General outline of the approach

GENERAL OUTLINE OF THE APPROACH The effect of general health standards on the level and growth of per caput income in the devel- oping countries has received little attention from economists. Despite the potential contribution of improvements in health to the overall process of economic development, economists have tended to remain silent on the subject of health care and disease control programmes. In particular, they have failed to provide specific advice or to elaborate planning methods for the benefit of those responsible for the health care sector. Unfortunately, the choice of health care activities has not generally reflected a conscious comparison between the benefits obtainable and the concomitant use of scarce resources. Public health administrators have often attempted to treat the selection of pro- grammes as a " technical " question, free of value judgements about the relative desirability of different health improvements. One result of this has been a concentration on diseases such as malaria of which complete eradication is technically feasible. A second result has been the use of " indicators" of the community's general health level, such as the infant mortality rate. This has led health administrators into the fallacy of assuming that programmes which reduce infant mortality actually raise the general level of health. Substantial resources have therefore been devoted to decreasing infant mortality, thus increasing population size but not improving health in other age groups. The authors' research in this area has been directed towards the development of a systematic approach to health sector planning, capable of integration into a more general economic development pro- gramme. The aim of the current phase of this research has been to devise an operational method of allocating scarce health sector funds, manpower, and facilities among different disease control pro- grammes and individual activities in a way that would yield the optimum feasible output in terms of reduced mortality, morbidity, and economic losses. At the core of this method is a description of the health care sector based on a linear activity analysis: a set of inputs and a set of outputs are associated with each health activity. This leads to an optimization procedure using a linear program- ming algorithm. The present study describes the basic conceptual scheme for formulating the health sector planning problem within the linear programming framework." The health sector plan is formulated in terms of a large number of curative and preventive activities. Each activity is defined by a set of conditional criteria-e.g., if a child is negative to the tuberculin test, vaccinate it; if it is positive, treat it in a parti- cular way. Each activity requires a set of inputs. Some inputs can be readily purchased (e.g., drugs and minor equipment), while others are available only in limited quantities that cannot be increased in the short run by spending more money. The planning problem is to determine the intensity with which each activity is to be operated. The plan must not call for larger quantities of the specifically limited inputs than are available nor for a greater total expenditure than the budget allocation allows. In addition to these input limits, the plan is also subject to population constraints. For example, in the instance mentioned above, the activity is limited by the number of children in the population. These input and population constraints are all linear and can therefore be expressed in the form required for linear programming. The specific information needed can be readily supplied by medical experts and health agencies. The calculation of the net value of each activity poses a number of difficult problems that are dealt with in this study. The basic structure of these calculations may be summarized as follows. Asso- ciated with each activity is a mix of potential services each with a different probability of being required (for example, in the case of a tuberculosis programme the services are vaccination, chemo- prophylaxis, and treatment). Each type of service leads to service outputs of several kinds: lives saved, reduced disability, reduced impairment, and eco- nomic benefits (i.e., the present value of the income that would otherwise be lost through morbidity and premature mortality). These service outputs include both the effects on the individuals receiving care and the effects on others, owing to the con- tagious nature of the disease. The calculation of the 1 An earlier brief exposition of this approach is given in: Feldstein, M. S. (1970) Health sector planning in developing countries, Economica, 37, 139. - 9- 10 M. S. FELDSTEIN ET AL. outputs ofany service reflects the medical technology, the disease epidemiology, the method of aggregating over time, and the assumptions used in measuring economic benefits. The weighting of service outputs by the probability of each type of service yields a set of outputs or benefits for each activity. The weighted sum of these multiple benefits-with weights reflecting the preferences of officials res- ponsible for policy-is the total benefit value of the activity. In view of the fact that any activity involves the use of resources that might otherwise be employed elsewhere in the economy, the value of these resources outside the health care sector (or outside the subsector if the plan is being for- mulated for a single problem) must be subtracted from the total benefit value in order to arrive at the net value of the activity.' These net values are the weights in the objective function of the linear programming problem. This method has been applied to the allocation of resources within a tuberculosis control pro- gramme. Tuberculosis provides a good example of most of the difficulties that would arise in applying this method. In particular, it poses the complex problems associated with a contagious disease. A significant feature of the approach consists in the feasibility of separating the requisite informa- tional inputs in such a way that they can be provided I The linear programming formulation of the health sector model should facilitate its incorporation into more general planning models of the type discussed in Bruno, M. (1966) Experiments with a multi-sectoral programming model. In: Adelman, I., ed., Theory and design of economic develop- ment, Baltimore, Johns Hopkins University Press; and Chenery, H. B. (1956) Econometrica, 24, 365-399. by medical and epidemiological experts. As a result, the application is susceptible of continual improve- ment as experts criticize specific coefficients and provide better data. A second important virtue of this approach is that the separate roles of value judgements and technical information are clearly distinguished. Because almost all the data and calcu- lations are of a technical nature, the technical staff of the health care planning agency can elaborate and improve the analysis without having to introduce their own value judgements into the planning process. The method described in this study is still a long way from being a practical planning device. A sub- stantial limitation is that the planning problem is formulated in an essentially static way. Resources are allocated for the current period only. Although the calculations take into account the effects of this care on health in the future, the method of planning described herein gives no guidance as to the optimum allocation of resources in future periods. A second shortcoming is that the choice of health sector activities has not been explicitly linked to the broader question of the effect of health on economic development. Nevertheless, the method in its current form can serve two useful functions. First, it can help both public health administrators and devel- opment planners to understand the structure of the health sector planning problem-the way in which preferences, population structure, disease incidence and prevalence, scarce resources, and technology are interrelated in determining the optimum set of activities. Secondly, it provides the basic framework around which to develop a more applicable method.