Forecasting Single Disease Cost of Cataract Based on Multivariable Regression Analysis and Backpropagation Neural Network.
In medical services, charge according to the disease is an important way to promote the reform of pricing mechanism, control the unreasonable growth of medical expenses, as well as reduce the burden on patients. Single disease cost forecasting that both identify potential influencing or driving fact...
| Publicado en: | Inquiry (00469580) Vol. 56 |
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| Autores principales: | , |
| Formato: | algorithm equations & formulas research tables/charts Journal Article |
| Publicado: |
Sage Publications Inc.
10/16/2019
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=139414394&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 139414394 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00469580 INQ jtl: Inquiry (00469580) issn: 00469580 maglogo: Y pubinfo: dt: 10/16/2019 vid: 56 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 139414394 139414394 139414394 10.1177/0046958019880740 139414394 ppct: 1 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Forecasting Single Disease Cost of Cataract Based on Multivariable Regression Analysis and Backpropagation Neural Network. aug: au: Qing, Fang Liu, Chuang affil: Business School, Sichuan University, Chengdu, China sug: subj: Forecasting Neural Networks (Computer) Health Care Costs Cataract Extraction Economics Human Multiple Linear Regression China Data Analysis Software Descriptive Statistics Lenses, Intraocular Pearson's Correlation Coefficient Models, Theoretical ab: In medical services, charge according to the disease is an important way to promote the reform of pricing mechanism, control the unreasonable growth of medical expenses, as well as reduce the burden on patients. Single disease cost forecasting that both identify potential influencing or driving factors and enable better proactive estimation of costs can guide the management and control of medical costs. This study aimed to identify the factors that affect the medical costs of single disease cataract and compare 2 regression models for anticipating acceptable medical cost forecasts. For this purpose, 483 patients with cataract surgery completed in West China Hospital from May 1, 2015, to October 1, 2015, were selected from hospital information system. For cost forecasting, multivariable regression analysis (MRA) and backpropagation neural network (BPNN) were used. Analysis of data was performed with SPSS21.0 and MATLAB2014a software. Total medical costs of patients with cataract (n = 483) ranged from 2015.00 to 13 359.00 CNY, and the mean ± standard deviation is 6292.29 ± 2639.43 CNY. Factors influencing costs of cataract in the MRA include, in importance order, intraocular lens (IOL) implantation (| r |: 0.805, P <.01), doctor level (| r |: 0.644, P <.01), payment source (| r |: 0.554, P <.01), admission status (| r |: 0.326, P <.01), additional diagnosis (| r |: 0.260, P <.01), type of surgery (| r |: 0.127, P <.05), and type of anesthesia (| r |: 0.126, P <.05). In terms of forecasting performance, BPNN (average error: 2.81%) outperforms, yet is less interpretable than MRA (average error: 5.79%). Both MRA and BPNN are technically and economically feasible in generating medical costs of cataract. And some insights on using results of the forecasting model in controlling and reducing disease costs are obtained. pubtype: Academic Journal doctype: algorithm equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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