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Connecting U.S. health expenditures with the health sector workforce.

The National Health Expenditure Accounts ( NHEA) produced by the Centers for Medicare and Medicaid Services report that U.S. health care spending was $2.6 trillion in 2010. More recent estimates from Altarum Institute confirm that the health sector represents 17.9 percent of our national output. The data from the Bureau of Labor Statistics show that the health sector continued to create jobs throughout the recession and recovery and now accounts for nearly one in nine jobs. For the first time, we link the workforce by occupation to national spending on health care services by aligning data sets from the BLS and Bureau of Economic Analysis with the NHEA. We find $1 trillion, or 57 percent of the $1.78 trillion spent on personal health care services, went to health sector labor. Characterizing the health sector workforce and its contribution to health expenditures Worms the potential for spending reductions and the implications of such reductions on employment.

Business Economics (2013) 48, 42-57.

Keywords: health sector, employment, health expenditure, occupation

The National Health Expenditure Accounts (NHEA) produced by the Centers for Medicare and Medicaid Services (CMS) report that U.S. health care spending was $2.59 trillion in 2010. More recent estimates (to September 2012) from Altarum Institute's Center for Sustainable Health Spending show national health expenditures (NHE) at $2.84 trillion, and indicate that the health sector comprises 17.9 percent of gross domestic product (GDP). Figure 1 shows health care spending as a percent of GDP and of potential GDP (PGDP), a measure that reduces business cycle effects and provides a clearer picture of where the health spending share of GDP is headed in the longer term [Roehrig 2011].

Figure 2 shows how total health care spending breaks down among major categories, with hospital care having the largest share by far (32 percent), and physician and clinical services accounting for the second biggest slice (19 percent). Surprisingly, given the large amount of attention devoted to it, prescription drugs account for only 10 percent of total national health expenditures.
Figure 2. Health Spending by Category, September 2012

Dental services 4%

Prescription drugs 10%

Nursing home 5%

Home health care 3%

Remaining personal health] care 11%

Other health spending 16%

Hospital care 32%

Physician & Clinical services 19%

Source: Altarum monthly National Health Expenditure estimates.

Note: Table made from pie chart.


While news reporting seems to stress "skyrocketing" health expenditure growth, Figure 3 tells a different story. Beginning in 2009, official data show the two lowest annual growth rates of health expenditures--hovering near 4 percent--in the 50-plus-year history of the NHEA. Altarum data, shown in Figure 3, suggest this trend has continued into 2012.(1)

The data from the Bureau of Labor Statistics (BLS) in Figure 4 show that the health sector has continued to create jobs throughout the recession and recovery. Since the start of the recession in December 2007, the health sector has added 1.4 million jobs (a cumulative growth of 10.1 percent), while nonhealth employment fell by 5.6 million jobs (a cumulative decline of 4.6 percent).

In 2011, $1.78 trillion of U.S. health expenditures, or about 11 percent of GDP, went to personal health care services received in hospitals, provider offices, nursing homes, and in the home. Correspondingly, as the share of GDP devoted to health care has grown, and the sector has remained a stabilizing force in the labor market during economic downturns (with the Great Recession being a particularly strong example), the share of total employment associated with the delivery of personal health care services has grown to an all-time high of 10.8 percent as of October 2012, as shown in Figure 5. (2)

While the health sector is a source of job creation, this growth must be balanced against concerns about high and growing health expenditures and the multifaceted burden they impose on governments (especially for the federal government given its responsibilities under the Affordable Care Act), businesses, and individuals [Kaiser Family Foundation 2012; PwC 2012]. A variety of strategies are being proposed for reducing health spending and its rate of growth. (3) These strategies may be aimed at either reducing the demand for services or reducing the cost of producing those services. Since labor is the major input to the production of health care services, any reductions in health care volume or costs will almost certainly be driven by, or impact, the health sector workforce.

An in-depth understanding of the nature of the health sector workforce and the contributions of various labor categories to total health expenditures is important for understanding the potential for savings and the implications of any cost saving proposals on employment. Current data sources track health spending and employment separately; but--with the exception of the industry input-output tables, which report a total employee compensation figure--do not connect the two in any detail [Kim, Gilmore, and Joliff 2012].(4) This is a startling realization in light of the size and importance of the health sector. Gene Steuerle, who has for many years decried this lack of detailed analysis, put it this way:
 For at least two decades now, I have argued strenuously that we need
 to expand resources, perhaps in the [CMS] Office of the Actuary, to
 complete the input-output matrix on national health spending. Crudely
 speaking, the CMS provides estimates of output, defined as price (p)
 times quantity (q) of services (sum of p x q). If you assume for ease
 of explanation that wages (iv) to labor (/) comprise most payments
 received (including wages of scientists, insurers, and
 administrators, and profits that are reinvested in humans developing
 newer technology and drugs), then on the opposite side of the ledger,
 aggregate spending comes close to equaling (sum of iv x /). Why do we
 want to develop both sets of estimates? For many reasons. For one, as
 national income accountants know, the complete balance sheet provides
 many checks on consistency, as numbers must now add up equally on
 both sides of that sheet. Second, the more complete picture allows us
 to detect where the growth in payments to individuals lies (e.g.,
 more practical nurses, or more payments to doctors, or more
 scientists, or higher payments to administrators). Third, from a
 policy perspective, it would help us make better judgments about how
 to adjust payment schedules, such as the Medicare physician payment
 schedule, and to assess the related issue of how much rapid expansion
 in some new treatment is driven by large opportunities for individual
 remuneration. (Take, for example, rapid growth in knee operations or
 doctors' owning sleep centers that detect sleep apnea.) Finally, the
 same balancing would then be required when it comes to making
 predictions for the future. For instance, in the actuaries' report,
 an input-output matrix would have provided a reality check through
 implied rates of growth in numbers of providers and related workers,
 as well as their incomes. [Steuerle 2009]


With other pressing demands and financial constraints, the CMS Office of the Actuary (OACT) has not yet been able to pursue this agenda. (5) In this paper, we take a significant step toward filling this critical gap. Our first goal was to establish the feasibility of linking U.S. health sector workforce data with official spending estimates. Given the feasibility of this exercise, we sought to create a data set with both employment and associated expenditures that allow examination of broad labor categories as well as detailed occupations in individual health care delivery settings and the health sector as a whole. We further aimed to generate this data set for multiple years, to better study the relationships among employment, compensation, and health spending. Descriptive information taken from this data set on health sector employment and the contribution of labor to health spending will shed light on the occupations most associated with health spending growth, trends in the health workforce and associated expenditures, and the tradeoffs between jobs and health spending. While this research is thus far long on data infrastructure development and short on policy recommendations, its import should not be lost: absent an input-output framework for the health sector, attempts to rein in spending over the long term will be operating in the dark with respect to which employment categories will be affected, and which provide the most leverage.

In what follows, Section I describes our methods, Section 2 presents our findings, and we make brief concluding remarks in Section 3.

1. Methods

Our approach was to (1) align the data from existing federal data sets on U.S. employment and health spending, (2) adjust the estimates to account for missing elements and definitional differences, and (3) conduct validity checks using other economy-wide and industry-specific data sources, making further adjustments as needed to construct a consistent and cohesive picture that links health sector labor and spending.

We began with employment and wage data by detailed occupation and industry from the BLS Occupational Employment Statistics (OES) survey.

We obtained data from 2002 through 2011 and narrowed our data set to all employment in the health industries plus all employment of health occupations across all industries. For this purpose, we defined health occupations as those beginning with two-digit codes 29 or 31 in the Standard Occupational Classification (SOC) system used by the OES.

The OES data are reported annually for a rolling 3-year, 6-panel survey of about 200,000 establishments (health and nonhealth), making the total sample size about 1.1 million establishments. This represents about 70 percent of establishments in the nation. Data on hospitals, in particular, are collected as a census, meaning that every hospital is surveyed at least once over the three-year period. The large sample size supports a significant level of detail by both occupation and industry. The tradeoff of the three-year rolling panel design is that the OES data are slower to reflect changes in employment or wages over time. Differences in coding schemes and definitions over time can also make time-series analysis problematic.

We obtained estimates of national health spending for personal health care services from the CMS OACT NHEA. Annual NHEA estimates are available historically and are current through 2010. To estimate 2011 spending, we used data underlying Altarum Institute's Health Sector Economic [Indicators.sup.SM] (HSEI) monthly Spending Brief [Altarum Institute 2012]. The HSEI contain spending estimates that are consistent with the NHEA but are available monthly and are more up to date (data released early each month pertain to 2 months earlier).

Figure 6 displays the components of the NHEA that were linked to employment. These components can be termed personal health care services--health care delivered to individuals in hospitals, provider offices, nursing homes, and in the home. Personal health care services accounted for $1.78 trillion in 2011, or about two-thirds of total national health expenditures. (Figure 6 also clearly depicts the categories other than personal health care services that make up NHEA.)

Creating a combined data set of health employment and spending required that we process and clean the source data, map the employment and wage data into the six NHEA personal health care services categories, and make a number of refinements for known definitional differences and discrepancies. This process is described below. Because our goal was to better understand U.S. health spending in terms of production inputs, where possible we adjusted other data sources to match the framework and definitions of the NHEA.

The employment and spending data sets originate from different sources and are designed to serve different purposes. Nevertheless, the use of common coding schemes and a CMS-published crosswalk allowed us to create an initial allocation of employment and wages by occupation to the personal health care services categories of the NHEA. Both the BLS OES and the CMS-published mapping of industries to the NHEA use the North American Industry Classification System (NAICS) coding scheme to identify the industry of employment or health expenditure. We used the crosswalk shown in Table 1 to allocate the BLS OES employment and wage data by industry into the NHEA personal health care services categories. This provided our initial estimate of employment and wages associated with each service delivery category.
Table 1. NAICS Industry Category to NHEA Health
Services Category Crosswalk
NAICS Code and Industry National Health Expenditure
 Account (NHEA) Category

62 Health Care and Social
Assistance

621 Ambulatory Health Care Services

6211 Offices of Physicians Physician and Clinical
 Services

6212 Offices of Dentists Dental Services

6213 Offices of other health
professionals

62131 Offices of chiropractors Other professional services

62132 Offices of optometrists Other professional services

62133 Offices of mental health Other professional services
practitioners

62134 Offices of physical, Other professional services
occupational and speech therapists,
and audiologists

62139 Offices of all other health
practitioners

621391 Office of podiatrists Other professional services

621399 Office of all other Other professional services
miscellaneous health practitioners

6214 Outpatient care centers

62141 Family Planning Centers Physician and Clinical
 Services

62142 Outpatient mental health and Physician and Clinical
substance abuse centers Services

62149 Other outpatient care centers

621491 HMO medical centers Physician and Clinical
 Services

621492 Kidney dialysis centers Physician and Clinical
 Services

621493 Freestanding ambulatory Physician and Clinical
surgical & emergency centers Services

621498 All other outpatient care Physician and Clinical
centers Services

6215 All other outpatient care
centers

621511 Medical and diagnostic labs Physician and Clinical
 Services

621512 Diagnostic imaging center Physician and Clinical
 Services

6216 Home health care services Home Health Care

6219 Other ambulatory care services

62191 Ambulance services Non-NHEA

621999 All other miscellaneous Personal Health Care (not in
ambulatory health care services analysis)

622 Hospitals

6221 General medical and surgical Hospital Care
hospitals

6222 Psychiatric and substance abuse Hospital Care
hospitals

6223 Specialty {except psychiatric Hospital Care
and substance abuse) hospitals

623 Nursing and residential care
facilities

6231 Nursing Care facilities Nursing home care

6232 Residential mental retardation,
mental health and substance abuse
facilities

62321 Residential mental retardation Personal Health Care (not in
facilities analysis)

62322 Residential mental health and Personal Health Care (not in
substance abuse facilities analysis)

6233 Community care facilities for
the elderly

623311 Continuing care retirement Nursing home care
communities

623312 Homes for the elderly Non-NHEA

6239 Other residential care Non-NHEA
facilities

624 Social assistance Non-NHEA

Source: Adapted from U.S. Centers for Medicare and Medicaid
Services, National Health Expenditure Accounts: Methodology
Paper, 2010 Definitions, Sources, and Methods.


Estimates of the self-employed

Since the sampling frame of the OES survey is drawn from state unemployment insurance databases, the OES does not capture self-employed owners of unincorporated businesses. Some portion of health practitioners such as physicians, dentists, chiropractors, and others fall into this category. To form a more complete picture of health sector employment, the U.S. Bureau of the Census, American Community Survey (ACS) was used to develop estimates of the self-employed.

The ACS is a large, household-based -survey that produces estimates of numbers of people employed by self-reported occupation and industry. While the ACS data contain only about half the number of occupations as the OES, the major health industries are represented; and the health occupational detail was sufficient to estimate the proportion of major health occupations that represent self-employed individuals in unincorporated businesses. For each major occupation (for example, physicians and surgeons) and industry, the ACS self-employed unincorporated workers were examined as a proportion of total workers in that category. Factors were developed to apply to the OES data to approximate a number of self-employed unincorporated in each category. For 2011, a total of about 280,000 self-employed workers were added to the 14,200,000 employees captured in the OES, and previous years were comparable in the order of magnitude of the adjustment. While a small number compared with overall health employment, most of these workers are physicians, dentists, or other highly paid practitioners working in the office setting.

Estimates of employee benefits

The OES data reported average annual wages and salaries for each occupation in each industry. To estimate total employee compensation, other sources were used to inflate wage and salary estimates from the OES to reflect the additional cost of employee benefits.

For most industry and occupation categories, the BLS National Compensation Survey (NCS) was used to derive factors to apply to wages and salaries to inflate them to full compensation costs that include benefits. About 30 percent of compensation went to benefits, so we multiplied wages by the derived benefits inflation factor of roughly 1.4. (6) This proportion varied by year and has been increasing slightly over time. For the self-employed, unincorporated workers added into the estimates, it was assumed that benefits would not be as generous, and the benefits inflation factor was set to half of private industry benefits per dollar of wages and salaries (roughly 1.2). While this parameter is somewhat arbitrary, it has a limited effect since benefits for all self-employed workers total less than 1 percent of health sector employee compensation.

For hospital employees, data from the American Hospital Association (AHA) annual survey of hospitals on total payroll, employee benefits, and total employee compensation was used to estimate a somewhat lower benefits inflation factor of about 1.26. AHA data also showed that about a quarter of hospital employees are part-time, which may account for a somewhat lower proportion of compensation going to benefits. Applying this lower benefits inflation factor also resulted in a better alignment between the proportion of total hospital revenues going to employee compensation computed using our data set and the proportion reported by the AHA.

Estimates of federal government health workers

State and local government health services are included in both the NHEA and in the OES employment and wage data. Federal health care services, such as those delivered at military or veterans' hospitals and clinics, are included in the NHEA spending estimates. However, the employment counts associated with these federal programs are not included in the OES data for the health care industries. The BLS receives federal payroll data to estimate federal government employment and wages but does not break out health care delivery from other government activities, so the OES federal government health employment figures are counted as federal government employment.

Since the NHEA also report spending by source of funds, we computed the percent of each NH EA personal health services category paid for by the Department of Defense, the Department of Veterans' Affairs, and the Indian Health Service, as an upper bound on the percent of employment we were missing in our OES estimates. Combined with an examination of budget data from the Department of Defense and Department of Veterans' Affairs on direct medical care provision, we developed rough estimates of the federal percent of each personal health care services category, as follows: both hospitals and physician offices were estimated at 3 percent; nursing homes were estimated at 2 percent; and dental services were estimated at 1 percent. We inflated all employment in each of these settings by the inflation factors associated with these percentages to estimate the missing federal health workers, assuming the distribution across occupations was similar for the missing federal workers in each setting as that observed in our OES data. Clearly, a more detailed study of the workforce employed in federal health care facilities would provide more precision in these estimates. Our goal here was to develop reasonable, ballpark adjustments to fill this small known discrepancy between the employment and spending estimates.

Adjustments to high income wage estimates

The OES wage data are collected as numbers of employees in each of 12 wage ranges. The salaries specified in the ranges are updated as needed for each period of survey administration. For example, the highest wage category in recent years was an annual salary of $187,200 or higher. OES uses other data sources for a distribution of wages within each survey category and does report some annual wages over $200,000. However, for occupations with average wages in the mid-six figures, including some categories in health care, OES underestimates wages. In the health sector, the high salary occupations of concern were primarily some physician specialties and chief executives, such as chief executive officers, chief operating officers, chief financial officers, and chief medical officers. Data from the Medical Group Management Association (MGMA) on physician salaries by specialty over time were examined and compared with OES salary estimates over time by physician specialty. Where there were consistent and large differences in the MGMA average salaries and the OES average wages by physician specialty, inflation factors ranging from 1.4 to 2.0 were applied to OES wage estimates for the following detailed categories: Anesthesiologists, Obstetrics/Gynecology Physicians, Physicians-All Other, and Surgeons. Wages for the small category of Chief Executive Officers were also adjusted upward by a factor of 1.5. Adjusting wages for these occupations added about $75 billion to the $1.1 trillion estimated health sector employee compensation for 2011.

Realignment of the NHEA expenditure data by industry

The NHEA are based on revenue data and are known to include some nursing home and home health expenditures as a component of hospital expenditures where these activities are co-located or co-owned. The BLS attempts to separate establishments within an enterprise when conducting the OES survey, and while the separation is probably not perfect, the OES is more likely to align jobs in nursing homes, home health, and hospitals with the correct delivery setting than is reflected in the NH EA spending data by setting. Based on studies conducted comparing the NHEA with the Medical Expenditure Panel Survey (MEPS) and identifying the degree to which home health and nursing home care is likely to be included in the NHEA hospital spending, we shifted 2 percent of hospital expenditures to home health and 4 percent to nursing homes to better align employment and spending estimates by setting [Sing and others 2006]. These figures were lower than the differences identified between NHEA and MEPS because we believe that the OES, while better at separating these settings than the NHEA, is not as clean as MEPS and so the discrepancies are likely to be smaller.

Computation of bottom-up employee compensation estimates

We multiplied our estimates of numbers of employees in each occupation and industry (adjusted for self-employed unincorporated and federal health workers) by our average wages plus benefits by occupation and industry (adjusted for the high wage occupations) in each health care delivery setting. We summed across occupations to produce an estimate of total employee compensation by setting, and summed across settings to represent all of health care delivery. We then compared these totals with the spending totals for each setting, and overall--using either NHEA or Altarum data--computed the fraction of total spending represented by employed labor and compared the fraction with other economy-wide and industry-specific data sources.

Validity checks and rescaling of estimates

For a high-level view of the percent of health industry output going to employee compensation, surplus, taxes, and nonlabor inputs to production, we examined the U.S. Bureau of Economic Analysis (BEA) input-output use tables. The input-output tables are developed in great detail every five years in the benchmark series, while less detailed versions are produced annually; however, the most recent benchmark data are for 2002, as discussed in footnote 4.

We examined the 2002 benchmark tables for five health care industries, as well as the 2002 through 2010 annual tables, which are available for two health care industries: hospitals and nursing and residential care facilities and ambulatory care services. We compared the percent of output associated with employee compensation and surplus with our estimates of total employee compensation. While there are some definitional differences between the BEA data and our data set--for example, the BEA input-output tables for the health industries do not include federal employ-ees--we would expect general consistency with the employee compensation shares reported in these matrices. Given the variety of adjustments made to the data, some of which were not industry-specific, and other potential sources of error such as the inclusion of part-time employees and the exclusion of overtime pay in our OES wage estimates, we were prepared to consider some resealing of our data to be consistent with other reliable big-picture sources.

For the broad hospital and residential industry, BEA annual input-output tables for 2002 through 2010 show that employee compensation represents between 50 and 53 percent of total industry output. Our bottom-up estimates for hospital care alone in recent years are about 52 percent, and the combined hospital and nursing home estimates are about 54 percent. Published AHA data show hospital employee compensation at 52 percent of total revenues. These checks against other data sources confirm that our detailed employment and wage data are consistent with the role of labor expenditures depicted in other overall pictures of these institutional health industries.

For the broad ambulatory care industry, BEA annual input-output tables for 2002 through 2010 show that employee compensation represents between 48 and 50 percent of total industry output. The input-output tables also report an estimate of gross operating surplus, which includes proprietors' income. The ambulatory services industry includes offices of physicians, dentists, and other health care practitioners, some of whose incomes may be included in this operating surplus. Recall that most of the several hundred thousand self-employed unincorporated health workers added to our OES estimates fell into this category. BEA publishes supplementary tables breaking out the gross operating surplus by industry by year into additional components, including the category "Other Gross Operating Surplus-noncorporate," which includes mostly proprietors' income. Combining BEA estimates of this component of surplus with estimates of employee compensation produces a total estimated labor compensation share of 56-59 percent for ambulatory services.

Our initial estimates of employee compensation for the combination of physician and clinical services, dental services, home health, and other professional services at 71 percent to 74 percent were higher than the ranges seen in the BEA data. We therefore resealed our estimates of wages and benefits by occupation in each of the four ambulatory services industries by a factor of 0.82 to bring our total employee compensation shares to 55-67 percent in these settings. This adjustment brought our estimate of the labor share of ambulatory services in line with the annual input-out figures.

2. Findings

In 2011, over 14.5 million health sector jobs supported the delivery of personal health care services in the United States. This number has been steadily growing, as shown for 2005 through 2011, in Table 2. The proportions of health care practitioners and technical occupations (including physicians, nurses, and therapists), health care support occupations (including aides and assistants), and all other occupations (including administrative, management, and maintenance) have remained steady at about 41, 21, and 38 percent, respectively. Surprisingly, over one-third of the jobs in health care delivery are not health care occupations. (7)
Table 2. Counts of Employees in Health Care Delivery by
Broad Occupational Category1 2005--2011 (in millions)

Employees in Health 2005 2006 2007 2008 2009 2010 2011
Care Delivery

Health care 5.2 5.3 5.4 5.6 5.7 5.9 6.0
practitioners arid
technical
occupations

Health care support 2.7 2.7 2.8 2.9 3.0 3.1 3.1
occupations

All other 4.9 5.0 5.1 5.2 5.3 5.3 5.4
occupations

Grand total 12.8 13.1 13.4 13.8 14.1 14.3 14.5

Source Altarum analysis of Bureau of Labor Statistics
and U.S. Census Bureau data.


We have observed the stabilizing effect of health sector jobs on the labor market throughout the recession and recovery. Each month's release of BLS Employment Situation data shows growth in health care jobs, but these timely monthly data cannot answer the question of what types of health jobs are being added, since the underlying data do not break out occupation. Our processed OES data, while slightly older and less sensitive to changes, provide information on occupation and industry in great detail, and thus can be examined for indications of the source of health sector job growth.

Table 3 shows the annual percent change in employment from 2005 through 2011 by broad occupational category, and the average annual change over this period. Health employment has been growing at an average annual rate of just over 2 percent per year. The steadiest growth is seen in the most highly skilled category of health care practitioners and technical occupations. Health care support occupations show a slightly stronger average rate, but growth in these types of occupations has been declining over the past three years, and was only 0.6 percent between 2010 and 2011. Growth in nonhealth occupations is relatively flat at an average rate of 1.5 percent per year. This high-level look indicates that the steady health sector job growth does not appear to be concentrated in lower paying or nonhealth occupations.
Table 3. Annual Growth in Health Care Employment by Broad
Occupational Category, 2005-2011

Annual Growth 2905-2006 2006-2001 2007-2008 2008-2009 2009-2010
in Health Care
Employment

Health care 1.6 2.2 3.2 2.2 2 3
practitioners
and technical
occupations
(%)

Health care 3.0 3.1 3.7 3.3 1.8
Support
occupations
(%)

Alt other 1.3 2.4 2.0 1.4 0.8
occupations
(%)

Grand total 1.8 2.5 2.8 2.1 1.6
(%)

Annual Growth 2010-2011 Average
in Health Care Annual
Employment

Health care 2.1 2.3
practitioners
and technical
occupations
(%)

Health care o;6 2.6
Support
occupations
(%)

Alt other 1.3 1.5
occupations
(%)

Grand total 1.5 2.1
(%)

Source: Altarum analysis of Bureau of Labor Statistics and
U.S. Census Bureau data.


Figure 7 displays our profile of U.S. health care employment in 2011. Of the 14.5 million employees in the health sector, about 9.1 million, or just under two-thirds, are health care practitioners or health care support occupations. As noted earlier, more than one-third of employees, about 5.4 million, are not health care practitioners or health care support occupations. Of these, 1.4 million could be considered health-related occupations, such as health care managers and some categories of therapists, while 4 million employees, or about 28 percent, are neither health nor health-related, most of which are administrative positions.
Figure 7. Profile of U.S. Health Care Employment, 2011

Dentists 0.1M

Pharmacists 0.1M

Non-health Occupations 4.0M

Aides and Assistants 3.3M

Nurses 3.0M

Other Health-Related Occupations 1.4M

Technicians 1.1M

MDs and DOs 0.6M

Therapists 0.5M

Other Diag. and Treat. Practitoners 0.4M

Note: Table made from pie chart.


Table 4 displays our employment data set findings at an additional level of occupational detail. Health care occupations and administrative occupations are broken out further, and the nonhealth occupations are broadly identified. Of note is the Computer and Mathematical Operations category. A common view stresses the high demand for health information technology (HIT) jobs in health care, and that most of the recent job growth falls in this area. (8) Our data show that computer-related jobs have been growing rapidly in the health sector, increasing by 50 percent from 2005 to 2011, but they still represent less than 1 percent of health employment.
Table 4. Counts of Employees in Health Care Delivery by
Occupational Category, 2005-2011 (in thousands)

Occupational 2005 2006 2007 2008 2009
Category

Architecture and 5.3 5.5 5.1 4.8 4.3
Engineering
Occupations

Arts, Design, 15.3 16.5 18.3 20.1 22.0
Entertainment,
Sports, and
Media

Building and 392.9 388.6 394.2 402.0 412.6
Grounds Cleaning
and Maintenance

Business and 145.7 155.0 160.5 167.2 171.4
Financial
Operation
Occupations

Community and 320.3 333.3 347.4 365.9 375.7
Social Services
Occupations

Computer and 66.7 71.6 76.8 82.3 87.9
Mathematical
Occupations

Construction and 16.2 16.5 15.4 15.6 15.8
Extraction
Occupations

Education, 28.2 28.1 33.4 31.8 32.8
Training, and
Library
Occupations

Farming, -- -- -- -- 0.1
Fishing, and
Forestry
Occupations

Food Preparation 454.0 455.0 464.9 470.3 478.8
and Serving
Related
Occupations

Health Care 5,243.5 5,327.7 5,446.6 5,620.4 5,743.7
Practitioners
and Technical
Occupations

Health 3,416.1 3.464.1 3,547.8 3,677.0 3,772.2
Diagnosing and
Treating
Practitioners

Health 1,779.0 1,815.7 1,849.0 1,880.0 1,904.3
Technologists
and Technicians

Other Health 48.4 47.9 49.8 63.4 67.2
Care
Practitioners
and Technical
Occupations

Health Care 2,668.0 2,748.7 2,833.0 2,937.0 3.035.4
Support
Occupations

Nursing, 1.644.6 1.686.1 1,745.1 1,804.7 1,879.1
Psychiatric, and
Home Health
Aides

Occupational and 117.5 124.8 124.8 129.3 132.2
Physical
Therapist
Assistants and
Aides

Other Health 905.9 937.7 963.0 1,002.9 1,024.0
Care Support
Occupations

Installation, 102.8 103.7 107.0 107.4 109.6
Maintenance, and
Repair
Occupations

Legal 1.1 1.3 1.7 1.8 1.5
Occupations

Life, Physical 68.4 67.4 69.1 73.5 78.2
.and Social
Science
Occupations

Management 379.2 378.7 383.0 401.9 423.4
Occupations

Office and 2,380.0 2.405.3 2,447.7 2,495.9 2,516.0
Administrative
Support
Occupations

Communications 52.4 50.0 48.6 460 45.1
Equipment
Operators

Financial 401.8 402.7 398.2 401.3 396.6
Clerks

Information and 621.6 633.2 656.7 680.2 692.4
Record Clerks

Material 68.5 69.3 68.5 70.6 74.2
Recording,
Scheduling,
Dispatching,
Distributing

Other Office and 390.2 384.7 361.5 347.1 353.7
Administrative
Support Workers

Secretaries and 675.4 691.2 729.8 758.5 758.6
Administrative
Assistants

Supervisors, 165.8 170.0 181.1 188.2 191.1
Office and
Administrative
Support Workers

Office and 4.3 4.2 3.3 4.1 4.3
Administrative
Support
Occupations

Personal Care 350.8 362.6 383.9 368.8 353.8
and Service
Occupations

Production 87.9 84.5 82.6 81.1 79.1
Occupations

Protective 58.0 58.2 57.8 58.2 58.2
Service
Occupations

Sales and 28.3 31.2 32.5 33.8 34.4
Related
Occupations

Transportation 34.9 36.2 36.3 36.0 36.7
and Material
Moving
Occupations

Grand total 12,847.4 13.075.7 13,397.1 13,775.8 14,071.3

Occupational 2010 2011
Category

Architecture and 3.8 4.6
Engineering
Occupations

Arts, Design, 23.0 23.9
Entertainment,
Sports, and
Media

Building and 408.1 406.2
Grounds Cleaning
and Maintenance

Business and 181.1 189.5
Financial
Operation
Occupations

Community and 376.2 372.8
Social Services
Occupations

Computer and 92.1 98.1
Mathematical
Occupations

Construction and 15.4 14.6
Extraction
Occupations

Education, 32.9 33.1
Training, and
Library
Occupations

Farming, -- 0.2
Fishing, and
Forestry
Occupations

Food Preparation 473.9 475.4
and Serving
Related
Occupations

Health Care 5.874.3 6.000.6
Practitioners
and Technical
Occupations

Health 3,878.1 3,979.1
Diagnosing and
Treating
Practitioners

Health 1.941.7 1.967.7
Technologists
and Technicians

Other Health 54.5 53.8
Care
Practitioners
and Technical
Occupations

Health Care 3,091.5 3,111.4
Support
Occupations

Nursing, 1,900.5 1,893.9
Psychiatric, and
Home Health
Aides

Occupational and 136.6 142.0
Physical
Therapist
Assistants and
Aides

Other Health 1.054.4 1,075.5
Care Support
Occupations

Installation, 109.3 111.0
Maintenance, and
Repair
Occupations

Legal 1.6 1.8
Occupations

Life, Physical 70.5 76.0
.and Social
Science
Occupations

Management 439.8 447.9
Occupations

Office and 2,523.8 2,508.8
Administrative
Support
Occupations

Communications 42.4 42.1
Equipment
Operators

Financial 396.6 389.8
Clerks

Information and 682.7 680.0
Record Clerks

Material 74.6 72.5
Recording,
Scheduling,
Dispatching,
Distributing

Other Office and 365.1 366.8
Administrative
Support Workers

Secretaries and 764.4 763.3
Administrative
Assistants

Supervisors, 194.2 189.7
Office and
Administrative
Support Workers

Office and 4.0 4.5
Administrative
Support
Occupations

Personal Care 377.7 433.6
and Service
Occupations

Production 76.6 74.3
Occupations

Protective 58.6 59.3
Service
Occupations

Sales and 35.6 40.1
Related
Occupations

Transportation 36.2 36.9
and Material
Moving
Occupations

Grand total 14,302.1 14,519.9


Our data set is able to drill down to yet another level. As an example, Table 5 shows employment over time by detailed occupation for the Health Care Technologists and Technicians category. Pharmacy technicians, cardiovascular technologists and technicians, and radiologic technologists and technicians are among the detailed occupations showing steady growth over the past six years.
Table 5. Counts of Employees in Health Care Delivery: Example
Breakout of Detailed Occupations for Health Technologists and
Technicians Category, 2005--2011 (in thousands)

Occupational 2005 2006 2007 2008 2009
Category

Health 1.779.0 1.815.7 1 849.0 1,880.0 1,904.3
Technologists and
Technicians

Cardiovascular 40.6 42.9 45.9 47.3 47.7
Technologists and
Technicians

Dental Hygienists 162.0 166.4 169.4 172.7 173.7

Diagnostic Medical 43.8 44.3 46.8 48.8 51.8
Sonographcrs

Dietetic 19.6 19.1 19.0 19.2 19.8
Technicians

Emergency Medical 42.1 44.1 45.5 46.6 45.1
Technicians and
Paramedics

Health 60.3 60.0 61.4 63.0 65.4
Technologists and
Technicians, All
Other

Licensed Practical 584.9 597.8 601.0 6)3.4 616.3
and Licensed
Vocational Nurses

Medical and 254.4 258.8 264.2 269.5 272.7
Clinical Laboratory
Technicians

Medical Records and 138.0 141.2 142.2 142.8 143.8
Health Information
Technicians

Nuclear Medicine 17.7 19.3 20.4 21.3 21.7
Technologists

Opticians. 30.5 30.8 31.2 32.8 33.6
Dispensing

Orthotists and 1.2 1.4 1.4 1.3 1.4
Prosthctists

Pharmacy 57.2 59.9 62.7 66.2 68.4
Technicians

Psychiatric 43.2 44.1 42.0 29.2 30.3
Technicians

Radiologic 179.0 185.1 195.1 202.5 207.9
Technologists and
Technicians

Respiratory Therapy 21.4 17.8 16.8 15.5 14.6
Technicians

Surgical 82.7 82.5 84.0 87.6 89.9
Technologists

Veterinary 0.3 0.3 0.2 0.2 0.2
Technologists and
Technicians

Occupational 2010 2011
Category

Health 1.941.7 1,967.7
Technologists and
Technicians

Cardiovascular 48.6 50.1
Technologists and
Technicians

Dental Hygienists 177.6 184.3

Diagnostic Medical 53.1 54.5
Sonographcrs

Dietetic 19.8 19.7
Technicians

Emergency Medical 43.5 43.7
Technicians and
Paramedics

Health 75.7 91.9
Technologists and
Technicians, All
Other

Licensed Practical 616.5 611.4
and Licensed
Vocational Nurses

Medical and 274.4 276.2
Clinical Laboratory
Technicians

Medical Records and 145.2 148.1
Health Information
Technicians

Nuclear Medicine 21.4 20.9
Technologists

Opticians. 34.7 334
Dispensing

Orthotists and 1.8 2.0
Prosthctists

Pharmacy 68.2 69.6
Technicians

Psychiatric 44.4 39.7
Technicians

Radiologic 211.5 214.7
Technologists and
Technicians

Respiratory Therapy 13.1 13.2
Technicians

Surgical 92.1 94.2
Technologists

Veterinary 0.2 0.1
Technologists and
Technicians


Share of health spending going to labor

A major objective of this effort was to link the health workforce to health expenditures. We find that $1 trillion, or 57 percent of the $1.78 trillion spent on personal health care services in 2011 went to labor employed in health care delivery, as shown by Table 6. The labor share of spending on health care delivery has increased slightly in recent years, from 55 percent in 2005 to 57 percent beginning in 2009. The figures in Table 6 break out labor expenditures into occupation at the 2-digit SOC level, with health care occupations broken out further at the 3-digit level.
Table 6. Health Care Spending by Occupational Category,
2005-2011 (in billions of dollars)

Occupational 2005 2006 2007 2008 2009 2010
Category

Architecture 0.4 0.4 0.4 0.4 0.3 0.3
and Engineering
Occupations

Arts, Design, 0.8 0.9 1.1 1.2 1.3 1.4
Entertainment.
Sports, and
Media

Building and 10.5 10.8 11.4 12.0 12.7 12.7
Grounds
Cleaning and
Maintenance

Business and 9.1 10.1 10.8 11.6 12.0 13.1
Financial
Operation
Occupations

Community and 15.0 16.3 17.6 19.1 19.9 20.3
Social Services
Occupations

Computer and 4.5 5.1 5.6 6.2 6.7 7.2
Mathematical
Occupations

Construction 0.9 1.0 0.9 1.0 1.0 1.0
and Extraction
Occupations

Education, 1.8 1.7 2.3 2.4 2.6 2.7
Training, and
Library
Occupations

Farming, -- -- -- -- 0.0 --
Fishing, and
Forestry
Occupations

Food 12.2 12.7 13.5 14.2 14.8 14.8
Preparation and
Serving Related
Occupations

Health Care 447.6 479.7 513.2 556.9 589.0 616.7
Practitioners
and Technical
Occupations

Health 358.9 384.7 412.5 449.8 478.0 502.9
Diagnosing and
Treating
Practitioners

Health 86.3 92.2 97.6 103.2 106.7 110.3
Technologists
and
Technicians

Other Health 2.5 2.7 3.1 3.9 4.4 3.6
Care
Practitioners
and Technical

Health Care 79.8 85.7 91.7 98.2 102.8 105.9
Support
Occupations

Nursing, 45.7 48.7 52.3 55.8 58.5 59.7
Psychiatric,
and Home Health
Aides

Occupational 4.8 5.3 5.6 6.1 6.6 6.9
and Physical
Therapist
Assistants,
Aides

Other Health 29.3 31.6 33.8 36.3 37.7 39.2
Care Support
Occupations

Installation, 4.4 4.6 5.0 5.2 5.5 5.6
Maintenance,
and Repair
Occupations

Legal 0.1 0.1 0.2 0.2 0.2 0.2
Occupations

Life, Physical, 5.2 5.4 5.7 6.3 6.9 6.4
and Social
Science
Occupations

Management 38.0 40.2 42.7 6.8 50.5 53.8
Occupations

Office and 80.1 84.5 88.6 93.4 96.5 98.2
Administrative
Support
Occupations

Personal Care 7.7 8.2 8.9 9.0 9.2 9.9
and Service
Occupations

Production 2.8 2.8 2.8 2.8 2.8 2.8
Occupations

Protective 2.1 2.2 r. 2.2 2.3 2.4 2.4
Service
Occupations

Sales and 1.3 1.5 1.6 1.7 1.8 1.9
Related
Occupations

Transportation 1.1 1.1 1.2 1.2 1.3 1.3
and Material
Moving
Occupations

Grand total 725.4 775.0 827.2 892.3 940.3 978.6
employee
compensation

Total personal 1,327.5 1,407.4 1,495.3 1,576.0 1,652.1 1,715.9
health care
services
spending

Share of 55% 55% 55% 57% 57% 57%
spending going
to employee
compensation

Occupational 2011
Category

Architecture 0.4
and Engineering
Occupations

Arts, Design, 1.5
Entertainment.
Sports, and
Media

Building and 12.8
Grounds
Cleaning and
Maintenance

Business and 13.8
Financial
Operation
Occupations

Community and 20.6
Social Services
Occupations

Computer and 7.9
Mathematical
Occupations

Construction 0.9
and Extraction
Occupations

Education, 2.7
Training, and
Library
Occupations

Farming, 0.0
Fishing, and
Forestry
Occupations

Food 15.1
Preparation and
Serving Related
Occupations

Health Care 645.0
Practitioners
and Technical
Occupations

Health 527.2
Diagnosing and
Treating
Practitioners

Health 114.3
Technologists
and
Technicians

Other Health 3.5
Care
Practitioners
and Technical

Health Care 108.6
Support
Occupations

Nursing, 60.4
Psychiatric,
and Home Health
Aides

Occupational 7.4
and Physical
Therapist
Assistants,
Aides

Other Health 40.8
Care Support
Occupations

Installation, 5.8
Maintenance,
and Repair
Occupations

Legal 0.2
Occupations

Life, Physical, 7.0
and Social
Science
Occupations

Management 56.2
Occupations

Office and 99.9
Administrative
Support
Occupations

Personal Care 11.5
and Service
Occupations

Production 2.8
Occupations

Protective 2.5
Service
Occupations

Sales and 2.2
Related
Occupations

Transportation 1.3
and Material
Moving
Occupations

Grand total 1,018.8
employee
compensation

Total personal 1,781.8
health care
services
spending

Share of 57%
spending going
to employee
compensation


Figure 8 displays a profile of health care spending by labor category for 2011. Comparing this spending profile with the employment profile in Figure 7 shows that aides and assistants and the nonhealth occupations represent about half of the jobs but only about one-third of the labor expenditures, while physicians and dentists represent less than 10 percent of the jobs but about one-quarter of the labor expenditures.
Figure 8. Profile of Health Care Spending by Labor
Category, 2011

Dentists $27B

Other Diag. and Treat. Practitoners $31B

Pharmacists $10B

Therapists $44B

MDs and DOs $217B

Technicians $63B

Other Health Related Occupations $75B

Non-health Occupations $190B

Aides and Assistants $122B

Nurses $239B

Source: Altarum analysis aligning Bureau of Labor Statistics
employment and wage data and other sources with the National
Health Expenditure Accounts.

Note: Table made from pie chart.


The share of spending going to labor and the distribution of spending by occupational category vary by delivery setting, as shown in Table 7 for 2011.
Table 7. Health Care Spending by Occupational Category and
Delivery Setting, 2011 (in billions of dollars)

2011 Health Dental Hospital Nursing Other Physician
Services Home Health Care Home Professional
Spending by Care Care Services
Occupational
Category
(Smillions)

Architecture and 0.0 0.0 0.3 0.0 0.0
Engineering
Occupations

Arts, Design, 0.0 0.1 0.9 0.2 0.0
Entertainment,
Sports, and
Media
Occupations

Building and 0.1 0.1 6.5 5.3 0.1
Grounds Cleaning
and Maintenance
Occupations

Business and 0.2 0.7 8.4 1.5 0.2
Financial
Operation
Occupations

Community and 0.0 1.6 8.8 1.5
Social Services
Occupations

Computer and 0.0 0.2 5.5 0.1 0.1
Mathematical
Occupations

Construction and 0.0 0.0 0.9 0.0 0.0
Extraction
Occupations

Education, 0.0 0.0 2.1 0.0 0.3
Training, and
Library
Occupations

Food Preparation 0.0 0.0 4.9 10.1 0.0
and Serving
Related

Occupations
Health Care 41.4 20.9 277.8 36.9 27.7
Practitioners
and Technical
Occupations

Health 26.3 16.7 223.1 19.7 25.7
Diagnosing and
Treating
Practitioners

Health 14.9 4.0 52.6 17.0 1.6
Technologists
and Technicians

Other Health 0.2 0.1 2.1 0.1 0.3
Care
Practitioners
and Technical

Occupations
Health Care 11.4 10.5 27.2 35.1 6.2
Support
Occupations

Nursing. 0.0 9.8 16.2 33.1
Psychiatric, and
Home Health
Aides

Occupational and 0.0 0.5 2.1 1.4 2.9
Physical
Therapist
Assistants and
Aides

Other Health 11.4 0.2 9.0 0.6 3.1
Care Support
Occupations

Installation, 0.0 0.1 3.2 2.0 0.0
Maintenance, and
Repair
Occupations

Legal 0.0 0.0 0.2 0.0 0.0
Occupations

Life, Physical 0.0 0.0 3.5 0.0 1.4
.and Social
Science
Occupations

Management 0.5 4.1 29.2 7.9 2.0
Occupations

Office and 10.4 3.6 34.5 5.4 7.0
Administrative
Support
Occupations

Personal Care 0.0 6.2 0.9 3.7 0.2
and Service
Occupations

Production 0.2 0.0 1.1 1.1 0.2
Occupations

Protective 0.0 0.0 2.1 0.3 0.0
Service
Occupations

Sales and 0.0 0.5 0.5 0.3 02
Related
Occupations

Transportation 0.0 0.1 0.6 0.4 0.0
and Material
Moving
Occupations

Grand total 64.4 48.5 419.3 112.4 47.2
spending on
employee
compensation

2011 personal 107.1 88.9 804.7 181.6 70.8
health care
services
spending

Share of 60% 55% 52% 62% 67%
spending going
to employee
compensation

2011 Health Grand Total
Services and
Spending by Clinical
Occupational Services
Category
(Smillions)

Architecture and 0.1 0.4
Engineering
Occupations

Arts, Design, 0.2 1.5
Entertainment,
Sports, and
Media
Occupations

Building and 0.7 12.8
Grounds Cleaning
and Maintenance
Occupations

Business and 2.7 13.8
Financial
Operation
Occupations

Community and 6.6 20.6
Social Services
Occupations

Computer and 2.0 7.9
Mathematical
Occupations

Construction and 0.0 0.9
Extraction
Occupations

Education, 2.7
Training, and
Library
Occupations

Food Preparation 15.1
and Serving
Related

Occupations
Health Care 240.4 645.0
Practitioners
and Technical
Occupations

Health 215.7 527.2
Diagnosing and
Treating
Practitioners

Health 24.1 114.3
Technologists
and Technicians

Other Health 0.7 3.5
Care
Practitioners
and Technical

Occupations
Health Care 18.2 108.6
Support
Occupations

Nursing. 1.1 60.4
Psychiatric, and
Home Health
Aides

Occupational and 0.4 7.4
Physical
Therapist
Assistants and
Aides

Other Health 16.7 40.8
Care Support
Occupations

Installation, 0.4 5.8
Maintenance, and
Repair
Occupations

Legal 0.0 0.2
Occupations

Life, Physical 2.0 7.0
.and Social
Science
Occupations

Management 12.7 56.2
Occupations

Office and 39.0 99.9
Administrative
Support
Occupations

Personal Care 0.5 11.5
and Service
Occupations

Production 0:2 2.8
Occupations

Protective 0.1 2.5
Service
Occupations

Sales and 0.8 2.2
Related
Occupations

Transportation 0.2 1.3
and Material
Moving
Occupations

Grand total 327.1 1,018.8
spending on
employee
compensation

2011 personal 528.7 1,781.8
health care
services
spending

Share of 62% 57%
spending going
to employee
compensation


Distribution of nonlabor inputs

Since we have aligned the estimate of total employee compensation computed from our detailed health industry and occupation data set with the BEA Industry input-output tables, we can form a complete picture of where the health spending dollars are going, including both labor and nonlabor inputs. We have already provided detail on employment and expenditures on labor. The input-output tables provide information on the 40 percent of ambulatory services and the 45 percent of hospital and nursing and residential care spending associated with nonlabor inputs.

Figures 9 and 10 highlight major categories of nonlabor inputs for 2010, the most recent year available for the annual input-output tables. In the delivery of ambulatory health care services, major cost shares go toward purchasing external management, administrative, and technical services (16 percent), chemical products, which are mostly pharmaceuticals (4 percent), and real estate (4 percent). In hospitals and other nursing and residential facilities, major cost shares go to real estate (12 percent), management, administrative, and technical services (11 percent), and food and beverages (3 percent). Management, administrative, and technical services purchased by health care providers include accounting, insurance, and employment services to supplement the labor directly employed. Assuming that the majority of these outsourced services are labor costs, then the total labor cost for employee compensation plus external labor services represent about three-quarters of the spending on ambulatory health care services and two-thirds of the spending on hospital and nursing and residential care.
Figure 9. 2010 Ambulatory Health Care Services
Input-Output Distribution

Other Other Health Care 3%

Other 11%

Manufacturing/Wholesale Trade 2%

Chemical Products 4%

Mgmt/Admin/Technical Services 16%

Real Estate 4%

Labor 60%

Source: Altarum analysis of Bureau of Economic Analysis
Annual Input-Output Use Tables.

Note: Table made from pie chart.

Figure 10. 2010 Hospitals and Nursing and Residential Care
Input-Output Distribution

Other Health Care 1%

Food & beverage 3%

Manufacturing/Wholesale Trade 3%

Chemical Products 3%

Mgmt/Admln/Technical Services 11%

Real Estate 12%

Labor 55%

Other 12%

Source: Altarum analysis of Bureau of Economic
Analysis Annual Input-Output Use Tables.

Note: Table made from pie chart.


3. Conclusions

The nation's health workforce is both a significant driver of expenditures and a potential source of spending reductions, either through reductions in employment or wages, or increases in productivity. It has been stated that up to 30 percent of U.S. health spending is "waste" [IOM 2012]. But which of the inputs to the production of health care services should be eliminated or reduced? Any discussion of significant cuts in health spending, whether from current or future health reform initiatives, must acknowledge that 57 percent of the $1.8 trillion spent in the U.S. on personal health care services goes directly to pay wages and benefits for the nearly one in nine jobs represented by this sector of our economy. Nevertheless, while not a central thrust of this paper, there are immense opportunities to improve the efficiency of the U.S. health care system, along both productive and allocative dimensions [Baicker, Chandra, and Skinner 2012].

We have demonstrated the feasibility of linking the NHEA, BLS employment data, and BEA input-output data to provide a previously unavailable resource from which it is possible to systematically investigate multiple, broad health workforce and spending issues. In the future, our aim is for researchers and policymakers to examine and apply this work to:

* identify the occupations that are driving costs in each NHEA service category;

* identify trends in the percent of health care expenditures going to nonhealth occupations and inputs;

* estimate workforce requirements associated with NHE forecasts;

* identify potential constraints on spending based on health workforce shortages by occupation;

* identify the potential impact of proposed approaches to controlling health care cost growth on health profession employment and compensation;

* provide a data consistency check across many dimensions of the complete labor-oriented, NHEA balance sheet constructed from this work.

Acknowledgments

The authors would like to thank Tamara Crouter for providing data analysis and programming support to this effort and Dr. Charles Roehrig, Director of Altarum's Center for Sustainable Health Spending, for originating the project concept and providing technical assistance and review. We would also like to thank three anonymous reviewers for helpful comments.

REFERENCES

Altarum Institute. 2012. Health Sector Economic Indicators Spending Brief #12-11, September 2012 Data, Altarum Institute, November 8, 2012. http://www.altarum. org/files/imce/CSHS-Spending-Brief Nov percent202012 .pdf.

Baicker, Katherine, Amitabh Chandra, and Jonathan Skinner. 2012. "Saving Money or Just Saving Lives? Improving the Productivity of US Health Care Spending." Annual Review of Economics, 4(July): 33-56.

Freeland, Mark. 2012. Personal communication with author, June 26

Institute of Medicine (IOM). 2012. Best care at lower cost: The path to continuously learning health care in America. edited by Mark Smith, Robert Saunders, Leigh Stuc-khardt, J. Michael McGinnis, eds. Washington, DC: The National Academies Press.

Kaiser Family Foundation. 2012. Health Care Costs: A Primer--Key Information on Health Care Costs and Their Impact, May. http://www.kff.org/insurance/up-load/7670-03.pdf.

Kaufman, Ken. 2012. Bending the Health Care Cost Curve: More Than Meets the Eye? Health Affairs Slog, April 13. http://healthaffairs.org/blog/2012/04/13/bending-the-health-care-cost-curve-more-than-meets-the-eye/.

Kim, D., T. Gilmore, and W. Jolla 2012. "Annual Industry Accounts: Advance Statistics on GDP by Industry for 2011." Survey of Current Business, 92(5): 6-22.

PwC, 2012. Medical Cost Trend: Behind the Numbers 2013, PwC Health Research Institute, May. http://www .pwc.com/us/en/heal th-ind ustriesIbehind-the-num bers; index.html.

Roehrig, Charles. 2011. The Case for Tracking Health Spending as a Share of 'Potential' GDP, Health Policy Forum, Altarum Institute, May 11. http://www.health-policyforumorg/pos (case- tracking-heal th-spending-sha re-potential-gdp.

Roehrig, Charles. 2012. A New Look at the Simpson-Bowles Budget Plan: Implications for Sustainable Health Spending, Health Policy Forum, Altarum Institute, October 30. http://wvvw.altarum.org/forum/post/new-look-simpson-bowles-budget-plan-impfications-sustainable-health-spending.

Roehrig, Charles, Ani Turner, Paul Hughes-Cromwick, and George Miller. 2012. "When the Cost Curve Bent--Pre-Recession Moderation in Health Care Spending." New England Journal of Medicine, 367(7): 590-2.

Sing, Merrile, Jessica Banthin, Thomas Selden, Cathy Cowan, and Sean Keehan. 2006. "Reconciling Medical Expenditure Estimates from the MEPS and NHEA, 2002." Health Care Financing Review, 28(1): 25-40.

Steuerle, Gene. 2009. "The New Spending Numbers: What They Tell Us, And What They Don't," Health Affairs Web Exclusive (February 24).

This paper was a winner of the NABE Contributed Paper Award for 2012 and was presented at the NABE Annual Meeting in October 2012.

doi:10.1057/be.2012.35

(1.) There is evidence that the spending growth slowdown began in 2005, thus pre-dating the Great Recession [Kaufman 2012: Roehrig and others 2012].

(2.) For longer historical context, the health share of total employment was 4.4 percent in 1970 and 5.9 percent in 1980. Also, health care absorbed 7.2 percent of GDP in 1970 and 9.1 percent of GDP in 1980.

(3.) Even with the aforementioned slowdown in health care expenditure growth, concerns over spending sustainability are legitimate [Roehrig 2012].

(4.) Note that there is a considerable lag between release of the once every 5-year "benchmark" input-output table and the reference year. For example, the 2007 benchmark input-output data will not be released until the end of 2013. This means that analysts must use the annual input-output tables which are dramatically less detailed and subject to revisions, as economic census data that lie behind the benchmark tables are interpolated and extrapolated, while waiting for the next release.

(5.) 0ACT was going to have the University of MD INFORUM model (Inter-industry Forecasting Project)--a dynamic input-output model embedded in a macro model--project occupations within industries, but this plan was never executed [Freeland 2012].

(6.) Compensation =0.7Compensation x Benefits Inflation Factor = >Benefits Inflation Factor = 1/0.7 = 1.4.

(7.) Conversely, there are significant numbers of individuals in health occupations that work outside of health industries, notably pharmacists who work in the retail sector or instructors who work in educational settings.

(8.) The American Recovery and Reinvestment Act (ARRA) of 2009, under its Health Information Technology for Economic and Clinical Health (HITECH) provision, aims to move the nation toward a paper-less health information network via the widespread adoption of electronic health records.

ANI TURNER and PAUL HUGHES-CROMWICK *

*Ani Turner is a Senior Health Policy Analyst and Deputy Director of the Altarum Institute Center for Sustainable Health Spending. In addition to her research management role, she leads the Center's health workforce analysis and modeling and monthly tracking of health sector employment. As a consultant to government and commercial clients for over two decades, she has developed models and conducted analyses of health-care resources, costs, and quality for the Department of Health and Human Services, the Department of Defense, individual States, and private health plans. She received her BA in Mathematics, summa cum laude, Phi Beta Kappa from the University of Michigan, where she is currently completing the Master of Applied Economics program.

Paul Hughes-Cromwick, MA, is Senior Health Economist, Center for Sustainable Health Spending, Altarum Institute, based in Ann Arbor, Michigan, where he leads outreach and business development. Prior to Altarum, he worked at the University of Michigan School of Nursing; the Henry Ford Health System; the University of Pittsburgh Graduate School of Public Health; the State of Connecticut, where he was Research Director for the Connecticut Partnership for Long Term Care Insurance; and the U.S. Department of Health and Human Services Office of the Assistant Secretary for Planning and Evaluation. Mr. Hughes-Cromwick serves on the Board of Health Alliance Plan HMO in Detroit, and chairs the NABE Health Economics Roundtable. He has a BS in math and philosophy from the University of Notre Dame and an MA in applied economics from Clark University, Worcester, Massachusetts.
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Comment:Connecting U.S. health expenditures with the health sector workforce.
Author:Turner, Ani; Hughes-Cromwick, Paul
Publication:Business Economics
Date:Jan 1, 2013
Words:9997
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