Systems Analysis and Mental Health Services Bellenden R. Hutcheson, M.D. Elliott A. Krause, Ph.D.
ABSTRACT: Systems analysis, a method originating in engineering and planning areas, evaluates the costs and consequences of alternative approaches to a goal given a known set of constraints. Mental health services are badly in need of a more rational approach to planning, and this article shows how specific systems analysis techniques can be used to describe a mental health system and, at the same time, to evaluate consequences and costs of changing the system in different ways. The limitations of the approach are also considered. The authors' main aim is a general introduction to the systems approach for mental health practitioners. SYSTEMS ANALYSIS: A DEFINITION Out of research and program planning needs in science and social service fields in the last 2o years, and originating in the operations research approaches developed in the forties, a new, hybrid profession has come into being: "systems analysis." The activities of the systems analyst, and the research methods at his command, will probably be of major importance to the mental health field in years to come. From the viewpoint of the engineer, systems engineering is an outgrowth of specific research, design, and testing techniques for solving management and decision problems which the heads of large organizations have been encountering. These techniques grew out of the massive logistics and coordination problems of World War II. The community applications of the approach are a more recent development. Lessing (5968) notes that: On a more immediately practical plane, systems engineering offers a new way to look individual large urban problems from all sides, weigh all possible alternative solutions with their costs and predictable consequences, and then get on with an optimum solution by the shortest possibleroute (p. 256). at
From the viewpoint of the sociologist, especially those in the tradition of Dr. Hutcheson is Assistant Commissioner for Children's Services, Massachusetts Department of Mental Health, 15 Ashburton Place, Boston, Mass. o2Io8; and Assistant Clinical Professor of Psychiatry, Laboratory of Community Psychiatry, Harvard Medical School. Dr. Krause is Assistant Professor of Sociology, Northeastern University, and Consultant to the Massachusetts Department of Mental Health. The authors wish to thank Mr. William Floyd, Senior Scientist, Spear, Inc., for his assistance with the matrix analysis. Community Mental Health Journal, Vol. 5 (1), 1969
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Community Mental Health Journal
Talcott Parsons (~952), the social system has always been a dominant theoretical concept, and the research problem of greatest importance has been to elucidate the dynamic interrelationships of different subsystems which make up the overall social system. For example, Hollingshead and Redlich (x958) show that the social class distinctions of American society are related to the prevalence of mental illness. In general, psychiatrists such as Caplan (~965) and sociologists such as Parsons concern themselves with the interpenetration of the social and psychological worlds of the individual. Writers such as Smelser (z963) have been interested in the economic system in its relationship to the social interaction system. Through the use of systems analysis approaches, it may be more possible to interrelate the data of psychology, sociology, and economics. Then the human community system and its subsystems can be inspected at the small group, community, and national level. The systems approach, as defined by one of its practitioners, "is an orderly way of looking at all the angles of a complex problem, to determine the best operating solution for a given set of constraints" (RCA Systems Development, z968). The systems analysis approach, as it is presently evolving, has several interrelated goals. These are: 9 . To decide on a mission or goal of the program which is to be subjected to a systems analysis. 2. To describe the boundaries of the system and the subsystems which make it up. 3- To ascertain the ways in which the system changes and the factors which produce the change. 4. To make a model mathematical or graphic in most cases which considers all elements of the systems both as static and as functioning in time. 5. To use the model to produce theoretical changes of different types, to see what possible outcomes would result from each set of changes. Otherwise phrased, to simulate a set of changes using the model. 6. To pick out the most desirable outcome, given previously agreed-upon goals, and then to do in reality the activities described in the model, which would reach this goal. 7. To cut costs, clarify problems, and avoid wasted time, by doing this experimental manipulation of analytical models using time and cost variables as part of the design, and thus to consider for a given region the most practical and efficient course to follow in achieving the desired end, before one actually intervenes in the situation. For the field of mental health service, the major goal or mission of the systems analysis approach would be to promote the mental health of a given local region, by isolating relevant factors which can be manipulated to favorably change the environment, human and nonhuman. In the mental health service field, therefore, systems analysis may bring ecology--the study of
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the interaction of people and their environment--into the area of ethology, the biological study of social behavior. The entire field of mental health, and especially the area of community mental health program planning, is in great need of a comprehensive approach such as the above, in the opinion of the authors. Important program decisions are always being made, and many more will be made in the future. Whether they are made while considering all the relevant factors---inside and outside of the traditional "mental health" orbit--may depend on whether systems analysis techniques are used as part of the planning and decision-making process. One technique of central importance in systems analysis is "input-output" or "inter-industry" analysis; it is a technique which could be of great importance to all health and welfare planning in the future. It is to this approach that we now turn. INPUT-OUTPUT ANALYSIS: A SYSTEMS ANALYSIS METHOD Since the time of Herbert Spencer, sociologists and government officials have been concerned with the problem of grasping significant data to illuminate the dimensions and forces which make up the social order, and which indicate directions of social change. Spencer (:1954) noted that social statistics could be used as follows: These facts, given with as much brevity as consistent with clearness and accuracy, should be so grouped and arranged that they may be comprehended in their ensemble, and contemplated as mutually dependent parts of one great whole. The aim should be so to present them that men may readily trace the consensus subsisting among them, with the view of learning what social phenomena coexistwith what others (p. V). In spite of the fact that Spencer was one of the first sociologists, the recent developments in the integration of this kind of data came not directly from this group but from the economists. After Keynes (5936) began the revolution in economics, government and social science realized the practical utility for planning, of regional and national economic data. In fact, the particular economic research method which was the inspiration behind the method discussed here grew out of an attempt to deliberately integrate general theory, new methods of data analysis, and the concrete data of everyday economic life.
Systems Analysis in Economics The discussion of systems analysis in economics will be limited to the pioneering and basic work of Wassily Leontief, as set out in his classic work, Input-Output Economics (596I). Leontief ranges the types of industry putting things into the overall society, in terms of sectors of the society producing goods, down one side of a master table, and the different types of sectors of the society which consume these produced items, across the top of the master table. Each intersection of a row and a column--each cell in the master table--represents the transaction between one sector as
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producer and the other as buyer of what is produced by this sector. Thus the alternative name of his analytical method: "inter-industry" analysis. This kind of organization of data makes it possible to see to what degree the output of each sector or type of industry is consumed by which other sectors (including each one as a consumer of its own output). In this way he can illustrate with a matrix of concrete interacting groups that "economic processes are interrelated in a systematic manner, a manner which can be thought of as a network of exchanges or transactions between all the sectors." He illustrates for the economic sphere the classical statement that all social processes are interrelated. The advantages of his input-output method are that they show how and where and to what extent, in the economic subsystem, events are interrelated: The effect of an event at any one point is transmitted to the rest of the economy step by step via the chain of transactions that links the whole system together (Leontief, p. 24). His next step is to create a mathematical model of the system: A table of ratios for the entire economy gives us, in as much detail as we require, a quantitatively determined picture of the internal structure of the system. This makes it possible to calculate in detail the consequences that result from the introduction into the system of changes suggested by the theoretical or practical problem at hand (p. 24). At this point let us present a simplified and imaginary table of Leontief's type and inspect it closely, as to what it means and what it does. Each number in each cell represents the dollar value (in millions) of all economic transactions between a given sector as producer (in the column on the left) and another given sector as consumer (those across the top of the table). Each sector is put in both as a producer and a consumer, as this is the way it is in any real society. Remembering that each cell measures the value of all transactions of the two interacting sectors, the zS** cell indicates that the goods and services sector sold the heavy industry sector $2 5 million worth of materials and labor (Table 2). TABLE I Master Input-Output Table for "Transylvania" Producer Sectors Goods and services
Consumer Sectors Heavy Agriculture industry
Goods and services Agriculture Heavy industry
25 3~ 5
~5 3o ~o
~5"* Io 5~
Total
5~
55
75
Total
45 7~ 65 580
Here, as in most real tables made up in input-output economics, the numbers represent the dollar value of the transactions made between different sec-
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tors of the economy. They are an index of the amount of activity involved in the interchange between the two sectors. Since money is directly quantifiable, it is possible here, for example, to go "across a row" for a given sector of the economy and see, proportionally, how much activity the sector has with all other sectors and with itself, as a buyer of what it produces. Let us go back to the table and look at the row labelled "Heavy industry." It is possible by this method to determine the proportional degree of activity which heavy industry has with (a) goods and services sector, (b) agriculture sector, and (c) its own sector as a consumer of what it produces. Here, going across the heavy industry row, we note that the main consumer of the output is its own sector (5o), with only one-tenth as much interchange going on with the goods and services sector (5), and a fifth as much as with agriculture (~o). Note that the other sectors distribute their product differently in terms of the proportion of other sectors which consume them. The overall chart here states all major interchanges between all major sectors in the economy as (a) producers and (b) consumers. The numbers in the cells measure the inter-industry activity or flow between each sector and all other sectors. Note that the advantage of Leontief's "input-output" or "inter-industry" tables is that one can see at a glance all the complex relationships involving who is giving how much of what to whom, for each of the entries down the side of his table, and across the top. The "internal structure of the economy" he speaks of is made up of the actual networks of interchange that go to make up the functioning system. These networks are represented mathematically in his tables and equations. The Social System as a Network of Interchanges The idea of the social significance of the exchange of things, people, words, and ideas was recognized by social anthropologists and early sociologists such as Spencer. In his study of primitive economics, the anthropologist Marcel Mauss (i954) stated that this model of reciprocal interchange or bartering of values, communications, gifts, and people would do quite well as an analytical model for the entire social system, not just in the area of economics. Making use of Mauss' insight, and recent attempts to generalize to all social processes using these new analysis models, we are interested here in making an ,inter-industry" systems analysis of a small metropolitan region, in which problems of mental illness and other forms of defined deviance from social norms will be plugged into an overall matrix which will consider general inputs to and outputs of the social system. This matrix should consider individuals, families, organizations, and the overall society as consumers of portions of the produced phenomena. The "transactions" here are the actual social interaction relationships themselves between the "consumers" and the "producers" as they occur and persist over time.
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Goals of Systems Analysis in the Mental Health Area At this point the discussion has gone from general issues involved in systems analysis to the problems of constructing specific social "inter-industry" models of a given region. The most relevant specific aims of systems analysis in mental health can now be presented: 9 . To develop a set of statistical indices of social process in a limited metropolitan region--indices both of mental illness-related pathology and ostensibly unrelated processes in the region and the society. 2. To range these indices in the form of one, or a series, of input-output or inter-industry matrices, to ascertain distribution patterns and amount of interchange at time X, between different sectors of the community. 3. To obtain measurements over a period of time on each index, to develop a set of trends in each area and in each possible interchange relationship, from time X to time Y. 4. To correlate and intercorrelate all trends in "mental health" and "nonmental health" areas, to see what varies along with what in the system, to determine chains of cause, effect, and correlation of events in the system. 5. To point out problems of maldistribution or misplaced or unbalanced interaction, given the interacting parties and the goals they have set for themselves (or others have set). 6. For purposes of prediction of future trends and for predicting the consequences of given changes, to describe by this pathway the factors in the overall interaction matrix which are related to changes in the mental health subsystem, as distinguished from those changes in the community which are neither directly nor indirectly related to changes in the mental health subsystem--and which do not therefore bring about changes in this subsystem when they change or are deliberately altered by mental health planning agencies. 7. Finally, to use these values obtained to simulate, in a mathematical model, all major social and economic community activities, and to predict trends in these activities by using this model, including potential outcomes of different "directed changes" or deliberate interventions in the system. SETTINGS SUITABLE FOR PRESENT ANALYSIS If the field of mental health practice were as well-defined and as inherently distinctive as the field of moon rocketry, then the application of systems analytical techniques in mental health would be less of a problem. It was in the United States space program that systems analysis scored one of its major achievements--the planning, orchestrating, timing, and executing of an extensively complex program. Since everyone agreed on what the vehicle was to be (a moon rocket) and everyone agreed on the goal (the moon), the problem was rationalized into steps. Lessing (2968) states that the following systems method has developed for most problems: A program is generally composed,depending on the nature of the problem, of four or
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five distinct phases. The first two are called the systems-study (or program-planning} phase and the exploratory (or project-planning) phase: they are sometimes considered as one, for both are occupied with basic planning. In these phases, the problem is defined or "structured," and the boundaries of the system are drawn. . . . Next, all relevant data on the system and its environment are assembled, the field is searched for all feasible options for solving the problems, and the whole body of information is analyzed so as to narrow the choice down to the best solutions. Once a managerial decision is made to proceed on the basis of this broad analysis, a third phase---known as the project, or development-planning phase--bagins. Now the solutions that seem best are studied in more detail; some are weeded out, others are put into research, and a projection is made of their development costs and the time they will take. The final managerial decision is then up to the agency that employs the systems engineers (p. ~57). Notice that the mental health service field at present is essentially at the first and second, or exploratory and program-planning stages, in many community mental health programs. The job at this point, before we can proceed with the full systems analysis technique, is to "draw the boundaries" of the system, "assemble the data," and "narrow the choice down to the best solutions." Here the word best has a major importance, for groups disagree over the ideal goals for mental health programs. Let us assume for the time being that the community groups involved in mental health service planning agree on broad goals, such as increasing happiness, and decreasing pathology of neurotic, psychotic, and psychopathic sorts in the community, what pathways and what programs are most useful in reaching this end? At this point it would appear wise to both limit and broaden the research efforts and the problem, in order to gain the most from systems analysis techniques at this stage in their development. The limitation most important to build into early research at this time would appear to be that of geography and topography. If the very first systems analysis approaches are carried out on small island or peninsular land areas of relatively homogeneous population, the number of variables and especially the boundary-drawing problem are relatively solved, at least in terms of this community as a social system. Thus the analysis of the internal system components---the groups and their activities with one another--can proceed more rapidly and with more assurance than if one "bites off" a whole metropolis to start with. While the preliminary systems study should be limited geographically, it appears critical at this time that it should not be limited to the "mental health service" orbit, or to a study of the interrelations of the mental health or the health and the welfare subsystems. This would defeat the entire purpose of the systems approach, which must view all mental health agencies, staff, and clientele as part of and affected by many other subsystems in the overall society. For example, as M. Harvey Brenner (5967) has recently proven, the overall national business cycle, as measured by unemployment rates, is directly and dosely correlated with rates of application for mental hospitalization--as unemployment goes up, so does pressure for admission to mental hospitals, and vice versa.
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The nonhealth and welfare world must be included in the preliminary model--the family subsystem, the business organization subsystem, and the national socioeconomic environment. After the analysis of factors influencing change in the mental health area, we can tell what influences change in the mental health problems and in the quality of services rendered, and which are irrelevant. As in the making of movies, one can always edit, but one cannot handle what one has not photographed. In our model of the interaction network, therefore, we must be all-inclusive to avoid the risk of missing the key factors because we naively assumed, a priori, that they were "irrelevant." A final reason for narrowing the focus to a region of manageable size has to do with the complexity of trends observable in any community or region. For practical purposes, it will be helpful to isolate major local trends early, to observe their influence on mental illness and pathology. For the purpose of making decisions on intervention, the more specific the locality, at least to begin with, the clearer the choices for intervention will be for the mental health profession and the community as a whole. The discussion has now defined systems analysis, seen how one of its central factors is used in economics, and qualified its use in mental health areas with two major precautions. It is possible now to see what actual techniques may be employed in the mental health area, and what their uses might be for the mental health practitioner. SPECIFIC RESEARCH STRATEGIES There are at least two major types of systems analysis which can be done at present, which would have direct practical use in mental health service planning. Some models aim at direct depiction of environmental influences, and others focus on alternative outcomes for a given set of constraints. Specific techniques include the use of input-output analysis, set theory, queuing theory, path analysis, and other mathematical approaches. To differing degrees, these approaches would also have long-range theoretical uses as well. In this article, two types of systems analysis techniques will be used. The first type of analysis we call the "raw interaction pattern" approach, and the second the "one-index" approach. After taking up each approach in turn, we can consider how they might be used together to get a more complete picture of the mental health subsystem of the overall society.
Raw Interaction Approach Let us consider a given small region, a part of a community, in terms of a set of social "sectors" analogous to the types of industrial sectors used by Leontief in his input-output or inter-industry analysis in economics. Instead of "heavy industry," "agriculture," and so on, the following set of sectors will be used:
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I. Household Sector (in study region)
Head of household Children Other adults II. Nonprofit Organization Sector (in study region) Mental health agencies Welfare agencies Public health agencies Hospitals and clinics (nonmental health) Deviance-control agencies Governmental organizations Political organizations Social clubs and recreational groups III. Profit Organization Sector (in and out of study program) Business organizations in study region Business organizations out of study region IV. Overall Environmental Sector Broader socioeconomic environmental factors (business cycles--national trends in socioeconomic area) Physical environment of study region Now each sector can be thought of as "producing" something which affects life in the study region. The household sector "produces" behavior which is relevant to the nonprofit organization sector, and the overall socioeconomic and physical environment. In fact, it is possible to consider each sector as interacting with each other sector, and form a master table for social activities similar to Table z above, for economic activities in the major sectors. The master table would have the outline seen in Table z. TABLE 2 Interchange Among Social Sectors Consumer Sectors Producer Sectors
Households
Nonprofit organizations
Profit organizations
Wider socioeco, environment
Wider physical environment
Households Nonprofit organizations Profit organizations Wider socioeco. environment Wider physical environment Each of the above sectors produces phenomena which affect each of the other sectors. Consider households. They contain, among many things, children and household heads. Household heads produce activity relevant to (z) their own household, (2) nonprofit organizations such as hospitals and wel-
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Community Mental Health Journal
fare organizations, (3) employing businesses, (4) the wider socioeconomic environment, since such phenomena as population growth and employment rates are in large part related to and caused by activities (or inactivities) of household heads. Similarly, children in households produce behavior of relevance to all the other sectors. What would a "raw interaction pattern" analysis have as its goals and uses, should all the blank ceils be filled in? The answer appears to be that such a matrix would act as an organizing device for the many different kinds of rates and statistics presently gathered on communities. To continue our example, it would act as a framework for organizing data on household size, usage of health agencies by households, employment rates, and so forth. This would be a way of examining a series of "social indicators" and seeing which vary along with which others in the community. But the "raw interaction pattern" approach has definite disadvantages from the point of view of a sophisticated systems analysis. It is a starting point, a master table to force the analyst to list and discover indices for the interaction of all possible sectors (and subsectors) of the community. But its disadvantage is that it cannot use any of the useful mathematical techniques of input-output analysis in economics. In that field, all the "inter-industry" or inter-sector interactions are indexed with one measure--dollars. Is it possible to use one rough index for a quantitative and mathematical model of the community relevant to service programs, and thus be able to use mathematical techniques for a systems analysis of the mental health service field? We think it is possible, and we turn to it next. One-Index Approach, with Time as the Index Time can be considered in various ways in science. We propose to use it here as a measuring device, In this kind of usage, it is superior in comparability, from region to region, than almost any other index, such as those of economics--dollars, pounds, and so on, which vary in basic value from year to year. If we take all the sectors relevant to a specific community region, and a limited period of time, we can see how each sector budgets its time with respect to each other sector. For example, taking all the household heads in region X let us call it "McKay's Peninsula"--we can see that these individuals must budget their waking time among the other sectors. Suppose we take a survey of the X region household heads. We can easily find the approximate distribution of hours spent by the zoo members of a random sample of household heads in this region (Table 3). We could then change these raw factors figures to percent of the total waking hours spent in each sector (Table 4). It is possible to do this "time-allocation" analysis for all the sodal bodies in each social sector how does each sector budget its total "live time" or activity-time among the other sectors. The expression "live time" is used here because both organizations in the nonprofessional and the professional sector can only be considered in terms of their open or active hours,
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TABLE 3 Waking Hours per Year Hours in nonprofit organizations
Hours at home (total)
zoo household heads
zoo,ooo
5o,ooo
Hours in profit organizations
Hours in wider environment
28o,ooo
zSo,ooo
Total hours
580,000
TABLE 4 Percent of Waking Hours Spent in Each Sector
At home
zoo household heads
In nonprofit organizations
~6
In profit organizations
~o
In wider environment
Total
24
~oo
5o
the hours in which they are in interaction with other community sectors and in which they are doing their own internal work. Eventually, the master table could appear as it does in Table 5. TABLE 5 McKay's Peninsula: Interaction Network Consumers of Active Time Sector II Sector III Nonprofit Profit Households organizations organizations Sector I
Interacting Partners
Total hours consumed
I
Households II Producers ofactive time
Nonprofit
~25,ooo
zoo,ooo
275,000
500,000
z,zoo,ooo
75o,ooo
~5o,ooo
3,000,000
4,400,0oo
400,0o0
orgs. III Profit
3,200,0o0
8,000,000
3,625,000
zx,5oo,ooo
orgs. Total output
6,625,ooo
x,25o,ooo
This is essentially a gigantic "time and motion" study of the overall community, in terms of how much time each sector spends with each other sector, in entire available time, per year. This would be a matrix model of the interaction pattern as it presently is. Now, by the use of relatively simple mathematical models, it is possible to introduce changes in some part
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Community Mental Health Journal
of the network, for example, in the amount of time householders spend in contact with nonprofit welfare agencies. If we hold constant all other time spent in Sector II (time spent with all other nonprofit organizations) what consequences will this have for the time spent in business organizations? This, in turn, if it changes (as it must), will alter the amount of time the business organizations have for their own pattern of interactions with all other community sectors. As Leontief (x96~) shows, there are relatively straightforward mathematical techniques which make it possible to make up a series of simultaneous equations and to solve them so that they indicate precisely what consequences there are throughout the network of changes introduced at any one point. Note this is the kind of systems model we said would be needed if there were any practical applications of the approach to the field of mental health service planning. This model allows us to experiment on the system by making a model of it, altering part of the model, and observing the consequences for the entire system. The next step could be to decide on goals or desired consequences which we would prefer if we altered some element in the system, i.e., some cell in the master table. Then we could try out different changes, to see which intervention came the closest to the ones which were sought.
"'Time is Money"--The Cost-Accounting Problem and Systems Analysi~ One of the main problems in real efforts in the worlds of either moon rocketry or mental health is the problem of limited funds. For this reason most action program decisions must answer the dual question of "how do we reach the goal?" and "how do we do it at minimum cost?" One of the most common kinds of economic analysis (comparing national economies) compares, across countries, the value of man-hours of labor, by translating this labor-time into commodities. We can, within any country, use the standards of the country and region to calculate the monetary value of time spent in activities in any one of the ceils of the master table given above. Thus it is possible to calculate the dollar value of the existing distribution of active time among the sectors of the system. Two alternative kinds of changes could be introduced into the model in Table 5. The costs for the alternative changes could be figured after the alternative activity-pattern changes were calculated. It might be that, on the face of it, change A and change B would both have the same consequences for the time spent by one other sector--and no difference in money-costs, but the secondary consequences would differ for the two changes. The model would clearly show this and show its extent. For example, suppose change A and change B both have the same consequences in terms of time spent by the nonprofit organizations sector, but change A would have the additional consequence of increased costs to householders (involving more of their time and its dollar value) while change B would have its major consequences
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in increased time, and thus costs, for business organizations. The model would allow us to figure this out ahead of time and allow the systems analysts or their clients to choose path A or path B, depending on their overall goals and the political and economic realities of the real situation. For example, one illustration of this issue is the alternate paths A and B in financing job training for the unemployed, The idea is to increase the time spent by the unemployed household heads in business organizations (as employees) and decrease the time spent at home. Path A would finance this out of the household heads sector (increase taxes, use dollars for training) while path B would let private industry do the financing. This would decrease the percent of time private industry could be doing productive work (training time is usually not productive in the immediate short run), increase the cost to industry, but still be politically more possible since the businesses can afford this and have a long view, where household heads may have a short view and not have the needed attitudes. The system analysis could show the time and dollar consequences of both approaches. Then if one of the goals was to pick out the most politically desirable pathway, we could definitely say that pathway B is the best one, as a result of analyzing the consequences of different alternative paths. Here the systems model shows its worth, as it is made to be experimented on and made to come up with alternative paths and cost statements for each.
Modifying McKay's Peninsula Two types of systems approaches have been presented: the "raw interaction" approach and a one-index approach with time as the index. The uses of the approaches in decision-making were considered where costs were a factor in the decision. Using our hypothetical McKay's Peninsula again, what steps must a professional group go through if it wants to modify the system as it exists, and use systems analytical techniques to help in a program for change? Having used the two data-processing models presented above to characterize McKay's Peninsula as it is, the next effort can be conceived of as modifying the time-allocation of activities of people in one of the sectors to reach a decided-upon goal. If the mental health area is of concern, the next task is to decide on the desired mental health mission, and to characterize this mission in terms of reallocation of time and costs. But this agreement on goals may be a major task in itself. One method of achieving a fair consensus on the mission or goal of the changes would be to use a balanced sample of practitioners, citizens, theoreticians, and administrators to arrive at a group goal. Then this can be translated into a new pattern of time and costs, using the systems models. Evaluation of the success of the change effort is twofold. First, we can see whether in fact the changes were accomplished to the extent of, and in the priority implied by, the stated goal of the professional and lay community of McKay's Peninsula. Second, if the goal is reached more completely by one professional group than by another,
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on the same problem and with the same time-costs, this will have major implications for future service planning in the community. IMPLICATIONS FOR MENTAL HEALTH PRACTICE The significance of the type of approach proposed here concerns the understanding of ihtegration of mental health activities into the overall social-economic system. It has implications for integrating psychology and social theory. The research should point to the real and the essentially artificial boundaries, in a model treating all variables together, and deciding only after the fact whether a variable of a factor is primarily a part of the mental health system or not, on the basis of empirical investigation. This is an approach that avoids the "pigeonholing" effect when investigations center down on some aspect of the mental health scene only to find after four years that the "background social variables" coalesced and caused the major changes involved in their study. This approach refuses to treat either the mental health or the "nonmental" health variables separately, but studies the complexities of their inevitable interaction in the community. Research of this type will select and use a series of indicators, not simply talk about them in a catalogue fashion. This will be one of the first tests of the use of intercorrelated social indicators in understanding the social process in a given real metropolitan region. In so doing, where information is available we will be able to know, over time, which variables are positively and negatively correlated with which others in terms of trend direction. To use a concrete example, if unemployment and cost of living go up, how does this double trend relate to changes in rate of welfare, ADC, hospitalization for mental illness, and bookings for juvenile disturbance? This type of systems research is important also because of its extensive use of environmental data, as factors built into the analysis of trends and interactions, rather than statically as in the case of categorizing people as "social class I or V," etc. The significant factors for mental health may be the change in these areas, rather than concrete levels. Systems analytical approaches will integrate economic and noneconomic factors, which is new, as far as we know, in community mental health research. Studies of this type would be the first time, to our knowledge, that the sophisticated and important input-output model of Leontief (~96~) was used for analyzing general social trends and mental illness-related trends, for a community. Leontief's model is explicit and can be modified for direct use in community mental health research, which is a step forward in comparison to most present-day discussions of the use of "social indicators." These always stop short of suggesting their actual use as part of a model for the analysis of data. The new step proposed here is the use of the input-output or "inter-industry" model in a systems approach that can use rationally, intelligently, and coherently in one framework the various types of data gathered for years now in health, welfare, and economics. Systems analytical research also has direct relevance for the "general
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theory" of social systems as espoused by Parsons, Shils, and their co-workers (z95~). They put reciprocity--exchange of values, communication, feelings and goods--in the center of their theoretical system. Research of the type proposed here can be used as a testing ground for some of the most general ideas in social systems theory. Will we find a system of interchange in a community? If not, what will we find in the way of interchange networks? What degree of closeness or non-closeness of relation will we find? The data of the systems analysis method will give us provisional concrete answers to some of these previously abstruse and abstract questions. The final major source of significance for the use of these techniques lies in their practical value to planners in community mental health. The use of the model and the techniques is especially appropriate for simulating the effects of hypothetical changes in input into the system. This is of major value in any planning effort in health, education, and welfare areas. LIMITATIONS OF THE SYSTEMS ANALYSIS METHOD The history of social service practice, and the planning for such practice, has seen many vogues and many techniques which were promising but which did not in the long run solve all the problems which they encountered. Systems analysis is only a technique and as such it, too, is subject to limitations. The five major ones which must be presented at this time are: information and its accuracy, the problems of goal-setting, the issue of method versus faith in method, the issue of "economizing" in health areas, and the problem of time limitations of decision-makers. The first problem for the use of systems analysis techniques, or any systematic techniques in planning, for that matter, is the problem of the completeness and the accuracy of information relevant to the task at hand. One of the main reasons why community mental health planning and the programs coming out of such planning have met with difficulties is that they had inaccurate information to work with. The gathering of information may be in itself a primary research problem for the analyst, and a practical problem for the service staff in the community. Without good information, no well-planned program is possible, yet the lack of this information makes systems analysis techniques all the more difficult to use. This is a chickenand-egg problem, with about the only solution being in most cases a special effort to gather more information in order to make a more accurate plan for the system. But this takes valuable time and that is another problem, which is considered below. The problem of goal-setting is a second major issue. The systems model of "inter-industry" tables does allow us to make alternative changes and come up with alternative results. But which one does the community want? Or, of even greater importance, what if the mental health professionals set up one set of goals and the community sets up another? The result, if citizen participation is not part of the planning and analysis procedure, will be a
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Community Mental Health Journal
systems analysis which comes up with just what the "mental health establishment" wants done, all worked out interms of minimum cost, but which may be quite irrelevant to felt community needs. Thus we suggest that citizen participation (part of the community mental health planning process in most progressive programs) be built into the systems analysis process, at the stage of goal-setting. If the community can participate in the goal-setting process, then the systems analysis procedure will be relevant and workable to the community and its needs. If the citizens are not consulted, then the systems analysis procedure can be a sophisticated method for perpetuating a very unsatisfactory status quo, which may please only some mental health professionals and no one else. A third major problem in the use of this technique is essentially based on the experience that the authors and some of their colleagues have had with other attempts to plan scientifically, using any form of systematic method. The expectations of the mental health professional, and the community, may be too great, considering the present state of the art of systems analysis. It is not a cure-all, although it is presently a fashionable technique in both natural science and social welfare areas. One should not confuse a research and planning technique with a system of moral values, a religion, or a universal panacea. Systems analysis is a technique, and as such it must prove its usefulness in each new situation. As with any technique, it may be more useful in some situations than in others. A fourth problem involves the issue of "economizing" in health areas, Techniques which analyze the distribution of time, resources, and professional activities are not "loyal" to any professional group, Nor do these techniques respect the usual status hierarchy of the service professions as to which are thought to be more important and which less important. Feelings may be hurt and antipathy generated against any research group which applies cost-effectiveness analysis to a service area. On the other hand, the technique itself can be perverted into a method for showing the cheapest way to provide service, which may not be the most advisable way to plan mental health services (or any community services) in the long run. If the true goal is objectivity and increase in effectiveness of service to the community, it should be possible to communicate this to the concerned service professions and gain their cooperation. Finally, there is the problem of time limitations and the time needed to carry on a comprehensive systems analysis. This could be called the problem of the harassed administrator. Systems analysis techniques are not by any means the fastest way to get an answer. The fastest way is to make a "seat of the pants" judgment and fire away. Yet these judgments have turned out wrong as many times as they have been right and, once the decision is made, it is no longer possible to consider alternatives. Therefore the more important the plan, the longer the period of time with which it is concerned, and the more the administrator is interested in considering alternatives, the more relevant systems analysis techniques become. They do not
Bellenden R. Hutcheson and Elliott A. Krause
45
p r o d u c e quick a n d easy solutions, b u t ttttBr m a y atttt to the scope of the k n o w n in the m e n t a l h e a l t h f i e l d - - a field, like m a n y others, full of p u z z l i n g unknowns. APPENDIX The mathematics of the approach presented in the body of the article involves the use of "input coefficients" and systems of simultaneous equation. Let the quantity of the output of sector i absorbed by sector j per unit of its total output j be described by the symbol Aij and be called the input coefficient of the product of sector i into sector j:
(l)
Xij A i j - Xj
In thousands, Table 5 in the text in raw form is: I II III
I
II
III
I25 2,200 4,400
:~o0 75~ 400
275 "r5o 3,200
6,625
1,25o
3,625
500 3,00o 8,000
The coefficient matrix, following Formula (2) above, is for the table:
275/8000
225/500 2200/500 4400/500
Ioo/3ooo 750/3o00 400/3000
250/8000 3200/8000
925o 4.200 8.800
or .033 .25o .233
.034 .0i 9 .4oo
For the use of this matrix of input coefficients in systems of simultaneous equations, solvable by matrix inversion techniques, see Leontief, 2962, pp. 238-242. REFERENCES Brenner, H. H. Economic change and mental hospitalization: New York State, 19Io-I960. Social Psychiatry, 2967, a, 28o-288. Caplan, G. Principles of preventive psychiatry. New York: Basic Books, 2964. Hollingshead, A., & Redlich, F. C. Social class and mental illness. New York: John Wiley, 2958. Keynes, J. M. The general theory of employment, interest, and money. London: Macmillan, I936. Leontief, W. Input-output economics. Cambridge: Harvard University Press, 296i. Lessing, L. Systems engineering invades the city. Fortune, January, 2968, 77, 155-257 9 Mauss, M. The gift: forms and functions of exchange in archaic societies. New York: Free Press, 2954. Parsons, T. The social system. New York: Free Press, 2952. Parsons, T., & Shils, E. A. (Eds.). Toward a general theory of action; Cambridge: Harvard University Press, 2952. RCA Systems Development (Smith, T. A., Patterson, T. G., & Everhard, F.) Descriptive organizational brochure. Camden, N.J., 2968. Smelser, J. N. The sociology of economic life. Englewood Cliffs: Prentice-Hall, 2963. Spencer, H. The study of sociology. London: Appleton, 1924.
ABSTRACT: Systems analysis, a method originating in engineering and planning areas, evaluates the costs and consequences of alternative approaches to a goal given a known set of constraints. Mental health services are badly in need of a more rational approach to planning, and this article shows how specific systems analysis techniques can be used to describe a mental health system and, at the same time, to evaluate consequences and costs of changing the system in different ways. The limitations of the approach are also considered. The authors' main aim is a general introduction to the systems approach for mental health practitioners. SYSTEMS ANALYSIS: A DEFINITION Out of research and program planning needs in science and social service fields in the last 2o years, and originating in the operations research approaches developed in the forties, a new, hybrid profession has come into being: "systems analysis." The activities of the systems analyst, and the research methods at his command, will probably be of major importance to the mental health field in years to come. From the viewpoint of the engineer, systems engineering is an outgrowth of specific research, design, and testing techniques for solving management and decision problems which the heads of large organizations have been encountering. These techniques grew out of the massive logistics and coordination problems of World War II. The community applications of the approach are a more recent development. Lessing (5968) notes that: On a more immediately practical plane, systems engineering offers a new way to look individual large urban problems from all sides, weigh all possible alternative solutions with their costs and predictable consequences, and then get on with an optimum solution by the shortest possibleroute (p. 256). at
From the viewpoint of the sociologist, especially those in the tradition of Dr. Hutcheson is Assistant Commissioner for Children's Services, Massachusetts Department of Mental Health, 15 Ashburton Place, Boston, Mass. o2Io8; and Assistant Clinical Professor of Psychiatry, Laboratory of Community Psychiatry, Harvard Medical School. Dr. Krause is Assistant Professor of Sociology, Northeastern University, and Consultant to the Massachusetts Department of Mental Health. The authors wish to thank Mr. William Floyd, Senior Scientist, Spear, Inc., for his assistance with the matrix analysis. Community Mental Health Journal, Vol. 5 (1), 1969
29
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Community Mental Health Journal
Talcott Parsons (~952), the social system has always been a dominant theoretical concept, and the research problem of greatest importance has been to elucidate the dynamic interrelationships of different subsystems which make up the overall social system. For example, Hollingshead and Redlich (x958) show that the social class distinctions of American society are related to the prevalence of mental illness. In general, psychiatrists such as Caplan (~965) and sociologists such as Parsons concern themselves with the interpenetration of the social and psychological worlds of the individual. Writers such as Smelser (z963) have been interested in the economic system in its relationship to the social interaction system. Through the use of systems analysis approaches, it may be more possible to interrelate the data of psychology, sociology, and economics. Then the human community system and its subsystems can be inspected at the small group, community, and national level. The systems approach, as defined by one of its practitioners, "is an orderly way of looking at all the angles of a complex problem, to determine the best operating solution for a given set of constraints" (RCA Systems Development, z968). The systems analysis approach, as it is presently evolving, has several interrelated goals. These are: 9 . To decide on a mission or goal of the program which is to be subjected to a systems analysis. 2. To describe the boundaries of the system and the subsystems which make it up. 3- To ascertain the ways in which the system changes and the factors which produce the change. 4. To make a model mathematical or graphic in most cases which considers all elements of the systems both as static and as functioning in time. 5. To use the model to produce theoretical changes of different types, to see what possible outcomes would result from each set of changes. Otherwise phrased, to simulate a set of changes using the model. 6. To pick out the most desirable outcome, given previously agreed-upon goals, and then to do in reality the activities described in the model, which would reach this goal. 7. To cut costs, clarify problems, and avoid wasted time, by doing this experimental manipulation of analytical models using time and cost variables as part of the design, and thus to consider for a given region the most practical and efficient course to follow in achieving the desired end, before one actually intervenes in the situation. For the field of mental health service, the major goal or mission of the systems analysis approach would be to promote the mental health of a given local region, by isolating relevant factors which can be manipulated to favorably change the environment, human and nonhuman. In the mental health service field, therefore, systems analysis may bring ecology--the study of
Bellenden R. Hutcheson and Eiliott A. Krause
31
the interaction of people and their environment--into the area of ethology, the biological study of social behavior. The entire field of mental health, and especially the area of community mental health program planning, is in great need of a comprehensive approach such as the above, in the opinion of the authors. Important program decisions are always being made, and many more will be made in the future. Whether they are made while considering all the relevant factors---inside and outside of the traditional "mental health" orbit--may depend on whether systems analysis techniques are used as part of the planning and decision-making process. One technique of central importance in systems analysis is "input-output" or "inter-industry" analysis; it is a technique which could be of great importance to all health and welfare planning in the future. It is to this approach that we now turn. INPUT-OUTPUT ANALYSIS: A SYSTEMS ANALYSIS METHOD Since the time of Herbert Spencer, sociologists and government officials have been concerned with the problem of grasping significant data to illuminate the dimensions and forces which make up the social order, and which indicate directions of social change. Spencer (:1954) noted that social statistics could be used as follows: These facts, given with as much brevity as consistent with clearness and accuracy, should be so grouped and arranged that they may be comprehended in their ensemble, and contemplated as mutually dependent parts of one great whole. The aim should be so to present them that men may readily trace the consensus subsisting among them, with the view of learning what social phenomena coexistwith what others (p. V). In spite of the fact that Spencer was one of the first sociologists, the recent developments in the integration of this kind of data came not directly from this group but from the economists. After Keynes (5936) began the revolution in economics, government and social science realized the practical utility for planning, of regional and national economic data. In fact, the particular economic research method which was the inspiration behind the method discussed here grew out of an attempt to deliberately integrate general theory, new methods of data analysis, and the concrete data of everyday economic life.
Systems Analysis in Economics The discussion of systems analysis in economics will be limited to the pioneering and basic work of Wassily Leontief, as set out in his classic work, Input-Output Economics (596I). Leontief ranges the types of industry putting things into the overall society, in terms of sectors of the society producing goods, down one side of a master table, and the different types of sectors of the society which consume these produced items, across the top of the master table. Each intersection of a row and a column--each cell in the master table--represents the transaction between one sector as
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Community Mental Health Journal
producer and the other as buyer of what is produced by this sector. Thus the alternative name of his analytical method: "inter-industry" analysis. This kind of organization of data makes it possible to see to what degree the output of each sector or type of industry is consumed by which other sectors (including each one as a consumer of its own output). In this way he can illustrate with a matrix of concrete interacting groups that "economic processes are interrelated in a systematic manner, a manner which can be thought of as a network of exchanges or transactions between all the sectors." He illustrates for the economic sphere the classical statement that all social processes are interrelated. The advantages of his input-output method are that they show how and where and to what extent, in the economic subsystem, events are interrelated: The effect of an event at any one point is transmitted to the rest of the economy step by step via the chain of transactions that links the whole system together (Leontief, p. 24). His next step is to create a mathematical model of the system: A table of ratios for the entire economy gives us, in as much detail as we require, a quantitatively determined picture of the internal structure of the system. This makes it possible to calculate in detail the consequences that result from the introduction into the system of changes suggested by the theoretical or practical problem at hand (p. 24). At this point let us present a simplified and imaginary table of Leontief's type and inspect it closely, as to what it means and what it does. Each number in each cell represents the dollar value (in millions) of all economic transactions between a given sector as producer (in the column on the left) and another given sector as consumer (those across the top of the table). Each sector is put in both as a producer and a consumer, as this is the way it is in any real society. Remembering that each cell measures the value of all transactions of the two interacting sectors, the zS** cell indicates that the goods and services sector sold the heavy industry sector $2 5 million worth of materials and labor (Table 2). TABLE I Master Input-Output Table for "Transylvania" Producer Sectors Goods and services
Consumer Sectors Heavy Agriculture industry
Goods and services Agriculture Heavy industry
25 3~ 5
~5 3o ~o
~5"* Io 5~
Total
5~
55
75
Total
45 7~ 65 580
Here, as in most real tables made up in input-output economics, the numbers represent the dollar value of the transactions made between different sec-
Bellenden R. Hutcheson and Elliott A. Krause
33
tors of the economy. They are an index of the amount of activity involved in the interchange between the two sectors. Since money is directly quantifiable, it is possible here, for example, to go "across a row" for a given sector of the economy and see, proportionally, how much activity the sector has with all other sectors and with itself, as a buyer of what it produces. Let us go back to the table and look at the row labelled "Heavy industry." It is possible by this method to determine the proportional degree of activity which heavy industry has with (a) goods and services sector, (b) agriculture sector, and (c) its own sector as a consumer of what it produces. Here, going across the heavy industry row, we note that the main consumer of the output is its own sector (5o), with only one-tenth as much interchange going on with the goods and services sector (5), and a fifth as much as with agriculture (~o). Note that the other sectors distribute their product differently in terms of the proportion of other sectors which consume them. The overall chart here states all major interchanges between all major sectors in the economy as (a) producers and (b) consumers. The numbers in the cells measure the inter-industry activity or flow between each sector and all other sectors. Note that the advantage of Leontief's "input-output" or "inter-industry" tables is that one can see at a glance all the complex relationships involving who is giving how much of what to whom, for each of the entries down the side of his table, and across the top. The "internal structure of the economy" he speaks of is made up of the actual networks of interchange that go to make up the functioning system. These networks are represented mathematically in his tables and equations. The Social System as a Network of Interchanges The idea of the social significance of the exchange of things, people, words, and ideas was recognized by social anthropologists and early sociologists such as Spencer. In his study of primitive economics, the anthropologist Marcel Mauss (i954) stated that this model of reciprocal interchange or bartering of values, communications, gifts, and people would do quite well as an analytical model for the entire social system, not just in the area of economics. Making use of Mauss' insight, and recent attempts to generalize to all social processes using these new analysis models, we are interested here in making an ,inter-industry" systems analysis of a small metropolitan region, in which problems of mental illness and other forms of defined deviance from social norms will be plugged into an overall matrix which will consider general inputs to and outputs of the social system. This matrix should consider individuals, families, organizations, and the overall society as consumers of portions of the produced phenomena. The "transactions" here are the actual social interaction relationships themselves between the "consumers" and the "producers" as they occur and persist over time.
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Community Mental Health Journal
Goals of Systems Analysis in the Mental Health Area At this point the discussion has gone from general issues involved in systems analysis to the problems of constructing specific social "inter-industry" models of a given region. The most relevant specific aims of systems analysis in mental health can now be presented: 9 . To develop a set of statistical indices of social process in a limited metropolitan region--indices both of mental illness-related pathology and ostensibly unrelated processes in the region and the society. 2. To range these indices in the form of one, or a series, of input-output or inter-industry matrices, to ascertain distribution patterns and amount of interchange at time X, between different sectors of the community. 3. To obtain measurements over a period of time on each index, to develop a set of trends in each area and in each possible interchange relationship, from time X to time Y. 4. To correlate and intercorrelate all trends in "mental health" and "nonmental health" areas, to see what varies along with what in the system, to determine chains of cause, effect, and correlation of events in the system. 5. To point out problems of maldistribution or misplaced or unbalanced interaction, given the interacting parties and the goals they have set for themselves (or others have set). 6. For purposes of prediction of future trends and for predicting the consequences of given changes, to describe by this pathway the factors in the overall interaction matrix which are related to changes in the mental health subsystem, as distinguished from those changes in the community which are neither directly nor indirectly related to changes in the mental health subsystem--and which do not therefore bring about changes in this subsystem when they change or are deliberately altered by mental health planning agencies. 7. Finally, to use these values obtained to simulate, in a mathematical model, all major social and economic community activities, and to predict trends in these activities by using this model, including potential outcomes of different "directed changes" or deliberate interventions in the system. SETTINGS SUITABLE FOR PRESENT ANALYSIS If the field of mental health practice were as well-defined and as inherently distinctive as the field of moon rocketry, then the application of systems analytical techniques in mental health would be less of a problem. It was in the United States space program that systems analysis scored one of its major achievements--the planning, orchestrating, timing, and executing of an extensively complex program. Since everyone agreed on what the vehicle was to be (a moon rocket) and everyone agreed on the goal (the moon), the problem was rationalized into steps. Lessing (2968) states that the following systems method has developed for most problems: A program is generally composed,depending on the nature of the problem, of four or
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35
five distinct phases. The first two are called the systems-study (or program-planning} phase and the exploratory (or project-planning) phase: they are sometimes considered as one, for both are occupied with basic planning. In these phases, the problem is defined or "structured," and the boundaries of the system are drawn. . . . Next, all relevant data on the system and its environment are assembled, the field is searched for all feasible options for solving the problems, and the whole body of information is analyzed so as to narrow the choice down to the best solutions. Once a managerial decision is made to proceed on the basis of this broad analysis, a third phase---known as the project, or development-planning phase--bagins. Now the solutions that seem best are studied in more detail; some are weeded out, others are put into research, and a projection is made of their development costs and the time they will take. The final managerial decision is then up to the agency that employs the systems engineers (p. ~57). Notice that the mental health service field at present is essentially at the first and second, or exploratory and program-planning stages, in many community mental health programs. The job at this point, before we can proceed with the full systems analysis technique, is to "draw the boundaries" of the system, "assemble the data," and "narrow the choice down to the best solutions." Here the word best has a major importance, for groups disagree over the ideal goals for mental health programs. Let us assume for the time being that the community groups involved in mental health service planning agree on broad goals, such as increasing happiness, and decreasing pathology of neurotic, psychotic, and psychopathic sorts in the community, what pathways and what programs are most useful in reaching this end? At this point it would appear wise to both limit and broaden the research efforts and the problem, in order to gain the most from systems analysis techniques at this stage in their development. The limitation most important to build into early research at this time would appear to be that of geography and topography. If the very first systems analysis approaches are carried out on small island or peninsular land areas of relatively homogeneous population, the number of variables and especially the boundary-drawing problem are relatively solved, at least in terms of this community as a social system. Thus the analysis of the internal system components---the groups and their activities with one another--can proceed more rapidly and with more assurance than if one "bites off" a whole metropolis to start with. While the preliminary systems study should be limited geographically, it appears critical at this time that it should not be limited to the "mental health service" orbit, or to a study of the interrelations of the mental health or the health and the welfare subsystems. This would defeat the entire purpose of the systems approach, which must view all mental health agencies, staff, and clientele as part of and affected by many other subsystems in the overall society. For example, as M. Harvey Brenner (5967) has recently proven, the overall national business cycle, as measured by unemployment rates, is directly and dosely correlated with rates of application for mental hospitalization--as unemployment goes up, so does pressure for admission to mental hospitals, and vice versa.
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Community Mental Health Journal
The nonhealth and welfare world must be included in the preliminary model--the family subsystem, the business organization subsystem, and the national socioeconomic environment. After the analysis of factors influencing change in the mental health area, we can tell what influences change in the mental health problems and in the quality of services rendered, and which are irrelevant. As in the making of movies, one can always edit, but one cannot handle what one has not photographed. In our model of the interaction network, therefore, we must be all-inclusive to avoid the risk of missing the key factors because we naively assumed, a priori, that they were "irrelevant." A final reason for narrowing the focus to a region of manageable size has to do with the complexity of trends observable in any community or region. For practical purposes, it will be helpful to isolate major local trends early, to observe their influence on mental illness and pathology. For the purpose of making decisions on intervention, the more specific the locality, at least to begin with, the clearer the choices for intervention will be for the mental health profession and the community as a whole. The discussion has now defined systems analysis, seen how one of its central factors is used in economics, and qualified its use in mental health areas with two major precautions. It is possible now to see what actual techniques may be employed in the mental health area, and what their uses might be for the mental health practitioner. SPECIFIC RESEARCH STRATEGIES There are at least two major types of systems analysis which can be done at present, which would have direct practical use in mental health service planning. Some models aim at direct depiction of environmental influences, and others focus on alternative outcomes for a given set of constraints. Specific techniques include the use of input-output analysis, set theory, queuing theory, path analysis, and other mathematical approaches. To differing degrees, these approaches would also have long-range theoretical uses as well. In this article, two types of systems analysis techniques will be used. The first type of analysis we call the "raw interaction pattern" approach, and the second the "one-index" approach. After taking up each approach in turn, we can consider how they might be used together to get a more complete picture of the mental health subsystem of the overall society.
Raw Interaction Approach Let us consider a given small region, a part of a community, in terms of a set of social "sectors" analogous to the types of industrial sectors used by Leontief in his input-output or inter-industry analysis in economics. Instead of "heavy industry," "agriculture," and so on, the following set of sectors will be used:
Bellenden R. Hutcheson and ElUott A. Krause
37
I. Household Sector (in study region)
Head of household Children Other adults II. Nonprofit Organization Sector (in study region) Mental health agencies Welfare agencies Public health agencies Hospitals and clinics (nonmental health) Deviance-control agencies Governmental organizations Political organizations Social clubs and recreational groups III. Profit Organization Sector (in and out of study program) Business organizations in study region Business organizations out of study region IV. Overall Environmental Sector Broader socioeconomic environmental factors (business cycles--national trends in socioeconomic area) Physical environment of study region Now each sector can be thought of as "producing" something which affects life in the study region. The household sector "produces" behavior which is relevant to the nonprofit organization sector, and the overall socioeconomic and physical environment. In fact, it is possible to consider each sector as interacting with each other sector, and form a master table for social activities similar to Table z above, for economic activities in the major sectors. The master table would have the outline seen in Table z. TABLE 2 Interchange Among Social Sectors Consumer Sectors Producer Sectors
Households
Nonprofit organizations
Profit organizations
Wider socioeco, environment
Wider physical environment
Households Nonprofit organizations Profit organizations Wider socioeco. environment Wider physical environment Each of the above sectors produces phenomena which affect each of the other sectors. Consider households. They contain, among many things, children and household heads. Household heads produce activity relevant to (z) their own household, (2) nonprofit organizations such as hospitals and wel-
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Community Mental Health Journal
fare organizations, (3) employing businesses, (4) the wider socioeconomic environment, since such phenomena as population growth and employment rates are in large part related to and caused by activities (or inactivities) of household heads. Similarly, children in households produce behavior of relevance to all the other sectors. What would a "raw interaction pattern" analysis have as its goals and uses, should all the blank ceils be filled in? The answer appears to be that such a matrix would act as an organizing device for the many different kinds of rates and statistics presently gathered on communities. To continue our example, it would act as a framework for organizing data on household size, usage of health agencies by households, employment rates, and so forth. This would be a way of examining a series of "social indicators" and seeing which vary along with which others in the community. But the "raw interaction pattern" approach has definite disadvantages from the point of view of a sophisticated systems analysis. It is a starting point, a master table to force the analyst to list and discover indices for the interaction of all possible sectors (and subsectors) of the community. But its disadvantage is that it cannot use any of the useful mathematical techniques of input-output analysis in economics. In that field, all the "inter-industry" or inter-sector interactions are indexed with one measure--dollars. Is it possible to use one rough index for a quantitative and mathematical model of the community relevant to service programs, and thus be able to use mathematical techniques for a systems analysis of the mental health service field? We think it is possible, and we turn to it next. One-Index Approach, with Time as the Index Time can be considered in various ways in science. We propose to use it here as a measuring device, In this kind of usage, it is superior in comparability, from region to region, than almost any other index, such as those of economics--dollars, pounds, and so on, which vary in basic value from year to year. If we take all the sectors relevant to a specific community region, and a limited period of time, we can see how each sector budgets its time with respect to each other sector. For example, taking all the household heads in region X let us call it "McKay's Peninsula"--we can see that these individuals must budget their waking time among the other sectors. Suppose we take a survey of the X region household heads. We can easily find the approximate distribution of hours spent by the zoo members of a random sample of household heads in this region (Table 3). We could then change these raw factors figures to percent of the total waking hours spent in each sector (Table 4). It is possible to do this "time-allocation" analysis for all the sodal bodies in each social sector how does each sector budget its total "live time" or activity-time among the other sectors. The expression "live time" is used here because both organizations in the nonprofessional and the professional sector can only be considered in terms of their open or active hours,
Bellenden R. Hutcheson and Elliott A. Krause
39
TABLE 3 Waking Hours per Year Hours in nonprofit organizations
Hours at home (total)
zoo household heads
zoo,ooo
5o,ooo
Hours in profit organizations
Hours in wider environment
28o,ooo
zSo,ooo
Total hours
580,000
TABLE 4 Percent of Waking Hours Spent in Each Sector
At home
zoo household heads
In nonprofit organizations
~6
In profit organizations
~o
In wider environment
Total
24
~oo
5o
the hours in which they are in interaction with other community sectors and in which they are doing their own internal work. Eventually, the master table could appear as it does in Table 5. TABLE 5 McKay's Peninsula: Interaction Network Consumers of Active Time Sector II Sector III Nonprofit Profit Households organizations organizations Sector I
Interacting Partners
Total hours consumed
I
Households II Producers ofactive time
Nonprofit
~25,ooo
zoo,ooo
275,000
500,000
z,zoo,ooo
75o,ooo
~5o,ooo
3,000,000
4,400,0oo
400,0o0
orgs. III Profit
3,200,0o0
8,000,000
3,625,000
zx,5oo,ooo
orgs. Total output
6,625,ooo
x,25o,ooo
This is essentially a gigantic "time and motion" study of the overall community, in terms of how much time each sector spends with each other sector, in entire available time, per year. This would be a matrix model of the interaction pattern as it presently is. Now, by the use of relatively simple mathematical models, it is possible to introduce changes in some part
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Community Mental Health Journal
of the network, for example, in the amount of time householders spend in contact with nonprofit welfare agencies. If we hold constant all other time spent in Sector II (time spent with all other nonprofit organizations) what consequences will this have for the time spent in business organizations? This, in turn, if it changes (as it must), will alter the amount of time the business organizations have for their own pattern of interactions with all other community sectors. As Leontief (x96~) shows, there are relatively straightforward mathematical techniques which make it possible to make up a series of simultaneous equations and to solve them so that they indicate precisely what consequences there are throughout the network of changes introduced at any one point. Note this is the kind of systems model we said would be needed if there were any practical applications of the approach to the field of mental health service planning. This model allows us to experiment on the system by making a model of it, altering part of the model, and observing the consequences for the entire system. The next step could be to decide on goals or desired consequences which we would prefer if we altered some element in the system, i.e., some cell in the master table. Then we could try out different changes, to see which intervention came the closest to the ones which were sought.
"'Time is Money"--The Cost-Accounting Problem and Systems Analysi~ One of the main problems in real efforts in the worlds of either moon rocketry or mental health is the problem of limited funds. For this reason most action program decisions must answer the dual question of "how do we reach the goal?" and "how do we do it at minimum cost?" One of the most common kinds of economic analysis (comparing national economies) compares, across countries, the value of man-hours of labor, by translating this labor-time into commodities. We can, within any country, use the standards of the country and region to calculate the monetary value of time spent in activities in any one of the ceils of the master table given above. Thus it is possible to calculate the dollar value of the existing distribution of active time among the sectors of the system. Two alternative kinds of changes could be introduced into the model in Table 5. The costs for the alternative changes could be figured after the alternative activity-pattern changes were calculated. It might be that, on the face of it, change A and change B would both have the same consequences for the time spent by one other sector--and no difference in money-costs, but the secondary consequences would differ for the two changes. The model would clearly show this and show its extent. For example, suppose change A and change B both have the same consequences in terms of time spent by the nonprofit organizations sector, but change A would have the additional consequence of increased costs to householders (involving more of their time and its dollar value) while change B would have its major consequences
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in increased time, and thus costs, for business organizations. The model would allow us to figure this out ahead of time and allow the systems analysts or their clients to choose path A or path B, depending on their overall goals and the political and economic realities of the real situation. For example, one illustration of this issue is the alternate paths A and B in financing job training for the unemployed, The idea is to increase the time spent by the unemployed household heads in business organizations (as employees) and decrease the time spent at home. Path A would finance this out of the household heads sector (increase taxes, use dollars for training) while path B would let private industry do the financing. This would decrease the percent of time private industry could be doing productive work (training time is usually not productive in the immediate short run), increase the cost to industry, but still be politically more possible since the businesses can afford this and have a long view, where household heads may have a short view and not have the needed attitudes. The system analysis could show the time and dollar consequences of both approaches. Then if one of the goals was to pick out the most politically desirable pathway, we could definitely say that pathway B is the best one, as a result of analyzing the consequences of different alternative paths. Here the systems model shows its worth, as it is made to be experimented on and made to come up with alternative paths and cost statements for each.
Modifying McKay's Peninsula Two types of systems approaches have been presented: the "raw interaction" approach and a one-index approach with time as the index. The uses of the approaches in decision-making were considered where costs were a factor in the decision. Using our hypothetical McKay's Peninsula again, what steps must a professional group go through if it wants to modify the system as it exists, and use systems analytical techniques to help in a program for change? Having used the two data-processing models presented above to characterize McKay's Peninsula as it is, the next effort can be conceived of as modifying the time-allocation of activities of people in one of the sectors to reach a decided-upon goal. If the mental health area is of concern, the next task is to decide on the desired mental health mission, and to characterize this mission in terms of reallocation of time and costs. But this agreement on goals may be a major task in itself. One method of achieving a fair consensus on the mission or goal of the changes would be to use a balanced sample of practitioners, citizens, theoreticians, and administrators to arrive at a group goal. Then this can be translated into a new pattern of time and costs, using the systems models. Evaluation of the success of the change effort is twofold. First, we can see whether in fact the changes were accomplished to the extent of, and in the priority implied by, the stated goal of the professional and lay community of McKay's Peninsula. Second, if the goal is reached more completely by one professional group than by another,
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on the same problem and with the same time-costs, this will have major implications for future service planning in the community. IMPLICATIONS FOR MENTAL HEALTH PRACTICE The significance of the type of approach proposed here concerns the understanding of ihtegration of mental health activities into the overall social-economic system. It has implications for integrating psychology and social theory. The research should point to the real and the essentially artificial boundaries, in a model treating all variables together, and deciding only after the fact whether a variable of a factor is primarily a part of the mental health system or not, on the basis of empirical investigation. This is an approach that avoids the "pigeonholing" effect when investigations center down on some aspect of the mental health scene only to find after four years that the "background social variables" coalesced and caused the major changes involved in their study. This approach refuses to treat either the mental health or the "nonmental" health variables separately, but studies the complexities of their inevitable interaction in the community. Research of this type will select and use a series of indicators, not simply talk about them in a catalogue fashion. This will be one of the first tests of the use of intercorrelated social indicators in understanding the social process in a given real metropolitan region. In so doing, where information is available we will be able to know, over time, which variables are positively and negatively correlated with which others in terms of trend direction. To use a concrete example, if unemployment and cost of living go up, how does this double trend relate to changes in rate of welfare, ADC, hospitalization for mental illness, and bookings for juvenile disturbance? This type of systems research is important also because of its extensive use of environmental data, as factors built into the analysis of trends and interactions, rather than statically as in the case of categorizing people as "social class I or V," etc. The significant factors for mental health may be the change in these areas, rather than concrete levels. Systems analytical approaches will integrate economic and noneconomic factors, which is new, as far as we know, in community mental health research. Studies of this type would be the first time, to our knowledge, that the sophisticated and important input-output model of Leontief (~96~) was used for analyzing general social trends and mental illness-related trends, for a community. Leontief's model is explicit and can be modified for direct use in community mental health research, which is a step forward in comparison to most present-day discussions of the use of "social indicators." These always stop short of suggesting their actual use as part of a model for the analysis of data. The new step proposed here is the use of the input-output or "inter-industry" model in a systems approach that can use rationally, intelligently, and coherently in one framework the various types of data gathered for years now in health, welfare, and economics. Systems analytical research also has direct relevance for the "general
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theory" of social systems as espoused by Parsons, Shils, and their co-workers (z95~). They put reciprocity--exchange of values, communication, feelings and goods--in the center of their theoretical system. Research of the type proposed here can be used as a testing ground for some of the most general ideas in social systems theory. Will we find a system of interchange in a community? If not, what will we find in the way of interchange networks? What degree of closeness or non-closeness of relation will we find? The data of the systems analysis method will give us provisional concrete answers to some of these previously abstruse and abstract questions. The final major source of significance for the use of these techniques lies in their practical value to planners in community mental health. The use of the model and the techniques is especially appropriate for simulating the effects of hypothetical changes in input into the system. This is of major value in any planning effort in health, education, and welfare areas. LIMITATIONS OF THE SYSTEMS ANALYSIS METHOD The history of social service practice, and the planning for such practice, has seen many vogues and many techniques which were promising but which did not in the long run solve all the problems which they encountered. Systems analysis is only a technique and as such it, too, is subject to limitations. The five major ones which must be presented at this time are: information and its accuracy, the problems of goal-setting, the issue of method versus faith in method, the issue of "economizing" in health areas, and the problem of time limitations of decision-makers. The first problem for the use of systems analysis techniques, or any systematic techniques in planning, for that matter, is the problem of the completeness and the accuracy of information relevant to the task at hand. One of the main reasons why community mental health planning and the programs coming out of such planning have met with difficulties is that they had inaccurate information to work with. The gathering of information may be in itself a primary research problem for the analyst, and a practical problem for the service staff in the community. Without good information, no well-planned program is possible, yet the lack of this information makes systems analysis techniques all the more difficult to use. This is a chickenand-egg problem, with about the only solution being in most cases a special effort to gather more information in order to make a more accurate plan for the system. But this takes valuable time and that is another problem, which is considered below. The problem of goal-setting is a second major issue. The systems model of "inter-industry" tables does allow us to make alternative changes and come up with alternative results. But which one does the community want? Or, of even greater importance, what if the mental health professionals set up one set of goals and the community sets up another? The result, if citizen participation is not part of the planning and analysis procedure, will be a
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systems analysis which comes up with just what the "mental health establishment" wants done, all worked out interms of minimum cost, but which may be quite irrelevant to felt community needs. Thus we suggest that citizen participation (part of the community mental health planning process in most progressive programs) be built into the systems analysis process, at the stage of goal-setting. If the community can participate in the goal-setting process, then the systems analysis procedure will be relevant and workable to the community and its needs. If the citizens are not consulted, then the systems analysis procedure can be a sophisticated method for perpetuating a very unsatisfactory status quo, which may please only some mental health professionals and no one else. A third major problem in the use of this technique is essentially based on the experience that the authors and some of their colleagues have had with other attempts to plan scientifically, using any form of systematic method. The expectations of the mental health professional, and the community, may be too great, considering the present state of the art of systems analysis. It is not a cure-all, although it is presently a fashionable technique in both natural science and social welfare areas. One should not confuse a research and planning technique with a system of moral values, a religion, or a universal panacea. Systems analysis is a technique, and as such it must prove its usefulness in each new situation. As with any technique, it may be more useful in some situations than in others. A fourth problem involves the issue of "economizing" in health areas, Techniques which analyze the distribution of time, resources, and professional activities are not "loyal" to any professional group, Nor do these techniques respect the usual status hierarchy of the service professions as to which are thought to be more important and which less important. Feelings may be hurt and antipathy generated against any research group which applies cost-effectiveness analysis to a service area. On the other hand, the technique itself can be perverted into a method for showing the cheapest way to provide service, which may not be the most advisable way to plan mental health services (or any community services) in the long run. If the true goal is objectivity and increase in effectiveness of service to the community, it should be possible to communicate this to the concerned service professions and gain their cooperation. Finally, there is the problem of time limitations and the time needed to carry on a comprehensive systems analysis. This could be called the problem of the harassed administrator. Systems analysis techniques are not by any means the fastest way to get an answer. The fastest way is to make a "seat of the pants" judgment and fire away. Yet these judgments have turned out wrong as many times as they have been right and, once the decision is made, it is no longer possible to consider alternatives. Therefore the more important the plan, the longer the period of time with which it is concerned, and the more the administrator is interested in considering alternatives, the more relevant systems analysis techniques become. They do not
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p r o d u c e quick a n d easy solutions, b u t ttttBr m a y atttt to the scope of the k n o w n in the m e n t a l h e a l t h f i e l d - - a field, like m a n y others, full of p u z z l i n g unknowns. APPENDIX The mathematics of the approach presented in the body of the article involves the use of "input coefficients" and systems of simultaneous equation. Let the quantity of the output of sector i absorbed by sector j per unit of its total output j be described by the symbol Aij and be called the input coefficient of the product of sector i into sector j:
(l)
Xij A i j - Xj
In thousands, Table 5 in the text in raw form is: I II III
I
II
III
I25 2,200 4,400
:~o0 75~ 400
275 "r5o 3,200
6,625
1,25o
3,625
500 3,00o 8,000
The coefficient matrix, following Formula (2) above, is for the table:
275/8000
225/500 2200/500 4400/500
Ioo/3ooo 750/3o00 400/3000
250/8000 3200/8000
925o 4.200 8.800
or .033 .25o .233
.034 .0i 9 .4oo
For the use of this matrix of input coefficients in systems of simultaneous equations, solvable by matrix inversion techniques, see Leontief, 2962, pp. 238-242. REFERENCES Brenner, H. H. Economic change and mental hospitalization: New York State, 19Io-I960. Social Psychiatry, 2967, a, 28o-288. Caplan, G. Principles of preventive psychiatry. New York: Basic Books, 2964. Hollingshead, A., & Redlich, F. C. Social class and mental illness. New York: John Wiley, 2958. Keynes, J. M. The general theory of employment, interest, and money. London: Macmillan, I936. Leontief, W. Input-output economics. Cambridge: Harvard University Press, 296i. Lessing, L. Systems engineering invades the city. Fortune, January, 2968, 77, 155-257 9 Mauss, M. The gift: forms and functions of exchange in archaic societies. New York: Free Press, 2954. Parsons, T. The social system. New York: Free Press, 2952. Parsons, T., & Shils, E. A. (Eds.). Toward a general theory of action; Cambridge: Harvard University Press, 2952. RCA Systems Development (Smith, T. A., Patterson, T. G., & Everhard, F.) Descriptive organizational brochure. Camden, N.J., 2968. Smelser, J. N. The sociology of economic life. Englewood Cliffs: Prentice-Hall, 2963. Spencer, H. The study of sociology. London: Appleton, 1924.
