Abstract

With the development of the era, the word “haze” was born, and more and more people suffer from respiratory diseases, particularly congestive heart failure and coronary artery disease and lung cancer.In the European Union, PM2.5 cuts life expectancy by 8.6 months.Bases on the medical data relating to the hospital, in July 2018-August of respiratory medical consultations and PM2.5value transfer function model is set up, after using the model on September 1st, 2018-September 20th respiratory medical consultations to make predictions, and comparing with the real value, the results show that compared with the ARIMA model, transfer function model predicts more accurately. In other words, the relationship between daily respiratory department visits and PM2.5value is more similar to the transfer function model.Finally, the transfer function model is used to predict the daily number of patients in respiratory department from September 21st to September 30th, 2018,Because the management of medical treatment is one of the important indicators reflecting the level of hospital management, the prediction of daily medical treatment volume can provide a reliable basis for the allocation of out-patient medical staff, and it is of great significance for hospitals to rationally arrange human, financial, material and other resources to improve economic and social benefits.

Highlights

  • With the development of the era, the word “haze” was born, and more and more people suffer from respiratory diseases, congestive heart failure and coronary artery disease and lung cancer.In the European Union, PM2.5 cuts life expectancy by 8.6 months.Bases on the medical data relating to the hospital, in July 2018-August of respiratory medical consultations and PM2.5value transfer function model is set up, after using the model on September 1st, 2018-September 20th respiratory medical consultations to make predictions, and comparing with the real value, the results show that compared with the ARIMA model, transfer function model predicts more accurately

  • The relationship between daily respiratory department visits and PM2.5value is more similar to the transfer function model.the transfer function model is used to predict the daily number of patients in respiratory department from September 21st to September 30th, 2018,Because the management of medical treatment is one of the important indicators reflecting the level of hospital management, the prediction of daily medical treatment volume can provide a reliable basis for the allocation of out-patient medical staff, and it is of great significance for hospitals to rationally arrange human, financial, material and other resources to improve economic and social benefits

  • 本文采用医院的有关医疗数据,对2018年7月-8月的 呼吸科日就诊量与PM2.5值建立传递函数模型,之后利用 模型对2018年9月1日-9月20日呼吸科日就诊量进行预测, 并与真实值进行比较,结果显示,与ARIMA模型相比, 传递函数模型预测得更为准确,也就是说呼吸科日就诊量 与PM2.5的关系更趋近于传递函数模型。利用传递函数模 型预测出2018年9月21日- 9月30日呼吸科日就诊量,可以

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Summary

Introduction

With the development of the era, the word “haze” was born, and more and more people suffer from respiratory diseases, congestive heart failure and coronary artery disease and lung cancer.In the European Union, PM2.5 cuts life expectancy by 8.6 months.Bases on the medical data relating to the hospital, in July 2018-August of respiratory medical consultations and PM2.5value transfer function model is set up, after using the model on September 1st, 2018-September 20th respiratory medical consultations to make predictions, and comparing with the real value, the results show that compared with the ARIMA model, transfer function model predicts more accurately. Email address: To cite this article: Xiao Weiwei, Fan Meixia. Study on the Relationship Between PM2.5 and Daily Consultations Volume in Respiratory Department Based on Transfer Function Model.

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