Productivity Growth in Medical and Health Care
Two recent working papers from researchers at the U.S. Bureau of Economic Analysis (BEA) have examined productivity growth in medical care. Productivity growth is the fundamental driver of improvements in living standards, and yet accurately measuring productivity remains challenging for the health care sector, which accounts for about 18 percent of the U.S. economy.
The first paper, by BEA researchers Calvin Ackley and Abe Dunn along with John A. Romley from the University of Southern California, provides the first framework for measuring productivity in health care that combines a utility-based measure of output with a cost-based measure of inputs, consistent with core principles of productivity theory. Prior research typically addresses only one side of this measurement problem. The paper then uses this framework to analyze nine conditions from 2002 through 2021, quantifying sustained improvements in medical-care productivity to provide the longest and most comprehensive assessment of productivity for acute conditions in the literature.
The paper’s central estimates imply productivity gains of 7.5 percent per year for these conditions, and the authors find the result consistent with the large welfare gains associated with improvements in population health documented in prior research. These results extend prior work by covering more conditions and a longer time period, and they remain qualitatively robust across multiple assumptions.
The second paper is also by Ackley, Dunn, and Romley, with the addition of Eli Liebman from the University of Georgia. This paper uses BEA’s Health Care Expenditure Statistics by Condition (HCESC) to measure health care spending by condition, enabling more meaningful output measurement than official statistics provide, which likely understate productivity growth by failing to capture improvements in medical technology and treatment quality.
The authors present a simple framework combining the HCESC with population health data to adjust prices and output for quality improvements. This framework appropriately treats hospitals, physicians, and prescription drugs as inputs into the treatment of a disease, rather than outputs. The comprehensive measures of spending by condition from the HCESC are critical for producing quality-adjusted price estimates, as it tracks the cost of treating the same conditions over time. Unlike the previous paper discussed, which focuses on nine health conditions, this paper produces a more comprehensive estimate covering all medical conditions.
The results, consistent with a growing body of literature, indicate that quality-adjusted prices for health care have declined relative to conventional price indexes, implying significant unmeasured productivity growth. The estimates suggest that official statistics may understate real output growth in the health sector by roughly 1 percent per year or more. Productivity gains may even be larger in other high-income countries, where life expectancy has risen more and spending has grown more slowly.
While challenges remain, such as how to disentangle medical and nonmedical contributors to health outcomes, the methodology outlined in this paper provides a new approach for improving the measurement of the health care sector.
