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February 13, 2017 – MCAT CARS Passage
Ambitious programs to improve the U.S. health care system typically include improving population health in their objectives. For example, that is one of the Institute for Healthcare Improvement’s “Triple Aims” (along with improving the patient experience and lowering the per capita cost of care). Similarly, the Affordable Care Act (ACA) is designed to improve population health in multiple ways, the most obvious being improved access to care. But the ACA also aims to improve the quality of care, enhance prevention, and promote health through the implementation of affordable care organizations (ACOs) and the establishment of a new Prevention and Public Health Fund.
One of the great challenges in these efforts lies in how to measure success. In general, population health is defined as the health outcomes of a group of individuals and how those outcomes are distributed within the group. But most discussions about measuring outcomes focus on the group as a whole and neglect distribution.
That’s unfortunate because, as every business person knows, what gets measured is what gets managed. If we simply measure overall population health, we can almost certainly improve it by focusing on low-hanging fruit — improving the health of groups that are easily accessible and most amenable to changing their behavior. (Think, for example, of the wellness programs that are common today in the business world.) But these efforts will inevitably widen health gaps, improving the health of some while leaving marginalized communities behind.
Closing those gaps should be at the heart of efforts to measure and improve population health, even it means sacrificing some efficiency. For example, much effort has gone into behavioral intervention apps, like those designed to help people quit smoking. Although the data is still out, it’s plausible that these apps make a difference for people who use them. But those users are almost certainly people who have ready access to the technology and the discipline to apply it. People who can neither afford a smartphone nor lead lives organized enough to be driven by apps are left out, widening the health gap between app users and non-users.
Such approaches probably explain what has happened with the decline in tobacco use in the United States. Only about 1 in 5 adults now smoke, a historic low, but we are stuck there because most smokers are in the lower socioeconomic brackets. An alternative approach would explicitly aim to narrow the gap by doing the harder and more expensive work of targeting smokers with fewer means and enrolling them in smoking-cessation programs. This might divert efforts from the smartphone strategy, perhaps resulting in somewhat higher overall smoking rates, sacrificing some efficiency and cost savings in favor of greater equity.
Why should we be willing to accept such sacrifices, especially at a time when health care costs dominate the headlines? There are three reasons:
Health equity could bridge social divides, yielding much larger dividends than simple cost savings. Health is a public good that forms part of the social fabric. Health inequities fray that fabric, contributing to broader resentments of social inequities.
Narrowing health gaps is a value that drives much health care. Neglecting such equity chips away at the credibility and standing of health care organizations. Nothing undercuts that standing like charges of “Cadillac care,” available only to society’s “haves.” And credibility and standing are essential resources for health care organizations seeking to advance our collective health.
In an increasingly interconnected world, it is impossible to separate social groups. Poor health in some groups threatens the health of all groups. Consider the recent outbreak of measles that began at Disneyland and spread widely because some parents oppose vaccinations for their children. When a critical portion of a community is immunized against a contagious disease, most members of the community are protected. This “herd immunity” is a function not only of whether an individual child is immunized, but how many children are immunized as well.
Or consider the recent Ebola epidemic in West Africa, which threatened to become a global pandemic. While concern about the health of West Africans may feel like a distant problem for some of us, their health in an age of ready travel is inextricably linked to the health of Americans — an inescapable fact that should impel even the most cost-conscious among us to call for investment in better health for all.
There are several ways we can change the focus of measurement of health indicators from absolute achievement to measurement that accounts for inter-group differences. First, we can make closing the health gaps between groups one of the prime objectives in health improvement.
Second, we can include relative indicators of health along with absolute indicators in metrics. This will require that health systems measure factors around which we may expect difference — like race, ethnicity, and income — and tabulate, report, and hold themselves accountable to relative achievement in health indicators across these groups.
Finally, we can establish incentives that promote both efficiency in improving the absolute numbers and equity in closing gaps. The job of stimulating the adoption of such incentives may initially have to fall to government. But over time they could become embedded in provider culture, effecting a shift in system indicators we value and reward. With such incentives, payers and providers could broaden their expectations about outcomes to include equity, which ultimately benefits everyone.
Adapted from hbr
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This was an article on Population Health.
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