MedPAC’s Policy Goal for Productivity 

Medicare’s payment systems should encourage 

efficiency: providers should be able to reduce the 

quantity of inputs required to produce a unit of 

service while maintaining quality. Within its 

framework for recommending updates to 

Medicare payment rates, MedPAC includes a 

target for productivity as a mechanism to 

encourage efficiency. Economic literature on the 

hospital industry, for example, suggests that 

providers who are under fiscal pressure generally 

have managed to slow their cost growth more 

than those facing less fiscal pressure.1 MedPAC’s 

productivity target is based on the Bureau of 

Labor Statistics' estimate of the 10-year moving 

average rate of past growth in total factor 

productivity for the economy as a whole, which 

currently equals 0.9 percent. 

Medicare payment rates to health care providers 

should be set so that the federal government 

benefits from providers’ productivity gains, just 

as private purchasers of goods in competitive 

markets benefit from the productivity gains of 

their suppliers. In developing its payment 

recommendations, MedPAC expects 

improvements in productivity consistent with the 

productivity gains achieved by the firms and 

workers who pay the taxes and premiums that 

support Medicare. When included in our update 

recommendation, the productivity factor is a 

policy objective, not an empirical estimate. 

However, to the extent that efficient providers are 

unable to achieve this productivity target, that 

outcome would be revealed subsequently in 

MedPAC’s analysis of payment adequacy, which 

is considered anew each year. 

Together with the productivity target, MedPAC’s 

update framework also considers cost-increasing 

advances in science and technology that improve 

the quality of care. Under a prospective payment 

system, providers already have an incentive to 

adopt technological changes that reduce the costs 

of caring for patients. Other technological 

changes increase the cost of care and, by design, 

payment systems for some providers already take 

this into account. But to account for costincreasing innovations that improve quality and 

may not be reflected in Medicare’s payment 

systems, MedPAC has recommended increasing 

payment rates through an allowance for 

“scientific and technological advances.” 

The American Hospital Association (AHA) has 

questioned whether a national average rate of 

productivity growth is a reasonable 

approximation for hospitals. In research 

sponsored by the AHA, Lichtenberg (2003) 

argues that productivity growth for the hospital 

industry is far lower than that for the economy as 

a whole and suggests that MedPAC use a 

hospital-specific measure of productivity growth. 

His suggestion reflects a lack of understanding 

about MedPAC’s productivity target, which is not 

meant to be an empirical estimate for any specific 

group of providers. In addition, his estimates 

suffer from common methodological 

shortcomings—problems that make the approach 

of using hospital-specific growth rates largely 

impractical. But the AHA goes further by citing 

Lichtenberg’s work as the reason to exclude the 

productivity target entirely in MedPAC’s 

recommendations for hospital updates (AHA 

2004). That argument is unreasonable because it 

presumes that there will be no productivity 

improvement in the hospital industry. In the 

discussion that follows, we explain the 

shortcomings in Lichtenberg’s approach in 

greater detail. 

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601 New Jersey Avenue, N.W. • Suite 9000 

Washington, DC 20001 

202-220-3700 • Fax: 202-220-3759 

www.medpac.gov

Glenn M. Hackbarth, J.D., Chairman 

Robert D. Reischauer, Ph.D., Vice Chairman 

Mark E. Miller, Ph.D., Executive Director
Problems in measuring growth of hospitalspecific productivity

Lichtenberg’s estimates of productivity growth 

show trends that are difficult to square with what 

was happening in the hospital industry at the 

time. Over the 1987-2001 period, he estimates 

that growth in hospital labor productivity was 

lower than that for economy-wide labor 

productivity in each year except 2001. 

Lichtenberg’s analysis shows high hospital 

productivity growth in 2001 (a year of significant 

cost growth), but does not find significant 

productivity growth in the early 1990s even 

though patients’ lengths of stay (and hospitals’ 

reported costs) were falling rapidly. 

He estimates productivity growth by deflating the 

value of hospital output by a price index, and then 

dividing by employment levels. A common 

problem with this approach involves using price 

deflators that do not capture changes in quality. 

Lichtenberg never acknowledges this issue, even 

though failing to capture quality improvements 

can significantly overstate price growth and 

thereby understate productivity growth 

(Newhouse, 2001). Currently, the Bureau of 

Labor Statistics rarely estimates the value of 

quality improvements when it builds prices 

indexes—computers and automobiles are 

exceptions. But the pace of medical innovation 

has been rapid and very important to the public’s 

health. Improvements in the quality of hospital 

services have helped to extend patients’ lives, 

raised their quality of life, and reduced medical 

errors. For those reasons, it is not clear that 

productivity growth in the hospital industry is, in 

fact, lower than that for the economy as a whole 

as Lichtenberg asserts. 

Moreover, estimates of productivity growth for 

health care industries are strongly affected by the 

role of administered prices—particularly through 

Medicare and Medicaid. As a result, year to year 

variation in health care spending may not 

measure changes in the value of real resources as 

well as in industries that are more purely 

competitive. By basing its policy goal on 

productivity growth in the entire economy, 

MedPAC avoids what would otherwise be a 

problem with circularity: using hospital revenues 

that are heavily influenced by Medicare’s 

payment rates to measure productivity growth 

that, in turn, is used to update Medicare’s 

payment rates. 

Lichtenberg’s paper centers around the notion 

that labor-intensive industries have lower 

productivity growth, and that hospitals are a 

labor-intensive industry. He states that labor 

costs are a much higher share of output of the 

health services sector (a broader combination of 

industries than hospitals alone) than in the 

general economy. But Lichtenberg’s estimate of 

labor intensity is higher than estimates for the 

hospital industry by the Centers for Medicare and 

Medicaid Services (Federal Register, August 

2002) and the number that Congress now allows 

hospitals to use in Medicare payment rates 

(Medicare Prescription Drug, Improvement, and 

Modernization Act of 2003). Those alternative 

estimates would put the hospital industry closer 

to average labor intensity than Lichtenberg’s 

analysis suggests.2

Even if hospitals are more labor-intensive, the 

nature of the workers they hire may embody 

relatively more “human capital,” which produces 

greater productivity gains than in other industries. 

Health care industries are accumulating human 

capital in the form of technical expertise and 

improved protocols. For example, if surgery 

techniques improve and patients recover from 

surgeries more rapidly, we will see shorter 

hospital stays that may use fewer resources per 

hospital discharge. 

Finally, Lichtenberg also argues that hospitals 

tend to be far less intensive in research and 

development (R&D) than other industries, and 

that industries with lower R&D intensity tend to 

have smaller productivity gains. Yet he ignores 

the context in which investments for R&D take 

place within health care industries. Most of the 

research that affects hospitals is paid for by other 

parties: medical schools, the federal government 

(through the National Institutes of Health), 

pharmaceutical companies, and medical device 

manufacturers. Additionally, some of the R&D 

that one should consider for the hospital sector 

may be purchased as intermediate goods (such as 

high-resolution imaging equipment) rather than 

produced by the hospital itself. 
Endnotes 

1. Gaskin and Hadley (1997) found that 

increasing HMO penetration and declining 

Medicare prospective payment rates restrained 

hospital cost growth in the late 1980s and early 

1990s. 

2. There are other methodological issues with his 

analysis as well. For example, Lichtenberg 

groups more than 450 industries into quartiles 

based on their degree of labor intensity. He then 

calculates simple mean values of labor intensity 

and growth in multifactor productivity by quartile 

to demonstrate that higher levels of labor 

intensity are associated with lower productivity 

growth. However, he does not show the variation 

in productivity growth within each of the four 

groups, which is likely to be considerable. Even 

granting that there is, on average, a systematic 

relationship between productivity and labor 

intensity, it does not follow that any specific 

industry has the average productivity growth of 

its quartile. 

References

Federal Register: August 1, 2002 (Volume 67, 

Number 148) Page 50031-50080. 

Gaskin D. and Hadley J. "The Impact of HMO 

Penetration on the Rate of Hospital Cost 

Inflation, 1985-1993." Inquiry. vol. 34:3, 1997. 

Letter from American Hospital Association 

Senior Vice President, Carmela Coyle, to 

MedPAC Commissioners, January 6, 2004, 

http://www.hospitalconnect.com/aha/advocacygrassroots/advocacy/agencyletters/content/MedP

AC040106.pdf. 

Lichtenberg, F. “Does hospital productivity grow 

at the same rate as productivity in the rest of the 

economy?” December 2003. 

Medicare Prescription Drug, Improvement, and 

Modernization Act of 2003 (P.L. 108-173). 

Newhouse J., “Medical Care Prices Indices: 

Problems and Opportunities, The Chung-Hua 

Lectures,” NBER Working Paper 8168, March 

2001. 

Staff Contact 

Rachel Schmidt 

(202) 220-3700 

February 9, 2004