Aging in Community Health Clinics (ACHES) Changes in Multimorbidity and Disability Among Race/Ethnic Older Adults COVID-19 Related Administrative Supplement

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Project Summary This work will advance our knowledge of the contributing role of specific pre-existing co-occurring chronic disease (multimorbidity) patterns and sociodemographic factors in the likelihood of contracting COVID-19 and experiencing adverse health-related outcomes among middle-aged and older vulnerable adults. We will address key gaps in knowledge: (1) Are there specific multimorbidity patterns that increase risk of COVID-19 infections, and do they vary by age and race/ethnicity? (2) What is the relationship between specific multimorbidity patterns and disease accumulation among patients with COVID-19, and does this differ by age or race/ethnicity? (3) What is the relationship between multimorbidity patterns and experiencing more severe COVID-19 disease course, and does that differ by age and race/ethnicity? And, (4) Are there differential mortality risks by multimorbidity pattern among patients with COVID-19, and does age or race/ethnicity moderate this relationship? Our proposed research leverages clinical electronic health record (EHR) data from large networks of CHCs for rapid evaluation of the impact of COVID-19 among people with multimorbidity. We anticipate important insights from findings that will inform clinical processes (workflow, clinical care decision-making) and policies that serve safety-net populations by identifying multimorbidity patterns predictive of rapid COVID-19 related health downturns. We propose two aims to: SA1. Identify multimorbidity patterns associated with COVID-19 diagnoses. Examine specific disease patterns associated with diagnoses (e.g., cardiovascular, metabolic disease) and sociodemographic correlates (e.g., age, race/ethnicity) that confer greater susceptibility to COVID-19. SA2: Identify trajectories of adverse health-related outcomes for patients with COVID-19. Understand the impact of COVID 19 on progression of chronic disease (i.e., multimorbidity accumulation) in patients with various multimorbidity patterns and determine whether different patterns of pre-existing multimorbidity are associated with greater adverse health outcomes from COVID 19 infection, such as more severe disease course (e.g., hospital admissions, ICU admissions, inpatient days, mortality). We will also evaluate whether sociodemographic correlates (e.g., age, race/ethnicity) are associated with greater multimorbidity accumulation, more severe course of COVID-19, and mortality.