title: Discovering the impact of preceding units' characteristics on the wait time of cardiac surgery unit from statistic data.
abstract: BACKGROUND
  Prior research shows that clinical demand and supplier capacity significantly affect the throughput and the wait time within an isolated unit. However, it is doubtful whether characteristics (i.e., demand, capacity, throughput, and wait time) of one unit would affect the wait time of subsequent units on the patient flow process. Focusing on cardiac care, this paper aims to examine the impact of characteristics of the catheterization unit (CU) on the wait time of cardiac surgery unit (SU).
  
  
  METHODS
  This study integrates published data from several sources on characteristics of the CU and SU units in 11 hospitals in Ontario, Canada between 2005 and 2008. It proposes a two-layer wait time model (with each layer representing one unit) to examine the impact of CU's characteristics on the wait time of SU and test the hypotheses using the Partial Least Squares-based Structural Equation Modeling analysis tool.
  
  
  RESULTS
  Results show that: (i) wait time of CU has a direct positive impact on wait time of SU (β = 0.330, p < 0.01); (ii) capacity of CU has a direct positive impact on demand of SU (β = 0.644, p < 0.01); (iii) within each unit, there exist significant relationships among different characteristics (except for the effect of throughput on wait time in SU).
  
  
  CONCLUSIONS
  Characteristics of CU have direct and indirect impacts on wait time of SU. Specifically, demand and wait time of preceding unit are good predictors for wait time of subsequent units. This suggests that considering such cross-unit effects is necessary when alleviating wait time in a health care system. Further, different patient risk profiles may affect wait time in different ways (e.g., positive or negative effects) within SU. This implies that the wait time management should carefully consider the relationship between priority triage and risk stratification, especially for cardiac surgery.
authors.affiliation: Computer Science Department, Hong Kong Baptist University, Hong Kong, Special Administrative Region, People's Republic of China. jiming@comp.hkbu.edu.hk
authors.forename: Jiming
authors.initials: J
authors.lastname: Liu
authors.forename: Li
authors.initials: L
authors.lastname: Tao
authors.forename: Bo
authors.initials: B
authors.lastname: Xiao
mesh_terms: D002170:Canada / Q000453:epidemiology; D006328:Cardiac Catheterization / Q000706:statistics & numerical data*; D003627:Data Interpretation, Statistical; D006295:Health Resources / Q000706:statistics & numerical data; D006761:Hospitals / Q000706:statistics & numerical data; D006801:Humans; D016018:Least-Squares Analysis; D015233:Models, Statistical; D013903:Thoracic Surgery / Q000706:statistics & numerical data*; D013997:Time Factors