Multilevel model and its application in evaluation of medicine policy intervention_Chinese Journal of Evidence-Based Medicine

Authors：

REN Yan ^1,2,3 , HUANG Yunxiang ^1,2,3 , ZHANG Yuanjin ^1,2,3 , YAO Minghong ^1,2,3 , JIA Yulong ^1,2,3 , YANG Min ⁴ ,  SUN Xin ^1,2,3

1. Chinese Evidence-based Medicine Center, West China Hospital, Sichuan University, Chengdu 610041, P.R.China;
2. NMPA Key Laboratory for Real World Data Research and Evaluation in Hainan, Chengdu 610041, P.R.China;
3. Sichuan Real World Data Research and Innovation Center, Chengdu 610041, P.R.China;
4. West China School of Public Health, Sichuan University, Chengdu 610041, P.R.China;

Corresponding author：

SUN Xin, Email: sunx79@hotmail.com

Keywords：

Multilevel model; Medicine policy; Effect evaluation; Regional healthcare big data

DOI：

10.7507/1672-2531.202108101

Video：

Export PDF Favorites Scan Get Citation

Abstract Full text Figures/Tables Video References Cited by

With the establishment and development of regional healthcare big data platforms, regional healthcare big data is playing an increasingly important role in health policy program evaluations. Regional healthcare big data is usually structured hierarchically. Traditional statistical models have limitations in analyzing hierarchical data, and multilevel models are powerful statistical analysis tools for processing hierarchical data. This method has frequently been used by healthcare researchers overseas, however, it lacks application in China. This paper aimed to introduce the multilevel model and several common application scenarios in medicine policy evaluations. We expected to provide a methodological framework for medicine policy evaluation using regional healthcare big data or hierarchical data.

Citation： REN Yan, HUANG Yunxiang, ZHANG Yuanjin, YAO Minghong, JIA Yulong, YANG Min, SUN Xin. Multilevel model and its application in evaluation of medicine policy intervention. Chinese Journal of Evidence-Based Medicine, 2021, 21(12): 1474-1479. doi: 10.7507/1672-2531.202108101 Copy

1.	Goldstain H. Multilevel statistical models (4th ed). New York: John Wiley & Sons, 2011.
2.	石磊. 多水平模型及其在经济分析中的应用. 数学建模及其应用, 2016, 5(1): 3-8.
3.	Ren Y, Yang M, Li Q, et al. Assessing dose-response effects of national essential medicine policy in China: comparison of two methods for handling data with a stepped wedge-like design and hierarchical structure. BMJ Open, 2017, 7(2): e013247.
4.	杨珉, 李晓松. 医学和公共卫生研究常用多水平统计模型. 北京: 北京大学医学出版社, 2007.
5.	Hua M, Lu Y, Ma X, et al. Association between the implementation of hospital-based palliative care and use of intensive care during terminal hospitalizations. JAMA Netw Open, 2020, 3(1): e1918675.
6.	Zombré D, De Allegri M, Ridde V. Immediate and sustained effects of user fee exemption on healthcare utilization among children under five in Burkina Faso: a controlled interrupted time-series analysis. Soc Sci Med, 2017, 179: 27-35.
7.	Ulfsdotter M, Enebrink P, Lindberg L. Effectiveness of a universal health-promoting parenting program: a randomized waitlist-controlled trial of all children in focus. BMC Public Health, 2014, 14: 1083.
8.	Huang YY, Cheng SH. A community pharmacist home visit project for high utilizers under a universal health system: A preliminary assessment. Health Policy, 2019, 123(4): 373-378.
9.	Li Q, Chen F, Yang M, et al. The effect of China's national essential medicine policy on health expenses: evidence from a national study. Inquiry, 2018, 55: 46958018787057.
10.	Chen F, Yang M, Li Q, et al. Does providing more services increase the primary hospitals' revenue. An assessment of national essential medicine policy based on 2 675 counties in China. PLoS One, 2018, 13(1): e0190855.

1. Goldstain H. Multilevel statistical models (4th ed). New York: John Wiley & Sons, 2011.
2. 石磊. 多水平模型及其在经济分析中的应用. 数学建模及其应用, 2016, 5(1): 3-8.
3. Ren Y, Yang M, Li Q, et al. Assessing dose-response effects of national essential medicine policy in China: comparison of two methods for handling data with a stepped wedge-like design and hierarchical structure. BMJ Open, 2017, 7(2): e013247.
4. 杨珉, 李晓松. 医学和公共卫生研究常用多水平统计模型. 北京: 北京大学医学出版社, 2007.
5. Hua M, Lu Y, Ma X, et al. Association between the implementation of hospital-based palliative care and use of intensive care during terminal hospitalizations. JAMA Netw Open, 2020, 3(1): e1918675.
6. Zombré D, De Allegri M, Ridde V. Immediate and sustained effects of user fee exemption on healthcare utilization among children under five in Burkina Faso: a controlled interrupted time-series analysis. Soc Sci Med, 2017, 179: 27-35.
7. Ulfsdotter M, Enebrink P, Lindberg L. Effectiveness of a universal health-promoting parenting program: a randomized waitlist-controlled trial of all children in focus. BMC Public Health, 2014, 14: 1083.
8. Huang YY, Cheng SH. A community pharmacist home visit project for high utilizers under a universal health system: A preliminary assessment. Health Policy, 2019, 123(4): 373-378.
9. Li Q, Chen F, Yang M, et al. The effect of China's national essential medicine policy on health expenses: evidence from a national study. Inquiry, 2018, 55: 46958018787057.
10. Chen F, Yang M, Li Q, et al. Does providing more services increase the primary hospitals' revenue. An assessment of national essential medicine policy based on 2 675 counties in China. PLoS One, 2018, 13(1): e0190855.

Chinese Journal of Evidence-Based Medicine

Multilevel model and its application in evaluation of medicine policy intervention

Abstract Full text Figures/Tables Video References Cited by

Previous Article

Next Article

Format

Content