Measuring Efficiency in Health Care: Analytic Techniques and Health Policy
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Measuring Efficiency in Health Care: Analytic Techniques and Health Policy
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Despite such expectations, similar results are mentioned by numerous other studies [ 24 - 29 ]. In our case, the difference in our results is a direct consequence of the fact that the stochastic frontier function, which is defined inside of the SFA method, lies above the data envelopment of data, in other words above the frontier function that is determined by the DEA method. It is therefore obvious that the stochastic frontier function, which is defined inside the SFA method, does not match our data the way a frontier function defined by the DEA method usually does.
A similar conclusion is mentioned in several other studies, not only in the field of healthcare economics, but also in the field of agriculture efficiency evaluation [ 23 , 30 , 31 ]. Within the SFA method, we should choose the function form of the frontier production unction and frontier cost function; this supposition is not necessary with the DEA method, as the method determined the two just stated functions by itself.
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Our results of the measures of efficiency estimated by the DEA method show several general hospitals are located exactly on the frontier function or at least in its immediate proximity. According to this, two general hospitals were habitually estimated as efficient during the observation period. Our results are therefore not in accordance with the measures of efficiency calculated based on the SFA method. The SFA method does not recognize any general hospital under observation as efficient; in other words, no general hospital can claim the value of 1, indicating no general hospital is located directly on the stochastic frontier function.
This situation is a direct consequence of the fact each method defines the frontier function differently. The DEA method uses the actual observation for determining the data envelopment of data, meaning at least one general hospital will always be located directly on the frontier function. The SFA method uses observation only as a supporting factor for determining the stochastic frontier function.
This is confirmed by most results supplied by efficiency analysis studies that analyze efficiency of providers with the SFA method and DEA method [ 29 , 32 , 33 ]. Between the results gained by the SFA method and the ones gained by the DEA method, there exists another very important difference. Similar observations are mentioned by Theodorifdis and Psychoudakis [ 34 ] and by Theodoridis and Anwar [ 23 ]. The SFA method can estimate the error illustrating methodological errors, among which are the wrong choice of function form, an impact of a variable we unintentionally omitted within the chosen model, data errors, environmental factors and so on [ 7 ].
In accordance with this statement, the results gained by the DEA method have greater variability than the ones supplied by the SFA method. As mentioned before, inefficiency is excluded from the measures of efficiency inside the SFA method, for it is labelled a consequence of a random error white noise. Parametric methods certainly have several advantages if we compare them to nonparametric methods.
If there is a prior supposition we are dealing with a sample of data that suits the criteria of the intervallic rational scale, the parametric methods render it possible for us to have a better insight into differences amongst individual hospitals. A considerable difference in the measures of efficiency between Celje General Hospital and Slovenj Gradec General Hospital inside the SFA method is very likely a consequence of the existing measure of economic efficiency, which is demonstrated by the optimal usage of inputs, depending on the chosen output.
In case the acquired sample of data are precisely defined and measured with consistency, the SFA method will deliver the necessary information; it not only presents us with the conclusion on which hospital is the most efficient, it also tells us how inefficient other hospitals are by comparison.
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The DEA method will deliver a similar conclusion, but it is better to rely on ranks and alphabetical order rather than on the differences in measures of efficiency that usually does not exist, because the DEA method can create a huge difference due to the nonparametric approach.
Numerous authors have revealed that the DEA method delivers more reliable results in case the number of units in a survey is relatively small; parametric tests become reliable only in case the number of observations is relatively extensive [ 10 , 26 - 28 ]. In case both methods deliver similar results, efficient secondary healthcare providers are relatively easy to locate. A problem arises when the two methods reach different conclusions; one method deliver proof on efficiency of certain hospitals, while the other method provides proof on efficiency of different hospitals.
In cases such as this one, a decision on the actual quality of data used for the analysis in question must be reached. The more we believe the data to be of high quality, the easier it is to conclude the analysis based on the SFA method.
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Several other authors agree, for they state researchers should be careful during interpretation of results they present to the designers of healthcare policy [ 25 , 36 , 37 ]. Most studies of efficiency in the field of health are state neither of the two methods can be labelled as the prevailing method of the healthcare providers' efficiency evaluation, and that it is only reasonable to use as many methods and approaches as possible [ 38 - 41 ].
In the field of healthcare economics, we can also find several studies that indicate the SFA method and DEA method are, along with several other approaches, an acceptable alternative for the analysis of influence of environmental variables and dynamic effects on efficiency of hospitals; the usage of both methods enables us to gain similar, but more consistent results of healthcare providers' efficiency analysis [ 29 , 32 , 42 , 43 ].
Our results on measures of efficiency of Slovene general hospitals supplied by our two chosen methods SFA and DEA are a useful tool that can aid managers and payers of healthcare services to better understand economic efficiency and its connection to healthcare providers. Accordingly, the decision makers in healthcare can decide with less difficulty on the continuing business operations of general hospitals, supported by the provided examples of best practises that were declared as the most efficient hospitals by our analysis.
The analysis of measures of efficiency of Slovene general hospitals is, however, especially useful for designers of healthcare policy. Extensive knowledge of measures of efficiency of general hospitals and their variations through time should considered a basis for ensuring they are always resources for the continuing operating of general hospitals, and a basis for the formation of secondary healthcare frontispiece of everything this sector can offer.
Conflict of interest: Authors state no conflict of interest. National Center for Biotechnology Information , U. Journal List Open Med Wars v. Open Med Wars. Published online Jul 6. Author information Article notes Copyright and License information Disclaimer.
Received Mar 15; Accepted May Abstract The chief aim of this study was to analyze secondary healthcare providers' efficiency, focusing on the efficiency analysis of Slovene general hospitals. Methods We researched the aspects of efficiency with two econometric methods. Results Results on measures of efficiency showed that the two chosen methods produced two different conclusions. Conclusion Our results are a useful tool that can aid managers, payers, and designers of healthcare policy to better understand how general hospitals operate. Introduction The first definition of the term efficiency in economic theory was originally offered by Farrell [ 1 ]; it was based on the works of Debreu [ 2 ] and Koopmans [ 3 ].
Methods The field of healthcare clearly indicates that the two most frequently used approaches to the providers' efficiency evaluation are the parametric approach and the nonparametric or deterministic approach. Efficiency evaluation with the SFA method Each definition of econometric model of stochastic frontier function first demands that a decision on the functional relation between outputs and inputs must be reached.
Efficiency evaluation with the DEA method The model we used within the DEA method is the input-oriented model of constant returns to scale. Sample and data Our analysis is focused on evaluating technical, allocative, and cost efficiency of twelve Slovene general hospitals that represent all general hospitals located in Slovenia. Results The SFA method has shown that through the entire observation period, Celje General Hospital has undeniably been the most technically efficient general hospital in Slovenia; its average value of technical efficiency was 0.
Open in a separate window. Table 2 Average values of technical, allocative and cost efficiency of general hospitals for each individual year, estimated by the SFA method and DEA method.taylor.evolt.org/laxow-gran-web.php
Measuring Efficiency in Health Care
Figure 1. Figure 2. Discussion Measures of efficiency estimated with both the SFA and DEA methods show quotients of technical, allocative, and cost efficiency in each hospital did not change fundamentally during our observation period. Footnotes Conflict of interest: Authors state no conflict of interest. References  Farrell M.
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