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Econometric models of medical decisi...

Bandyopadhyay, Sumana.

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Econometric models of medical decision making and health outcomes.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Econometric models of medical decision making and health outcomes./
作者:	Bandyopadhyay, Sumana.
面頁冊數:	151 p.
附註:	Source: Dissertation Abstracts International, Volume: 67-12, Section: A, page: 4621.
Contained By:	Dissertation Abstracts International67-12A.
標題:	Economics, General. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=NR19783
ISBN:	9780494197837

Econometric models of medical decision making and health outcomes.
Bandyopadhyay, Sumana.

Econometric models of medical decision making and health outcomes. - 151 p.

Source: Dissertation Abstracts International, Volume: 67-12, Section: A, page: 4621.

Thesis (Ph.D.)--York University (Canada), 2006.

Finally, treatment choice is explicitly modeled in conjunction with the survival rate, where the choice of treatment has a direct impact on the survival rates of patients.

ISBN: 9780494197837Subjects--Topical Terms:

1017424
Economics, General.

Econometric models of medical decision making and health outcomes.
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500 $a Source: Dissertation Abstracts International, Volume: 67-12, Section: A, page: 4621.
502 $a Thesis (Ph.D.)--York University (Canada), 2006.
520 $a Finally, treatment choice is explicitly modeled in conjunction with the survival rate, where the choice of treatment has a direct impact on the survival rates of patients.
520 $a In this thesis three structural models are developed to examine the roles of patients and physicians in shared or joint medical decision making, allowing each party's preferences to simultaneously affect the other's decision function and to examine the resulting health outcomes, as measured by patients' survival rates. This is applied to Canadian End-Stage Renal Disease (ESRD) patients who, with their physicians, choose between Transplantation, Heamodialysis and Peritoneal Dialysis.
520 $a For estimating joint treatment decisions, a likelihood function is developed based on Poirier's (1980) model of partial observability. A number of results emerge including strong evidence that decision making in this context is indeed a shared process.
520 $a Estimation of the survival rates of patients undergoing different treatments for the same disease is important for many medical, economic and actuarial reasons. An obvious complication is that unobservable factors may lead to selection biases. One way to control for selection bias is to condition on observable covariates. This may reduce the problem, but unobservable factors may still have an impact on the patients' outcomes and contribute to estimation bias. In case of survival models this can occur whether or not the unobservable is correlated with (or independent of) the control variables. A Mixed Proportional Hazard rate setup is used to study the length of treatment of ESRD, estimating different forms of survival models. Models are estimated both with and without unobserved heterogeneity. Choice of treatment is found to have a significant impact on survival rates and also quite correlated with unobservables.
520 $a This study makes a contribution to two areas of research. From a statistical perspective, the partial observability class of models has at its disposal less information than that used in the genre of discrete choice models since the variable of interest, treatment decision, is a product of two indicator variables. From a social science perspective, the issue of shared decision making has so far been largely descriptive rather than analytical.
590 $a School code: 0267.
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710 2 $a York University (Canada). $3 1017889
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