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Guidelines for pragmatic assessment for health planning in developing countries
Health Policy, 21 (1992) 187-209 lsevierScience Publishers B.V. All rights reserved. ON%8510/92/$05.00 01992 ? ,?
187
HPE 00476
Guidelines for pragmatic assessment for health planning in developing countries Bonita Stantona and Annemarie Woutersb aDepartment of Pediatrics, School of Medicine, University of Maryland, Maryland, USA and bDepartment of International Health, School of Hygiene and Public Health, Johns Hopkins University, Baltimore, Maryland, USA Accepted 31 January 1992
Although the primary health care strategy implemented since the Alma Ata declaration of ‘health for all’ appears to have contributed to improvements in selected health outcomes, the current ad hoc approach to health assessment and planning has impeded more substantial gains. A comprehensive yet pragmatic framework for country-level health programmers is needed that would permit consideration of the multiple steps involved in policy formulation and implementation. In the present paper, drawing upon an epidemiologic model (Iterative Measurement Loop) and an economic model (Cost-Effectiveness Analysis), we present guidelines for a pragmatic assessment for health planning. A format is provided for the conduct of these tasks which is operational in nature, is specific to the target country (or relevant region), can simultaneously consider multiple interventions, and is comprehensible to persons without sophisticated medical and/or economic backgrounds. Such a format enables articulation and consideration of local concerns as well as national and global considerations. Cost-effectiveness;
Health policy formulation;
National Health Program
Introduction The. need for a direct approach to health planning
Completion of the first decade since the Alma Ata declaration of ‘health for Address for cowespondencez Professor Bon&a Stanton, M.D., Chief, Division of General Pediatrics, University of Matyland at Baltimore, 2nd moor, Wcbrn Health Center, 700 West Lombard Street, Baltimore, MD 21201-1091, USA.
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all’ [l] has prompted evaluation of progress achieved by the current primary health care strategy [2-4]. Although this strategy appears to have contributed to improvements in selected health outcomes [5,6] most developing countries are still far from reaching the goals set in the Alma Ata declaration [7,8]. Debates regarding appropriate measures to achieve these goals have been extensive, but have generally not been practical in their orientation [9,10]. The practical problems facing country health programmers are substantial. First, as noted by the Commission on Health Research for Development, health sector planning requires the simultaneous addressing of multiple problems from multiple perspectives 141.Second, program formulation periods are both unremitting and generally of short duration, leaving little opportunity for long-range strategic planning. Third, data quantity and quality are uneven; planning is more developed where data is available and thus programs become data driven rather than conceptually-based. Fourth, donors generally have their own global priorities (usually disease oriented). These priorities, rather than comprehensive national assessments, determine their efforts. In total, these practical constraints have lead to the perpetuation of an ad hoc approach to problem identification and resolution, A comprehensive and yet pragmatic framework for country-level health programmers that would permit consideration of the multiple steps involved in policy formulation and implementation is necessary to advance beyond the ad hoc planning approach [l 11. Such a framework should direct national health policy formulation and implementation with a comprehensive perspective of the health sector. The framework should enable country programmers to identify general ‘trade-offs’ between, as opposed to precise estimates of, the cost and effects of various interventions. A first step towards the development of a framework for the pragmatic assessment for health planning (PAHP) is the articulation of relevant guidelines. To achieve a pragmatic and comprehensive approach to national health planning, such guidelines will need to incorporate five characteristics reflective of the practical constraints noted in the previous paragraph. (1) Interdirc@linary: Information regarding epidemiology, medical practice, economics, management and behavioral science must be obtained and reviewed collectively to ensure that the health plan is medically appropriate, effective, financially feasible, cost&bctive and culturally sensitive. This characteristic is essential for obtaining the comprehensive perspective of the health sector. (2) Expediant: Time constraints will be sign&ant in the planning process. Generally preparation of the annual plan must take place in a few months. The guidelines focuses on activities which can be implemented by a small team in 3 to 4 months. Selection of priority areas of analysis and investigation is necessary to make the guidelines operational. (3) OpportmCtic (utilize existinglseconaby data): Existing data sets supplemented by expert opinion should be maximally employed. Collection of primary data is usually not feasible in annual planning exercises. Rather, efforts should be spent on collecting all available secondary data (by detailed geopolitical subdivisions if possible) relevant to the proposed framework. Some parameters which are not available in existing data can be estimated using expert opinion (e.g. delphi techniques). Relevant data include (a) epidemiologic information; (b) descriptions of
189 medically appropriate and potentially available health interventions; (c) public and private health expenditures: (d) inventories of current health inf&tructure: manpower, facilities, equipment, management etc.; (e) studies of community effkacy of various medical interventions, if available; and (f) studies of cost-effectiveness of potentislly available medical interventions, (4) Non-fechnical: Sophisticated and/or specialized technical expertise may not always be available during the planning process. While team members should be familiar with the disciplines included in the approach, avoiding dependence on high-kvel specialized staff will make the guidelines more operational. (5) Cormtry-spec$c: The guidelines should facilitate identitkation of national and/or local health needs. The process should be simultaneously tokrant of multiple types and sources of data and promotive of extrapolation and/or generalization to ffl data voids as well as directing more systematic data gathering exercises for the future.
The use of existing models to serve as a basis for the guidelines Clearly the development of such guidelines is not a trivial undertaking. However, existing models, such as the Iterative Measurement Loop (IML) [12], could serve as a useful organizing framework if embellished and altered by conceptual and methodologic advances from multiple disciplines. The IML consists of six steps: (1) burden of illness; (2) etiology or causation; (3) community effectiveness; (4) efficiency; (5) synthesis and implementation; and (6) monitoring and reassessment. (See Chart 1 for further description of these steps.) The IML was designed to provide ‘a framework for assembling the specific subset of information that is most likely to help in reducing the burden of both morbidity (symptoms, physical, emotional social and functional impairment) and mortality for a disease. This is accomplished by subdividing the spectrum of health information inquiries into steps that constitute a logical progression - from quantifying the burden of illness to identifying its likely causes to validating interventions that prevent or ameliorate it and evaluating their efficiency’ [12]. The IML offers considerable insight into the assessment of burden of illness and causation (steps l-3). However, relatively little is said
slmmary
of the Iterative Loop Me&l’
(1) Defining the burden of illness: (2) Etiology of causation: (3) Community effectiveness:
Describes the burden of illness that exists in a population (e.g. percent mortality, morbidity) L%xriis direct and indirect causes of illness and death (e.g. biologic causes and cultural practices resulting in diseases) Describes impact of intervention in a specific
(4) EtIkkncy
&Ei the relative costs per health benefit achkved in relation to alternative interven-
Synthesis and impkmentation: (6) Monitoring and reassessment:
Integrates previous steps Assesses output and process of program
tiOllS (5)
*See ref. [12] for detaikd description of the model.
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regarding economic evaluation, assessment of efficiency, equity, and synthesis and integration of the epidemiologic and economic data. By contrast, Cost-Effective Analysis/Cost Benefit Analysis (CEA/CBA) for program planning and management in international development [13] offers relatively greater insight into economic analysis but with less epidemiologic analysis. CEA analysis is most powerful when the decisions it informs involve choices of different techniques for achieving the same narrowly defined outcome. Cost-effectiveness estimates provide an ordering of interventions; however, epidemiologic and technical information is required to determine the scope of application in a given country. An extensive experience with use of CEA in program management has been recently summarized [13]. ‘- Performing an analysis of costs and benetits can be very helpful to decision makers because the process of analysis gives structure to the problem, allows an open consideration of all relevant effects of a decision, and forces the explicit treatment of key assumptions....[However], CEA/CBA exhibits too many methodological and other limitations, however, to justify relying solely on the results of formal CEA/CBA studies in making a decision. Thus, although CEA/ CBA is useful for assisting in many decisions, it should not be the sole or prime determinant of a decision.’
CEA consists of 4 basic steps: (1) goal setting (e.g. defining the health problem); (2) specifying health intervention alternatives; (3) predicting costs and effects and (4) program selection. (See Chart 2 for further description of these steps.) Health plans are ultimately determined by using the decision rule of CEA, programs selected yield the largest net benefit. In light of the serious resource constraints facing most health sectors in LDCs, policy makers must carefully examine the ‘tradeoffs’ between the costs and benefits of the integration of chart2 srmlmaryIJfMst-eff~velWss alnly7ds (1) Goal setting: The fast of the steps is to define the health nroblem to be addressed. Tvoical problems are excessive infant mortality, maternal mortality etc. It is in this step where the iML can strenghten CEA. Goal setting clearly depends on good epidemologic analysis (burden of iBness and causation). (2) Specifying ulternatives: Given the main health problems to be addressed health interventions must be specifiid. Again, IML can strengthen this aspect of CEA by providing clear information on available medical practices and community effectiveness of each potential intervention. (3) Predict~g costs and effects: The strength of CEA is in itemizing various cost comuonents of the project including investment and recurrent costs. This is corn&me&d with the-epidemiologic information on effectiveness. Not all project constraints and benefits can be quantified,
however, they are identitkd to the greatest extent possible. (4) Program selection: In principle, selection is based on which program offers the greatest impact per unit cost; however, in most situations, the final choice is restricted by one or more constraints. These may include specifii objective constraints (e.g. reduction of health indictors by a specific amount), resource constraints (e.g. limited number of prz-.kian, managers, building materials etc.), budget constraints (e.g. financial feasibility).
191 Table 1
(a) CEA = Community Effectveness Communitv Costa =-EfTicacy + Diagnostic + Health Provider (b) Community Effectiveness Accuracy Compliance * Patient + Coverage Compliance
various health interventions into a community. The value of all community resources used in the program are counted as costs regardless of who pays for them. The goal is to maxim&e effectiveness in the population as a whole rather than for any given individual. Community effectiveness depends on the conditional probability of five factors including efficacy of the intervention, diagnostic accuracy, health provider compliance, patient compliance and coverage [12].’ These concepts are depicted in Table 1. From this formulation, the interdisciplinary nature of health planning becomes very clear. Information regarding epidemiology, medical practice, economics, management and behavioral science must be obtained and reviewed collectively to ensure that the health plan is medically appropriate, effective, financially feasible, cost-effective and culturally sensitive. Such an analysis is potentially feasible in many developing countries. Both because Western health programs in these countries are new [ 141and planning in many developing countries tends to occur in a centralized fashion [ 151,there is considerable control over the introduction of technologies and the maintenance of those previously introduced. Thus, there is substantial homogeneity in the infrastructure nation- (or state) wide, and the costs of both the development and/or the operation of health systems are potentially accessible in many developing countries [16]. The emergence of guidelines for a pragmatic pladng
assessment
for health
In combining the IML and CEA to provide guidelines for a pragmatic assessment for health planning we envision a framework consisting of four major steps. A Epiakmiologic assessment: Cdkztion of key epidemiologic indicators of mortality and morbidity for detailed geographic subdivisions of the area for which a health plan is being designed. B Description of potentially available technologies i. Identification of potential technologies to address these diseaxs or conditions. ii. Determination of effi (iipact of intervention under ideal conditions). C Assessment of the costs and effectiveness of each potentMy available technology i. Compilation of costcffectiveness literature. ii. Adjustments to cost estimates. iii. Estimation of effectivemw in the community.
192 iv. Assessment of other constraints to program implementation. D EffEiency and equity: assessing ‘tradho~s’ between costs/constraints and el’ftiveness
For the remainder of this paper we shall delineate the purpose of each step, discuss the underlying principles of the step, identify potential useful methodologies and indicate future research needs. As a pZanning framework, PAHP does not seek to propose methodologies for implementation and evaluation per se (step 6 of the IML) but, in agreement with the IML, recognizes that analysis of such evaluation data will be essential to next subsequent rounds of planning activities and hence will be, in part, incorporated into the PAHP. Likewise, as a set of guidelines, PAHP does not attempt to undertake a CEA study but rather to delineate trade-offs between effects and costs in broader terms. Step A. Epidemiologic a-nt
The purpose of this step is to identify the relative contribution of diseases and conditions to morbidity and mortality amongst the differing target groups. Such a compilation of epidemiologically significant disease categories should direct the search for appropriate interventions, but, in and of itself, will not determine the interventions to be implemented. That decision-process (the focus of the subsequent steps) will be based on a thorough assessment of personnel requirements, complexity of logistics, facility requirements and monetary cost. Information needed for the conduct of these subsequent analyses should thus direct the data gathering exercise in this step. Such epidemiologic requirements are substantially addressed. in the first two steps of the IML (‘Burden of Illness’ and ‘Etiology’) but as the IML is intended for both country health programmers and researchers [12] certain points warrant discussion here. First, where available, data depicting the relative (as opposed to absolute) magnitude of the problem within the country is most useful for planning purposes.2 Likewise, health services utilization data is an inadequate data base for purposes of assessing the burden of illness for health planning.3 In most developing countries national household survey data (e.g. Demographic and Health Surveys) and/or more detailed ‘case’ studies are available until routine and/or ongoing sample systems have been designed and implemented. Analyses in which morbidity and mortality are combined into a single index [17] illustrate future directions and potentials for health plating.4 As methodologies are refined and national epidemiologic expertise is developed, such advances in data utilization will be optimal. However, in the interim, simpler analytic techniques, simple displays of morbidity/mortality rates/ percentages, and parallel but separate assessments of morbidity and mortality should not be viewed as inadequate. Reasonable estimates can be calculated for incidence and case-fatality rates for most of the important diseases in many countries by extrapolating from secondary information. Thus, for example,
193
use of the delphi technique or variations thereof, could be employed to obtain expert consensus for parameters not otherwise readily available. Sensitivity analysis should be used to identify instances where more empirical data is necessary to strengthen ‘best guesses’ [181. Typically a morbidity and mortality profile will depict disease categories. While occasional interventions may be directed against entire categories (i.e. oral rehydration therapy against watery diarrhea) generally interventions are targeted against specific causes of diseases or disease categories (i.e. vaccines against specific courses of diarrhea). Thus, national programmers must be aware of data regarding causation and where country specific data is not available, know that limited investigations of causality may be warranted (i.e. investigate the etiology of dysentery). However, national health programmers will generally not be involved in the conduct of basic causal research. In its current published form [12], the second step (‘Etiologic’) of the IML has a strong orientation towards basic causal research. Such a basic research orientation is neither necessary nor adequate for the practical issues in ‘causality’ being addressed by the PAHP. Bather what is needed is a methodology which indicates when etiologic confirmatory work is necessary, how extrapolation from existing data sets can provide a proxy for confirmatory studies, and/or what simplified procedures for primary data-gathering for causal confirmation are available. Examples of such directive guides include the WHO national diarrhea1 disease control program manuals [19]. Step B. Describing the available technologies I-
potential teclmologim to address the conditions. The importance of accurate identification of technologies (preventive and curative) potentially available to address the targeted health condition is obvious. Seemingly this step should be a simple technological task, requiring only a biomedically sophisticated consultant who is able to access the current literature. However, the acquisition of appropriate and comprehensive information will have profound implications for the successful conduct of the remaining tasks. For most curative and some preventive health interventions consideration must be given not only to the potential treatment intervention(s), but to the screening and diagnostic interventions as well. Beyond a description of the technologies themselves, operational information should be provided including: (1) personnel requirements (including total numbers and level of training of personnel necessary for the implementation of the diagnostic and treatment/ preventive aspects); (2) the physical infrastructure necessary to support all aspects of the intervention; and (3) the support or auxiliary equipment, supplies and efforts (including patient education) required to effect or implement the intervention. Without deliberate specification of these requirements for implementation of the intervention, a technological preoccupation is inevitable [20,21] with subsequent errant efficiency estimations (vide infia).
194
DeWmining efficacyof the intervention. Under ‘ideal’circumstances, does the intervention ‘work’? Were the task at hand the conduct or assessment of previously conducted efficacy trials of potential interventions, arguably this task could be subsumed in the review of existing technologies (the first task). That is, to the extent that this task is technical with specifically delineated procedures, then it may be performed by an outside ‘consultant’ or group for similar to the assessment of existing the country-level programmer, technologies. However, meaningful assessment of efficacy requires in-depth knowledge of the epidemiology of the potential host country or state. The importance of local determination of casualty (etiology) discussed in the previous section becomes apparent here. While some interventions may impact on several or all of the diseases within the clinical syndrome (as, for example, oral rehydration solution for watery diarrhea), for others the intervention will be highly specific (e.g. the current parenteral cholera vaccine). Therefore, an estimate of efficacy of an intervention on morbidity or mortality in the national setting must be based on an assessment of the contribution towards mortality or morbidity of each disease against which the intervention is efficacious. For example, regardless of the efficacy of a cholera vaccine and overall prevalence of diarrhea, the vaccine will not lower morbidity or mortality if none of the diarrhea is caused by vibrio cholera. Thus, for any given disease or disease cluster there are likely to be several interventions directed at differing causes (or stages) of the disease process with varying degrees of efficacy in prevention/ therapy. There are a multitude of epidemiological approaches for estimating the efficacy of health interventions in improving health outcomes, but they vary in reliability, generalixability, costs and time factors. A recent summary of this issue notes that ‘BeforeAfter Comparisons’ and ‘Non-Randomized Treated and Non-Treated Comparisons’ are frequently misused and generally produce biased conclusions [18]. Stronger study designs include Case-Control and Randomized Field Trials; however, they must be conducted with methodological rigor to produce reliable results. Syntl~esis of information regarding ‘available tedmologies’.
To further the quest for guidelines which are practical, a consolidation of the necessary information regarding existing technologies into a simplified format would be desireable. As a example, in Graph 1 we present a synthesis of the information necessary regarding ‘available technologies’ for conduct of the subsequent exercises for one illustrative disease, tetanus. The graph is deliberately general in nature, focusing on the level of preventive, curative and/or rehabilitative input required for differing outcomes, rather than the precise technology. This graphic display enables an informed decision as to what magnitude of decrease in morbidity and/or, mortality might be expected from a given intervention and what type of personnel/facility and infrastructure would be necessary to implement this intervention.
195
Vaccine
Chemopfophylalais
Curative Treatment
Community Level - No effective intervention See Appcndk Tsbk 2
‘Key’ to Graphs 1 and 2 for dcfinitions/cxplanations
of “input’and ‘eftkacy’.
Potential preventive interventions have been roughly classified according to whether they are ‘community’ (require cooperation/organization at a national or community level, i.e. legislation, roads), or for family/individual interventions, according to whether they are a vaccine, chemoprophylaxis or behavioral. (Although it is axiomatic that any intervention involving performance of individuals should have a behavioral component, in this context ‘behavioral’ interventions are limited to those in which the entire intervention is education or other inducements for behavioral change.) Potential impact of curative treatment of patients presenting with tetanus is depicted in the final box. Inputs required may be grossly characterized as follows: personnel according to level of training by general category (i.e.- thoracic surgeon
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versus pediatrician versus community health worker); description of the facilities according to basic functional aspects (i.e. no water on premises versus tubewell water versus piped-in-house water); level of co-existing technologies and supplies (i.e. simple microscopy versus bacteriologic culturing versus immunologic diagnostic capability); and, patient and/or community education efforts. (See Appendix: ‘Key’ to Graphs 1 and 2 for full description and definition of categories). A compilation of such charts for each disease category of epidemiologic significance would provide the necessary foundation for the subsequent exercise of matching country needs and potential intervention technologies with the existing infrastructure. Step C. Asses&g technology
the costs and effectiveness of each potentially
available
An important feature of cost-effectiveness is that comparisons are made between the full set of alternative interventions to deal with a given health problem. The objective of steps A and B has been to carefully identify the full range of options to be considered in resource allocation decisions. In order to assess the costs and benefits of each potentially available technology, four exercises are required: (1) compilation of existing cost-effectiveness/costbenefit literature; (2) adjustments to cost estimates; (3) estimation of community effectiveness; and (4) assessment of other constraints to program implementation. Compilation of cost-effectivewss literature. Ideally one would want to use cost-benefit analyses which not only assess costs but incorporate valuation of health outcomes; however, such studies are rarely available and difficult to undertake. By contrast, cost-effectiveness analyses are more generally available. CEA analysis is a powerful tool for choices between different techniques for achieving the same narrowly defined goal, but is limited in its ability to compare programs with different health outcomes. Nevertheless, a compilation of cost-effectiveness literature will provide general information on known ‘trade-offs’ between the costs and effects of various interventions. Great care should be taken in applying cost-effectiveness estimates to different projects because several considerations will affect interpretation [ 181. Thus, the mathematical principle for m aximization states that marginal costs should equal marginal benefits. CEA analyses should be conducted using marginal costs and marginal effects; however, estimates of averages are typically more available. In some situations, average and marginal estimates may be quite different (e.g. health care delivery at the periphery). This may substantially alter CEA calculations. Moreover, many costs and effects of programs may occur with some time lags. These timing effects may vary across countries and may or may not be dealt with in CEA estimates. Elements of both costs and effects may require significant adjustments. Key
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aspects which may vary by project circumstances are highlighted below. Adjustments to cost estimates. Cost items: The basic principle of CEA for health sector planning requires that an item is a cost of the project if it would not have been incurred and used up otherwise, unless it is a preexisting cost at the time the project decision is made. A comprehensive itemization of all cost elements should be made to check control for omissions or overcounting. Sunk costs: In many developing countries, the health infrastructure and system has been developed over a period of one or two decades [ 143and have involved substantial investments of time, money, management and training. That is, what systems do exist have generally not resulted from trivial investments and thus should not be regarded as readily expendable or even alterable. Interventions will not be introduced in a void and major alterations in an existing infrastructure could not be accomplished with ease. The existing health infrastmcture investment is a ‘sunk cost’ for those new interventions which could make use of the existing system. In CEA, sunk costs are not included because they would have been incurred even if the new intervention were not implemented. For example, if a potential program to be implemented is a tuberculosis control program, prior initial investment in microbiologic and radiologic facilities are ‘sunk costs’ and not added to the cost estimates of the new option. In countries where significant previous investments exist, adjustment of sunk costs is likely to substantially alter CEA estimates. In Graph 2, existing and needed resources are compared qualitatively to reflect primarily the degree of ‘sunk costs’ and to provide some indication of ‘start-up costs’.5 (Start-up costs are described in more detail in the section on budget constraints.) Needed inputs (N) are juxtaposed against existing Q inputs. Categories of potential preventive interventions are defined as for Graph 1 (see text page 195 and Appendix: ‘Key’). Potential treatment interventions are then classified according to issues in triaging and therapeutic outcomes. In the column labelled ‘screening’ we contemplate the volume of persons presenting with the disease (or a disease within the differential diagnosis), the activities which would have to be undertaken to triage such people, and the level of personnel and facility required for the triaging exercise. ‘Majority’ refers to the level of drugs, equipment and personnel training to cure or adequately treat over half of the patients with the targeted disease. ‘Minority’ addresses the same issues but for the remainder of patients not able to be accommodated by the ‘majority’ approach. ‘Stragglers’ refers to that small (arbitrarily defined as less than 10%) of patients whose needs cannot be addressed by either of the first two approaches. This graphic display enables quick and easy visualization of the ‘fit’ of the intervention within the system. The Q inputs can essentially be viewed as sunk costs which should not be included in the cost-effectiveness estimates. For each type of input, if (N) is greater than (E), additional investment is required by the amount (NE) some of which may be one-time start up costs. The larger the gap, generally the
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worse the cost-effectiveness of the project. If(N) is less than or equal to (E), no additional investment in that input is required and the project is more costeffective under the given country circumstance~.~ Joint costs: Frequently a potential intervention might be able to share some of the inputs of another project. Many inputs used in the health sector contribute simultaneously to the production of several distinctly different kinds of outputs. For example, the radiologic unit could service both the TB program and a trauma unit. Joint cost allocation adjustments would be required to allocate the costs to the appropriate outputs; the full cost of an input would not be attributed to a single output. Scale of activity: It should also be recognized that cost-effectiveness estimates may be affected by the scale of activity. Service delivery systems may experience increasing, decreasing or constant returns depending on the scale of activity. For example, community health worker programs have been found to exhibit decreasing returns to scale [23]; thus, small programs will have more favorable cost-effectiveness estimates than large national programs. CEA generally produces an estimate of a single point on the cost function. Efficticy: Ultimately, CEA estimates are used to design the most efficient health care plan. However, because of the multitude of factors which affect CEA results, one must be extremely carefully in interpreting differences in CEA estimates as differences in efficiency. Factors such as timing, scale, marginal versus average analysis will influence results. Also, if demand patterns change, programs will fluctuate in cost-effectiveness if they exhibit non-constant returns to scale. Estimation of effectiveness in the ‘co~~~~unity’. Assessment of the interaction between the exidng health infrastructure and the new intervention is an essential next step. Obviously studies which have been conducted in the actual locale under ‘field’circumstances are ideal for such an assessment. However, as generally only a few effectiveness studies for a given intervention will be conducted, such information will not usually be available. Modifications to estimate community effectiveness, as defined earlier, will be required. Equation B (Table 1) graphically illustrates the importance of simultaneous entertainment of multiple considerations in estimating effectiveness. Depiction of the concept as one of multiplication demonstrates that to be effective all five variables are important because a ‘zero’ in any cell would result in an ineffective intervention regardless of performance of the other four variables. Unfortunately, the amount of information required for completion of the .five main variables, each with several essential sub-components, renders it unlikely that the formula could be precisely calculated for most countries. However, building upon the basic concept of such a formula, effectiveness studies conducted in other settings in which comparability of at least some of the key variables is known to exist could be utilized. Clearly methodologies must be established for extrapolation from such studies. In the interim,
202 of eomparlson of possiblyrdevant dlara~rlslica between targeteommu&y ad eomlnanitiea (eommmity A and B) whereeftieaey studieswereprehncdy conducted
Fmmple
Community characteristics
Study communities Target community
A
B
10% 40% 1:200
3% 15% 1:looO
40% annual
15% dailY integrated
Baseline
Percent of population vaccinated at baseline 3% Percent population with radio access 20% Ratio of community health workers/population I:900 Percent of population within 5 miles of sites offering vaccine 2; Delivery strategy integrated
-paign vertical
l’bo years ajter vaccination program initiated
Percent of targeted population (infants) vaccinated: Percent reduction in infant mortality: Percent reduction in disease-specific mortality in infants:
35% 15%
60%
30%
50%
35%
however, we may suggest that delineation of the relevant variables juxtaposed against those that were equivalent to the national setting from several studies should begin to enable relatively accurate estimations of actual effectiveness. Thus, for example, let us assume that a vaccination program against tetanus is being contemplated for a hypothetical ‘target country’. Much is known regarding potentially relevant health service characteristics of this country, but no efficacy or effectiveness trial of the vaccine has been conducted in this region. However, in the evaluation of efficacy studies of the vaccine in other settings many of these potentially relevant community characteristics have been described. A simple chart contrasting these characteristics (such as that displayed in Table 2) might enable some (albeit crude) assessment of which study site was more similar to the current target community. This approach would provide a more accurate estimation of anticipated benefit from the proposed vaccine campaign than by only drawing inference from a range of effectiveness values without reference to community comparability. As noted earlier, employment of the delphi technique among experts to provide ‘best guesses’ for missing values is an alternative or complimentary approach. Two other concerns pertaining to effectiveness are worth noting. First, effects (both positive and negative) of a program may be much wider that included in the CEA analysis. Second, when health outcomes are diverse some sort of valuation of each outcome is required before an overall assessment can be made. This is especially true for health outcomes which affect different age groups and which take place over varying time periods. Weighting health outcomes by social discount factors and a productivity index is sometimes used. This is likely to be beyond the scope of a pragmatic planning exercise;
203
nevertheless, the importance of issues should be recognized, especially in crosscultural settings. Assessment of other amstdnts to program implemmtation. Several different types of constraints, both monetary and non-monetary can operate to impede program implementation. Such constraints are rarely immutable and thus require periodic re-examination. Such constraints have been variously categorized [131. Specific - objective constraints: This constraint arises if an immutable decision has been made that a certain specified quantitative goal must be reached that would preclude other uses of resources (i.e. 700 community health workers must receive a 2-week training course; alternative training uses might then be pre-emptied). iuutual - exclusivity constraints: Such a constraint can arise if, for technological reasons, only one alternative is possible or if components of separate alternatives are interdependent (i.e. an outreach, community-based EPI program targeting under-five versus a facility based ‘all-comers’ approach). Budgetary constraints: Affordability will undermine the effectiveness of the potential intervention; it is a necessary condition of an efficient health plan. The affordability of the initial investment program is often a substantial problem. One time start-up costs (not included in CEA) can be prohibitive. However, another more frequent dilemma is to determine the recurrent cost portion of a program which is a consequence of the initial investment and to assess its financial feasibility. A quick way to assess the recurrent cost implications of an investment is to multiply a previously estimated r-coefficient (the ratio between a project’s annual recurrent costs and its total investment cost) by the total investment costs. The r-coefficients vary tremendously by project (e.g. 20% for hospitals to 50% for primary health care services in Malawi) [22]. Resource constraints: Most CEA analyses use market prices to estimate costs; financial rather than economic costs are reflected. To reflect true scarcity of resources in the economy, economists use shadow pricing. In the health sector, financial and economic costs differ substantially with respect to labor and foreign exchange. For example, managerial resources are usually scarce. Although shadow prices are not likely to be readily available, planners should take note of particularly scarce resources to adjust previous estimates of costeffectiveness to their own circumstances. Capacity for behavioral change: This may be a particularly important ‘resource constraint’. Often changes in behaviors, whether of the health personnel or of the community members, have required years of multiple approaches to effect; systems which either disrupt these positive changes or assume new change can occur without substantial investments will not accurately portray the match between the new intervention and the existing infrastructure.
204
Legal constraints andpolitical constraints: These may impact on implementation although the degree to which these should be specifically and proactively considered by health programmers will vary by circumstance and locale. Step D. Efficiency and equity: asses&g and effectiveness
‘trade-offs’ between costs/constraints
Following the basic principles of CEA we are attempting to compare, in approximate terms, the trade offs between costs and effectiveness of various interventions. Efftciency estimates must be applied at both a ‘program’ level (i.e. what intervention will ‘best’ lower diarrhea1 morbidity/mortality) and, for national health planning, at a sector level (what combination of health programs will ‘best’ lower overall morbidity (mortality). PAHP provides guidelines for assessing ‘tradeoffs’ in a logical and comprehensive fashion. First, a subsample of medical intervention is considered - only those which are appropriate for the identified patterns of mortality and morbidity (summary of steps A and B). Second, rough estimates of CEA for the subsample of medical interventions are presented based on previous literature. Further assessment of these CEA estimates is made by considering (in a qualitative manner) how costs and effectiveness may need to be adjusted with country-specific circumstances. Additionally, the financial feasibility and presence of other non-monetary constraints of the interventions are considered. Finally, there must be consideration of the distribution of costs and benefits among the population. Clearly no simple formula will be generated to provide a definitive answer to health programming needs. Rather, the purpose of PAHP is to elucidate a broadly based discussion of all possible tradeoffs. By exclusion of options at each step, the programmer is faced with a more manageable number of options for which the expected costs and effectiveness as well as the constraints and unmeasurables are articulated. Such a process permits a logical progression from identification of national (as opposed to international) health problems through consideration of options how best to address these problems. Summary We have delineated guidelines for assessment for health planning and where possible have offered pragmatic suggestion on how to conduct the various steps. These guidelines offer an approach for health planning which is simultaneously: (1) operational in orientation; (2) draws upon multidisciplinary perspectives; (3) tailored for the specific country (or state) for which the interventions are being considered; (4) capable of entertaining the demands of multiple interventions; and (5) comprehensible by country programmers who will have variable backgrounds in health and economics.
205
Acknowledgements Many of the ideas expressed in this paper originated from discussions and collaboration with William Reinke Ph.D., Robert Black, M.D., MPH, John Clemens, M.D. and Christopher Chamberlain, Ph.D. Thoughtful comments on an earlier draft of the manuscript were made by Ann Marie Gadomski, M.D., MPH. Manuscript preparation was facilitated by Jeanette Roberts and Juanita Morris.
References 1 WHO, Primary Health Care, Presented at ‘The International Conference on Primary Health Care’ Ahna Ata, USSR, September 1978. 2 Chen, L.C., Primary health care in developing countries: overcoming operational, technical and social barriers, The Lancet, 2 (1986) 12-1264. 3 WHO, From Ahna Ata to the year 2000~ a mid-point perspective, Presented at the World Health Organization Meeting, Riga, USSR, March 1988. 4 Commission on Health Research for Development, Health Research: Essential Lii to Equity in Development, Oxford University Press, New York, 1990. 5 United Nations Children Fund (IJbJJCEF), The State of the World’s Children, Oxford University Press, New York, 1989. 6 Gwatkin, D.R., Wilcox, J.R. and Wray, J.D., Can health and nutrition interventions make a difference? Overseas Development Council, Washington, DC., 1980. 7 Wolff&s, I., Limitations of the primary health care model, A case study from Bangladesh, Tropical Geographical Medicine, 40 (1988) 45-51. 8 Rosentield, A. and Maine, D., Maternal mortality - a neglected tragedy?, The Lancet, 2 (1985) 83-85. 9 Editorial, The debate on selective or comprehensive primary health care, Social Science Medicine, 26 (1988) 877-878. 10 Wisner, B., GGBI versus PHC7 Some changes of selective primary health care, Social Science Medicine, 26 (1988) 963-969. 11 Stanton, B.F., Clemens, J. and Black, R.E., Addressing National and Regional Health Needs: A Framework for Health Planning, International Journal of Health Plan Management (in press). 12 Bennett, K.J., Tugwell, P., Sackett, D. and Haynes, B., Relative risks, bendits, and costs of intervention. In R.S. Warren and A.A.F. Mahmond @da), Tropical and Geographic Medicine, McGraw Hill, 1990,pp. 205-228. 13 Siragelden. I., Salkever, D. and Gsbom, R., Evaluating Population Programs, Jntemational Experience with Cost-Effectiveness Analysis and Cost-Benefit Analysis, The Johns Hopkins University, Croom Helm Ltd., St. Martins Press, New York, 1983, pp. I-103. 14 Smith, D.L. and Bruant, J.H., Building the infrastructure for primary health care: an overview of vertical and intregrated approaches, Social Science Medicine, 26 (1988) 909-917. 15 Solter, S.L., Hasibuan, A.A. and Yusuf, B., An epidemiological approach to health planning and problem-solving in lndonesion, Health Policy and Planning, 1 (1986) 99-108. 16 Stanton, B. and Clemens, J., User fees for health care in developing countries: A case study of Bangladesh, Social Science Medicine, 29 (1989) 1199-1205. 17 Ghana Health Assessment Project Team, A quantitative method for assessing the health impact of different diseases in less developed countries, International Journal of Epidemiology, 10 (1981) 73-80. 18 Morrow, R.H., Dunlop, D.W. and Rosentield, P., Cost-effectiveness analysis: an essential tool for health-related decision making in developing countries (submitted for publication).
206 19 WHO, Estimating
20 21 22
23 24
Costs for Cost-Etfectiveness Analysis - Guidelines for Managers of Diarrhoeal Disease Control Programmw, Document CDD/SER/88.3,1988. Bonair, A., Rosenfield, P. and Tengvald, IL, Medicaltechnologies in developing countries: issues of technology development, Transfer, Diffusion and Use, 28 (1989) 769-781. Institute of Medicine (IOM), Technological innovation: comparing development of drugs, Devices and Procedures in Medicine, National Academy Press, Washington, DC, 1989. Over, A.M., Economic and Financial Analysis of the Health Sector in Developing Countries: A Training Manual, The World Bank Educational Development Institute, Washington D.C., (1991). Berman, P. et al,, Community-based health workers: Head start or false start towards health for all? Social Science Medicine, 25 (1987) 443459. Essential Drugs Project, Bangladesh (EDP), Progress Reports No. 1-5; Essential Drugs Project Bangladesh, Ju+September, 1987.
Endnotes 1 CEA does not usually assess the distributional impacts of the health programs in question. It is possible, however, to incorporate social weighing in the valuation of inputs and outcomes of the project. Thus, for example, social weighing typically enhances the attractiveness of projects that redistribute income to the poor. While on a practical level such social weighing schemes are not available, the assessment can (and arguably should) take note of distributional goals. A review of methods for examinln g equity are beyond the scope of this paper. 2 By contrast, absolute disease/mortality levels may be more useful for monitoring and evaluation and for intluencing donor and/or sectional resource allocation. 3 Seeking of health care is based not only on acruul illness, but on a multiplicity of other factors including perceived ilhress, perceived vulnerability, resource constraints, perceived effmacy of the health resources, etc. Thus, such data may be useful in subsequent impact evaluation of the intervention, but community-based data is most useful for assessing real burden. 4 This index recognizes that the goal of all health care expenditure is to improve health. The amount of health a society has is measured by the number of healthy days people could enjoy in the absence of disease. By adding together the healthy life days lost by different population subgroups from all diseases, it is possrble to compute the total disease burden of a society. 5 Although beyond the scope of this paper to discuss in detail, for the interested reader the existing health inputs summarized in Table 2 are derived from an analysis of the health infrastructure in Bangladesh [ 16,241. 6 In fact, if(N) is less than (E), additional investment in that input is not necessary, but the input (i.e. personnel, facility) is actually ‘more’than what is required (i.e. an abundance of physicians are available for tasks that could be performed by community health workers).
Appendix Key to Graphs 1 and 2
Impact:
Anticipated reduction in disease mortality and/or morbidity rate of the targeted population Low < 10% Moderate lo-20% 20-30% =gh Very high > 30%
207 Direct
Factors that are required for implementation se, not those related to support services
of the intervention per
Personnel (operations): LOW
Moderate High Very high
Minimal training beyond task specific skills; estimated training time - 2 weeks to 2 months (e.g. Health Assistant, Female Welfare Assistant in Bangladesh) Full curriculum in basic primary health care; no speciality training (e.g. Medical Assistant, CHW in Bangladesh) Higher medical training enabling positioning of full differential diagnosis and treatment options; basic technical skills (e.g. medical officer in Bangladesh) Subspecialty medical training with highly specific diagnostic treatment and/or surgical skills (e.g. obstetrical specialist/ consultant in Bangladesh)
Nursing: Qualitative assessment of time required for direct patient care by
professional (e.g. beyond what a family member could provide) No nursing care required by professionals None Minimal time requirement, possibly administration of drug Low Infrequent, regular nursing demand Moderate Frequent, regular nursing demand High Very intensive demand, nearly on&o-one nurse to patient Very high Technology: LOW
Moderate High Very high
Suppoti
Level of underlying support factors required for implementation the intervention
Facility: None
Low Moderate
High
Simple equipment, locally available (e.g. brochures, common antibiotics) Basic equipment potentially available in country (e.g. otoscope and microscope, basic surgical tools, etc.) Relatively sophisticated equipment not regularly produced in country although theoretically could be (e.g. incubators) Highly specialized equipment not produced in country (e.g. respirators, CT scans) of
Field work only Static facility without hospital beds (e.g. Union Health and Welfare Center, rural dispensary in Bangladesh) Clinic/hospital with overnight beds, dependable source of water, electricity and basic operating theatre (e.g. Upazilla Health Complex in Bangladesh) Hospital with overnight beds, functional OR, radiology, blood
208
Very high
bank, and microbiology (e.g. District Hospital in Bangladesh) Highly specialized support including modem intensive care units, etc.
Personnel (supervision and/or support):
Low Moderate High
Very high
Minimal supervisory/support requirement (e.g. surgeon requires little supervision) Supervisory requirements generally low although at times (especially beginning of project) may be higher Constant supervision will be necessary although generally could be done through flow charts 2 or more supervisory levels may be necessary Constant supervision necessary with frequent site/field visitation; multiple supervisory levels may be required
Technology:
Low Moderate
High Very high
Basic equipment generally available at field level facilities (e.g. vaccine carrier, salter scale) or community (posters, leaflets) Equipment, blood pressure cuffs, ophthalmoscopes, microscopes, refrigerators, surgical equipment for D&C (e.g. see DDS kit contents for UHFWC’s in Bangladesh) or, in community (e.g. radios or tubewells) Specialized equipment including cardiac monitors, anesthesia devices, basic surgical equipment beyond simple obstetrical procedures or in community (e.g. televisions or in house water) Highly specialized equipment including respirators, pulse oximeters, highly specialized surgical equipment or for community (VCR’s, home PC’s or sophisticated mobile emergency centers)
Nursing: Qualitative assessment of time required for direct patient care by
professional (e.g. beyond what a family member could provide) None No nursing care required by professionals Low Minimal time requirement, possibly administration of drug Moderate Infrequent, regular nursing demand Frequent, regular nursing demand High Very high Very intensive demand, nearly one-to-one nurse to patient Transport (reflects either health care worker to patient or patient to source of
None LOW
High
health care): No reasonable means of access Access reasonable by foot or systems accessible to all (rickshaw, boat, bus) Requires use of transport which is available but to which access would be limited either because of cost (car, baby taxi)
209
Very high
or physical constraints (need roads first) Requires sophisticated vehicle (ambulance, helicopter, speed boat)
Logistics:
Low Moderate
f-W
Very high
Little or no flow of consummable items required; little or no maintenance Requires periodic but regular flow of non-perishable items or episodic flow of items that are available from local market; minor maintenance requirements which can be attended by local personnel Requires episodic flow of non-perishable or regular periodic flow of perishable items (e.g. vaccine); maintenance requires skilled personnel but predictable intervals and/or who could be coming to service other equipment Requires regular and episodic flow of perishable items; maintenance requires frequent, non-predictable inputs from highly specialized personnel
187
HPE 00476
Guidelines for pragmatic assessment for health planning in developing countries Bonita Stantona and Annemarie Woutersb aDepartment of Pediatrics, School of Medicine, University of Maryland, Maryland, USA and bDepartment of International Health, School of Hygiene and Public Health, Johns Hopkins University, Baltimore, Maryland, USA Accepted 31 January 1992
Although the primary health care strategy implemented since the Alma Ata declaration of ‘health for all’ appears to have contributed to improvements in selected health outcomes, the current ad hoc approach to health assessment and planning has impeded more substantial gains. A comprehensive yet pragmatic framework for country-level health programmers is needed that would permit consideration of the multiple steps involved in policy formulation and implementation. In the present paper, drawing upon an epidemiologic model (Iterative Measurement Loop) and an economic model (Cost-Effectiveness Analysis), we present guidelines for a pragmatic assessment for health planning. A format is provided for the conduct of these tasks which is operational in nature, is specific to the target country (or relevant region), can simultaneously consider multiple interventions, and is comprehensible to persons without sophisticated medical and/or economic backgrounds. Such a format enables articulation and consideration of local concerns as well as national and global considerations. Cost-effectiveness;
Health policy formulation;
National Health Program
Introduction The. need for a direct approach to health planning
Completion of the first decade since the Alma Ata declaration of ‘health for Address for cowespondencez Professor Bon&a Stanton, M.D., Chief, Division of General Pediatrics, University of Matyland at Baltimore, 2nd moor, Wcbrn Health Center, 700 West Lombard Street, Baltimore, MD 21201-1091, USA.
188
all’ [l] has prompted evaluation of progress achieved by the current primary health care strategy [2-4]. Although this strategy appears to have contributed to improvements in selected health outcomes [5,6] most developing countries are still far from reaching the goals set in the Alma Ata declaration [7,8]. Debates regarding appropriate measures to achieve these goals have been extensive, but have generally not been practical in their orientation [9,10]. The practical problems facing country health programmers are substantial. First, as noted by the Commission on Health Research for Development, health sector planning requires the simultaneous addressing of multiple problems from multiple perspectives 141.Second, program formulation periods are both unremitting and generally of short duration, leaving little opportunity for long-range strategic planning. Third, data quantity and quality are uneven; planning is more developed where data is available and thus programs become data driven rather than conceptually-based. Fourth, donors generally have their own global priorities (usually disease oriented). These priorities, rather than comprehensive national assessments, determine their efforts. In total, these practical constraints have lead to the perpetuation of an ad hoc approach to problem identification and resolution, A comprehensive and yet pragmatic framework for country-level health programmers that would permit consideration of the multiple steps involved in policy formulation and implementation is necessary to advance beyond the ad hoc planning approach [l 11. Such a framework should direct national health policy formulation and implementation with a comprehensive perspective of the health sector. The framework should enable country programmers to identify general ‘trade-offs’ between, as opposed to precise estimates of, the cost and effects of various interventions. A first step towards the development of a framework for the pragmatic assessment for health planning (PAHP) is the articulation of relevant guidelines. To achieve a pragmatic and comprehensive approach to national health planning, such guidelines will need to incorporate five characteristics reflective of the practical constraints noted in the previous paragraph. (1) Interdirc@linary: Information regarding epidemiology, medical practice, economics, management and behavioral science must be obtained and reviewed collectively to ensure that the health plan is medically appropriate, effective, financially feasible, cost&bctive and culturally sensitive. This characteristic is essential for obtaining the comprehensive perspective of the health sector. (2) Expediant: Time constraints will be sign&ant in the planning process. Generally preparation of the annual plan must take place in a few months. The guidelines focuses on activities which can be implemented by a small team in 3 to 4 months. Selection of priority areas of analysis and investigation is necessary to make the guidelines operational. (3) OpportmCtic (utilize existinglseconaby data): Existing data sets supplemented by expert opinion should be maximally employed. Collection of primary data is usually not feasible in annual planning exercises. Rather, efforts should be spent on collecting all available secondary data (by detailed geopolitical subdivisions if possible) relevant to the proposed framework. Some parameters which are not available in existing data can be estimated using expert opinion (e.g. delphi techniques). Relevant data include (a) epidemiologic information; (b) descriptions of
189 medically appropriate and potentially available health interventions; (c) public and private health expenditures: (d) inventories of current health inf&tructure: manpower, facilities, equipment, management etc.; (e) studies of community effkacy of various medical interventions, if available; and (f) studies of cost-effectiveness of potentislly available medical interventions, (4) Non-fechnical: Sophisticated and/or specialized technical expertise may not always be available during the planning process. While team members should be familiar with the disciplines included in the approach, avoiding dependence on high-kvel specialized staff will make the guidelines more operational. (5) Cormtry-spec$c: The guidelines should facilitate identitkation of national and/or local health needs. The process should be simultaneously tokrant of multiple types and sources of data and promotive of extrapolation and/or generalization to ffl data voids as well as directing more systematic data gathering exercises for the future.
The use of existing models to serve as a basis for the guidelines Clearly the development of such guidelines is not a trivial undertaking. However, existing models, such as the Iterative Measurement Loop (IML) [12], could serve as a useful organizing framework if embellished and altered by conceptual and methodologic advances from multiple disciplines. The IML consists of six steps: (1) burden of illness; (2) etiology or causation; (3) community effectiveness; (4) efficiency; (5) synthesis and implementation; and (6) monitoring and reassessment. (See Chart 1 for further description of these steps.) The IML was designed to provide ‘a framework for assembling the specific subset of information that is most likely to help in reducing the burden of both morbidity (symptoms, physical, emotional social and functional impairment) and mortality for a disease. This is accomplished by subdividing the spectrum of health information inquiries into steps that constitute a logical progression - from quantifying the burden of illness to identifying its likely causes to validating interventions that prevent or ameliorate it and evaluating their efficiency’ [12]. The IML offers considerable insight into the assessment of burden of illness and causation (steps l-3). However, relatively little is said
slmmary
of the Iterative Loop Me&l’
(1) Defining the burden of illness: (2) Etiology of causation: (3) Community effectiveness:
Describes the burden of illness that exists in a population (e.g. percent mortality, morbidity) L%xriis direct and indirect causes of illness and death (e.g. biologic causes and cultural practices resulting in diseases) Describes impact of intervention in a specific
(4) EtIkkncy
&Ei the relative costs per health benefit achkved in relation to alternative interven-
Synthesis and impkmentation: (6) Monitoring and reassessment:
Integrates previous steps Assesses output and process of program
tiOllS (5)
*See ref. [12] for detaikd description of the model.
190
regarding economic evaluation, assessment of efficiency, equity, and synthesis and integration of the epidemiologic and economic data. By contrast, Cost-Effective Analysis/Cost Benefit Analysis (CEA/CBA) for program planning and management in international development [13] offers relatively greater insight into economic analysis but with less epidemiologic analysis. CEA analysis is most powerful when the decisions it informs involve choices of different techniques for achieving the same narrowly defined outcome. Cost-effectiveness estimates provide an ordering of interventions; however, epidemiologic and technical information is required to determine the scope of application in a given country. An extensive experience with use of CEA in program management has been recently summarized [13]. ‘- Performing an analysis of costs and benetits can be very helpful to decision makers because the process of analysis gives structure to the problem, allows an open consideration of all relevant effects of a decision, and forces the explicit treatment of key assumptions....[However], CEA/CBA exhibits too many methodological and other limitations, however, to justify relying solely on the results of formal CEA/CBA studies in making a decision. Thus, although CEA/ CBA is useful for assisting in many decisions, it should not be the sole or prime determinant of a decision.’
CEA consists of 4 basic steps: (1) goal setting (e.g. defining the health problem); (2) specifying health intervention alternatives; (3) predicting costs and effects and (4) program selection. (See Chart 2 for further description of these steps.) Health plans are ultimately determined by using the decision rule of CEA, programs selected yield the largest net benefit. In light of the serious resource constraints facing most health sectors in LDCs, policy makers must carefully examine the ‘tradeoffs’ between the costs and benefits of the integration of chart2 srmlmaryIJfMst-eff~velWss alnly7ds (1) Goal setting: The fast of the steps is to define the health nroblem to be addressed. Tvoical problems are excessive infant mortality, maternal mortality etc. It is in this step where the iML can strenghten CEA. Goal setting clearly depends on good epidemologic analysis (burden of iBness and causation). (2) Specifying ulternatives: Given the main health problems to be addressed health interventions must be specifiid. Again, IML can strengthen this aspect of CEA by providing clear information on available medical practices and community effectiveness of each potential intervention. (3) Predict~g costs and effects: The strength of CEA is in itemizing various cost comuonents of the project including investment and recurrent costs. This is corn&me&d with the-epidemiologic information on effectiveness. Not all project constraints and benefits can be quantified,
however, they are identitkd to the greatest extent possible. (4) Program selection: In principle, selection is based on which program offers the greatest impact per unit cost; however, in most situations, the final choice is restricted by one or more constraints. These may include specifii objective constraints (e.g. reduction of health indictors by a specific amount), resource constraints (e.g. limited number of prz-.kian, managers, building materials etc.), budget constraints (e.g. financial feasibility).
191 Table 1
(a) CEA = Community Effectveness Communitv Costa =-EfTicacy + Diagnostic + Health Provider (b) Community Effectiveness Accuracy Compliance * Patient + Coverage Compliance
various health interventions into a community. The value of all community resources used in the program are counted as costs regardless of who pays for them. The goal is to maxim&e effectiveness in the population as a whole rather than for any given individual. Community effectiveness depends on the conditional probability of five factors including efficacy of the intervention, diagnostic accuracy, health provider compliance, patient compliance and coverage [12].’ These concepts are depicted in Table 1. From this formulation, the interdisciplinary nature of health planning becomes very clear. Information regarding epidemiology, medical practice, economics, management and behavioral science must be obtained and reviewed collectively to ensure that the health plan is medically appropriate, effective, financially feasible, cost-effective and culturally sensitive. Such an analysis is potentially feasible in many developing countries. Both because Western health programs in these countries are new [ 141and planning in many developing countries tends to occur in a centralized fashion [ 151,there is considerable control over the introduction of technologies and the maintenance of those previously introduced. Thus, there is substantial homogeneity in the infrastructure nation- (or state) wide, and the costs of both the development and/or the operation of health systems are potentially accessible in many developing countries [16]. The emergence of guidelines for a pragmatic pladng
assessment
for health
In combining the IML and CEA to provide guidelines for a pragmatic assessment for health planning we envision a framework consisting of four major steps. A Epiakmiologic assessment: Cdkztion of key epidemiologic indicators of mortality and morbidity for detailed geographic subdivisions of the area for which a health plan is being designed. B Description of potentially available technologies i. Identification of potential technologies to address these diseaxs or conditions. ii. Determination of effi (iipact of intervention under ideal conditions). C Assessment of the costs and effectiveness of each potentMy available technology i. Compilation of costcffectiveness literature. ii. Adjustments to cost estimates. iii. Estimation of effectivemw in the community.
192 iv. Assessment of other constraints to program implementation. D EffEiency and equity: assessing ‘tradho~s’ between costs/constraints and el’ftiveness
For the remainder of this paper we shall delineate the purpose of each step, discuss the underlying principles of the step, identify potential useful methodologies and indicate future research needs. As a pZanning framework, PAHP does not seek to propose methodologies for implementation and evaluation per se (step 6 of the IML) but, in agreement with the IML, recognizes that analysis of such evaluation data will be essential to next subsequent rounds of planning activities and hence will be, in part, incorporated into the PAHP. Likewise, as a set of guidelines, PAHP does not attempt to undertake a CEA study but rather to delineate trade-offs between effects and costs in broader terms. Step A. Epidemiologic a-nt
The purpose of this step is to identify the relative contribution of diseases and conditions to morbidity and mortality amongst the differing target groups. Such a compilation of epidemiologically significant disease categories should direct the search for appropriate interventions, but, in and of itself, will not determine the interventions to be implemented. That decision-process (the focus of the subsequent steps) will be based on a thorough assessment of personnel requirements, complexity of logistics, facility requirements and monetary cost. Information needed for the conduct of these subsequent analyses should thus direct the data gathering exercise in this step. Such epidemiologic requirements are substantially addressed. in the first two steps of the IML (‘Burden of Illness’ and ‘Etiology’) but as the IML is intended for both country health programmers and researchers [12] certain points warrant discussion here. First, where available, data depicting the relative (as opposed to absolute) magnitude of the problem within the country is most useful for planning purposes.2 Likewise, health services utilization data is an inadequate data base for purposes of assessing the burden of illness for health planning.3 In most developing countries national household survey data (e.g. Demographic and Health Surveys) and/or more detailed ‘case’ studies are available until routine and/or ongoing sample systems have been designed and implemented. Analyses in which morbidity and mortality are combined into a single index [17] illustrate future directions and potentials for health plating.4 As methodologies are refined and national epidemiologic expertise is developed, such advances in data utilization will be optimal. However, in the interim, simpler analytic techniques, simple displays of morbidity/mortality rates/ percentages, and parallel but separate assessments of morbidity and mortality should not be viewed as inadequate. Reasonable estimates can be calculated for incidence and case-fatality rates for most of the important diseases in many countries by extrapolating from secondary information. Thus, for example,
193
use of the delphi technique or variations thereof, could be employed to obtain expert consensus for parameters not otherwise readily available. Sensitivity analysis should be used to identify instances where more empirical data is necessary to strengthen ‘best guesses’ [181. Typically a morbidity and mortality profile will depict disease categories. While occasional interventions may be directed against entire categories (i.e. oral rehydration therapy against watery diarrhea) generally interventions are targeted against specific causes of diseases or disease categories (i.e. vaccines against specific courses of diarrhea). Thus, national programmers must be aware of data regarding causation and where country specific data is not available, know that limited investigations of causality may be warranted (i.e. investigate the etiology of dysentery). However, national health programmers will generally not be involved in the conduct of basic causal research. In its current published form [12], the second step (‘Etiologic’) of the IML has a strong orientation towards basic causal research. Such a basic research orientation is neither necessary nor adequate for the practical issues in ‘causality’ being addressed by the PAHP. Bather what is needed is a methodology which indicates when etiologic confirmatory work is necessary, how extrapolation from existing data sets can provide a proxy for confirmatory studies, and/or what simplified procedures for primary data-gathering for causal confirmation are available. Examples of such directive guides include the WHO national diarrhea1 disease control program manuals [19]. Step B. Describing the available technologies I-
potential teclmologim to address the conditions. The importance of accurate identification of technologies (preventive and curative) potentially available to address the targeted health condition is obvious. Seemingly this step should be a simple technological task, requiring only a biomedically sophisticated consultant who is able to access the current literature. However, the acquisition of appropriate and comprehensive information will have profound implications for the successful conduct of the remaining tasks. For most curative and some preventive health interventions consideration must be given not only to the potential treatment intervention(s), but to the screening and diagnostic interventions as well. Beyond a description of the technologies themselves, operational information should be provided including: (1) personnel requirements (including total numbers and level of training of personnel necessary for the implementation of the diagnostic and treatment/ preventive aspects); (2) the physical infrastructure necessary to support all aspects of the intervention; and (3) the support or auxiliary equipment, supplies and efforts (including patient education) required to effect or implement the intervention. Without deliberate specification of these requirements for implementation of the intervention, a technological preoccupation is inevitable [20,21] with subsequent errant efficiency estimations (vide infia).
194
DeWmining efficacyof the intervention. Under ‘ideal’circumstances, does the intervention ‘work’? Were the task at hand the conduct or assessment of previously conducted efficacy trials of potential interventions, arguably this task could be subsumed in the review of existing technologies (the first task). That is, to the extent that this task is technical with specifically delineated procedures, then it may be performed by an outside ‘consultant’ or group for similar to the assessment of existing the country-level programmer, technologies. However, meaningful assessment of efficacy requires in-depth knowledge of the epidemiology of the potential host country or state. The importance of local determination of casualty (etiology) discussed in the previous section becomes apparent here. While some interventions may impact on several or all of the diseases within the clinical syndrome (as, for example, oral rehydration solution for watery diarrhea), for others the intervention will be highly specific (e.g. the current parenteral cholera vaccine). Therefore, an estimate of efficacy of an intervention on morbidity or mortality in the national setting must be based on an assessment of the contribution towards mortality or morbidity of each disease against which the intervention is efficacious. For example, regardless of the efficacy of a cholera vaccine and overall prevalence of diarrhea, the vaccine will not lower morbidity or mortality if none of the diarrhea is caused by vibrio cholera. Thus, for any given disease or disease cluster there are likely to be several interventions directed at differing causes (or stages) of the disease process with varying degrees of efficacy in prevention/ therapy. There are a multitude of epidemiological approaches for estimating the efficacy of health interventions in improving health outcomes, but they vary in reliability, generalixability, costs and time factors. A recent summary of this issue notes that ‘BeforeAfter Comparisons’ and ‘Non-Randomized Treated and Non-Treated Comparisons’ are frequently misused and generally produce biased conclusions [18]. Stronger study designs include Case-Control and Randomized Field Trials; however, they must be conducted with methodological rigor to produce reliable results. Syntl~esis of information regarding ‘available tedmologies’.
To further the quest for guidelines which are practical, a consolidation of the necessary information regarding existing technologies into a simplified format would be desireable. As a example, in Graph 1 we present a synthesis of the information necessary regarding ‘available technologies’ for conduct of the subsequent exercises for one illustrative disease, tetanus. The graph is deliberately general in nature, focusing on the level of preventive, curative and/or rehabilitative input required for differing outcomes, rather than the precise technology. This graphic display enables an informed decision as to what magnitude of decrease in morbidity and/or, mortality might be expected from a given intervention and what type of personnel/facility and infrastructure would be necessary to implement this intervention.
195
Vaccine
Chemopfophylalais
Curative Treatment
Community Level - No effective intervention See Appcndk Tsbk 2
‘Key’ to Graphs 1 and 2 for dcfinitions/cxplanations
of “input’and ‘eftkacy’.
Potential preventive interventions have been roughly classified according to whether they are ‘community’ (require cooperation/organization at a national or community level, i.e. legislation, roads), or for family/individual interventions, according to whether they are a vaccine, chemoprophylaxis or behavioral. (Although it is axiomatic that any intervention involving performance of individuals should have a behavioral component, in this context ‘behavioral’ interventions are limited to those in which the entire intervention is education or other inducements for behavioral change.) Potential impact of curative treatment of patients presenting with tetanus is depicted in the final box. Inputs required may be grossly characterized as follows: personnel according to level of training by general category (i.e.- thoracic surgeon
196
versus pediatrician versus community health worker); description of the facilities according to basic functional aspects (i.e. no water on premises versus tubewell water versus piped-in-house water); level of co-existing technologies and supplies (i.e. simple microscopy versus bacteriologic culturing versus immunologic diagnostic capability); and, patient and/or community education efforts. (See Appendix: ‘Key’ to Graphs 1 and 2 for full description and definition of categories). A compilation of such charts for each disease category of epidemiologic significance would provide the necessary foundation for the subsequent exercise of matching country needs and potential intervention technologies with the existing infrastructure. Step C. Asses&g technology
the costs and effectiveness of each potentially
available
An important feature of cost-effectiveness is that comparisons are made between the full set of alternative interventions to deal with a given health problem. The objective of steps A and B has been to carefully identify the full range of options to be considered in resource allocation decisions. In order to assess the costs and benefits of each potentially available technology, four exercises are required: (1) compilation of existing cost-effectiveness/costbenefit literature; (2) adjustments to cost estimates; (3) estimation of community effectiveness; and (4) assessment of other constraints to program implementation. Compilation of cost-effectivewss literature. Ideally one would want to use cost-benefit analyses which not only assess costs but incorporate valuation of health outcomes; however, such studies are rarely available and difficult to undertake. By contrast, cost-effectiveness analyses are more generally available. CEA analysis is a powerful tool for choices between different techniques for achieving the same narrowly defined goal, but is limited in its ability to compare programs with different health outcomes. Nevertheless, a compilation of cost-effectiveness literature will provide general information on known ‘trade-offs’ between the costs and effects of various interventions. Great care should be taken in applying cost-effectiveness estimates to different projects because several considerations will affect interpretation [ 181. Thus, the mathematical principle for m aximization states that marginal costs should equal marginal benefits. CEA analyses should be conducted using marginal costs and marginal effects; however, estimates of averages are typically more available. In some situations, average and marginal estimates may be quite different (e.g. health care delivery at the periphery). This may substantially alter CEA calculations. Moreover, many costs and effects of programs may occur with some time lags. These timing effects may vary across countries and may or may not be dealt with in CEA estimates. Elements of both costs and effects may require significant adjustments. Key
197
aspects which may vary by project circumstances are highlighted below. Adjustments to cost estimates. Cost items: The basic principle of CEA for health sector planning requires that an item is a cost of the project if it would not have been incurred and used up otherwise, unless it is a preexisting cost at the time the project decision is made. A comprehensive itemization of all cost elements should be made to check control for omissions or overcounting. Sunk costs: In many developing countries, the health infrastructure and system has been developed over a period of one or two decades [ 143and have involved substantial investments of time, money, management and training. That is, what systems do exist have generally not resulted from trivial investments and thus should not be regarded as readily expendable or even alterable. Interventions will not be introduced in a void and major alterations in an existing infrastructure could not be accomplished with ease. The existing health infrastmcture investment is a ‘sunk cost’ for those new interventions which could make use of the existing system. In CEA, sunk costs are not included because they would have been incurred even if the new intervention were not implemented. For example, if a potential program to be implemented is a tuberculosis control program, prior initial investment in microbiologic and radiologic facilities are ‘sunk costs’ and not added to the cost estimates of the new option. In countries where significant previous investments exist, adjustment of sunk costs is likely to substantially alter CEA estimates. In Graph 2, existing and needed resources are compared qualitatively to reflect primarily the degree of ‘sunk costs’ and to provide some indication of ‘start-up costs’.5 (Start-up costs are described in more detail in the section on budget constraints.) Needed inputs (N) are juxtaposed against existing Q inputs. Categories of potential preventive interventions are defined as for Graph 1 (see text page 195 and Appendix: ‘Key’). Potential treatment interventions are then classified according to issues in triaging and therapeutic outcomes. In the column labelled ‘screening’ we contemplate the volume of persons presenting with the disease (or a disease within the differential diagnosis), the activities which would have to be undertaken to triage such people, and the level of personnel and facility required for the triaging exercise. ‘Majority’ refers to the level of drugs, equipment and personnel training to cure or adequately treat over half of the patients with the targeted disease. ‘Minority’ addresses the same issues but for the remainder of patients not able to be accommodated by the ‘majority’ approach. ‘Stragglers’ refers to that small (arbitrarily defined as less than 10%) of patients whose needs cannot be addressed by either of the first two approaches. This graphic display enables quick and easy visualization of the ‘fit’ of the intervention within the system. The Q inputs can essentially be viewed as sunk costs which should not be included in the cost-effectiveness estimates. For each type of input, if (N) is greater than (E), additional investment is required by the amount (NE) some of which may be one-time start up costs. The larger the gap, generally the
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201
worse the cost-effectiveness of the project. If(N) is less than or equal to (E), no additional investment in that input is required and the project is more costeffective under the given country circumstance~.~ Joint costs: Frequently a potential intervention might be able to share some of the inputs of another project. Many inputs used in the health sector contribute simultaneously to the production of several distinctly different kinds of outputs. For example, the radiologic unit could service both the TB program and a trauma unit. Joint cost allocation adjustments would be required to allocate the costs to the appropriate outputs; the full cost of an input would not be attributed to a single output. Scale of activity: It should also be recognized that cost-effectiveness estimates may be affected by the scale of activity. Service delivery systems may experience increasing, decreasing or constant returns depending on the scale of activity. For example, community health worker programs have been found to exhibit decreasing returns to scale [23]; thus, small programs will have more favorable cost-effectiveness estimates than large national programs. CEA generally produces an estimate of a single point on the cost function. Efficticy: Ultimately, CEA estimates are used to design the most efficient health care plan. However, because of the multitude of factors which affect CEA results, one must be extremely carefully in interpreting differences in CEA estimates as differences in efficiency. Factors such as timing, scale, marginal versus average analysis will influence results. Also, if demand patterns change, programs will fluctuate in cost-effectiveness if they exhibit non-constant returns to scale. Estimation of effectiveness in the ‘co~~~~unity’. Assessment of the interaction between the exidng health infrastructure and the new intervention is an essential next step. Obviously studies which have been conducted in the actual locale under ‘field’circumstances are ideal for such an assessment. However, as generally only a few effectiveness studies for a given intervention will be conducted, such information will not usually be available. Modifications to estimate community effectiveness, as defined earlier, will be required. Equation B (Table 1) graphically illustrates the importance of simultaneous entertainment of multiple considerations in estimating effectiveness. Depiction of the concept as one of multiplication demonstrates that to be effective all five variables are important because a ‘zero’ in any cell would result in an ineffective intervention regardless of performance of the other four variables. Unfortunately, the amount of information required for completion of the .five main variables, each with several essential sub-components, renders it unlikely that the formula could be precisely calculated for most countries. However, building upon the basic concept of such a formula, effectiveness studies conducted in other settings in which comparability of at least some of the key variables is known to exist could be utilized. Clearly methodologies must be established for extrapolation from such studies. In the interim,
202 of eomparlson of possiblyrdevant dlara~rlslica between targeteommu&y ad eomlnanitiea (eommmity A and B) whereeftieaey studieswereprehncdy conducted
Fmmple
Community characteristics
Study communities Target community
A
B
10% 40% 1:200
3% 15% 1:looO
40% annual
15% dailY integrated
Baseline
Percent of population vaccinated at baseline 3% Percent population with radio access 20% Ratio of community health workers/population I:900 Percent of population within 5 miles of sites offering vaccine 2; Delivery strategy integrated
-paign vertical
l’bo years ajter vaccination program initiated
Percent of targeted population (infants) vaccinated: Percent reduction in infant mortality: Percent reduction in disease-specific mortality in infants:
35% 15%
60%
30%
50%
35%
however, we may suggest that delineation of the relevant variables juxtaposed against those that were equivalent to the national setting from several studies should begin to enable relatively accurate estimations of actual effectiveness. Thus, for example, let us assume that a vaccination program against tetanus is being contemplated for a hypothetical ‘target country’. Much is known regarding potentially relevant health service characteristics of this country, but no efficacy or effectiveness trial of the vaccine has been conducted in this region. However, in the evaluation of efficacy studies of the vaccine in other settings many of these potentially relevant community characteristics have been described. A simple chart contrasting these characteristics (such as that displayed in Table 2) might enable some (albeit crude) assessment of which study site was more similar to the current target community. This approach would provide a more accurate estimation of anticipated benefit from the proposed vaccine campaign than by only drawing inference from a range of effectiveness values without reference to community comparability. As noted earlier, employment of the delphi technique among experts to provide ‘best guesses’ for missing values is an alternative or complimentary approach. Two other concerns pertaining to effectiveness are worth noting. First, effects (both positive and negative) of a program may be much wider that included in the CEA analysis. Second, when health outcomes are diverse some sort of valuation of each outcome is required before an overall assessment can be made. This is especially true for health outcomes which affect different age groups and which take place over varying time periods. Weighting health outcomes by social discount factors and a productivity index is sometimes used. This is likely to be beyond the scope of a pragmatic planning exercise;
203
nevertheless, the importance of issues should be recognized, especially in crosscultural settings. Assessment of other amstdnts to program implemmtation. Several different types of constraints, both monetary and non-monetary can operate to impede program implementation. Such constraints are rarely immutable and thus require periodic re-examination. Such constraints have been variously categorized [131. Specific - objective constraints: This constraint arises if an immutable decision has been made that a certain specified quantitative goal must be reached that would preclude other uses of resources (i.e. 700 community health workers must receive a 2-week training course; alternative training uses might then be pre-emptied). iuutual - exclusivity constraints: Such a constraint can arise if, for technological reasons, only one alternative is possible or if components of separate alternatives are interdependent (i.e. an outreach, community-based EPI program targeting under-five versus a facility based ‘all-comers’ approach). Budgetary constraints: Affordability will undermine the effectiveness of the potential intervention; it is a necessary condition of an efficient health plan. The affordability of the initial investment program is often a substantial problem. One time start-up costs (not included in CEA) can be prohibitive. However, another more frequent dilemma is to determine the recurrent cost portion of a program which is a consequence of the initial investment and to assess its financial feasibility. A quick way to assess the recurrent cost implications of an investment is to multiply a previously estimated r-coefficient (the ratio between a project’s annual recurrent costs and its total investment cost) by the total investment costs. The r-coefficients vary tremendously by project (e.g. 20% for hospitals to 50% for primary health care services in Malawi) [22]. Resource constraints: Most CEA analyses use market prices to estimate costs; financial rather than economic costs are reflected. To reflect true scarcity of resources in the economy, economists use shadow pricing. In the health sector, financial and economic costs differ substantially with respect to labor and foreign exchange. For example, managerial resources are usually scarce. Although shadow prices are not likely to be readily available, planners should take note of particularly scarce resources to adjust previous estimates of costeffectiveness to their own circumstances. Capacity for behavioral change: This may be a particularly important ‘resource constraint’. Often changes in behaviors, whether of the health personnel or of the community members, have required years of multiple approaches to effect; systems which either disrupt these positive changes or assume new change can occur without substantial investments will not accurately portray the match between the new intervention and the existing infrastructure.
204
Legal constraints andpolitical constraints: These may impact on implementation although the degree to which these should be specifically and proactively considered by health programmers will vary by circumstance and locale. Step D. Efficiency and equity: asses&g and effectiveness
‘trade-offs’ between costs/constraints
Following the basic principles of CEA we are attempting to compare, in approximate terms, the trade offs between costs and effectiveness of various interventions. Efftciency estimates must be applied at both a ‘program’ level (i.e. what intervention will ‘best’ lower diarrhea1 morbidity/mortality) and, for national health planning, at a sector level (what combination of health programs will ‘best’ lower overall morbidity (mortality). PAHP provides guidelines for assessing ‘tradeoffs’ in a logical and comprehensive fashion. First, a subsample of medical intervention is considered - only those which are appropriate for the identified patterns of mortality and morbidity (summary of steps A and B). Second, rough estimates of CEA for the subsample of medical interventions are presented based on previous literature. Further assessment of these CEA estimates is made by considering (in a qualitative manner) how costs and effectiveness may need to be adjusted with country-specific circumstances. Additionally, the financial feasibility and presence of other non-monetary constraints of the interventions are considered. Finally, there must be consideration of the distribution of costs and benefits among the population. Clearly no simple formula will be generated to provide a definitive answer to health programming needs. Rather, the purpose of PAHP is to elucidate a broadly based discussion of all possible tradeoffs. By exclusion of options at each step, the programmer is faced with a more manageable number of options for which the expected costs and effectiveness as well as the constraints and unmeasurables are articulated. Such a process permits a logical progression from identification of national (as opposed to international) health problems through consideration of options how best to address these problems. Summary We have delineated guidelines for assessment for health planning and where possible have offered pragmatic suggestion on how to conduct the various steps. These guidelines offer an approach for health planning which is simultaneously: (1) operational in orientation; (2) draws upon multidisciplinary perspectives; (3) tailored for the specific country (or state) for which the interventions are being considered; (4) capable of entertaining the demands of multiple interventions; and (5) comprehensible by country programmers who will have variable backgrounds in health and economics.
205
Acknowledgements Many of the ideas expressed in this paper originated from discussions and collaboration with William Reinke Ph.D., Robert Black, M.D., MPH, John Clemens, M.D. and Christopher Chamberlain, Ph.D. Thoughtful comments on an earlier draft of the manuscript were made by Ann Marie Gadomski, M.D., MPH. Manuscript preparation was facilitated by Jeanette Roberts and Juanita Morris.
References 1 WHO, Primary Health Care, Presented at ‘The International Conference on Primary Health Care’ Ahna Ata, USSR, September 1978. 2 Chen, L.C., Primary health care in developing countries: overcoming operational, technical and social barriers, The Lancet, 2 (1986) 12-1264. 3 WHO, From Ahna Ata to the year 2000~ a mid-point perspective, Presented at the World Health Organization Meeting, Riga, USSR, March 1988. 4 Commission on Health Research for Development, Health Research: Essential Lii to Equity in Development, Oxford University Press, New York, 1990. 5 United Nations Children Fund (IJbJJCEF), The State of the World’s Children, Oxford University Press, New York, 1989. 6 Gwatkin, D.R., Wilcox, J.R. and Wray, J.D., Can health and nutrition interventions make a difference? Overseas Development Council, Washington, DC., 1980. 7 Wolff&s, I., Limitations of the primary health care model, A case study from Bangladesh, Tropical Geographical Medicine, 40 (1988) 45-51. 8 Rosentield, A. and Maine, D., Maternal mortality - a neglected tragedy?, The Lancet, 2 (1985) 83-85. 9 Editorial, The debate on selective or comprehensive primary health care, Social Science Medicine, 26 (1988) 877-878. 10 Wisner, B., GGBI versus PHC7 Some changes of selective primary health care, Social Science Medicine, 26 (1988) 963-969. 11 Stanton, B.F., Clemens, J. and Black, R.E., Addressing National and Regional Health Needs: A Framework for Health Planning, International Journal of Health Plan Management (in press). 12 Bennett, K.J., Tugwell, P., Sackett, D. and Haynes, B., Relative risks, bendits, and costs of intervention. In R.S. Warren and A.A.F. Mahmond @da), Tropical and Geographic Medicine, McGraw Hill, 1990,pp. 205-228. 13 Siragelden. I., Salkever, D. and Gsbom, R., Evaluating Population Programs, Jntemational Experience with Cost-Effectiveness Analysis and Cost-Benefit Analysis, The Johns Hopkins University, Croom Helm Ltd., St. Martins Press, New York, 1983, pp. I-103. 14 Smith, D.L. and Bruant, J.H., Building the infrastructure for primary health care: an overview of vertical and intregrated approaches, Social Science Medicine, 26 (1988) 909-917. 15 Solter, S.L., Hasibuan, A.A. and Yusuf, B., An epidemiological approach to health planning and problem-solving in lndonesion, Health Policy and Planning, 1 (1986) 99-108. 16 Stanton, B. and Clemens, J., User fees for health care in developing countries: A case study of Bangladesh, Social Science Medicine, 29 (1989) 1199-1205. 17 Ghana Health Assessment Project Team, A quantitative method for assessing the health impact of different diseases in less developed countries, International Journal of Epidemiology, 10 (1981) 73-80. 18 Morrow, R.H., Dunlop, D.W. and Rosentield, P., Cost-effectiveness analysis: an essential tool for health-related decision making in developing countries (submitted for publication).
206 19 WHO, Estimating
20 21 22
23 24
Costs for Cost-Etfectiveness Analysis - Guidelines for Managers of Diarrhoeal Disease Control Programmw, Document CDD/SER/88.3,1988. Bonair, A., Rosenfield, P. and Tengvald, IL, Medicaltechnologies in developing countries: issues of technology development, Transfer, Diffusion and Use, 28 (1989) 769-781. Institute of Medicine (IOM), Technological innovation: comparing development of drugs, Devices and Procedures in Medicine, National Academy Press, Washington, DC, 1989. Over, A.M., Economic and Financial Analysis of the Health Sector in Developing Countries: A Training Manual, The World Bank Educational Development Institute, Washington D.C., (1991). Berman, P. et al,, Community-based health workers: Head start or false start towards health for all? Social Science Medicine, 25 (1987) 443459. Essential Drugs Project, Bangladesh (EDP), Progress Reports No. 1-5; Essential Drugs Project Bangladesh, Ju+September, 1987.
Endnotes 1 CEA does not usually assess the distributional impacts of the health programs in question. It is possible, however, to incorporate social weighing in the valuation of inputs and outcomes of the project. Thus, for example, social weighing typically enhances the attractiveness of projects that redistribute income to the poor. While on a practical level such social weighing schemes are not available, the assessment can (and arguably should) take note of distributional goals. A review of methods for examinln g equity are beyond the scope of this paper. 2 By contrast, absolute disease/mortality levels may be more useful for monitoring and evaluation and for intluencing donor and/or sectional resource allocation. 3 Seeking of health care is based not only on acruul illness, but on a multiplicity of other factors including perceived ilhress, perceived vulnerability, resource constraints, perceived effmacy of the health resources, etc. Thus, such data may be useful in subsequent impact evaluation of the intervention, but community-based data is most useful for assessing real burden. 4 This index recognizes that the goal of all health care expenditure is to improve health. The amount of health a society has is measured by the number of healthy days people could enjoy in the absence of disease. By adding together the healthy life days lost by different population subgroups from all diseases, it is possrble to compute the total disease burden of a society. 5 Although beyond the scope of this paper to discuss in detail, for the interested reader the existing health inputs summarized in Table 2 are derived from an analysis of the health infrastructure in Bangladesh [ 16,241. 6 In fact, if(N) is less than (E), additional investment in that input is not necessary, but the input (i.e. personnel, facility) is actually ‘more’than what is required (i.e. an abundance of physicians are available for tasks that could be performed by community health workers).
Appendix Key to Graphs 1 and 2
Impact:
Anticipated reduction in disease mortality and/or morbidity rate of the targeted population Low < 10% Moderate lo-20% 20-30% =gh Very high > 30%
207 Direct
Factors that are required for implementation se, not those related to support services
of the intervention per
Personnel (operations): LOW
Moderate High Very high
Minimal training beyond task specific skills; estimated training time - 2 weeks to 2 months (e.g. Health Assistant, Female Welfare Assistant in Bangladesh) Full curriculum in basic primary health care; no speciality training (e.g. Medical Assistant, CHW in Bangladesh) Higher medical training enabling positioning of full differential diagnosis and treatment options; basic technical skills (e.g. medical officer in Bangladesh) Subspecialty medical training with highly specific diagnostic treatment and/or surgical skills (e.g. obstetrical specialist/ consultant in Bangladesh)
Nursing: Qualitative assessment of time required for direct patient care by
professional (e.g. beyond what a family member could provide) No nursing care required by professionals None Minimal time requirement, possibly administration of drug Low Infrequent, regular nursing demand Moderate Frequent, regular nursing demand High Very intensive demand, nearly on&o-one nurse to patient Very high Technology: LOW
Moderate High Very high
Suppoti
Level of underlying support factors required for implementation the intervention
Facility: None
Low Moderate
High
Simple equipment, locally available (e.g. brochures, common antibiotics) Basic equipment potentially available in country (e.g. otoscope and microscope, basic surgical tools, etc.) Relatively sophisticated equipment not regularly produced in country although theoretically could be (e.g. incubators) Highly specialized equipment not produced in country (e.g. respirators, CT scans) of
Field work only Static facility without hospital beds (e.g. Union Health and Welfare Center, rural dispensary in Bangladesh) Clinic/hospital with overnight beds, dependable source of water, electricity and basic operating theatre (e.g. Upazilla Health Complex in Bangladesh) Hospital with overnight beds, functional OR, radiology, blood
208
Very high
bank, and microbiology (e.g. District Hospital in Bangladesh) Highly specialized support including modem intensive care units, etc.
Personnel (supervision and/or support):
Low Moderate High
Very high
Minimal supervisory/support requirement (e.g. surgeon requires little supervision) Supervisory requirements generally low although at times (especially beginning of project) may be higher Constant supervision will be necessary although generally could be done through flow charts 2 or more supervisory levels may be necessary Constant supervision necessary with frequent site/field visitation; multiple supervisory levels may be required
Technology:
Low Moderate
High Very high
Basic equipment generally available at field level facilities (e.g. vaccine carrier, salter scale) or community (posters, leaflets) Equipment, blood pressure cuffs, ophthalmoscopes, microscopes, refrigerators, surgical equipment for D&C (e.g. see DDS kit contents for UHFWC’s in Bangladesh) or, in community (e.g. radios or tubewells) Specialized equipment including cardiac monitors, anesthesia devices, basic surgical equipment beyond simple obstetrical procedures or in community (e.g. televisions or in house water) Highly specialized equipment including respirators, pulse oximeters, highly specialized surgical equipment or for community (VCR’s, home PC’s or sophisticated mobile emergency centers)
Nursing: Qualitative assessment of time required for direct patient care by
professional (e.g. beyond what a family member could provide) None No nursing care required by professionals Low Minimal time requirement, possibly administration of drug Moderate Infrequent, regular nursing demand Frequent, regular nursing demand High Very high Very intensive demand, nearly one-to-one nurse to patient Transport (reflects either health care worker to patient or patient to source of
None LOW
High
health care): No reasonable means of access Access reasonable by foot or systems accessible to all (rickshaw, boat, bus) Requires use of transport which is available but to which access would be limited either because of cost (car, baby taxi)
209
Very high
or physical constraints (need roads first) Requires sophisticated vehicle (ambulance, helicopter, speed boat)
Logistics:
Low Moderate
f-W
Very high
Little or no flow of consummable items required; little or no maintenance Requires periodic but regular flow of non-perishable items or episodic flow of items that are available from local market; minor maintenance requirements which can be attended by local personnel Requires episodic flow of non-perishable or regular periodic flow of perishable items (e.g. vaccine); maintenance requires skilled personnel but predictable intervals and/or who could be coming to service other equipment Requires regular and episodic flow of perishable items; maintenance requires frequent, non-predictable inputs from highly specialized personnel