Race, Income, and Medical Care Spending Patterns in High-Risk Primary Care Patients: Results From the STOP-DKD (Simultaneous Risk Factor Control Using Telehealth to Slow Progression of Diabetic Kidney Disease) Study.
dc.contributor.author | Machen, Leah | |
dc.contributor.author | Davenport, Clemontina A | |
dc.contributor.author | Oakes, Megan | |
dc.contributor.author | Bosworth, Hayden B | |
dc.contributor.author | Patel, Uptal D | |
dc.contributor.author | Diamantidis, Clarissa | |
dc.date.accessioned | 2024-01-02T20:07:00Z | |
dc.date.available | 2024-01-02T20:07:00Z | |
dc.date.issued | 2022-01 | |
dc.description.abstract | Rationale & objectiveLittle is known about how socioeconomic status (SES) relates to the prioritization of medical care spending over personal expenditures in individuals with multiple comorbid conditions, and whether this relationship differs between Blacks and non-Blacks. We aimed to explore the relationship between SES, race, and medical spending among individuals with multiple comorbid conditions.Study designCross-sectional evaluation of baseline data from a randomized controlled trial.Setting & participantsThe STOP-DKD (Simultaneous Risk Factor Control Using Telehealth to Slow Progression of Diabetic Kidney Disease) study is a completed randomized controlled trial of Duke University primary care patients with diabetes, hypertension, and chronic kidney disease. Participants underwent survey assessments inclusive of measures of socio-demographics and medication adherence.PredictorsRace (Black or non-Black) and socioeconomic status (income, education, and employment).OutcomesThe primary outcomes were based on 4 questions related to spending, asking about reduced spending on basic/leisure needs or using savings to pay for medical care. Participants were also asked if they skipped medications to make them last longer.Analytical approachMultivariable logistic regression stratified by race and adjusted for age, sex, and household chaos was used to determine the independent effects of SES components on spending.ResultsOf 263 STOP-DKD participants, 144 (55%) were Black. Compared with non-Blacks, Black participants had lower incomes with similar levels of education and employment but were more likely to reduce spending on basic needs (29.2% vs 13.5%), leisure activities (35.4% vs 20.2%), and to skip medications (31.3% vs 15.1%), all P < 0.05. After multivariable adjustment, Black race was associated with increased odds of reduced basic spending (OR, 2.29; 95% CI, 1.14-4.60), reduced leisure spending (OR, 1.94; 95% CI, 1.05-3.58), and skipping medications (OR, 2.12; 95% CI, 1.12-4.04).LimitationsThis study was conducted at a single site in Durham, North Carolina, and nearly exclusively included insured patients. Further, the impact of the number of comorbid conditions, medication costs, or copayments was not assessed.ConclusionsIn primary care patients with multiple chronic diseases, Black patients are more likely to reduce spending on basic needs and leisure activities to afford their medical care than non-Black patients of equivalent SES.Clinicaltrialsgov identifierNCT01829256. | |
dc.identifier | S2590-0595(21)00225-9 | |
dc.identifier.issn | 2590-0595 | |
dc.identifier.issn | 2590-0595 | |
dc.identifier.uri | ||
dc.language | eng | |
dc.publisher | Elsevier BV | |
dc.relation.ispartof | Kidney medicine | |
dc.relation.isversionof | 10.1016/j.xkme.2021.08.016 | |
dc.rights.uri | ||
dc.subject | Chronic kidney disease | |
dc.subject | medical costs | |
dc.subject | medical spending | |
dc.subject | racial disparities | |
dc.title | Race, Income, and Medical Care Spending Patterns in High-Risk Primary Care Patients: Results From the STOP-DKD (Simultaneous Risk Factor Control Using Telehealth to Slow Progression of Diabetic Kidney Disease) Study. | |
dc.type | Journal article | |
duke.contributor.orcid | Bosworth, Hayden B|0000-0001-6188-9825 | |
duke.contributor.orcid | Diamantidis, Clarissa|0000-0001-8212-6288 | |
pubs.begin-page | 100382 | |
pubs.issue | 1 | |
pubs.organisational-group | Duke | |
pubs.organisational-group | School of Medicine | |
pubs.organisational-group | Staff | |
pubs.organisational-group | Basic Science Departments | |
pubs.organisational-group | Clinical Science Departments | |
pubs.organisational-group | Institutes and Centers | |
pubs.organisational-group | Biostatistics & Bioinformatics | |
pubs.organisational-group | Medicine | |
pubs.organisational-group | Psychiatry & Behavioral Sciences | |
pubs.organisational-group | Medicine, General Internal Medicine | |
pubs.organisational-group | Medicine, Nephrology | |
pubs.organisational-group | Duke Cancer Institute | |
pubs.organisational-group | Duke Clinical Research Institute | |
pubs.organisational-group | Institutes and Provost's Academic Units | |
pubs.organisational-group | University Institutes and Centers | |
pubs.organisational-group | Duke Global Health Institute | |
pubs.organisational-group | Center for the Study of Aging and Human Development | |
pubs.organisational-group | Initiatives | |
pubs.organisational-group | Duke Science & Society | |
pubs.organisational-group | Population Health Sciences | |
pubs.organisational-group | Duke Innovation & Entrepreneurship | |
pubs.organisational-group | Psychiatry & Behavioral Sciences, Behavioral Medicine & Neurosciences | |
pubs.organisational-group | Duke - Margolis Center For Health Policy | |
pubs.publication-status | Published | |
pubs.volume | 4 |
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