r(sh)gģt(y)~е\(yn)üЧur(ji)
l(f)r(sh)g2018-05-29 11:43
x}r(sh)g + t(y) Їl(wi)I(y)201704
ժҪĿ:̽ӑr(sh)gģA(y)yt(y)~еĿ:ijt(y)Ժ2010~2014l(f)DЅˌ(sh)Ht(y)ӛ~M(fi)Ô(sh)(j)A(ch),D_(d)~Ɣ(sh)(j)YM(jn)ۙо,l(f)F(xin)׃Ҏ(gu),\(yn)SPSS19.0ҽģr(sh)gģ,2015ijt(y)Ժl(f)ӛ~M(fi)M(jn)A(y)y,Ì(sh)Hl(f)ӛ~M(fi)M(jn)(yn)CY(ji):о,r(sh)gģ͜yA(y)yMֵc^yֵw3.37%,c(sh)HrǺY(ji)Փ:r(sh)gģܞt(y)Ժt(y)~ƹеěQc(yng)ṩ(j)
[Abstract]:Objective: to explore the feasibility of time series model in predicting the total amount of medical insurance. Methods: based on the actual medical insurance charge data of the insured in a hospital from 2010 to 2014, the data of total amount control in D city were tracked and studied, and the regularity of periodic change was found. A time series model was established by using SPSS19.0 expert modeler to predict the charge of accounting in a hospital in 2015. Results: the results show that the predicted fitting value of the time series model is 3.37 different from the observed value, which is basically consistent with the actual situation. Conclusion: the time series model can provide reference for the decision-making and application of medical insurance total control management.
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𡿣V|ʡУ܌W(xu)c(din)(sh)(yn)(xing)Ŀl(wi)оcur(ji)c(din)(sh)(yn)ҡ(̖(ho):2015WSYS0010)
̖(ho)F842.684;R197.1
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1 꾧;س;;ƽ;;Ԫr(sh)gģͼ䑪(yng)[A];2011Їl(wi)y(tng)Ӌ(j)W(xu)(hu)(hu)hՓļ[C];2011
ľ̖(ho)1950763
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