Do Anesthesiologists Have a Role in Promoting Equitable Health Care?

The lack of equity in the U.S. healthcare system is nothing short of a public health crisis. Between 1999 and 2020, Black individuals experienced approximately 1.6 million excess deaths and 80 million excess years of life lost compared to White individuals.¹  The magnitude of this inequity was laid bare during the recent pandemic; individuals from minoritized groups accounted for 36% of COVID-19 deaths and 70% of non–COVID-19 excess deaths.²  These racial disparities in health outcomes are not rooted in biologic differences. Instead, they result from social determinants of health, such as lack of insurance coverage, and structural racism as manifested by unequal health care.

In this issue, Guglielminotti et al.³  aim to examine how a change to federal law impacts a racial and socioeconomic disparity that characterizes our care of pregnant women—namely, that Black and Hispanic women, and women without private insurance, are less likely to receive labor neuraxial analgesia.⁴ 

Their study used a methodologically rigorous quasi-experimental research design—difference-in-difference analysis—to examine whether the 2010 Dependent Coverage Provision of the Patient Protection and Affordable Care Act (which required private health insurance companies to allow young adults to stay on their parent’s plan until age 26 yr) increased the use of labor neuraxial analgesia. New healthcare policies would ideally be studied in a randomized controlled trial. Since randomized controlled trials are rarely feasible in public health, researchers frequently take advantage of natural experiments in which patients are assigned to groups in a seemingly random (but not truly random) fashion. The goal of difference-in-difference analysis is to limit the threats to causal inference by comparing outcomes before and after the implementation of an intervention to the outcomes of a control group over the same time period. In a difference-in-difference design,⁵  there are two groups of patients: an intervention group (in this case, patients who are eligible for the Dependent Care Coverage Provision [patients 21 to 25 yr]) and a control group (patients who are not eligible for this policy [patients 27 to 31 yr]). Neither group was exposed to the new policy during the “pre-period.” During the post-period, the intervention group was exposed to the new policy (patients 21 to 25 yr), while the nonintervention group was not exposed to the new policy (patients 27 to 31 yr). Using this regression-based technique, changes in outcomes in the intervention group between the pre- and post-period were adjusted for the changes in the control group between the pre- and post-period (i.e., the counterfactual) to identify the effect of the intervention.

Alternatively, a simple pre-post design is often used. In this case, there is no control group, and the effect of an intervention is identified as the change in outcome between the pre- and the post-period. However, this simple pre-post design does not control for the possibility that the outcome of interest changed over time and would have done so without the intervention. In contrast, the difference-in-difference analysis controls for underlying time trends and includes a control group. Not controlling for an underlying common time trend can lead to spurious findings. For example, using a simple pre-post research design, two seminal studies reported improvements in surgical mortality with participation in the Veterans Administration and the American College of Surgeons (Chicago, Illinois) National Surgical Quality Improvement Program.^6,7  Two subsequent studies, based on difference-in-difference analysis, showed no benefit to participation in American College of Surgeons National Surgical Quality Improvement Program.^8,9 

In order for difference-in-difference analysis to be valid, the time trends of the control and intervention groups during the pre-period must be parallel, as reported by Guglielminotti et al. If this is not the case, divergent time trends can be accommodated using comparative interrupted time series analysis. Notably, Guido Imbens won the Nobel Prize in Economics in 2021 for his work developing quasi-experimental methods to examine causal inferences using observational data.

In their paper, Guglielminotti et al. demonstrated that the 2010 Dependent Coverage Provision of the Patient Protection and Affordable Care Act, which required private health insurance companies to allow young adults to stay on their parent’s plan until age 26 yr, was associated with a slight increase in the use of neuraxial analgesia during labor. However, the magnitude of this increase was small, reflecting the very small (1.2 percentage-point) increase in the proportion of women with private insurance after this policy was implemented. The authors note that the 1.0 percentage-point increase in the use of labor neuraxial analgesia is unlikely to be clinically significant. In implementing this advanced econometric technique, Guglielminotti et al. are helping to lay the foundation for creating a more equitable healthcare system. Physician-scientists, including many anesthesiologists, have been at the vanguard of identifying examples of inequitable health care. However, we need to do more than document inequity in the healthcare system; we need to work with policy-makers to design and implement policies to reduce inequity.

Anesthesiologists play a critical role in the delivery of intraoperative and perioperative healthcare services. Given the profound inequities in U.S. health care, how can our field advance the cause of health equity? First, we must systematically assess our practice to identify where disparities in our care exist. This may include difficult self-assessments in which we identify and correct hidden biases that may negatively influence our clinical choices. Then we must help identify policies (including government policies) and practices to close these gaps. Last, we need to help lead efforts by physician organizations to promote policies in our hospitals, and at the state and federal levels that will address inequity.

Individually, we may feel powerless as physicians to alter healthcare policy, but collectively we can achieve change. Several professional societies have advocated for healthcare equity, including the American Society of Anesthesiologists (ASA; Schaumburg, Illinois),¹⁰  American Heart Association (Dallas, Texas),¹¹  American Medical Association (Chicago, Illinois),¹²  American College of Physicians (Philadelphia, Pennsylvania),¹³  and Society of Thoracic Surgeons (Chicago, Illinois).¹⁴  Some, like the ASA, have emphasized the importance of ensuring access to high-quality health insurance as a critical factor in promoting healthcare equity.¹⁰  Uninsured or inadequately insured individuals face substantial barriers to accessing essential healthcare services. They have a limited choice of providers, frequently receive care from lower-quality providers, and may be more likely to be denied coverage for specific treatments. Karen Domino recounted in 2022, while delivering the Ellison Pierce Lecture at the ASA, her experiences caring for a trauma patient who had been transferred to her hospital after initially undergoing a “wallet biopsy” at another hospital.¹⁵  As shocking as a wallet biopsy is, the reality of insurance-based disparities is even worse: mortality rates in patients undergoing noncardiac surgery with Medicaid insurance and without insurance are 29% and 75% higher, respectively, compared to patients with private insurance, after controlling for surgical complexity and patient comorbidity.¹⁶ 

The study by Guglielminotti et al. was conducted in the context of many Americans lacking health insurance coverage, which is the problem the Affordable Care Act’s dependent coverage expansion aimed to address. However, despite Medicaid expansion and the dependent coverage expansion, and a significant reduction in uninsured rates among Black Americans (from 20% to 12%), many Americans still lack insurance coverage.¹⁷  Even with this increase in insurance coverage, one in four Americans have no health insurance at some point over a 2-yr period.¹⁸  Furthermore, as noted above, the type of insurance coverage (Medicaid vs. private insurance) is an important determinant of outcomes. Black individuals (ages 18 to 64 yr) are less likely to have private insurance (55% vs. 73%) and are more likely to have public insurance (30% vs. 18%), or no insurance compared to White individuals (12% vs. 9%).¹⁷  Achieving equity for historically marginalized Americans requires us to reexamine the structure of our market-driven healthcare system in which patient access and outcomes are partly a function of insurance.

Achieving equitable health care requires that we extend the same quality of care to all patients. Older adults earning less than 138% of the Federal Poverty Level have a fourfold higher mortality rate compared to higher-income individuals (1.7% vs. 0.4%).¹⁹  There is a shocking 14.6-yr gap in life expectancy between U.S. men in the bottom 1% and top 1% income groups.²⁰  Although more equitable health care will not eliminate this gap, improving health equity may help narrow this gap. But can we afford to do this? In 2021, the United States spent $4.3 trillion on health care or $12,914 per person, accounting for 18.3% of the gross domestic product.²¹  Although the United States spends more on health care as a percentage of gross domestic product than any other of the 37 democracies with market-based economies in the Organisation for Economic Co-operation and Development (Paris, France), the United States is the only high-income country without universal healthcare coverage.^22–24 

In the preceding paragraph, we asked whether the United States, arguably one of the wealthiest nations in the world, can afford equitable health care. To date, our society has decided that the answer is a qualified yes. On the one hand, the number of uninsured Americans has dropped significantly under the Affordable Care Act. It will likely drop even more with the implementation of the Inflation Reduction Act. On the other hand, Congress’s repeal of the individual mandate and the Supreme Court decision that rendered Medicaid expansion optional have blunted the impact of the Affordable Care Act. The repeal of the individual mandate, which required people to obtain health insurance or pay a tax penalty, may cause some of these gains in insurance coverage to diminish.²⁵  The repeal of the individual mandate reduces the likelihood that healthy people without employer-based insurance will purchase health insurance, leading to higher costs and less affordable coverage for people who opt to participate in the Health Insurance Marketplace.

The question asked in the study by Guglielminotti et al. focused on the dependent coverage expansion of the Affordable Care Act, but an important question to ask more broadly is whether greater access to health insurance will lead to better health outcomes and better health equity. Many of the social determinants of health, such as socioeconomic status, education, employment, and social support, may be modifiable by changes in social policy. However, control over these social determinants of health fall outside of the healthcare system. Insurance coverage, on the other hand, is a critical social determinant of health that is modifiable by state and federal policymakers, and evidence is steadily mounting that insurance coverage does, in fact, save lives. In the landmark study in Oregon, in which 20,000 low-income residents participated in a randomized controlled trial of Medicaid expansion, Medicaid coverage resulted in significant improvements in self-reported health but no improvements in health outcomes.²⁶  However, nearly 10 yr after the implementation of Medicaid expansion under the Affordable Care Act, mounting evidence based on rigorous nonrandomized studies now suggests that expanding insurance coverage leads to significant improvements in access to care,^27,28  condition-specific outcomes,^29,30  self-reported health,^28,31  and population-level survival.³²  Medicaid expansion is also associated with improved access to optimal surgical care for common and serious surgical diseases,³³  and enhanced access to cancer surgery.³⁴  It is estimated that individuals living in expansion states experienced a 6 to 9% decrease in annual mortality due to Medicaid expansion.^19,35  It is also estimated that one life would be saved for every 239 to 316 adults acquiring health insurance at a cost between $327,000 and $867,000 per life saved.³⁵  These findings have important implications for the implementation of new Medicaid work or eligibility requirements, currently under consideration in nearly 40% of U.S. states, that may reverse some of the gains under the Affordable Care Act.³⁶  Together, this evidence suggests that providing health insurance coverage for the 27.5 million Americans who currently lack health insurance would meaningfully impact the health outcomes of some of the most vulnerable Americans.

The status quo of healthcare disparities is unacceptable. Health care should not be a commodity reserved for those who can pay for it. High-quality health care should be universal. Do any of us believe that some of our patients deserve worse health care than we receive as physicians? Do our legislators believe that they, as government employees, deserve better health care than the people they serve? It is imperative that we leverage our collective voices and resources to achieve universal, equitable health care. As we advocate for change, we should remember the possibility that any of us, or our loved ones, could be part of the staggering statistic of one in four Americans who lack health insurance at some point over a 2-year period. This possibility underscores the urgent need for change that ensures high-quality health care is a fundamental human right for all Americans.

The authors wish to thank Brian Bateman, M.D. (Stanford University, Stanford, California), for his assistance and insights during the preparation of the manuscript.

This work was supported by a grant from the National Institute on Aging (Bethesda, Maryland; R01AG074492) and the Department of Anesthesiology and Perioperative Medicine at the University of Rochester School of Medicine and Dentistry (Rochester, New York). The funders played no role in the design and conduct of the study; review or approval of the manuscript; or decision to submit the manuscript.

Dr. Joynt Maddox receives research support from the National Heart, Lung, and Blood Institute (Bethesda, Maryland; R01HL143421 and R01HL164561), National Institute of Nursing Research (Bethesda, Maryland; U01NR020555), National Institute on Aging (Bethesda, Maryland; R01AG060935, R01AG063759, and R21AG065526), National Center for Advancing Translational Sciences (Bethesda, Maryland; UL1TR002345), and Humana (Louisville, Kentucky). She also serves on the Health Policy Advisory Council for the Centene Corporation (St. Louis, Missouri). The other authors are not supported by, nor maintain any financial interest in, any commercial activity that may be associated with the topic of this article.