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c:) Approaches to Measuring Demand and Supply CONGRESS DIRECTED that this study identify projected needs, availa- bility, and requirements of various types of health care delivery systems for each type of allied health personnel." Before it could respond to this charge, however, the committee had to resolve several issues of scope and approach. 1. Current versus future "needs, availability, and requirements" The com- mittee believes that, given its limited funds and time, it can make a greater contribution by providing its best assessment of future needs and require- ments for allied health personnel and its best assessment of the kinds of adjustments that will be needed to meet those needs and requirements. Although it recognizes that there is intense interest in the current situation, the committee believes that most of the study's resources would have been exhausted in performing a systematic assessment of that situation. The future outlook, on the other hand, is crucial to strategic planning and policy; therefore, the committee chose to devote most of its efforts to developing a picture of the future. To the extent that it became aware of perceptions of current imbalances in demand and supply of allied health personnel as the study progressed, those perceptions are noted in the report. 2. "Each type of allied health personnel" As the charge implied and the committee clearly recognized, it is neither feasible nor useful to consider the needs and availability of allied health personnel collectively. The allied health rubric comprises occupations with varying labor market character- istics (e.g., paths of entry, levels and types of responsibilities, wages and 44

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MEASURING DEMAND AND SUPPLY 45 salaries, labor force entries and exits, and work sites). As a consequence the demand and supply situation must be considered separately for each occupational field. The approach used in this study has been to examine 10 allied health fields in some depth to illustrate the diversity among them. To the extent possible, these fields are used as the basis for several general conclusions about the future employment outlook. 3. "Needs, availability, and requirements" Two different approaches are implied by the charge. "Needs," as used in the context of health personnel planning, refers to a normative idea of the number and type of personnel required to provide therapeutic and preventive services to a defined pop- ulation. Need is usually defined independently of economic constraints. Demand (or effective demand), on the other hand, refers to the number and type of personnel required to fill the available jobs and provide services for which consumers are willing and able to pay. The committee elected to assess future needs and requirements in terms of the effective demand for allied health personnel. This decision was based on the committee's judgment that this approach is of most use for realistic planning. However, in the case of long-term care (see Chapter 8), the committee chose to take a patient-centered approach in examining the future need for allied health personnel. 4. Planning horizon The committee selected the year 2000 for its pro- jections of future demand and supply. Because most of the available base data are for 1986, this decision means, in effect, looking ahead 15 years. The committee recognizes the great uncertainty that goes with so long a horizon. Yet many decisions require some assessment of the future, how- ever rough, and the types of decisions that affect the labor market for allied health practitioners (e.g., starting or modifying educational pro- grams) necessitate long lead times. On balance, then, the committee's de- cision was to take the long view. DATA FOR ASSESSING DEMAND AND SUPPLY The committee was limited to the use of existing data as the basis for its assessment of demand and supply in allied health fields because it was not possible to design, field, and analyze a survey within the available study time, particularly considering the requirement for the Office of Manage- ment and Budget's approval of such a survey. The paucity of existing data on allied health fields severely constrained the committee's ability to carry out its charge. Thanks in large part to significant federal investments in developing data bases in medicine, dentistry, and nursing, previous Insti- tute of Medicine (IOM) studies of those fields have been able to draw on large amounts of data and on requirements and supply projections made by the Bureau of Health Professions of the Department of Health and

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46 ALLIED HEALTH SERVICES Human Services based on those data. In the allied health fields, however data are limited. Nonetheless, some data do exist. BLS collects information on employ- ment, earnings, and labor force behavior of a number of allied health occupations in its ongoing analysis of the U.S. work force. The decennial censuses and the Current Population Survey offer detailed information by occupation. In addition, allied health associations conduct surveys of their members that provide invaluable data on persons meeting their member- ship criteria. Associations of hospitals, nursing homes, and home health care agencies also collect data on employment in their constituent institu- t~ons. The committee has examined these and other data sources to inform its assessment of personnel demand and supply. In the sections that follow, we point out problems and weaknesses in the data and offer some sug- gestions for improvement that, if heeded, will ease the way for future studies. ASSESSING CURRENT DEMAND AND SUPPLY How do we know if there is a current shortage of allied health personnel? This is not a straightforward question. First of all, the term shortage has a variety of meanings. Sometimes it is defined normatively: a shortage exists if there are fewer respiratory therapists than are needed, according to some definition of need. Economists define a shortage as a situation in which fewer people are employed than employers would like to employ at the current wage. Although they may be cognizant of other factors that influ- ence employers' decisions to employ workers and prospective employees' decisions to seek work, economists traditionally focus on levels of salaries and wages, and sometimes on fringe benefits, as the principal variables that equilibrate employer demand and the labor supply.* According to eco- nomic theory, if the labor market were functioning properly, a shortage could exist only temporarily because employers would pay more to attract more workers until all jobs were filled. Thus, economists view any labor shortage as reflecting either a lag in the adjustment of the labor supply to demand or an imperfection in the functioning of the labor market. For example, if the demand for labor grows at a rapid rate over a period of time, a temporary labor shortage may occur. Barriers to adjustment can also result in labor demand and supply not coming into balance. These factors will be described later. *This explanation is somewhat oversimplified, however, because other aspects such as the risk involved in work and working conditions are also considered in economic analyses of labor d mend and supply.

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MEASURING DEMAND ED SUPPLY 47 A shortage can occur over the short term or the long term, although long-term shortages are unusual unless there is some market imperfection such as a price ceiling that prohibits market adjustments. In the short term, workers must be recruited from the existing pool, and employers must use existing technology. Over the long term, however, new workers can be trained and new technologies employed to change the nature of the work. Indicators of a Labor Shortage A number of signals can indicate that labor shortages exist. Such signals include large numbers of job vacancies, rising compensation levels, and low unemployment levels. Vacancies The most commonly cited indicator of a labor shortage is job vacancies. A large number of vacant positions or a high ratio of vacancies to total employment is taken as evidence of a shortage. "Large" and "high," of course, are relative to some expected level of vacancies. This expectation may be based on historical vacancy levels for the occupation of interest or on a comparison with current vacancy levels in other occupations. There are some vacancies in an occupation at all times because of job turnover. Because job mobility is important to a well-functioning labor market, such vacancies can be viewed as a sign of the market's health rather than its pathology. As Hall (1978) has pointed out, The role of vacancies can only be understood against the background of the ceaseless motion within the labor market.... Every month, several million workers change jobs, and hundreds of thousands of others move in and out of the labor force. Much of this turnover is attributable to fluctuations in the labor requirements of individual employers and the rest to the changing circumstances of individual workers. vacancy rates are not reliable indicators of job opportunities for several reasons. For one thing, the highest rates occur in occupations with the highest turnover; construction work is an example often cited. Among the health occupations, turnover is much higher for nurses' aides than for highly trained personnel (e.g., medical technologists or physical therapists). In addition, reported vacancies should be viewed with caution because they do not always represent a shortage. If, through one mechanism or another, wages are kept below the level that would bring demand and supply into equilibrium, employer demand will always exceed the number of allied health personnel who want to work at the going wage. Such excess demand cannot really be characterized as a shortage but rather as an imperfection in the operation of the market.

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48 ALLIED HEALTH SERVICES Sloan (1975), Yett (1975), and others have pointed out in the context of nursing that if the labor market is not competitive and therefore one or several employers have some control over wage levels, the market can be in equilibrium even though there are vacant jobs. In this case, an employer would report vacancies but would not raise wages to fill them. Another possible explanation for market equilibrium in the midst of vacancies is the systematic undervaluation of work in occupations in which female workers predominate. Institutional barriers long-standing custom, the misperception of market conditions by employers, and inflexible recruit- ment practices rather than an insufficient number of qualified persons available to work may account for vacancies. Compensation Levels Another signal that is often interpreted as indicating a shortage is rising compensation levels. Wages are the element that is most easily observed, but compensation in this instance means the entire package offered by employers: wages or salaries, benefits, hours, and conditions of work. If employers are unable to attract workers with their current package, pre- sumably, they will improve it. Increases in compensation levels, however, are not in themselves evidence of a shortage. Rather, they may indicate normal and often temporary market adjustments in an environment of rising demand. Relative changes in compensation levels are better indicators of labor market conditions than are absolute changes. If the earnings of physical therapists are rising much faster than earnings in, for example, medical technology or teaching (fields that require similar educational investments) and if employers are unable to fill vacant physical therapist positions, we might conclude that there is a shortage, or at least that, at present, demand is outstripping supply. If market signals are sufficiently strong that is, compensation rises, unemployment drops, and so forth the shortage pre- sumably would be alleviated over time by new entrants to the physical therapy field. The interim may bring painful dislocations, however. Services may have to be curtailed, or substitute workers may have to be employed, with an unacceptable decrement in quality. In some industries, of course, such dislocations are viewed as normal. Unemployment Levels Some frictional unemployment (a level of unemployment resulting from the time involved in changing jobs) is characteristic of a dynamic labor market in which people change jobs, often with an interval in between. Unemployment levels will tend to be relatively higher in occupations with

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MEASURING DEMAND AND SUPPLY 49 high turnover. Very low unemployment levels (virtually everyone seeking employment is finding it) are another signal that may indicate a labor shortage. Low unemployment levels are especially indicative of shortages if vacancy levels remain high. The employment experience of new graduates is one indicator of con- ditions in the labor market. If, for instance, most physical therapy graduates find work in the field within a year after graduation, the labor market may be tight. As with the other signals mentioned above, however, caution must be exercised in interpreting such signals. New graduates can be hired at lower wages than experienced therapists, and some employers may prefer to substitute less experienced workers for more experienced ones to keep costs down. In addition, new graduates tend to be more mobile; therefore, their experience may be more favorable than that of other, less mobile workers. Any one of these signals alone does not indicate a shortage. On the other hand, when a number of them occur together, especially if they persist over time, it becomes ever more likely that there is a real problem. If employers are constrained from making such adjustments as substituting less highly trained employees for more highly trained ones (for example, substituting corrective therapists for physical therapists) or importing work- ers from abroad, or if the necessary adjustments are unacceptable to society, it would be fair to call the problem a labor shortage. Data for Assessing Current Vacancies National data on job vacancies are not available. For both technical and budgetary reasons, BLS does not collect vacancy data. The American Hos- pital Association collects data on allied health employment but not on vacancies. Qualitative assessments are often made in surveys of local em- ployers by, for example, education administrators. Surveys by professional associations may include questions about their members' perceptions of the labor market in their communities. Anecdotal data are reported in health care journals and newsletters from time to time. In addition, regional or state development bodies such as the state-sponsored Massachusetts Tech- nology Development Corporation sometimes attempt to make assessments. Data on Salaries and Wages The BLS Industry Wage Survey program collects and publishes average straight-time hourly wages for selected occupations in hospitals and nursing homes in 23 standard metropolitan statistical areas (SMSAs). Hospital sur- veys were conducted in 1978, 1981, and 1985; the allied health occupations that were covered included diagnostic medical sonographers, electroen- cephalographic technicians, electrocardiographic technicians, medical lab-

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50 ALLIED HEALTH SERVICES oratory technicians, medical technologists, nuclear medicine technologists, radiation therapy technologists, radiographers, surgical technologists, die- titians, medical record administrators and technicians, and all of the therapy occupations. The survey excluded such elements of compensation as pre- mium pay for overtime and work on night shifts or holidays and such in- kind compensation such as room and board. Fringe benefits were also excluded. These data are quite useful for examining trends in basic wages in urban hospitals and nursing homes and for comparing wage levels among SMSAs. Occupational earnings are available from the Census Bureau's Current Population Survey. Data on the earnings of allied health association mem- bers are collected through member surveys. In addition, the University of Texas Medical Branch at Galveston annually surveys 33 hospitals, 16 med- ical schools, and 28 medical centers. Unemployment statistics are collected monthly by BLS. Although ex- tremely useful in the aggregate, these data have some weaknesses when used to assess market conditions in specific occupations. Unemployed per- sons are classified by the occupation in which they were last employed. Thus, a person seeking work as an audiologist whose last job was as a teacher would be categorized as an unemployed teacher. Recent graduates seeking their first job are excluded from the unemployment figures by occupation. As with other market indicators, BLS occupational unemploy- ment data must be used carefully and only after being critically examined. Surveys by allied health professional associations generally elicit infor- mation on whether their members are employed and where. Less fre- quently do they provide information (e.g., whether the respondent is looking for work) that would complement data from the Current Population Sur- vey. CAHEA has conducted surveys of education program directors about offers to their graduates as a means of assessing the job market; some state education departments conduct similar surveys. In addition, individual educators sometimes survey employers in their community regarding em- ployment opportunities. How to Improve Data on Current Allied Health Personnel Demand and Supply The balance between the current demand for and supply of allied health personnel is of concern to a wide range of organizations, to educators seeking jobs for their students, to facility administrators who are unsure about the availability of needed personnel, and to allied health practitioners and the associations that represent them, all of whom are concerned about jobs, compensation, and career prospects. In functional terms an assessment of current personnel demand and supply is the essential baseline data point from which projections start. Current information about the labor market

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MEASURING DEMAND AND SUPPLY 51 also enables those in positions to do so to act early to prevent the occurrence of serious imbalances and the need for major corrective action later. In the previous sections, we have noted the types of data that are needed to estimate current demand and supply. Some of these types of data are available but usually only for certain allied health fields in some localities. Health care institutions are already responding to heavy demands for op- erating data and are reluctant to add to their burden in the absence of a belief that such data will serve their interests. Additional data collection activities should be undertaken only after a careful consideration of the benefits of such efforts and of ways to minimize the burden of undertaking them. The data to assess current labor market conditions are more readily available for other health care professions such as physicians and nurses- than for allied health fields. The committee believes that the lack of data about allied health fields, compared with the data available on other types of providers, reflects an underestimation of the role of allied health prac- titioners in the health care system. Both the large contribution to care made by such practitioners and the high total costs associated with the aggregate use of allied health professionals strongly suggest that data collection strat- egies that allow the assessment of current personnel demand and supply should be seriously explored. For example, associations of employers could try to develop simple, inexpensive surveys to learn about problems in recruiting. Survey questions might include the following: What kinds of employees are you finding the most difficult to recruit? Are you using any exceptional recruitment mea- sures? What actions are you taking to cope with vacancies? These surveys might be conducted in a small sample of "sentinel" institutions as frequently as twice a year. Professional associations should use standard labor statistics terminology to increase the usefulness of their surveys to BLS and vice versa. It is especially important to count people who are not working but who are actively seeking work; these are the people the U.S. Department of Labor categorizes as unemployed. Professional associations should also explore longitudinal studies of a sample of their members; studies of this type could provide better data on members' work histories, labor force participation, earnings, and other characteristics than can be gathered from the cross- sectional surveys that are usually conducted. In addition to technical im- provements, associations should look for ways to make their research more relevant to current policy issues. Associations would be well served to strengthen the links between their research and policy functions. The committee also recommends that the U.S. Department of Health and Human Services' Health Resources and Services Administration (HRSA) reconstitute the Forum on Allied Health Data as a technical assistance endeavor. HRSA should also hold workshops with experts in survey design,

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52 ALLIED HEALTH SERVICES statistics, and labor economics to help the allied health associations improve their data collection programs. Other possibilities for improving the infor- mation on current labor market conditions for allied health personnel include the following: When renewing licenses, state licensing bodies could ask whether ap- plicants are currently employed in their field, employed in another occu- pation, looking for work, or not looking for work. State and regional health planning agencies could make larger in- vestments in education and employment data and planning. They could also operate as an important link between educational institutions and employers. Educational institutions could pool information on the job-finding experiences of recent graduates and alumni. Local experience could be aggregated to develop state and national pictures. ASSESSING FUTURE DEMAND AND SUPPLY Forecasts of the future are often inaccurate, either because they do not take into account all of the relevant factors or because the factors change in ways that were not or could not have been predicted. Yet decision making is based on assumptions about the future, however crudely they are formed. The committee's task has been to use the limited data available to formulate a "best guess" and to let that projection inform its recommendations. Thus, the committee's recommendations are based on the interpretation of gen- eral trends in the work force and in the economy and of specific projections for selected allied health fields. Several approaches are possible to assess future needs and requirements for allied health personnel. Some of the approaches that have been used for other types of health manpower fields are described below to illustrate the available assessment options, the ways they can be used, and the types of data that are needed for their use. Needs-based projections usually define the number of personnel re- quired to provide a given set of services to a defined population. The needs approach, which was pioneered by the Committee on the Costs of Medical Care in the 1930s, involves two types of judgment: (1) the quantity and type of health care services judged to be appropriate, and (2) the appro- priate division of responsibility for those services among the various types of health care personnel. The projections that finally result depend on who makes these judgments and on their views of what constitutes good health care. Needs-based models represent an unconstrained social ideal: they are norms against which to compare actual performance. They can be used to establish health care program objectives and to assess the probable avail- ability of personnel to meet those objectives.

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MEASURING DEMAND AND SUPPLY 53 The Graduate Medical Education National Advisory Committee, which was established by the secretary of health and human services in the late 1970s, used a needs-based approach to project physician requirements for 1990. The committee began with estimates of the incidence of particular illnesses or medical conditions in the population and then made judgments about which conditions required medical care, how many visits would be required, and how many of these visits might be "delegated" to persons other than physicians. The total estimated visits were transformed into physician requirements based on assumptions about productivity (Jacoby, 1981). A model of requirements for nurses developed by the Western Interstate Commission on Higher Education also had its foundations in judgments of need. Panels of nurses provided professional judgments about desirable changes in health care delivery and about the mix of registered nurses (RNs) and licensed practical nurses (LPNs) needed to provide the desired services (Bauder, 1983~. Another approach to projecting health care human resources require- ments is to extrapolate from current levels. Instead of assigning ideal health care services utilization levels (and their corresponding health care per- sonnel requirements) to projected population segments, current utilization levels are projected into the future. Most simply, current health care per- sonnel-to-population ratios are applied to population projections. The Bu- reau of Health Professions of the Department of Health and Human Services uses this method to project physician requirements by starting with current utilization levels and then adjusting for projected changes in population, trends in health insurance benefits, and other factors that affect utilization such as the cost of health care services. Productivity assumptions are used to translate projected utilization into the number of physicians required. The Division of Nursing also employs a model that projects population, per-capita use of health care services, and the associated required numbers of RNs and LPNs. The simplest extrapolation models are strictly mechanical; the health care personnel-to-population model is an example. More sophisticated models incorporate "behavioral" components, such as the price elasticity of demand for health care services, and then make independent projections of prices. They may also incorporate changes in production technology for ex- ample, capital-labor substitution or the division of tasks among health care personnel. As extrapolation models become more sophisticated, they begin to re- semble models of economic demand. A demand model is based on the relationship of such independent variables as health status, income, and prices to the demand for health care services. In the case of labor demand, the model is based on such variables as wages, the price of capital, and product prices. Although not strictly a demand model, the BLS projections

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54 ALLIED HEALTH SERVICES of employment are made in the context of projected labor force and eco- . . . nomlc actlvlty. The committee chose to rely heavily on the BLS employment projections for its assessment of future demand. The principal reasons for this reliance were the following: ~ The BLS projections are grounded in projections of the entire econ- omy, which include projections of the work force and levels of economic activity. Health care expenditures and health care industries employment are estimated in the context of growth in other types of expenditures and employment in all other institutions. BLS's projections use a consistent methodology across occupations. Not only can the allied health occupations be compared with each other, but they can be viewed in the context of all other occupations for which projections have been made in the same way. The BLS projections are widely known and used; they are reviewed regularly and revised biennially. The committee did not, however, use these projections uncritically. It took several factors into account in using the BLS data: Occupational employment projections are subject to considerable er- ror, more so than the projections of total employment by industry. BLS staff use their knowledge and judgment to project the number of jobs for each occupation in an industry. For the health care industry, many judgments have to be made about how changes in health care fi- nancing and delivery will affect different occupations. Because these judg- ments by BLS staff are not published, it is difficult to subject the results to a critical assessment. The occupational definitions used by BLS are not identical to those of professional associations or educators. Although great improvements have been made in the system of occupational classification, BLS definitions still rely more heavily on functions and less heavily on credentials. In addition, the data are not adequate in some cases to distinguish among different levels within occupations. For instance, BLS combines data for laboratory technologists and technicians. In some instances (e.g., for per- fusionists, dialysis technicians, and cardiovascular technologists), no em- ployment projections are made. (See Appendix E for further discussion and evaluation of BLS data.) HOW BLS MAKES EMPLOYMENT PROJECTIONS Because the committee relied heavily on BLS for its assessment of future demand, it is important to understand how these projections are made.

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MEASURING DEMAND AND SUPPLY 55 BLS projections are made from a base year to a target year. The base for the bureau's most recent projections was 1986; the target year was 2000. Harold Goldstein, in a background paper (1987) prepared for the com- mittee, characterized the BLS approach as follows: The basic approach followed is to estimate the employment in each occupation that ~ ~ A will be generated by economic demand. This goes back to the demand for the goods or services the occupation provides, and this in turn is affected by the total spendable income available to consumers and government and to the changing patterns of what they spend it on. These are influenced by a wide variety of social and economic factors, including changing tastes and styles, scientific discoveries and technological change affecting both what is produced and how it is produced, the growth and changing composition of the population, taxation and government expenditures policies ("guns or butter") and what other countries are buying from and selling to us. There are several steps in the projection sequence, the first of which is . . 1 ~ ~ ~ the projection of the labor force. The foundation for this projection is the Census Bureau's population projections by age, sex, and race, which are based on assumptions about birth rates, death rates, and migration in and out of the United States. Labor force participation for each age, sex, and race group is projected by extrapolating from past participation rates. The projected labor force participation rates are applied to the corresponding population projections to arrive at the projected labor force in the target year. Next, BLS uses a macroeconomic model to develop projections of the gross national product (GNP) and major categories of demand and income. Some of the assumptions that affect the macroeconomic model, such as population projections, are fairly certain; other assumptions, such as net imports, energy prices, and the exchange value of the dollar, are quite uncertain, depending as they do on international political and economic developments. Because assumptions about certain key variables have major impacts on the projections, BLS produces three sets of macroeconomic projections based on differing sets of assumptions. These assumptions in- volve the levels of expenditures in major components of federal spending, the major components of state and local government spending, the size ~ . ~ and composition ot the population, and the key variables underlying for- eign trade. Low, medium, and high projections of GNP are then produced from differing assumptions for each of these variables (Table 2-11. The effect of these variations in assumptions can be seen in the figures for GNP and employment. The low, moderate, and high GNP projections that result from these and other assumptions are (in billions of dollars) $4,617, $5,161, and $5,552, respectively. The corresponding projections of total employment (in thousands) are 126,432, 133,030, and 137,533 (Monthly Labor Review, 19871.

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56 ALLIED HEALTH SERVICES TABLE 2-1 Assumptions Used in Making Spending and Labor Force Projections for the Year 2000 Variable Federal defense spending ($ billions) Federal nondefense spending ($ billions) State and local spending on education ($ billions) Size of the civilian labor force (millions) Low 222.5 97.3 195.3 134.5 Moderate High 25 1.0 1 03.4 223.1 138.8 263.0 108.2 232.5 141.1 BLS next estimates the principal GNP components: personal consump- tion of durable and nondurable goods and services, capital investment, foreign trade (imports and exports), and government expenditures. These estimates of final demand are translated into estimated levels of production for each industry in the economy using an input-output table based on historical relationships that is compiled by the Department of Commerce. The input-output table shows what each industry in the economy pur- chases from every other industry. For example, the automobile industry purchases raw materials (iron ore), intermediate products (tires and glass), and services (electrical power and transportation) from other industries to produce its final product, automobiles (Goldstein, 1987~. This step in the projection process results in estimates of the level of production for every industry in the target year. The next-to-last step is the estimation of total employment for each industry from a regression equation that estimates worker-hours as a func- tion of industry output, the unemployment rate (a measure of capacity utilization), the relative price of labor, and the ratio of output to capital. The estimated worker-hours are translated into the number of workers by dividing worker-hours by the estimated annual hours per worker. Finally, BLS develops estimates of occupational employment by industry, using base year data on the distribution of industry employment by oc- cupation. Sources of data for these estimates include the Occupational Employment Survey conducted periodically by state employment security agencies under a BLS-state cooperative program (see Appendix E for a discussion of OES and other data sources), the decennial census, and the Current Population Survey. In projecting occupational employment in each industry, adjustments are made in the occupational composition of the industry. In the BLS estimates, the health services industry is broken down into components that reflect the different employment settings (e.g., hospitals, physicians' offices, nursing homes). The next step of the process takes into account factors that are not explicitly included in the mathematical model. BLS analysts with responsibilities for specific occupations consult experts (e.g., the staff of the professional associations), use the relevant literature,

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MEASURING DEMAND AND SUPPLY 57 and make site visits to assess whether staffing patterns are likely to change and if so, how they will change. Because the aggregate employment for each industry provides the parameters of employment, BLS analysts confer with each other to determine how each occupation in each industry will fare relative to one another. For example, the analysts who follow health occupations will meet to discuss hospital staffing patterns, the changes that are expected, and why those changes will occur. Factors that are taken into account include new technologies that are likely to change staffing intensity, changes in insurance coverage, and regulatory policies that may influence the demand for a service or individual occupation. Table 2-2 shows the BLS low, moderate, and high projections of em- ployment in the allied health fields for the year 2000. The differences among the three projections are attributable to different assumptions about economic growth and aggregate employment. The same assumptions about and adjustments to the occupational distribution of employment are used in all three groups of projections. . TABLE 2-2 Bureau of Labor Statistics Wage and Salary Employment (in thousands) in the Allied Health Fields, Actual for 1986 and Projections for the Year 2000 Occupation Clinical laboratory technologists and . . tec nnlclans 1986 Employment Lowa Projected Employment for the Year 2000 Moderateb Highc 238 87 40 r ~ Dental hygienists Dietitians Emergency medical technicians Medical record technicians 40 Nuclear medical technologists 10 Occupational therapists Physical therapists Radiologic technologists and . . tecnulclans Respiratory therapists Speech-language pathologists/ audiologists aThe low projection reflects annual growth rates of 1.6 percent in GNP, 1 percent in the civilian labor force, and 0.9 percent in employment. bThe moderate projection represents annual growth rates of 2.4 percent in GNP, 1.2 percent in the civilian labor force, and 1.2 percent in employment. CThe high projection represents annual growth rates of 3 percent in GNP, 1.3 percent in the civilian labor force, and 1.5 percent in employment. SOURCE: Silvestri and Lukasiewicz, 1987. 26 56 114 56 42 285 134 52 73 67 12 43 109 296 141 54 75 70 12 45 115 183 190 74 76 58 307 145 55 77 72 12 46 118 196 78 61 63

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58 ALLIED HEALTH SERVICES FUTURE SUPPLY In a dynamic labor market the supply of workers in an occupation is constantly changing. New graduates emerge from education programs. People enter the labor market who have worked in other occupations or who have studied related subjects. Individuals leave the work force and later reenter; some leave permanently. Projecting the future supply of workers in an occupation requires, first, an estimation of how many people are in the field in a base year and then an estimation of the various inflows and outflows that will occur between the base year and the target year. Which inflows and outflows are important depends on the purpose of the projection. For example, in the nursing field, there has been concern voiced about the many trained nurses who are outside the nursing work force, either working in other fields or not working at all. Although data on licensed nurses provide a picture of those nurses who keep their licenses active, some have argued that there may be many nurses who have dropped their licenses but who, in some sense, constitute a potential supply. If market conditions warrant, the argument goes, these nurses could be attracted back to work, even if some retraining were necessary. This pool of trained workers can be estimated and projected using data on the number of graduates and applying standard mortality rates to each age group. The supply estimated by this life table approach represents an estimate of all living nursing graduates (Institute of Medicine, 19831. For this purpose, the only inflow is new graduates, and the only outflow is death. However, if the question is whether there will be enough nurses to fill the jobs that we expect to be available in the future, more information is needed about the likelihood that those who are not in the work force will reenter it. We also need to know about the likelihood that nurses who are in the work force will leave. Variations in the rates of reentry and loss from the labor force and the average time practitioners spend in the labor force produce large differences in the supply projected for the future. For most purposes, it is the "effective" supply of health personnel, trained and want- ing to work, that is of greater interest. The committee, where feasible, has projected the future supply of work- ers in allied health fields in the year 2000, assuming inflows to and outflows from the labor market remain as they were in 1986 and the number of allied health program graduates remains at the current level. These as- sumptions are unrealistic, but they are used to indicate the magnitude of change that must take place to meet future demand. The committee used a simple arithmetic equation to arrive at its projections. The work force at the beginning of one year was said to equal the work force at the beginning of the year before, minus those persons leaving the work force for reasons

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MEASURING DEMAND AND SUPPLY 59 other than unemployment, plus graduates of allied health programs and other additions. These additions include people resuming work and people transferring from other occupations. The base year for our observations was 1986. To achieve comparability among fields, the BLS estimate of total employment for each occupation was used. An estimated number of unemployed practitioners was added in each case. For some allied health fields the number of graduates in 1986 was as- sumed to remain constant through the year 2000. When it was reasonable to do so, the 1986 share of bachelor's degrees granted in a field, relative to all bachelor's degrees granted, was applied to the Center for Education Statistics' projection of bachelor's degrees to be granted each year through 2000. Labor force accession and separation rates that BLS derives from Current Population Survey data were used to determine additions to and losses from the work force. Because the sample size of most allied health fields in the survey is small and estimates are subject to great sampling variability, we used rates of labor force accession and separation for larger groups. For example, the rates for therapists overall were applied to physical, oc- cupational, and respiratory therapists separately. In approximating addi- tions to the work force, the accession rate for 1983-1984 was applied to the 1984 work force to generate an estimate of the number of persons who joined the work force in 1984. That number was held constant each year. . . . Chapter 4 brings together the committee's information about the de- mand for and supply of allied health practitioners. The BLS employment projections for each field to the year 2000 are evaluated in light of expec- tations about the forces that drive demand. The results of the process to estimate the supply of workers that has been described in this chapter are compared to the expected demand. To this, the committee has added its knowledge of how the fields are faring in current labor markets and the trends in the fields in numbers of graduates and programs to make an assessment of the future balance between demand and supply. DATA FOR PROJECTING THE FUTURE SUPPLY OF ALLIED HEALTH WORKERS Current (Base Year) Supply The BLS Industry-Occupational Employment matrix estimates the number of employed persons in each of 480 occupations. It is not an unduplicated count; wage and salary workers holding two jobs would be counted twice. The most recent data, used as the base for employment projections to the

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60 ALLIED HEALTH SERVICES year 2000, were for 1986. The next year for which these data will be available is 1988. The occupational classifications used in the Occupational Employment Survey, the principal source of data for the matrix, are consistent with the standard occupational classifications used by all federal agencies that collect data. They represent a balance between comprehensive coverage that pro- vides quality data and the ability (and willingness) of employers to respond. (Appendix C gives the current definitions used in hospitals.) These cate- gories and definitions should be continually evaluated and modified, if necessary, to portray the allied health work force accurately. The other data source for examining the base year supply of workers is membership data from allied health associations. For fields that are well defined and have a single route of entry, and in which the associations represent a very large proportion of the field (e.g., occupational therapy), this source usually provides a good estimate. For many allied health fields, however, association membership data are incomplete or nonexistent. (See Appendix D for a discussion of the different sources of data on the supply of workers for each field.) New Entrants For fields in which the bachelor's degree is the entry-level educational requirement, there are two main sources of data. The U.S. Department of Education collects historical data on degrees awarded by field of study. These data include the allied health fields of occupational therapy, physical therapy, dental hygiene, medical record librarianship, medical laboratory technologies, radiologic technologies, and speech pathology and audiology. The Center for Education Statistics periodically makes projections of the total number of bachelor's degrees and the number of awards to men and women. These projections are based on mathematical projections of his- torical trends in college enrollment by different age groups. As discussed earlier, the committee has projected new entrants from bachelor's degree programs in some fields by assuming that the field's share of bachelor's degrees in the years 1987 through 2000 will remain constant at the 1986 level. The second principal source of data on new graduates is the bodies that accredit education programs. CAHEA is the largest, representing 24 allied health field occupations in 1987. Others include the American Physical Therapy Association and the American Speech-Language-Hearing As- sociation. Estimates of the number of future new entrants to the various fields can be extrapolated from historical figures on graduates. Individual states can use data from their own higher education institutions.

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MEASURING DEMAND AND SUPPLY 61 Other Inflows The weakest links in projecting the future supply of allied health workers are the data for estimating entrants from outside the labor force, from other occupations, and from abroad (immigration). These inflows (and mirroring outflows) are important short-run labor market adjustment mechanisms. The BLS staff has made some headway by matching Current Populaton Survey data and calculating inflows and outflows for the matched observations (Eck, 1984~. Yet for occupations with small numbers of work- ers (such as many of the allied health fields), these estimates are based on an extremely small number of observations. Estimating inflows and out- flows of workers is an area in which the professional associations could do a great deal to improve the data. The Forum on Allied Health Data, with the help of appropriate expert consultants, should give attention to this serious data weakness. CONCLUSIONS AND RECOMMENDATIONS The committee found that available data for assessing the current supply of allied health personnel are inadequate, and it suggests that efforts be made to improve these data. The BLS employment (demand) projections are quite valuable and, when used in conjunction with other data, are likely to be the only available demand estimates that are comparable across fields. The federal government has a responsibility to monitor the health care work force and to inform participants in the health care labor market and public policymakers of trends and developments. The work of the Bureaus of Health Professions and Labor Statistics and the Center for Education Statistics is to be commended and should be built upon. To improve the data on allied health fields, the committee recommends that the secretary of health and human services convene an interagency task force com- posed of representatives from BLS, the Center for Education Statistics, and other agencies that collect relevant data on the allied health work force. This task force should work toward increasing the amount and improving the quality of data needed to inform public policy decision makers, health care managers, unions, prospective~students, and aca- demic institutions about the allied health occupations. Staff for the task force should be provided by the U.S. Public Health Service focal point for allied health personnel that is recommended in Chapter 5. REFERENCES Eck, A. 1984. New occupational separation data improve estimates of job replacement needs. Monthly Labor Review 107:3-10.

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62 ALLIED HEALTH SERVICES Goldstein, H. 1987. Projections of demand and supply in occupations. Paper prepared for the Committee to Study the Role of Allied Health Personnel, Institute of Medicine. November. Hall, R. E. 1978. lob vacancy statistics in the United States. Background paper no. 3. Washington, D.C: National Commission on Employment and Unemployment Statis- tics. May. Institute of Medicine. 1983. Nursing and Nursing Education: Public Policies and Private Actions. Appendix 5, Projections of Registered Nurse Supply and Requirements. Washington, D.C.: National Academy Press. acoby, I. 1981. Physician manpower: GMENAC and afterwards. Public Health Reports 96(4) :295. Saunders, N. C. 1987. Projections 2000: Economic projections to the year 2000. Monthly Labor Review 110(9): 11 - 18. Silvestri, G. T., and Lukasiewicz, l. M. 1987. Monthly Labor Review 110(9) :46-63. Sloan, F. 1975. The Geographic Distribution of Nurses and Public Policy. Washington, D.C.: U.S. Government Printing Office.