基于时间序列模型的某三甲医院心力衰竭入院人数及治疗趋势预测

doi:10.3969/j.issn.1006-5253.2022.03.001

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Abstract Objective To establish a prediction model for the number of hospitalized patients with heart failure and average hopitalization days by using Winters exponential smoothing method, and to explore its application value and provide scientific basis for hospital management.Methods The number of hospitalized patients with heart failure and their average hopitalization days were collected from the electronic medical record system of a tertiary hospital, and the Winston exponential smoothing model was constructed by means of model diagnosis and parameter optimization to predict and analyze the trend of admission and treatment of heart failure in this hospital. The predicted results were evaluated.Results The data of patients with heart failure from January 2007 to December 2016 in this hospital were set as training samples for simulation construction and parameter optimization, and the data from January to December 2017 were used as test samples for prediction and verification. The results showed that the mean absolute percentage error (MAPE) of the prediction model was 7.055%, the mean stationary R²was 0.738, and the MAPE of the prediction model was 4.323%, the mean stationary R²was 0.698. The actual number of inpatients and the average length of stay were within 95% confidence interval of the predicted value, indicating that the Winters exponential smoothing model could be used to predict the number of inpatients and average length of stay of heart failure.Conclusion The Winters exponential smoothing model can predict the seasonal trend of the number and average length of stay of patients with heart failure, and provide a scientific basis for the rational allocation of medical resources of hospitals.

Key words： Winters exponential smoothing method heart failure seasonal variation average hospitalization days number of inpatients

Received: 08 March 2022

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	Liu Min
	Guo Xianxi
	Wu Yue

Cite this article:

Liu Min,Guo Xianxi,Wu Yue. Prediction of hospitalization and treatment trend of heart failure in a tertiary hospital based on time series model[J]. journal1, 2022, 29(3): 161-168.

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http://manu58.magtech.com.cn/Jwk_zgyytj/EN/10.3969/j.issn.1006-5253.2022.03.001 OR http://manu58.magtech.com.cn/Jwk_zgyytj/EN/Y2022/V29/I3/161

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