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Impact of the Affordable Care Act on...
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ProQuest Information and Learning Co.
Impact of the Affordable Care Act on Hospital Accessibility.
紀錄類型:
書目-語言資料,手稿 : Monograph/item
正題名/作者:
Impact of the Affordable Care Act on Hospital Accessibility./
作者:
Oumarou Sidibe, Mariama.
面頁冊數:
1 online resource (96 pages)
附註:
Source: Dissertation Abstracts International, Volume: 78-10(E), Section: B.
標題:
Engineering. -
電子資源:
click for full text (PQDT)
ISBN:
9781369851250
Impact of the Affordable Care Act on Hospital Accessibility.
Oumarou Sidibe, Mariama.
Impact of the Affordable Care Act on Hospital Accessibility.
- 1 online resource (96 pages)
Source: Dissertation Abstracts International, Volume: 78-10(E), Section: B.
Thesis (Ph.D.)--North Carolina Agricultural and Technical State University, 2017.
Includes bibliographical references
The 2010 Affordable Care Act (ACA) aims to expand health insurance coverage to over 30 million previously uninsured Americans. Many people are uninsured and cannot afford access to healthcare. However, even before this happens, we are facing supply-side problems. Many regions face shortages of hospitals/doctors, defined by low geographical accessibility and/or long queues. In this research we explore the location patterns of existing hospitals in the context of the insured and the uninsured to evaluate hospital accessibility and to improve service access. We used the assignment problem, an optimization method that minimizes total travel time of patients insured and/or uninsured, going to the closest hospital taking the capacity of the hospital into account. We calculate travel time as the estimated driving time along the road network between a block group centroid to any hospital. However data on health insurance coverage at a fine geographical level are not available to capture how access is influenced by either insured or uninsured status. The Bureau of Labor Statistics (BLS) has used state-level data and econometric modeling to estimate health insurance coverage rates at the US County level, called Small Area Health Insurance Estimates (SAHIE). In the present research we use a similar model through data mining techniques to calculate estimates at the Census Block Group level. We use these estimates to describe differences in insurance coverage rates and accessibility to hospitals for the insured versus the uninsured. We then discuss potential implications of the 2010 ACA. As a larger fraction of the population becomes insured, their usage of hospitals will increase, causing hospitals to fill up more quickly, diverting some people to hospitals farther away.
Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018
Mode of access: World Wide Web
ISBN: 9781369851250Subjects--Topical Terms:
561152
Engineering.
Index Terms--Genre/Form:
554714
Electronic books.
Impact of the Affordable Care Act on Hospital Accessibility.
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The 2010 Affordable Care Act (ACA) aims to expand health insurance coverage to over 30 million previously uninsured Americans. Many people are uninsured and cannot afford access to healthcare. However, even before this happens, we are facing supply-side problems. Many regions face shortages of hospitals/doctors, defined by low geographical accessibility and/or long queues. In this research we explore the location patterns of existing hospitals in the context of the insured and the uninsured to evaluate hospital accessibility and to improve service access. We used the assignment problem, an optimization method that minimizes total travel time of patients insured and/or uninsured, going to the closest hospital taking the capacity of the hospital into account. We calculate travel time as the estimated driving time along the road network between a block group centroid to any hospital. However data on health insurance coverage at a fine geographical level are not available to capture how access is influenced by either insured or uninsured status. The Bureau of Labor Statistics (BLS) has used state-level data and econometric modeling to estimate health insurance coverage rates at the US County level, called Small Area Health Insurance Estimates (SAHIE). In the present research we use a similar model through data mining techniques to calculate estimates at the Census Block Group level. We use these estimates to describe differences in insurance coverage rates and accessibility to hospitals for the insured versus the uninsured. We then discuss potential implications of the 2010 ACA. As a larger fraction of the population becomes insured, their usage of hospitals will increase, causing hospitals to fill up more quickly, diverting some people to hospitals farther away.
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