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08年icm论文(神经网络算法)

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发表于 2009-1-30 10:00 |只看该作者 |倒序浏览
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Summary
( K/ X) j# B/ F5 K8 |2 {Social attention has been increasingly paid to health care systems varied in effectiveness and1 T4 Z6 n% `' n/ l# [  ?4 R7 u
efficiency. This ** addresses the assessment and prediction of health care system. First and
* H; X8 P. R+ ^) lforemost, a metrics list is established and refined for further assessment. Secondly, model tests are
9 ^! N8 |( Q- O# D. d1 C" Rconducted between countries. Thirdly, a predictive model based on the relationship between
1 c8 x  ~4 d3 q& \9 Ychanges and performance is proposed for restructure of the United States health system." ?$ `* U: L' Y/ U8 s  H
Under the guidance of WHO Health System Performance Framework, we gain an insight of the
* M3 b+ m+ a# c. Yproblem. Focusing on the outcomes, health, responsiveness and financial protection, we devise' N: a) A& l8 L8 n
metrics to build an index system for evaluat ion. Lists which describe each metric are presented
2 O, y7 T: }! b! \$ P5 v3 ^0 v" N4 G6 jafterwards. Using Comprehensive Evaluation Method (CEM), combinations of metrics are carried
! w2 z$ w' @8 mout, yielding metric o for effectiveness and for efficiency , which are the ultimate goals of A o P+ r$ }- e+ z) \# \% |  y& z- o
health care system. With these metrics, we can compare the relative quality of systems. After a8 X& Y( [  F: Y0 s, a5 ^, f
thorough search of data sources, we refine the metrics list based on data availability, and also
) R# }. M6 \* j5 m, ]present the estimating and obtaining approaches." Q8 o; F) }  F* p; `. [$ d
For the purpose of international comparison, Principal Components Analysis is applied to choose9 V6 p6 s! v' y0 g4 N
the most important and viable metrics. Life expectancy at birth, prevalence of tuberculosis,- C. ]$ R7 l4 S, F
immunization coverage among 1-years-olds and fairness of financial contribution are finally
$ z& R; D4 k4 X: wselected. Then modified Analytical Hierarchy Process is processed to weigh each metric. The test6 }# P; |% l) J
results between the United States and two other countries are showed below:5 R$ C, k3 ~3 Z# V9 k/ U
Investigating the discrepancy between results, we attribute the cause to the differences in devise of
6 N5 p7 w8 P$ v  Z" G+ B" gmetrics and weights in CEM.  k4 i0 p6 s5 \8 O/ b
Then we propose a novel framework for prediction of restructure. Stepwise Regression Analysis is0 g& ~8 i! W+ {$ C9 G
introduced to find the relationship between the major contributing input factors and outcomes.  D) S" U* a9 ?/ ^# ^$ R
Further more, after analyzing the variations of functions, possible policy changes to improve are
2 H, X6 w1 B' w0 ~5 lrecommended, including strengthening primary care system and conducting a single payer system.% h/ O* w+ z  w7 E  h
Finally, the strength and weakness of our models are summarized, as well as two urgent aspects for
$ h( l6 D& e1 y  s" Y2 S$ D. A$ Afuture work. The main achievements and contributions of this ** are concluded in the end.
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