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Measuring overtreatment: a structural model to estimate the impact of non-clinical factors on healthcare utilization

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Title
Measuring overtreatment: a structural model to estimate the impact of non-clinical factors on healthcare utilization
TitleInfo (displayLabel = Other Title); (type = alternative)
Title
Structural model to estimate the impact of non-clinical factors on healthcare utilization
Name (ID = NAME001); (type = personal)
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Arrieta
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Alejandro
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Alejandro Arrieta
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author
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Klein
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Roger
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Advisory Committee
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Roger W Klein
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chair
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Russell
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Louise
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Advisory Committee
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Louise Russell
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internal member
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Killingsworth
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Mark
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Advisory Committee
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Mark Killingsworth
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internal member
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Monheit
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Alan
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Advisory Committee
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Alan Monheit
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outside member
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Rutgers University
Role
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degree grantor
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Graduate School - New Brunswick
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theses
OriginInfo
DateCreated (qualifier = exact)
2008
DateOther (qualifier = exact); (type = degree)
2008-10
Language
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English
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electronic
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application/pdf
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text/xml
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ix, 100 pages
Abstract
It is well acknowledged that, in the agency relationship between physicians and patients, the informational advantage gives doctors an incentive to deviate from the appropriate treatment, thus incurring over- or under- utilization. However, the empirical consequence of this problem has not been adequately considered. In particular, physician agency creates a gap between appropriate treatment and actual treatment whose characteristics and effects on estimation are analogous to a classification error.
This thesis proposes a structural model based on misclassification in which the physician behavior characterizes the structure of the measurement error. The model produces consistent estimators and is able to measure the degree of over- and under-utilization by separating out the effect of clinical and non-clinical variables on treatment decision. The model is applied to cesarean section deliveries performed in New Jersey in 1999-2002. The results show a moderate but growing rate of non-clinically required c-sections of around 3.2%, implying that the rapid growth of c-section rates over these years is explained mainly by non-clinical factors.
In the second chapter, the model is used to study how reform in the Peruvian health system has increased physician incentives to overuse c-sections in private hospitals. C-section rates in the private sector grew from 27% to 48% after the health reform of 1997, while the rates remained constant at 19% in the public sector. Using a national survey, it is estimated that each year more than 13 thousand women are over-treated, having a c-section without medical reasons. This document highlights the consequences of unnecessary c-sections on women's reproductive rights, and establishes important implications and recommendations for other health reforms in Latin America.
The third chapter extends the parametric estimation of the structural misclassification model to a semi-parametric estimation based on a double-index semi-parametric maximum likelihood with bias correction (Klein and Vella, 2008). I show that misspecification error due to a wrong assumption in error distribution may lead to an important inconsistency in parametric estimates, thus justifying the use of a semi-parametric technique to support results. The parametric and semi-parametric models are compared using a Monte Carlo study and an application for c-section deliveries.
Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references (p. 93-99).
Subject (ID = SUBJ1); (authority = RUETD)
Topic
Economics
Subject (ID = SUBJ2); (authority = ETD-LCSH)
Topic
Medical care
Subject (ID = SUBJ3); (authority = ETD-LCSH)
Topic
Physician and patient
Subject (ID = SUBJ4); (authority = ETD-LCSH)
Topic
Medical economics
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Title
Graduate School - New Brunswick Electronic Theses and Dissertations
Identifier (type = local)
rucore19991600001
Identifier (type = hdl)
http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.17426
Identifier
ETD_1079
Location
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NjNbRU
Identifier (type = doi)
doi:10.7282/T3S46S9F
Genre (authority = ExL-Esploro)
ETD doctoral
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The author owns the copyright to this work.
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Open
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Name
Alejandro Arrieta
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Copyright holder
Affiliation
Rutgers University. Graduate School - New Brunswick
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Non-exclusive ETD license
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Author Agreement License
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I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
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