Pular para o conteúdo principal

ETHNOS_APP

Início • Busca • Periódicos • Lista 0

Evaluating Telehealth Uptake Among North Carolina Medicaid Beneficiaries With Musculoskeletal Conditions

Insights From the Covid-19 Pandemic

Dados Bibliográficos

ID9101571
AutoresSalama S Freed (0000-0001-7158-0792, Department of Health Policy and Management, Milken Institute School of Public Health, The George Washington University, Washington, DC, autor correspondente), Kelley A Jones (0000-0001-8208-4487, Department of Population Health Sciences, Duke University School of Medicine), Rebecca Whitaker (0000-0003-4500-3451, Duke University), Rebecca G Whitaker (Duke University), Katherine Norman (0000-0002-3064-5294, Department of Population Health Sciences, Duke University School of Medicine), Marissa Carvalho (Department of Physical Therapy and Occupational Therapy, Duke Health, Durham NC), Abhigya Giri (Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, The George Washington University, Washington, DC), Ashley Lake (Duke University), Ashley Davis Lake (Duke University), Yolande Pokam Tchuisseu (0000-0001-7999-0091, Duke University), Samantha Repka (Duke University), Karina Vasudeva (Department of Health Policy and Management, The University of North Carolina at Chapel Hill, Chapel Hill, NC), Nadia Bey (Duke University), N Mahfouz Bey (0009-0006-4273-7053, Duke University), Janet Prvu Bettger (0000-0001-9708-8413, Temple University, autor correspondente)
Ano2023
Volume61
Fascículo11
Páginas750-759
Data de publicação2023-11-01
Peer ReviewedSim
Open AccessNão
TipoARTICLE
PeriódicoMedical Care (JOURNAL)
Identificadores do periódicoISSN: 0025-7079 • E-ISSN: 1537-1948
EditoraOvid Technologies (Wolters Kluwer Health) (PUBLISHER)
DOI10.1097/mlr.0000000000001915
PMID37733405
OpenAlexW4386910638
IdiomaEN
Referências citadas24

BACKGROUND: The shift from in-person to virtual visits, known as telehealth (TH), during the COVID-19 pandemic was a significant change for North Carolina (NC) Medicaid beneficiaries seeking treatment for musculoskeletal (MSK) conditions, as remote care for these conditions was previously unavailable. We used this policy change to investigate factors associated with TH uptake and whether TH availability mitigated disparities in access to care or affected emergency department (ED) visits among these beneficiaries. RESEARCH DESIGN: Using 2019-2021 NC Medicaid claims, we identified beneficiaries receiving treatment for MSK conditions before COVID-19 (March 2019-February 2020) and analyzed uptake of newly available TH during COVID-19 (April 2020-March 2021). We used descriptive analysis and Poisson generalized estimating equations to quantify TH uptake, factors associated with TH uptake, and the association with ED visits during COVID-19. RESULTS: Black and Hispanic beneficiaries were less likely to use TH compared with White and non-Hispanic counterparts (10%, P <0.001 and 20%, P =0.03, respectively). Adults eligible for Tailored Plans, specialized NC Medicaid plans for those with significant behavioral health needs or intellectual/developmental disabilities, were less likely to use TH [adjusted risk ratio (ARR):0.83, 95% CI (0.78, 0.87)]; youth eligible for Tailored Plans were more likely to use TH [ARR:1.28, 95% CI (1.16, 1.42)]. Lower county-level internet access was associated with lower TH use [ARR: 0.85, 95% CI (0.82, 0.99)]. No statistical difference in ED utilization was observed between TH users and non-users. CONCLUSIONS: TH has the potential to deliver convenient care to beneficiaries with MSK conditions who can access it. Further research and policy changes should explore and address underlying factors driving disparities and improve equitable access to care for this population

Environmental health · Family medicine · Health care · Health equity · Medicaid · Poisson regression · Population · Public health · Telehealth · Telemedicine · COVID-19 and healthcare impacts · Demography · Medicine · Musculoskeletal Disorders and Rehabilitation · Nursing · Telemedicine and Telehealth Implementation · Gerontology

  • Easy SAS Calculations for Risk or Prevalence Ratios and Differences

    Donna Spiegelman•American Journal of Epidemiology•2005

  • A Modified Poisson Regression Approach to Prospective Studies with Binary Data

    Guangyong Zou•American Journal of Epidemiology•2004

  • A new method of classifying prognostic comorbidity in longitudinal studies

    Open Access•Mary E Charlson, Peter Pompei et al.•Journal of Chronic Diseases•1987

  • Geographic, racial/ethnic, and socioeconomic inequities in broadband access

    Open Access•Whitney E Zahnd, NATHANIEL BELL et al.•The Journal of Rural Health•2022

  • Back and neck pain are related to mental health problems in adolescence

    Open Access•Clare S Rees, Anne J Smith et al.•BMC Public Health•2011

  • Coding Algorithms for Defining Comorbidities in ICD-9-CM and ICD-10 Administrative Data

    Hude Quan, Vijaya Sundararajan et al.•Medical Care•2005

  • Telehealth Utilization Among Adult Medicaid Beneficiaries in North Carolina with Behavioral Health Conditions During the Covid-19 Pandemic

    Open Access•Alexis French, Kelley A Jones et al.•Journal of Racial and Ethnic…•2024

Velocidade de citaçãohistorical
Altamente citadoNão
Ethnos_APP • Projeto Open Source • Licença MIT • Frontend v2.0.0 • Privacidade e Cookies • Documentação da API: api.ethnos.app/docs • Código da API: GitHub • DOI: 10.5281/zenodo.17049435 • Código do Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae