Measuring the Quality of Healthcare

Abstract

Recently, enormous efforts to measure the quality of healthcare have been made to attain information on ways to improve the quality of healthcare. However, this area of research is still at an early stage of development and more research is required. This article outlines a framework by which the quality of healthcare can be analyzed on the basis of the three quality dimensions introduced by Donabedian. The article then goes on to test the validity of this (theoretical) framework within an empirical analysis. Because of increasing financial shortages within health systems, this article focuses on the treatment of myocardial infarction, which is one of the costliest and most prevalent diseases. This approach establishes a link between medical and economic problems. The variables for structure quality (i.e. number of cardiologists, number of catheterization facilities) were sourced and evaluated from the ‘Herzberichte der Jahrgange’ (‘heart reports’) compiled by Bruckenberger for the period 1994–2004 for the 16 German federal states. Data from the Federation of Quality Assurance (BQS) were used for the evaluation of process quality (i.e. adequacy of indication for coronary angiography). Finally, administrative data from the German Federal Statistical office for 1994–2004 were used to determine the variables of outcome quality (i.e. standardized mortality rate due to myocardial infarction, potential years of life lost <70 years due to myocardial infarction). Three hypotheses were tested using panel data: (i) a better structure and/or process quality increases the probability of getting a better outcome quality for the clinical picture under observation; (ii) by employing additional input factors (such as additional catheterization facilities), the probability of getting a good outcome quality is increased; and (iii) in addition to structure quality and process quality, factors lying outside of the sphere of influence of the health system have an additional influence on outcome quality (marginal gains would decrease in this case). Three models were used to test these hypotheses using fixed effects estimation. The empirical analysis produced three results. First, the analysis confirms the predicted causality between the different dimensions of quality of care for the German federal states. Notably, the number of catheterization facilities has a highly significant positive influence on the outcome quality. Second, support is found for decreasing marginal gain of inputs. Third, a good structure and a good process quality alone cannot guarantee good outcome quality. However, the analysis also showed that, in addition to healthcare provided, there are other determinants that also affect the outcome quality of healthcare. Further empirical investigation regarding the influence of these factors on the outcome dimension could elaborate on our findings and deliver additional insights.