Application value of SARIMA model in forecasting and analyzing inpatient cases of pediatric limb fractures_Chinese Journal of Evidence-Based Medicine

Authors：

WANG Lufei ¹ , NIE Yijing ¹ ,  YANG Xiaodong ²

1. West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, P.R.China;
2. Department of Pediatric Trauma, West China Hospital, Sichuan University, Chengdu 610041, P.R.China;

Corresponding author：

YANG Xiaodong, Email: yxd2260483@126.com

Keywords：

Limb fracture; Time series analysis; Seasonal auto-regressive moving average model; Prediction

DOI：

10.7507/1672-2531.201906049

Video：

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Abstract Full text Figures/Tables Video References Cited by

Objective To establish a forecasting model for inpatient cases of pediatric limb fractures and predict the trend of its variation.Methods According to inpatient cases of pediatric limb fractures from January 2013 to December 2018, this paper analyzed its characteristics and established the seasonal auto-regressive integrated moving average (SARIMA) model to make a short-term quantitative forecast.Results A total of 4 451 patients, involving 2 861 males and 1 590 females were included. The ratio of males to females was 1.8 to 1, and the average age was 5.655. There was a significant difference in age distribution between males and females (χ²=44.363, P<0.001). The inpatient cases of pediatric limb fractures were recorded monthly, with predominant peak annually, from April to June and September to October, respectively. Using the data of the training set from January 2013 to May 2018, a SARIMA model of SARIMA (0,1,1)(0,1,1)₁₂ model (white noise test, P>0.05) was identified to make short-term forecast for the prediction set from June 2018 to November 2018, with RMSE=8.110, MAPE=9.386, and the relative error between the predicted value and the actual value ranged from 1.61% to 8.06%.Conclusions Compared with the actual cases, the SARIMA model fits well with good short-term prediction accuracy, and it can help provide reliable data support for a scientific forecast for the inpatient cases of pediatric limb fractures.

Citation： WANG Lufei, NIE Yijing, YANG Xiaodong. Application value of SARIMA model in forecasting and analyzing inpatient cases of pediatric limb fractures. Chinese Journal of Evidence-Based Medicine, 2020, 20(6): 651-655. doi: 10.7507/1672-2531.201906049 Copy

1.	Hedström EM, Svensson O, Bergström U, et al. Epidemiology of fractures in children and adolescents. Acta Orthop, 2010, 81(1): 148-153.
2.	Kang HM, Kim MG, Hong SM, et al. Comparison of temporal bone fractures in children and adults. Acta Oto-Laryngologica, 2013, 133(5): 469-474.
3.	王海波, 李明. 小儿骨折的流行病学特点及相关影响因素研究进展. 现代医药卫生, 2016, 32(15): 2333-2336.
4.	Naranje SM, Erali RA, Warner WC. Epidemiology of pediatric fractures presenting to emergency departments in the United States. J Pediatr Orthop, 2016, 36(4): e45-e48.
5.	Feng H, Duan G, Zhang R, et al. Time series analysis of hand-foot-mouth disease hospitalization in Zhengzhou: establishment of forecasting models using climate variables as predictors. PLoS One, 2014, 9(1): e87916.
6.	李小升, 马春柳, 雷海科, 等. SARIMA 模型在医院门诊量预测中的应用. 中国病案, 2013, 14(3): 37-40.
7.	Leslie WD, Morin SN, Lix LM, et al. Comparison of treatment strategies and thresholds for optimizing fracture prevention in Canada: a simulation analysis. Arch Osteoporos, 2019, 15(1): 4.
8.	Merlijn T, Swart KMA, van der Horst HE, et al. Fracture prevention by screening for high fracture risk: a systematic review and meta-analysis. Osteoporos Int, 2019, Epub ahead of print.
9.	Hadley-Miller N, Carry PM, Brazell CJ, et al. Trends in Trampoline Fractures: 2008-2017. Pediatrics, 2020, 145(1): e20190889.
10.	Clark EM. The epidemiology of fractures in otherwise healthy children. Curr Osteoporos Rep, 2014, 12(3): 272-278.
11.	刘晓光, 郭源, 吕艳伟. 北京地区 10 977 例儿童骨折分析. 中国矫形外科杂志, 2014, 22(24): 2233-2237.
12.	李秋燕, 王津雨. 应用 SARIMA 模型预测医院出院人次. 中国病案, 2016, 17(7): 32-35.
13.	Wren TA, Shepherd JA, Kalkwarf HJ, et al. Racial disparity in fracture risk between white and nonwhite children in the United States. J Pediatr, 2012, 161(6): 1035-1040.
14.	Brudvik C, Hove LM. Childhood fractures in Bergen, Norway: identifying high-risk groups and activities. J Pediatr Orthop, 2003, 23(5): 629-634.
15.	Rennie L, Court-Brown CM, Mok JY, et al. The epidemiology of fractures in children. Injury, 2007, 38(8): 913-922.
16.	Masterson E, Borton D, O'Brien T. Victims of our climate. Injury, 1993, 24(4): 247-248.
17.	廉恒丽, 俞剑琴, 傅映晖. ARIMA 与 SARIMA 模型在医院门诊人次与出院人次预测中的应用. 中国医院统计, 2017, 24(2): 81-84.

1. Hedström EM, Svensson O, Bergström U, et al. Epidemiology of fractures in children and adolescents. Acta Orthop, 2010, 81(1): 148-153.
2. Kang HM, Kim MG, Hong SM, et al. Comparison of temporal bone fractures in children and adults. Acta Oto-Laryngologica, 2013, 133(5): 469-474.
3. 王海波, 李明. 小儿骨折的流行病学特点及相关影响因素研究进展. 现代医药卫生, 2016, 32(15): 2333-2336.
4. Naranje SM, Erali RA, Warner WC. Epidemiology of pediatric fractures presenting to emergency departments in the United States. J Pediatr Orthop, 2016, 36(4): e45-e48.
5. Feng H, Duan G, Zhang R, et al. Time series analysis of hand-foot-mouth disease hospitalization in Zhengzhou: establishment of forecasting models using climate variables as predictors. PLoS One, 2014, 9(1): e87916.
6. 李小升, 马春柳, 雷海科, 等. SARIMA 模型在医院门诊量预测中的应用. 中国病案, 2013, 14(3): 37-40.
7. Leslie WD, Morin SN, Lix LM, et al. Comparison of treatment strategies and thresholds for optimizing fracture prevention in Canada: a simulation analysis. Arch Osteoporos, 2019, 15(1): 4.
8. Merlijn T, Swart KMA, van der Horst HE, et al. Fracture prevention by screening for high fracture risk: a systematic review and meta-analysis. Osteoporos Int, 2019, Epub ahead of print.
9. Hadley-Miller N, Carry PM, Brazell CJ, et al. Trends in Trampoline Fractures: 2008-2017. Pediatrics, 2020, 145(1): e20190889.
10. Clark EM. The epidemiology of fractures in otherwise healthy children. Curr Osteoporos Rep, 2014, 12(3): 272-278.
11. 刘晓光, 郭源, 吕艳伟. 北京地区 10 977 例儿童骨折分析. 中国矫形外科杂志, 2014, 22(24): 2233-2237.
12. 李秋燕, 王津雨. 应用 SARIMA 模型预测医院出院人次. 中国病案, 2016, 17(7): 32-35.
13. Wren TA, Shepherd JA, Kalkwarf HJ, et al. Racial disparity in fracture risk between white and nonwhite children in the United States. J Pediatr, 2012, 161(6): 1035-1040.
14. Brudvik C, Hove LM. Childhood fractures in Bergen, Norway: identifying high-risk groups and activities. J Pediatr Orthop, 2003, 23(5): 629-634.
15. Rennie L, Court-Brown CM, Mok JY, et al. The epidemiology of fractures in children. Injury, 2007, 38(8): 913-922.
16. Masterson E, Borton D, O'Brien T. Victims of our climate. Injury, 1993, 24(4): 247-248.
17. 廉恒丽, 俞剑琴, 傅映晖. ARIMA 与 SARIMA 模型在医院门诊人次与出院人次预测中的应用. 中国医院统计, 2017, 24(2): 81-84.

Chinese Journal of Evidence-Based Medicine

Application value of SARIMA model in forecasting and analyzing inpatient cases of pediatric limb fractures

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