Questionnaire

3.1.1 Hospital Output: Health as a Latent Variable

In order to measure hospital output, it is not enough to describe the tasks that are carried out (surgery, radiotherapy, medication, wound dressing, and accommodation, etc.) or bundles of tasks such as medical, nursing or hotel services. All of these tasks are only a means to an end.

One gets closer to true output by asking the question of what the patients (or referring physicians acting on their behalf) want, what they expect from hospitalization, and what taxpayers expect to obtain in return for their contribution to the financing of the hospital. In the majority of cases, expectations are in terms of a positive contribution to the patient’s state of health, that is, the curing of disease (or control of its development) and the alleviation of pain. Even though there is little disagreement with regard to these objectives, the degree of their realization may hardly serve as a basis for the payment of hospital services. The difficulties lie with the measurement as well as the imputation of outputs to services performed.

In order to measure the extent of recovery of patients, their state of health would have to be evaluated not only at the beginning and at the end of hospital treatment but frequently years after the stay, using objective criteria. This is – except for obvious indicators such as survival and complication rates – a fairly hopeless undertaking because health is not only multi-dimensional but also contains a considerable subjective component. Even if this difficulty is surmounted, one should not simply tie payment for hospital services to the measured change in the state of health achieved during the period of hospitalization. For the relevant benchmark for assessing hospital performance is not the patient’s actual state before admission, but the (hypothetical) state that would have been realized without hospital treatment at the end of the observation period. The importance of this distinction becomes very clear in cases where hospital treatment can only slow down the progressive course of an incurable patients hold expectations not only with regard to the final state of their health after hospital treatment but also with regard to their

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physical and mental well-being during hospitalization (to the extent that the disease will permit), as life goes on in the hospital. This aspect takes on special significance if the disease itself can no longer be fought and only suffering can be alleviated, that is, when dealing with incurable and terminally ill patients. Objective and reliable measurement of subjective wellbeing during hospitalization, however, is just as difficult as measuring the influence of hospitalization on the patient’s health status. Finally, the customers of a hospital not just cover people that will actually be treated as patients, but the whole population of its catchment area. The mere existence of a hospital provides people with the security that in case of accident or serious illness inpatient treatment will be available. This so called ‘option demand’ is satisfied by hospital beds held on reserve, along with the necessary staff and equipment.

3.1.2 The Multi-Stage Character of Production in the Hospital

As the final outcome of hospital activity (particularly the improvement of a patient’s health status) can only be measured imperfectly, observable quantities suitable to serve as output indicators have to be identified for obtaining an operational definition of the term, ‘efficient use of resources’. In the present context, it seems appropriate to list various indicators of hospital activity and to classify them according to the stage of production, using a scheme that may help to describe hospital activity from an economic perspective. The indicators commonly used are:

(i) Quantities of factors of production (hours worked by physicians, by the nursing staff and by other employees, drugs and dressings, electricity, fuel etc.);

(ii) Quantities of individual medical and nursing services performed (medications, injections, physical therapies, temperature measurements, meals etc.);

(iii) The number of patients or cases treated, possibly differentiated according to various types of diseases

(iv) The number of patient days, possibly differentiated according to intensity of care

3.1.3 The Heterogeneity of Hospital Output

Another problem with defining and measuring the output of a hospital stems from a considerable amount of heterogeneity, be it at the level of output indicators or of intermediate products.

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Consider the number of cases treated in a hospital in the course of a year. Is it possible to describe adequately a hospital’s outputs imply by counting the number of cases? Is it appropriate to say that a hospital that treats 1,000 cases achieves more than the one that treats 995?

Obviously, the 1,000 cases of the first hospital might consist of 500 minor fractures and 500 uncomplicated tonsillectomies whereas the second hospital might be a heart unit specializing in transplantations. One must therefore take into consideration that the ‘case treated’ does not constitute a homogeneous quantity but a mental construct that needs to be specified through its characteristics. This means that a treatment case must be differentiated along various dimensions, for example:

(i) The type of illness that has called for hospital treatment (principal diagnosis);

(ii) The severity of the illness and complications arising during treatment;

(iii) The stage of the disease (e.g., in the case of cancer);

(iv) Concomitant diseases (secondary diagnosis);

(v) Patient characteristics reflecting her or his contribution to the ‘production of recovery’, such as age and possibly sex.

In view of these distinctions, to which still more could be added, a purist must come to the conclusion that heterogeneity of case mix can only adequately be taken into account by considering each patient as an output category of her or his own. Following this principle, however, one would forego the possibility of comparing the output vectors of two or more hospitals. This would put an end to the economic analysis of the hospital in the quest of, for example, measuring the degree of efficiency or determining a performance-based payment system. A reasonable compromise between the rigorous approach just outlined and the total abandonment of case differentiation may be achieved by dividing patients into a manageable number of groups, using the distinguishing characteristics mentioned above. This division is known as patient classification and purports to form a manageable number of patient groups that are as homogeneous as possible. Moreover, assignment to a group should be unique and reproducible using objective criteria. Obviously, there is a conflict between the criteria

‘manageable number’ and ‘greatest possible homogeneity within each group’ which can only be

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resolved by weighing the relative disadvantages caused by their violation. The three most common patient classification systems are:

(i) The International Classification of Diseases (ICD) originally developed as a basis for mortality statistics and thus solely referring to (principal) diagnoses. In its three-digit version, the ICD consists of more than 900 groups, while aggregation to the level of 110 main groups is already very coarse. For instance, all benign neoplasms form one single group in this categorization.

(ii) Diagnosis Related Groups (DRGs) developed at Yale University in the 1970s with the explicit objective to create relatively cost-homogeneous groups. Besides the principal diagnosis, DRGs take into account the existence of concomitant disease and

complications, the age of the patient, and the type of treatment (surgical or conservative), getting by with approximately 500 groups.

(iii) Patient Management Categories (PMCs), also developed in the United States (Pittsburgh) and consisting of a total of 840 groups compared to DRGs, PMCs put emphasis on concomitant diseases and the treatment strategies chosen by the hospital.

SELF ASSESSMENT EXERCISE

Discuss the indicators of hospital activity and classify them according to the stage of production.