Quebec.
  • Assessment of 17 chronic conditions using both self-reported and administrative data, examining prevalence and agreement between sources.

Main Results:

  • Prevalence of individual chronic conditions varied significantly (1.2%–68.7%) based on the data source.
  • Agreement between data sources for chronic conditions was highly variable (kappa coefficients 0.05–0.73).
  • Estimated multimorbidity prevalence reached up to 95.9%, with associations between factors and multimorbidity differing by data source.

Conclusions:

  • Integrating self-reported and administrative data is essential for accurate case identification of chronic conditions and multimorbidity.
  • Relying on a single data source risks underestimating the true prevalence of multimorbidity in older primary care populations.
  • Comprehensive data integration is vital for characterizing the healthcare needs of the growing elderly population.