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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
|招呼Ta 关注Ta
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Summary
  B3 S1 q. T3 ]* B" M/ w; CSocial attention has been increasingly paid to health care systems varied in effectiveness and: h  \" a  e" x5 n% v6 e! C
efficiency. This ** addresses the assessment and prediction of health care system. First and
& V" A/ d; c! h& d  Eforemost, a metrics list is established and refined for further assessment. Secondly, model tests are
* X/ G/ v3 F* p+ B+ O$ u- Qconducted between countries. Thirdly, a predictive model based on the relationship between0 n" R  l/ s# c9 @# v- i
changes and performance is proposed for restructure of the United States health system.
( {: [. {' X# Z% L" U3 oUnder the guidance of WHO Health System Performance Framework, we gain an insight of the
: u, o5 `7 H6 `2 L& Fproblem. Focusing on the outcomes, health, responsiveness and financial protection, we devise
" O+ c, \& U# y+ D" ometrics to build an index system for evaluat ion. Lists which describe each metric are presented
2 L$ ?/ r* D- i: v' K5 [+ l" L+ Rafterwards. Using Comprehensive Evaluation Method (CEM), combinations of metrics are carried. C# y/ [2 e6 Q! ?& T- Q
out, yielding metric o for effectiveness and for efficiency , which are the ultimate goals of A o P
! g* |2 s5 \$ u' L9 O& Xhealth care system. With these metrics, we can compare the relative quality of systems. After a  ~8 h* D: V" I- h( t3 S+ @
thorough search of data sources, we refine the metrics list based on data availability, and also
! e% f5 S" r* j$ G( i' ]present the estimating and obtaining approaches.
: l1 e. I* l6 }1 d5 GFor the purpose of international comparison, Principal Components Analysis is applied to choose
3 J6 M9 ?+ m5 [! x  Y' X$ Pthe most important and viable metrics. Life expectancy at birth, prevalence of tuberculosis,
2 p0 K/ ?3 R1 \immunization coverage among 1-years-olds and fairness of financial contribution are finally, r9 R: G% K9 |) Y" G# D; y
selected. Then modified Analytical Hierarchy Process is processed to weigh each metric. The test, o8 Z" h( ~  \4 p4 S  F
results between the United States and two other countries are showed below:$ _/ x' E# C1 t1 P
Investigating the discrepancy between results, we attribute the cause to the differences in devise of) p# _1 n2 U1 v; Z  E! z% T3 V& h
metrics and weights in CEM.
# U/ ]4 }; X$ O+ W" eThen we propose a novel framework for prediction of restructure. Stepwise Regression Analysis is$ A  @1 T1 H- I" p% \* c5 Z
introduced to find the relationship between the major contributing input factors and outcomes.4 R/ o# v) j1 V
Further more, after analyzing the variations of functions, possible policy changes to improve are
& T" R! G( G5 x: wrecommended, including strengthening primary care system and conducting a single payer system.+ o0 j1 i$ o; X4 `9 T$ e
Finally, the strength and weakness of our models are summarized, as well as two urgent aspects for
( {" m9 e/ d6 w3 b2 V/ k. S7 efuture work. The main achievements and contributions of this ** are concluded in the end.
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