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JAMA Forum Archive, 2012-2019: Health policy commentary from leaders in the field
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Making Health Care More Productive

With a staggering amount of waste, as documented in the recent JAMA study, a key question is whether our health care system can produce the same or better outcomes for less money—in other words, can it become more productive or efficient? Until recently, the answer seemed to be “no.” But things may be changing.

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Health Care Productivity

Historically, the health care system has a poor track record of productivity gains, especially compared with other sectors of the economy. In a National Bureau of Economic Research article published in 2011, David M. Cutler, PhD, of Harvard University, reported that productivity growth in health, education, and social services was negative between 1995 and 2005, meaning that instead of doing more and/or costing less, these sectors did less and/or cost more. In comparison, the average across industries was positive 2.4% growth, with durable goods and information technology sectors leading the pack with productivity growth about 7% and 6%, respectively.

Other work backs this up. In a study published in 2011, researchers reported similar statistics. Another study showed that hospital productivity gains have lagged those of the overall economy for decades; another showed decreasing productivity by hospitals from 2001 to 2011.

However, prior work focused on the amount of health care delivered (like admissions or hospital days) and not on the quality of health it produced. One notable exception is a 2015 study published in Health Affairs, which measured not only how much care hospitals provided but also whether the care they delivered kept patients alive and out of the hospital for at least 30 days. By this measure, hospital productivity grew 14% for heart attacks, heart failure, and pneumonia over the 2002-2011 period—and it grew faster than the overall economy in the last few years of the analysis. Although results like this from one study should not be taken as evidence that we have solved the productivity problem in health care, it is an encouraging sign.

Productivity, Information Technology, and Organizational Change

In a JAMA Forum post in April,  Cutler suggested other reasons for optimism about health care productivity: there are steps that health care organizations can take to enhance efficiency. For example, more care could be funneled toward high-volume specialists and centers that deliver better outcomes, or health systems could become more sophisticated in matching patients with clinicians so that they see those physicians who deliver the appropriate intensity or type of care but no more.

Harnessing electronic medical data, predictive analytics can also help target resources to whom they’re needed. Other uses of information technology may help streamline administrative work, reducing costs. And, as Boston University policy analyst Elsa Pearson, MPH, and I wrote, in a JAMA Forum post earlier this year, in a setting in which information technology has intervened too far— electronic health record documentation during a patient visit—medical scribes are a means of regaining some of the lost productivity.

Electronic consultations (eConsults) are another productivity-enhancing use of information technology. When a question arises needing specialist input, instead of referring the patient for a visit, primary care physicians in some systems can use eConsults to get answers electronically and at lower cost. As has been demonstrated in several studies, eConsults can reduce unnecessary visits to specialists, freeing them up to see patients who truly require their services face to face. When eConsults were introduced in the San Francisco Department of Public Health in 2005, wait times decreased. The same occurred in the Los Angeles County Department of Health Services; 3 years after its system was in place, specialists wait times had decreased 17%, a significant drop.

A 2018 randomized trial examined eConsults for psychiatric consultations in Allina Health, a large, integrated delivery system in the Twin Cities metropolitan area. Twenty-two randomly selected clinics received the intervention between August 2015 and June 2016, after which it was introduced to the 23 control clinics. The study found a 24% improvement in primary care clinicians’ reported ease of obtaining a consultation, which could be a source of productivity gains.

There are certainly other ways to boost health care efficiency, but these examples exemplify the potential for information technology to help us obtain greater value from health care spending.

Greater Value From Better Treatments

Two other recent studies published in Health Affairs suggest additional ways we might obtain greater value from the health care system. Treatments for specific diseases have improved, in some cases contributing to lower spending or slower spending growth.

One of these studies found that the use of pharmaceutical treatments for cardiovascular disease from 1999 through 2012 cut cardiovascular events in half. In turn, half of the slowdown in Medicare spending growth over this period can be attributed to this reduction in cardiovascular events. The second study found that the quality of life for individuals with 7 prevalent conditions responsible for most mortality and morbidity—breast and lung cancer, cerebrovascular disease, chronic obstructive pulmonary disease, diabetes, HIV/AIDS, and ischemic heart disease—increased from 1995 to 2015. For 4 of the conditions—lung cancer, ischemic heart disease, cerebrovascular disease, and HIV/AIDS—spending per case went down. In other words, people had better outcomes for less money.

None of this means there isn’t waste in the health care system. The latest estimate suggests as much as 25% of spending in this area is wasteful. Even if the health care system is becoming more efficient in some ways, that doesn’t mean it’s as efficient as it could be or that we’re definitively on the road to driving out all the waste. History suggests that improving productivity in health care is extremely hard and extremely rare.

About the author: Austin B. Frakt, PhD,is the Director of the Partnered Evidence-based Policy Resource Center, Veterans Health Administration; an Associate Professor at Boston University’s School of Public Health; and a Senior Research Scientist with the Department of Health Policy and Management at the Harvard T.H. Chan School of Public Health. He blogs about health economics and policy at The Incidental Economist, tweets at @afrakt, and is a regular contributor for the New York Times. The views expressed in this post are that of the author and do not necessarily reflect the position of the Department of Veterans Affairs, Boston University, or Harvard University.  (Image: Doug Levy)
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