title: Operational and contextual drivers of hospital costs.
abstract: OBJECTIVE
  The purpose of this paper is to examine empirically how operational performance and contextual factors contribute to differences in overall patient care costs across different hospitals.
  
  
  METHODS
  Administrative data are employed from a sample of hospitals in New York State to construct measures of contextual factors, operational performance, and cost per patient. Operational performance and cost variables are adjusted to account for case mix differences across hospitals. Hierarchical regression is used to analyze the effects of contextual and operational variables on cost performance.
  
  
  RESULTS
  Increased length of stay, increased patient volume, and educational mission were associated with higher cost per patient. Mortality performance was associated with lower cost per patient. However, it was not found that location, size, or ownership status had a significant relationship with cost performance.
  
  
  CONCLUSIONS
  This paper identifies several significant relationships between contextual and operational variables and hospital costs. From a managerial perspective, these findings highlight the fact that some drivers of cost in hospitals are under the control of managers. One of the primary cost drivers in the study is length of stay, which implies that there is significant room for improvement in healthcare performance through a focus on operational excellence.
  
  
  CONCLUSIONS
  For researchers, the present study highlights the relative importance of operational versus contextual factors, with respect to cost performance in hospitals. The results of this study also provide direction for additional research into the role operational performance might play in determining the overall organizational performance in a hospital.
authors.affiliation: College of Business, University of Colorado at Colorado Springs, Colorado Springs, Colorado, USA. gstock@uccs.edu
authors.forename: Gregory N
authors.initials: GN
authors.lastname: Stock
authors.forename: Christopher
authors.initials: C
authors.lastname: McDermott
mesh_terms: D003365:Costs and Cost Analysis; D003953:Diagnosis-Related Groups / Q000191:economics; D006739:Hospital Administration / Q000191:economics*; D006742:Hospital Bed Capacity / Q000191:economics; D017721:Hospital Costs / Q000458:organization & administration* / Q000706:statistics & numerical data; D017052:Hospital Mortality; D006753:Hospital Records / Q000706:statistics & numerical data; D006761:Hospitals / Q000145:classification; D016304:Hospitals, Private / Q000191:economics; D006784:Hospitals, Teaching / Q000191:economics; D006786:Hospitals, Urban / Q000191:economics; D006801:Humans; D007902:Length of Stay / Q000191:economics; D009518:New York