title: Examining variations in hospital productivity in the English NHS.
abstract: OBJECTIVE
  Numerous papers have measured hospital efficiency, mainly using a technique known as data envelopment analysis (DEA). A shortcoming of this technique is that the number of outputs for each hospital generally outstrips the number of hospitals. In this paper, we propose an alternative approach, involving the use of explicit weights to combine diverse outputs into a single index, thereby avoiding the need for DEA.
  
  
  METHODS
  Hospital productivity is measured as the ratio of outputs to inputs. Outputs capture quantity and quality of care for hospital patients; inputs include staff, equipment, and capital resources applied to patient care. Ordinary least squares regression is used to analyse why output and productivity varies between hospitals. We assess whether results are sensitive to consideration of quality.
  
  
  RESULTS
  Hospital productivity varies substantially across hospitals but is highly correlated year on year. Allowing for quality has little impact on relative productivity. We find that productivity is lower in hospitals with greater financial autonomy, and where a large proportion of income derives from education, research and development, and training activities. Hospitals treating greater proportions of children or elderly patients also tend to be less productive.
  
  
  CONCLUSIONS
  We have set out a means of assessing hospital productivity that captures their multiple outputs and inputs. We find substantial variation in productivity among English hospitals, suggesting scope for productivity improvement.
authors.affiliation: Centre for Health Economics, University of York, Alcuin A Block, York, YO10 5DD, UK.
authors.forename: Adriana
authors.initials: A
authors.lastname: Castelli
authors.forename: Andrew
authors.initials: A
authors.lastname: Street
authors.forename: Rossella
authors.initials: R
authors.lastname: Verzulli
authors.forename: Padraic
authors.initials: P
authors.lastname: Ward
mesh_terms: D000367:Age Factors; D017598:Efficiency, Organizational; D006739:Hospital Administration / Q000706:statistics & numerical data*; D006801:Humans; D008511:Medicine; D010361:Patients / Q000706:statistics & numerical data; D010557:Personnel Administration, Hospital / Q000706:statistics & numerical data; D011787:Quality of Health Care / Q000706:statistics & numerical data; D013222:State Medicine / Q000706:statistics & numerical data*