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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
, |6 o4 g9 @! x0 R/ h& T& J2 N: M9 aSocial attention has been increasingly paid to health care systems varied in effectiveness and
  F2 W& z) z* _efficiency. This ** addresses the assessment and prediction of health care system. First and  y* S$ O( S2 {9 S4 u
foremost, a metrics list is established and refined for further assessment. Secondly, model tests are
4 ]! l: c1 U, Y8 t( |conducted between countries. Thirdly, a predictive model based on the relationship between: a8 h6 ~! h0 Z& s% E
changes and performance is proposed for restructure of the United States health system.# Z+ [' `7 O- _2 ^
Under the guidance of WHO Health System Performance Framework, we gain an insight of the
0 e; B( S+ ]5 H7 u+ L( }5 [problem. Focusing on the outcomes, health, responsiveness and financial protection, we devise- b. Z8 Q" l+ X( y! E
metrics to build an index system for evaluat ion. Lists which describe each metric are presented& `3 r# g/ f8 i/ N2 R
afterwards. Using Comprehensive Evaluation Method (CEM), combinations of metrics are carried8 U* w$ V6 n8 V! O3 r  X
out, yielding metric o for effectiveness and for efficiency , which are the ultimate goals of A o P
! S; k9 z3 W% h$ G  w( x$ ^health care system. With these metrics, we can compare the relative quality of systems. After a
4 k+ m2 H. h" N0 S; ^' F) _thorough search of data sources, we refine the metrics list based on data availability, and also. n) d! C: e! d& _
present the estimating and obtaining approaches.  c/ w3 o: k0 W) p+ Y9 P$ k7 J1 L' O: Q
For the purpose of international comparison, Principal Components Analysis is applied to choose2 d& t2 I! t' u" z' z9 N
the most important and viable metrics. Life expectancy at birth, prevalence of tuberculosis,/ {* ]5 ~& [! g( D- z8 r
immunization coverage among 1-years-olds and fairness of financial contribution are finally, a8 w4 e7 e8 s  O) |8 Y
selected. Then modified Analytical Hierarchy Process is processed to weigh each metric. The test2 R6 h% |* q4 ?$ C9 O
results between the United States and two other countries are showed below:& g( ?0 o( v/ V2 T0 m  H( X7 b
Investigating the discrepancy between results, we attribute the cause to the differences in devise of4 l" N/ v' Y" @
metrics and weights in CEM.* U# k. E+ @( Y. G  ^
Then we propose a novel framework for prediction of restructure. Stepwise Regression Analysis is
, k! c3 d, E% a; w  k" y6 Aintroduced to find the relationship between the major contributing input factors and outcomes.
- K: j+ I) A* z2 ]Further more, after analyzing the variations of functions, possible policy changes to improve are
3 w' }; |5 J2 }. o3 J9 zrecommended, including strengthening primary care system and conducting a single payer system.. ^! e" t0 i1 h9 e
Finally, the strength and weakness of our models are summarized, as well as two urgent aspects for8 w8 e4 |+ G2 u( d
future work. The main achievements and contributions of this ** are concluded in the end.
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