Predictive analysis of internet-based oncology outpatient visits trend based on ARIMA and GM(1,1)models
Objective To investigate the changing trend of the current situation of Internet-based oncology outpatient treatment and provide support for the development and management of Internet hospitals.Methods The ARIMA and GM(1,1)models were constructed based on the Internet-based outpatient data of a cancer hospital from January 2021 to June 2023,and the fitting effect was evaluated by mean absolute error(MAE)and root mean square error(RMSE).Based on the model,the pro-portion of Internet-based outpatient visits and the offline outpatient visits were predicted from July to December 2023.Results ARIMA(1,1,2)and GM(1,1)models were used to predict the proportion of Internet-based outpatient visits.The average abso-lute errors were 2.06%and 2.41%,and the root-mean-square errors were 3.01%and 3.17%,respectively.The ARIMA(0,1,1)and GM(1,1)models were used to predict the proportion of Internet-based outpatient visits to the offline outpatient visits,with the rate of the average absolute errors of 0.58%and 1.08%,respectively,and the rate of the root mean square errors 0.75%and 1.31%,respectively.The figures indicated that the ARIMA model had a better prediction effect.The forecast results showed that the predicted value of Internet outpatient service in December 2023 was 90.35%,and the predicted value of Internet-based outpatient service accounted for 16.46%of the offline outpatient service.Conclusion In 2021-2023,the proportion of Inter-net-based outpatient visits in the cancer hospital showed a steady trend,and the proportion of Internet outpatient visits in the off-line outpatient visits showed a rising trend.Therefore,hospitals need to establish a continuous monitoring mechanism,constantly adjust management strategies and measures to meet the needs of patients and continue to promote the high-quality development of Internet-based medical services.
ARIMAGM(1,1)InternetCurrent situation of medical treatmentPredictive study
万方数据
维普
