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The influence of social determinants of health on epilepsy treatment delays in an Arizona Medicaid population.
Sirven, Joseph; Sprout, Gregory T; Speer, Matthew; Simic, Grant; Ems, Derek; Harootunian, Gevork; Reddy, Swapna.
Afiliação
  • Sirven J; Arizona State University, 550 N 3(rd) St, Phoenix, AZ 85004, USA; Mayo Clinic, 4500 San Pablo Rd S, Jacksonville, FL 32224, USA. Electronic address: Sirven.Joseph@mayo.edu.
  • Sprout GT; Arizona State University, 550 N 3(rd) St, Phoenix, AZ 85004, USA. Electronic address: gregorysprout@email.arizona.edu.
  • Speer M; Arizona State University, 550 N 3(rd) St, Phoenix, AZ 85004, USA. Electronic address: Matthew.Speer@asu.edu.
  • Simic G; UCB Pharma, 1950 Lake Park Dr SE, Smyrna, GA 30080, USA. Electronic address: Grant.Simic@UCB.com.
  • Ems D; UCB Pharma, 1950 Lake Park Dr SE, Smyrna, GA 30080, USA. Electronic address: derek.ems@ucb.com.
  • Harootunian G; Center for Health Information and Research, Arizona State University, 502 E Monroe St, Mercado Bldg C, Suite C320, Phoenix, AZ 85004, USA. Electronic address: Gevork.Harootunian@asu.edu.
  • Reddy S; Arizona State University, 550 N 3(rd) St, Phoenix, AZ 85004, USA. Electronic address: Swapna.Reddy@asu.edu.
Epilepsy Behav ; 126: 108473, 2022 01.
Article em En | MEDLINE | ID: mdl-34920347
ABSTRACT

OBJECTIVE:

The purpose of this study was to better understand the role of social determinants of health (SDoH) in both treatment delays and treatment gaps for individuals with epilepsy (IWE) enrolled in Arizona's Medicaid program using predictive models at the population and individual levels.

METHODS:

In this retrospective cohort study, two statistical regression models were developed using Arizona Medicaid medical and pharmacy claims records from 2015-2019 and selected census tract-level SDoH data. Three treatment outcomes were defined timely treatment (treated within thirty days); delayed treatment (treated after thirty days); and untreated. For the first model, least squares regression was used to regress the epilepsy treatment delays on selected SDoH factors at the population-level. For the second model, multinomial logistic regression was used to estimate associations between epilepsy treatment delays and individual-level sociodemographic factors.

RESULTS:

Of the 5965 IWE identified with a new epilepsy diagnosis during the study period, 43.1% were treated with a mean delay of 180 days. Among the treated population, 42% received timely treatment. A treatment gap of at least 40.6% and potentially up to 56.9% was calculated. Individuals with epilepsy diagnosed in an inpatient setting or in emergency departments were more likely to be treated and receive timely treatment than those diagnosed in an office or clinic setting. Individuals with epilepsy diagnosed in "other" settings were more likely to go untreated or receive delayed treatment than a patient diagnosed in an office or clinic. Compared to IWE aged 31-50 years, IWE aged 0-30 years were more likely to receive timely treatment, IWE aged 51-64 years were more likely to receive delayed treatment, and IWE aged 65 years or older were more likely to go untreated. Widowed IWE were more likely to go untreated relative to single patients. Individuals with epilepsy experiencing homelessness were also more likely to go untreated. Unemployed IWE were more likely to go untreated or receive delayed treatment. Native American IWE were more likely to go untreated compared to White patients.

CONCLUSIONS:

Treatment gaps and treatment delays are experienced by IWE in the Arizona Medicaid population. The SDoH factors predicted to impact treatment delays include care setting, age, race, marital status, homelessness, and employment.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Medicaid / Epilepsia Tipo de estudo: Diagnostic_studies / Observational_studies / Prognostic_studies Limite: Adolescent / Adult / Aged / Child / Child, preschool / Humans / Infant / Middle aged / Newborn País/Região como assunto: America do norte Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Medicaid / Epilepsia Tipo de estudo: Diagnostic_studies / Observational_studies / Prognostic_studies Limite: Adolescent / Adult / Aged / Child / Child, preschool / Humans / Infant / Middle aged / Newborn País/Região como assunto: America do norte Idioma: En Ano de publicação: 2022 Tipo de documento: Article