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

Authors

  • 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

Keywords:

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

Abstract

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

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2017-02-28

Issue

Volume 2, Issue 1, January-February-2017

Section

Research Articles

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How to Cite

[1]
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 , IInternational 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.