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.
Published in | Science Discovery (Volume 8, Issue 6) |
DOI | 10.11648/j.sd.20200806.12 |
Page(s) | 128-133 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2020. Published by Science Publishing Group |
Daily Consultation Volume, PM2.5, Transfer Function Model, ARIMA Model
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APA Style
Xiao Weiwei, Fan Meixia. (2020). Study on the Relationship Between PM2.5 and Daily Consultations Volume in Respiratory Department Based on Transfer Function Model. Science Discovery, 8(6), 128-133. https://doi.org/10.11648/j.sd.20200806.12
ACS Style
Xiao Weiwei; Fan Meixia. Study on the Relationship Between PM2.5 and Daily Consultations Volume in Respiratory Department Based on Transfer Function Model. Sci. Discov. 2020, 8(6), 128-133. doi: 10.11648/j.sd.20200806.12
AMA Style
Xiao Weiwei, Fan Meixia. Study on the Relationship Between PM2.5 and Daily Consultations Volume in Respiratory Department Based on Transfer Function Model. Sci Discov. 2020;8(6):128-133. doi: 10.11648/j.sd.20200806.12
@article{10.11648/j.sd.20200806.12, author = {Xiao Weiwei and Fan Meixia}, title = {Study on the Relationship Between PM2.5 and Daily Consultations Volume in Respiratory Department Based on Transfer Function Model}, journal = {Science Discovery}, volume = {8}, number = {6}, pages = {128-133}, doi = {10.11648/j.sd.20200806.12}, url = {https://doi.org/10.11648/j.sd.20200806.12}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sd.20200806.12}, 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.}, year = {2020} }
TY - JOUR T1 - Study on the Relationship Between PM2.5 and Daily Consultations Volume in Respiratory Department Based on Transfer Function Model AU - Xiao Weiwei AU - Fan Meixia Y1 - 2020/11/04 PY - 2020 N1 - https://doi.org/10.11648/j.sd.20200806.12 DO - 10.11648/j.sd.20200806.12 T2 - Science Discovery JF - Science Discovery JO - Science Discovery SP - 128 EP - 133 PB - Science Publishing Group SN - 2331-0650 UR - https://doi.org/10.11648/j.sd.20200806.12 AB - 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. VL - 8 IS - 6 ER -