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Health decision aids during clinical...

Decker, Carole Jane.

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Health decision aids during clinical decision making: Statistical models for predicting health status and survival.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Health decision aids during clinical decision making: Statistical models for predicting health status and survival./
作者:	Decker, Carole Jane.
面頁冊數:	198 p.
附註:	Source: Dissertation Abstracts International, Volume: 65-08, Section: B, page: 3945.
Contained By:	Dissertation Abstracts International65-08B.
標題:	Health Sciences, Nursing. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3143338
ISBN:	0496013602

Health decision aids during clinical decision making: Statistical models for predicting health status and survival.
Decker, Carole Jane.

Health decision aids during clinical decision making: Statistical models for predicting health status and survival. - 198 p.

Source: Dissertation Abstracts International, Volume: 65-08, Section: B, page: 3945.

Thesis (Ph.D.)--The University of Kansas, 2004.

Involving patients in decisions about care they receive has been shown to decrease limitations on functional ability imposed by disease (Greenfield, Kaplan, & Ware, 1985). Individualizing information clinicians share with patients can be dauntin

ISBN: 0496013602Subjects--Topical Terms:

1017798
Health Sciences, Nursing.

Health decision aids during clinical decision making: Statistical models for predicting health status and survival.
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520 $a Involving patients in decisions about care they receive has been shown to decrease limitations on functional ability imposed by disease (Greenfield, Kaplan, & Ware, 1985). Individualizing information clinicians share with patients can be dauntin
520 $a Fifteen final variables remained in the four models predicting health status and survival. The models were moderately strong (adjusted R2 = .390 to .417, c-statistic = .702 to .789). Variables predictive of outcomes were: (a) angina frequency i
520 $a A combination of statistical and clinical approaches successfully reduced a large dataset to a parsimonious and statistically valid set of variables that predicted health status outcomes and survival. Ultimately, these models could be used by cl
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