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Predicting the Market Demand for Prescription Drugs in Hospitals–Taking an Antihypertensive Drug as an Example

Chen Dongjie, Wang Shuling *   

  1. School of Business Administration, Shenyang Pharmaceutical University, Shenyang 110016, China
  • 出版日期:2017-12-20 发布日期:2017-12-20

Predicting the Market Demand for Prescription Drugs in Hospitals–Taking an Antihypertensive Drug as an Example

Chen Dongjie, Wang Shuling *   

  1. School of Business Administration, Shenyang Pharmaceutical University, Shenyang 110016, China
  • Online:2017-12-20 Published:2017-12-20
  • Contact: Wang Shuling, associate professor. Major research area: retail pharmacy management, human resource management, marketing etc. Tel.: 13998302138, E-mail: 405861417@ qq.com.

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摘要： Objective To build a forecasting model based on the historical prescription drug sales data to predict the market demand for prescription drugs in hospitals so as to provide reference for analyzing the demand of the hospital retail market. Methods Qualitative and quantitative methods were adopted in combination with Excel and Matlab software use. Comparative analysis, time series analysis and grey model method were also used. Results and Conclusion Grey prediction model were used to obtain posterior variance testing c=0.051, p=1, based on the data of antihypertensive drugs in a first-class hospital, which meant the prediction accuracy was good. This model was used to forecast the market demands in May, June and July and they were 1003, 1207 and 1305 respectively, which were relatively accurate. Therefore, the construction of a grey model provide a reasonable basis for the short-term drug purchase in hospitals.

关键词: hospital retail, prescription drug demand forecasting, grey forecasting model

Abstract: Objective To build a forecasting model based on the historical prescription drug sales data to predict the market demand for prescription drugs in hospitals so as to provide reference for analyzing the demand of the hospital retail market. Methods Qualitative and quantitative methods were adopted in combination with Excel and Matlab software use. Comparative analysis, time series analysis and grey model method were also used. Results and Conclusion Grey prediction model were used to obtain posterior variance testing c=0.051, p=1, based on the data of antihypertensive drugs in a first-class hospital, which meant the prediction accuracy was good. This model was used to forecast the market demands in May, June and July and they were 1003, 1207 and 1305 respectively, which were relatively accurate. Therefore, the construction of a grey model provide a reasonable basis for the short-term drug purchase in hospitals.

Key words: hospital retail, prescription drug demand forecasting, grey forecasting model

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