Measuring hospital efficiency in Austria--a DEA approach.
We investigate the evolution of efficiency and productivity in the hospital sector of an Austrian province for the time period 1994-1996. We use panel data to design non-parametric frontier models (Data Envelopment Analysis) and compare efficiency scores and time patterns of efficiency across medical fields. As health outcomes hardly can be measured in a direct way we make use of two different approaches for output measurement: In a first approach, we employ the number of case mix-adjusted discharges and of inpatient days, in a second we use credit points, which are calculated in course of the newly introduced diagnosis related group-type financing system. We calculate and compare individual efficiency scores for hospital wards as decision making units (DMU) in specified medical fields. To our knowledge the calculation of ward-specific efficiency scores has not up till now been the unit of non-parametric efficiency analysis. Our two models find different results: Model 1 with conservative output measurement calculates an average efficiency level of 96%, while model 2 with credit points for output measurement puts average efficiency at 70%. Whereas average efficiency in model 1 hardly changes and in model 2 increases modestly in the period 1994-1996, a closer look at single hospitals displays a variety of different efficiency developments over time.
Hofmarcher
Maria M
MM
Institute for Advanced Studies, Vienna, Austria.
Paterson
Iain
I
Riedel
Monika
M
D001317:Austria; D003659:Decision Making, Organizational; D017598:Efficiency, Organizational / Q000706:statistics & numerical data*; D006302:Health Services Research / Q000379:methods; D016304:Hospitals, Private / Q000458:organization & administration* / Q000706:statistics & numerical data; D006779:Hospitals, Public / Q000458:organization & administration* / Q000706:statistics & numerical data; D007902:Length of Stay; D015233:Models, Statistical; D010044:Outpatient Clinics, Hospital / Q000458:organization & administration / Q000706:statistics & numerical data; D018709:Statistics, Nonparametric