Generating Older Adult Multimorbidity Trajectories Using Various Comorbidity Indices and Calculation Methods

Area of Science:

• Gerontology
• Public Health
• Health Services Research

Background:

• Multimorbidity trajectories are crucial for understanding aging population health patterns.
• Identifying unhealthy trajectories can inform public health and clinical interventions.
• Current methods for constructing multimorbidity trajectories lack standardization.

Purpose of the Study:

• To compare and contrast multimorbidity trajectories constructed using various methods.
• To analyze differences between Charlson Comorbidity Index (CCI) and Elixhauser Comorbidity Index (ECI) aging trajectories.
• To explore acute versus chronic score derivations and the impact of social determinants of health.

Main Methods:

• Group-based trajectory modeling (GBTM) was used to estimate multimorbidity trajectories.
• Medicare claims data from 86,909 individuals aged 66-75 (in 1992) over 21 years were analyzed.
• Models incorporated social determinants of health, including income, race/ethnicity, and sex.

Main Results:

• All 8 generated trajectory models identified distinct low-chronic disease and high-chronic disease trajectories.
• All models met established statistical criteria for well-performing group-based trajectory models.
• Differences were observed between trajectories derived from CCI and ECI, and between acute and chronic score calculations.

Conclusions:

• Multimorbidity trajectories can be reliably constructed using GBTM with Medicare data.
• These trajectories can help clinicians identify at-risk older adults for timely intervention.
• Further research can refine trajectory models by incorporating social determinants of health more deeply.