Differences in Outpatient Health Care Utilization 12 Months after COVID-19 Infection by Race/Ethnicity and Community Social Vulnerability

Roth, Sarah E.; Govier, Diana J; Marsi, Katherine; Cohen-Cline, Hannah

doi:10.3390/ijerph19063481

Cited by 14 publications

(7 citation statements)

References 42 publications

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“…Consequently, attempts at elucidating how multimorbidity is occurring have been heavily constrained by the lack of integrated technologies and opportunities for data aggregation that exists within the domain of biomedical informatics. [13][14][15][16][17][18][19][20][21][22][23][24][25] Examining the capacities of the learning health systems (LHS) and processes in which multimorbidity data are collected and managed has not been prioritized, [14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30] leaving much of what is known about multimorbidity to focus on simply revealing patterns of chronic conditions among elderly patients (i.e., ages ≥65). Therefore, the aim of this study was to 1) characterize patterns of multimorbidity across patients, more broadly, among all demographic groups (i.e., age, gender, race, and ethnicity) and 2) concurrently, identify opportunities to strengthen the informatics capacity (i.e., technologies, data, and processes) of a learning health system, using the Arkansas Clinical Data Repository as a use case.…”

Section: Introductionmentioning

confidence: 99%

Cultivating informatics capacity for multimorbidity: A learning health systems use case

Williams

Garza

Lipchitz

et al. 2022

Journal of Multimorbidity and Comorbidity

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Background The aim of this study was to characterize patterns of multimorbidity across patients and identify opportunities to strengthen the informatics capacity of learning health systems that are used to characterize multimorbidity across patients. Methods Electronic health record (EHR) data on 225,710 multimorbidity patients were extracted from the Arkansas Clinical Data Repository as a use case. Hierarchical cluster analysis identified the most frequently occurring combinations of chronic conditions within the learning health system’s captured data. Results Results revealed multimorbidity was highest among patients ages 60 to 74, Caucasians, females, and Medicare payors. The largest numbers of chronic conditions occurred in the smallest numbers of patients (i.e., 70,262 (31%) patients with two conditions, two (<1%) patients with 22 chronic conditions). The results revealed urgent needs to improve EHR systems and processes that collect and manage multimorbidity data (e.g., creating new, multimorbidity-centric data elements in EHR systems, detailed longitudinal tracking of compounding disease diagnoses). Conclusions Without additional capacity to collect and aggregate large-scale data, multimorbidity patients cannot benefit from the recent advancements in informatics (i.e., clinical data registries, emerging data standards) that are abundantly working to improve the outcomes of patients with single chronic conditions. Additionally, robust socio-technical system studies of clinical workflows are needed to assess the feasibility of integrating the collection of risk factor data elements (i.e., psycho-social, cultural, ethnic, and socioeconomic attributes of populations) into primary care encounters. These approaches to advancing learning health systems for multimorbidity could substantially reduce the constraints of current technologies, data, and data-capturing processes.

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Section: Introductionmentioning

confidence: 99%

Cultivating informatics capacity for multimorbidity: A learning health systems use case

Williams

Garza

Lipchitz

et al. 2022

Journal of Multimorbidity and Comorbidity

View full text Add to dashboard Cite

show abstract

“…Our results are consistent with previous findings identifying specific subgroups as more vulnerable to both acute-COVID ( 38 ) and several symptoms of long-COVID ( 39 – 41 ). Additionally, recent evidence indicates higher rates of healthcare utilization (e.g., visits with a primary care provider) in the year following the acute COVID infection among socially vulnerable populations ( 42 ), highlighting the potential burden on healthcare facilities and staff among marginalized communities. Notably, in the current analysis, individuals from the high-income group that experienced mild or severe acute-COVID symptomatology also reported relatively high rates of long-term symptoms.…”

Section: Discussionmentioning

confidence: 99%

Prevalence of Long-COVID Among Low-Income and Marginalized Groups: Evidence From Israel

Heller

Chun

Shapira³

et al. 2022

Int J Public Health

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Objective: To identify the socioeconomic and demographic factors associated with the prevalence of self-reported long-COVID symptoms.Method: We examined the association between acute-COVID (SARS-CoV-2) and long-COVID symptoms, by a cross-sectional analysis of data obtained on a prospective online-survey, conducted from November to December 2021 on a nationally-representative sample of the Israeli population (N = 2,246).Results: Findings suggest that there is a greater likelihood of experiencing long-COVID symptoms among low-income and among marginalized groups. After controlling for demographic and socioeconomic attributes, those who had moderate/severe acute-COVID were 1.3 (p < 0.05) times more likely to experience a long-term symptom and also reported more long-term symptoms (2.2 symptoms) than those who have not been infected (1.4 symptoms; p < 0.01). Among the low-income group, a larger gap in symptom count was found between those who had moderate/severe acute-COVID (3.3 symptoms) and those who had not been infected (1.8 symptoms, p < 0.05).Conclusion: Our findings highlight the importance of raising awareness of long-COVID among marginalized population groups, and to the therapeutic options available. Such efforts should be tailored and should consider the unique socioeconomic and cultural characteristics, as well as the preexisting low access to healthcare services among these groups.

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“…For example, COVID-19 related mortality experienced among racial/ethnic minority adults was 1.9–2.4 times greater than non-Hispanic adults (Badalov et al, 2022). Estimates also show a disproportionate burden of COVID-19 infection (Adhikari et al, 2020; Kimani et al, 2021) and hospitalizations (Karaca-Mandic et al, 2021; Roth et al, 2022) experienced by racial/ethnic adults. Even as the U.S. federal government has rescinded the COVID-19 national public health emergency, non-Hispanic Black and Latinx adults are still grappling with the consequences of elevated COVID-19 transmission/infection and mortality inequities at the height of the pandemic.…”

Section: Introductionmentioning

confidence: 99%

COVID-19-Associated Food Insecurity and Mental Health Symptoms Among Latinx Adults in the United States

Trabilsy,

Ortiz,

Camacho-Rivera

2023

Hisp Health Care Int

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Introduction: U.S. Latinx adults were disproportionately burdened by COVID-19 infection, as well as food insecurity compared to their non- Hispanic white adults. It is less clear if within-group variations among U.S. Latinx adults exist in food insecurity and mental health outcomes. Methods: We conducted a secondary data analysis of repeated cross-sectional survey waves from the Understanding America Study (UAS) study ( N = 182,865). We computed multivariable generalized linear regression models to examine associations between food insecurity, demographic characteristics, and depressive symptoms. Results: Participants with a history of food insecurity had a higher prevalence of depressive symptoms compared to those without a history of food insecurity (21.1% compared to 5.23%, p < .0001). Mexican participants reported a significantly higher prevalence of depression compared to Latino participants of Puerto Rican, Central American, or another Latino ethnicity (8.94% compared to 2.84%, 1.76%, and 2.91%, respectively, p < .0001). Associations of self-reported food insecurity among men and women varied by asthma status. Conclusions: Our study demonstrates that participants with a history of food insecurity had a higher prevalence of depressive symptoms compared to those without a history of food insecurity. Our findings also illuminate the importance of disaggregating U.S. Latinx adults when examining associations between food insecurity and mental health.

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Differences in Outpatient Health Care Utilization 12 Months after COVID-19 Infection by Race/Ethnicity and Community Social Vulnerability

Cited by 14 publications

References 42 publications

Cultivating informatics capacity for multimorbidity: A learning health systems use case

Cultivating informatics capacity for multimorbidity: A learning health systems use case

Prevalence of Long-COVID Among Low-Income and Marginalized Groups: Evidence From Israel

COVID-19-Associated Food Insecurity and Mental Health Symptoms Among Latinx Adults in the United States

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