Cluster analysis of COVID-19 recovery center patients at a clinic in Boston, MA 2021-2022: impact on strategies for access and personalized care

Arch Public Health. 2023 Mar 14;81(1):39. doi: 10.1186/s13690-023-01033-2.

Abstract

Background: There are known disparities in COVID-19 resource utilization that may persist during the recovery period for some patients. We sought to define subpopulations of patients seeking COVID-19 recovery care in terms of symptom reporting and care utilization to better personalize their care and to identify ways to improve access to subspecialty care.

Methods: Prospective study of adult patients with prior COVID-19 infection seen in an ambulatory COVID-19 recovery center (CRC) in Boston, Massachusetts from April 2021 to April 2022. Hierarchical clustering with complete linkage to differentiate subpopulations was done with four sociodemographic variables: sex, race, language, and insurance status. Outcomes included ICU admission, utilization of supplementary care, self-report of symptoms.

Results: We included 1285 COVID-19 patients referred to the CRC with a mean age of 47 years, of whom 71% were female and 78% White. We identified 3 unique clusters of patients. Cluster 1 and 3 patients were more likely to have had intensive care unit (ICU) admissions; Cluster 2 were more likely to be White with commercial insurance and a low percentage of ICU admission; Cluster 3 were more likely to be Black/African American or Latino/a and have commercial insurance. Compared to Cluster 2, Cluster 1 patients were more likely to report symptoms (ORs ranging 2.4-3.75) but less likely to use support groups, psychoeducation, or care coordination (all p < 0.05). Cluster 3 patients reported greater symptoms with similar levels of community resource utilization.

Conclusions: Within a COVID-19 recovery center, there are distinct groups of patients with different clinical and socio-demographic profiles, which translates to differential resource utilization. These insights from different subpopulations of patients can inform targeted strategies which are tailored to specific patient needs.

Keywords: Community health; Disparities; Equity; Informatics; Quality of care.