Treatment Delays in Epilepsy Care- How Do Social Determinants of Health Influence this Gap in Care

Project: Research project

Project Details

Description

Treatment Delays in Epilepsy Care- How Do Social Determinants of Health Influence this Gap in Care Treatment Delays in Epilepsy Care- How Do Social Determinants of Health Influence this Gap in Care Epilepsy is a common disorder in the United States (US) and globally that affects patients and caregivers health and quality of life. In the US, approximately 3.4 million people, or 1.2% of the population, are living with epilepsy; and the number is increasing. Patients with a diagnosis of epilepsy face many challenges, and untreated epilepsy can result in poor health outcomes with potentially serious implications. Antiepileptic drugs (AEDs) are the essence of epilepsy treatment. Clinical guidelines recommend treating epilepsy as early as possible, but despite the availability of effective treatments, initiation of AEDs is often significantly delayed. In the US, one-third of newly diagnosed patients remain untreated up to 3 years after epilepsy diagnosis (Khalilani, 2019). This significant treatment gap increases the risk of medical events, ED visits and hospital admissions, however at this time there is limited research to explain the delay in AED initiation. Current thinking on population health would indicate that Social Determinants of Health (SDoH) may play a role in this critical gap in care. SDoH include factors such as ethnicity, age, gender, socioeconomics, housing, physical environment, employment and health behaviors, as well as access to healthcare and the quality of care. There is limited research about the impact of SDoH on epilepsy and given the importance of these factors on health outcomes this represents a significant gap in knowledge for the epilepsy community. A recent study outlines a framework for evaluating how SDoH affect epilepsy care management and health outcomes (Slaflarski, 2014). This framework proposes several areas that would be addressable by UCB such as improving access to regular epilepsy care, improving patient/provider factors, medication adherence, changing health behaviors, and improving psychosocial support. To our knowledge, this project will provide the first substantial research looking at the correlation between SDoH and epilepsy outcomes, and the insights generated about AED treatment delay may influence strategies for improving health outcomes in the epilepsy population in Arizona and beyond. RESEARCH PROJECT DESCRIPTION The Research Project is estimated to take place over seven (7) consecutive months. The Research Project will encompass a scoping literature review, gathering of SDoH data at a census tract-level, development of a predictive statistical model, building of an interactive Geographic Information System map (GIS Map), statistical analyses, development of poster/s to be presented at relevant population health and epilepsy conferences, and preparation of a manuscript for publication in a peer-reviewed journal. Initially a scoping literature review will be conducted by ASU to identify best practices regarding initiation of AED treatment, health outcomes related to AED treatment delays, and research on the implications of SDoH in epilepsy and other similar health conditions. At the completion of the literature review, a summary report will be developed. The Institutions CHiR team will develop a model that will relate the AED treatment gap for a patient with epilepsy with the SDoH at the census tract-level. The model will be built such that the relationships between SDoH and epilepsy treatment gaps can be quantified and examined in a study of census-tract level communities across Arizona (the Study). CHiR will develop a report describing the model and its use so it may be replicated in future studies. The following historical data will be gathered and included in the S tudy: 1. Existing Medicaid claims data from patients in Arizona with epilepsy are available from the years 2008 - 2017. This data will be used to determine the actual AED treatment gap for each patient and the census tract associated with the patients residential address. 2. SDoH data at the census tract-level. CHiR will extract the SDoH values specific to each patients census tract for each SDoH factor selected for inclusion in the study (see list below). CHiR will clean, standa
StatusFinished
Effective start/end date1/1/2012/5/20

Funding

  • INDUSTRY: Domestic Company: $212,826.00

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