In the Netherlands every year lists are published on the performance of Dutch hospitals. The lists tell the consumer which hospital scores best on a variety of key performance indicators such as customer friendliness, the number of cancelled OR sessions and the number of caesareans performed. Consulting firms, consumer agencies and even newspapers present rankings of the hospitals, each are using their own methodology. This leads to different rankings for the same hospital, leaving the to-be patient confused about the results. How should a (potential) patient decide on which hospital to go to? Wouldn’t it be better to have an overall score for each of the hospitals, so a simple ranking based on that figure can be constructed? Question is of course how to create such a ranking.
It is not only the consumer that is interested in the ranking of the hospital. Hospitals themselves also like to know where they stand compared to their piers. Since the Dutch healthcare market is changing from regulated (with fixed prices for services) to a more liberated market (with free pricing for some standardized products) a low ranking could implicate less “customers” leading to lower revenues. Also the liberation of the market leads to more pressure on effectiveness and efficiency of the hospitals. But how can we compare the performance of hospitals? How to benchmark the performance of each of them and rank the hospitals on an objective and simple way?
I came across this question in a project a few months ago. Hospitals are accustomed to benchmarking, but the drawbacks of the techniques used were something they would like to get rid of. In most cases some kind of ratio analysis is used. Clearly this doesn’t give you objective measures and does not allow for a simple ranking. Various ratios can direct in contradictory directions. So we had to search for better techniques. We came a cross a linear programming based technique, Data Envelopment Analysis. This technique supports the benchmarking questions for the hospitals but also can also be used in ranking hospitals either as a whole or per type of care.
Data envelopment analysis (DEA) is a much used technique in benchmarking, also in healthcare. Is has been developed in the 1970’s by Charens, Cooper and Rhodes. In DEA the most efficient combination of production units is constructed, called the efficient frontier. Efficiency is then measured as the distance to that efficient frontier. See http://www.emp.pdx.edu/dea/wvedea.html for more details on DEA. By modelling the hospitals as production units with certain inputs and outputs, DEA can be used to identify which hospital converts the inputs into outputs the most efficient. The efficiency score can than be used to rank the hospitals.
A nice feature of DEA is that it can be used to determine how a hospital can improve its performance, either by lowering its use of inputs (i.e people, cost, equipment, etc), of increasing the outputs (patients served, quality, etc).
The project was performed at middle sized hospitals in the Netherlands for the clinic and day care departments. The results were received very well; next step will be to extend the benchmark to other parts of the hospital like the OR and out patient clinic.
I came across this question in a project a few months ago. Hospitals are accustomed to benchmarking, but the drawbacks of the techniques used were something they would like to get rid of. In most cases some kind of ratio analysis is used. Clearly this doesn’t give you objective measures and does not allow for a simple ranking. Various ratios can direct in contradictory directions. So we had to search for better techniques. We came a cross a linear programming based technique, Data Envelopment Analysis. This technique supports the benchmarking questions for the hospitals but also can also be used in ranking hospitals either as a whole or per type of care.
Data envelopment analysis (DEA) is a much used technique in benchmarking, also in healthcare. Is has been developed in the 1970’s by Charens, Cooper and Rhodes. In DEA the most efficient combination of production units is constructed, called the efficient frontier. Efficiency is then measured as the distance to that efficient frontier. See http://www.emp.pdx.edu/dea/wvedea.html for more details on DEA. By modelling the hospitals as production units with certain inputs and outputs, DEA can be used to identify which hospital converts the inputs into outputs the most efficient. The efficiency score can than be used to rank the hospitals.
A nice feature of DEA is that it can be used to determine how a hospital can improve its performance, either by lowering its use of inputs (i.e people, cost, equipment, etc), of increasing the outputs (patients served, quality, etc).
The project was performed at middle sized hospitals in the Netherlands for the clinic and day care departments. The results were received very well; next step will be to extend the benchmark to other parts of the hospital like the OR and out patient clinic.
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