Hybridizing Bayesian Probabilistic Models and Crowd Wisdom Techniques for Effective Medical Forecasting : Evidence from China's Jiangsu Province

Authors(5) :-Henry Asante Antwi, Zhou Lulin, Mary Opokua Ansong, Samuel Owusu Mensah, Zinet Abdullai

The extant literature is replete with studies that depict the accuracy of predicting demand using an ensemble of statistical and non-statistical methodologies. Yet an emerging theme in contemporary research provides support for the integration of Prediction Markets within public and private hospitals to reduce costs and free up valuable resources, ultimately bettering quality of life and service. Our study compared the post sample prediction error of an enhanced prediction market tool and exponential smoothing to predict patient arrivals in selected departments in a hospital in China. The prediction market estimates provide a more accurate forecast on two-of-three occasions compared to exponential smoothing model in all the three departments under consideration. Despite the range of experience both in the field of work and the hospital itself, no correlation was found between experience in either and the accuracy of estimates within each of the three units. Similar to the experience, the age variables is also highly insignificant in correlation with estimate accuracy

Authors and Affiliations

Henry Asante Antwi
School of Management, Jiangsu University, 301 Xuefu Road, Zhenjiang, Jiangsu, P.R. China and Institute of Medical Insurance and Healthcare Management, Jiangsu University, Zhenjiang, Jiangsu, P.R. China
Zhou Lulin
School of Management, Jiangsu University, 301 Xuefu Road, Zhenjiang, Jiangsu, P.R. China and Institute of Medical Insurance and Healthcare Management, Jiangsu University, Zhenjiang, Jiangsu, P.R. China
Mary Opokua Ansong
School of Management, Jiangsu University, 301 Xuefu Road, Zhenjiang, Jiangsu, P.R. China and Department of Computer Science, School of Applied Science, Kumasi Polytechnic, P. O. Box 854, Kumasi, Ghana
Samuel Owusu Mensah
School of Management, Jiangsu University, 301 Xuefu Road, Zhenjiang, Jiangsu, P.R. China
Zinet Abdullai
School of Management, Jiangsu University, 301 Xuefu Road, Zhenjiang, Jiangsu, P.R. China

Royal Devon, Linear Regression Model, Exponential Smoothing Method, Climatical Conditions, OPD, IC, DC

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Publication Details

Published in : Volume 2 | Issue 1 | January-February 2017
Date of Publication : 2017-02-28
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 135-140
Manuscript Number : CSEIT172120
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Henry Asante Antwi, Zhou Lulin, Mary Opokua Ansong, Samuel Owusu Mensah, Zinet Abdullai, "Hybridizing Bayesian Probabilistic Models and Crowd Wisdom Techniques for Effective Medical Forecasting : Evidence from China's Jiangsu Province ", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 1, pp.135-140 , January-February.2017
URL : http://ijsrcseit.com/CSEIT172120

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