METHODS FOR EVALUATION OF INSTITUTIONAL BENCHMARK IN HEALTH CARE

C. de Vecchis
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C. de Vecchis: Resfirma s.r.l, Roma, Italy

Chapter 19 in Monitoring, Evaluating, Planning Health Services, 1999, pp 210-218 from World Scientific Publishing Co. Pte. Ltd.

Abstract: AbstractIn this work we will present methods and instruments for the evaluation of the Institutional Benchmark in Health Care and in every other field of public interventions. In particular we will see the methods for goal optimisation in a problem of resources allocation and the known methods for the definition of goal functions. We can define the Institutional Benchmark in a problem of resources as the ratio between the value obtained of the goal function and the maximum value that could be obtained using the same resources. In resources allocation problems there are n goals that are often conflicting with each other so we have to deal with a multiobjective optimisation. Moreover, the evaluation of the priority of one goal over another must be a political decision and must be taken by the political institutions. For this reason we have to speak of non-inferiority rather then optimality. There are different ways to define non-inferiority; we propose the concept of Pareto-optimality adapted to services. We will discuss the advantages that this definition of noninferiority can achieve. We will formulate the multiobjective programming defining the objective functions (utility functions) and the constraint functions. The hardest part of the work is to express the objective functions in terms of resources, that is, to define the functional link between the resources used and the objective achieved. We will spend part of this work presenting the available methods to generate the utility functions automatically from historical data and we will see advantages and disadvantages of each method. Once defined the multiobjective programming problem, we will recall the known methods available for solving it, in particular we will present the weights method and the constraints method. The utility functions will be in a non-analytical form so we will discuss briefly about methods dealing with this kind of functions. In particular we will see the advantages of genetic algorithms. We will conclude our work with a critical evaluation on an application in the local health care field, presenting our conclusions and suggesting future work.

Keywords: Healthcare; Management; Quality; Planning; Emergency Services; Evaluation; Hospital Systems; Monitoring (search for similar items in EconPapers)
Date: 1999
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