title: 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.
abstract: To introduce multilevel repeated measures (RM) models and compare them with multilevel difference-in-differences (DID) models in assessing the linear relationship between the length of the policy intervention period and healthcare outcomes (dose-response effect) for data from a stepped-wedge design with a hierarchical structure.
  
  
  
  The implementation of national essential medicine policy (NEMP) in China was a stepped-wedge-like design of five time points with a hierarchical structure. Using one key healthcare outcome from the national NEMP surveillance data as an example, we illustrate how a series of multilevel DID models and one multilevel RM model can be fitted to answer some research questions on policy effects.
  
  
  
  Routinely and annually collected national data on China from 2008 to 2012.
  
  
  
  34 506 primary healthcare facilities in 2675 counties of 31 provinces.
  
  
  
  Agreement and differences in estimates of dose-response effect and variation in such effect between the two methods on the logarithm-transformed total number of outpatient visits per facility per year (LG-OPV).
  
  
  
  The estimated dose-response effect was approximately 0.015 according to four multilevel DID models and precisely 0.012 from one multilevel RM model. Both types of model estimated an increase in LG-OPV by 2.55 times from 2009 to 2012, but 2-4.3 times larger SEs of those estimates were found by the multilevel DID models. Similar estimates of mean effects of covariates and random effects of the average LG-OPV among all levels in the example dataset were obtained by both types of model. Significant variances in the dose-response among provinces, counties and facilities were estimated, and the 'lowest' or 'highest' units by their dose-response effects were pinpointed only by the multilevel RM model.
  
  
  
  For examining dose-response effect based on data from multiple time points with hierarchical structure and the stepped wedge-like designs, multilevel RM models are more efficient, convenient and informative than the multilevel DID models.
authors.affiliation: West China School of Public Health, Sichuan University, Chengdu, Sichuan, People's Republic of China.
authors.forename: Yan
authors.initials: Y
authors.lastname: Ren
authors.affiliation: West China School of Public Health, Sichuan University, Chengdu, Sichuan, People's Republic of China.|West China Research Center for Rural Health Development, Sichuan University, Chengdu, Sichuan, People's Republic of China.|School of Medicine, University of Nottingham, Nottingham, UK.|Swinburne University of Technology, Victoria, Australia.
authors.forename: Min
authors.initials: M
authors.lastname: Yang
authors.affiliation: West China Research Center for Rural Health Development, Sichuan University, Chengdu, Sichuan, People's Republic of China.
authors.forename: Qian
authors.initials: Q
authors.lastname: Li
authors.affiliation: West China School of Public Health, Sichuan University, Chengdu, Sichuan, People's Republic of China.|West China Research Center for Rural Health Development, Sichuan University, Chengdu, Sichuan, People's Republic of China.
authors.forename: Jay
authors.initials: J
authors.lastname: Pan
authors.affiliation: West China School of Public Health, Sichuan University, Chengdu, Sichuan, People's Republic of China.
authors.forename: Fei
authors.initials: F
authors.lastname: Chen
authors.affiliation: West China School of Public Health, Sichuan University, Chengdu, Sichuan, People's Republic of China.
authors.forename: Xiaosong
authors.initials: X
authors.lastname: Li
authors.affiliation: Center for Health Statistical Information, National Health and Family Planning Commission of the People's Republic of China, Beijing, People's Republic of China.
authors.forename: Qun
authors.initials: Q
authors.lastname: Meng
mesh_terms: D002681:China; D003625:Data Collection / Q000379:methods*; D018954:Drugs, Essential; D006291:Health Policy; D006801:Humans; D015233:Models, Statistical; D055361:Multilevel Analysis; D017063:Outcome Assessment, Health Care; D010045:Outpatients; D012107:Research Design
chemical_list: D018954:Drugs, Essential
keywords: China; Dose-response effect; Multilevel Difference-in-Differences model; Multilevel repeated measures model; National essential medicine policy