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Milbank Quarterly Classics Population health
David A. Kindig
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“Medical measures appear to have contributed little to the overall decline in mortality in the United States since about 1900.” Readers might assume that this statement is from a recent research article or policy report featuring the social determinants of health. But no, it is from the 1977 seminal Milbank Quarterly article by John and Sonja McKinlay titled “The Questionable Contribution of Medical Measures to the Decline of Mortality in the United States in the Twentieth Century.”1
John McKinlay is a medical sociologist and epidemiologist, and Sonja is a mathematical statistician. They both ended their full‐time careers leading the New England Research Institutes. Natives of New Zealand, they both received doctorates at the University of Aberdeen in Scotland. While working in the United Kingdom, they were exposed to the English and Welsh research of Thomas McKeown, and at ages 35 and 34, wondered whether his thesis that specific medical measures had little effect on overall mortality declines also applied in the United States. In 2008, John received the American Sociological Association Distinguished Career Award for the Practice of Sociology. That award cited his use of “sociology to identify gaps in literature, frame new research questions, and convince others of the importance of his ideas in areas others may view as entirely unrelated to sociology.”
John B. McKinlay and Sonja M. McKinlay
These qualities were evident when I first read their 1977 article in 1995 while writing my sabbatical book, Purchasing Population Health: Paying For Results, in which I reproduced two of its figures. Figure 2 remains a striking image and illustrates their major line of evidence that declines from 1900 to 1973 in US all‐cause mortality (primarily from 11 infectious diseases) had already bottomed out before increases in health care spending began its dramatic escalation. For the five infectious diseases that showed a mortality impact after interventions were introduced (influenza, pneumonia, diphtheria, pertussis, and poliomyelitis), there was only a 3.5% contribution to the decline in total mortality over this period.
The McKinlays then asked the question “if they [medical measures] were not primarily responsible for it [the decline in mortality], then how is it to be explained?” They did not answer this question themselves, but referred back to McKeown, who had concluded that “the main influences were: (a) rising standards of living, of which the most significant feature was a better diet; (b) improvements in hygiene; and (c) a favorable trend in the relationship between some micro‐organisms and the human host.”2 However, in their conclusion they magnified this point, stating that “profound policy implications follow from either a confirmation or a rejection of the thesis. If one subscribes to the view that we are slowly but surely eliminating one disease after another because of medical interventions, then there may be little commitment to social change and even resistance to some reordering of priorities in medical expenditures. Hopefully, this paper will serve as a catalyst for such research, incorporating adequate data and appropriate methods of analysis, in an effort to arrive at a more viable alternative explanation.”
As surprising as this may have been in 1977, it is even more shocking that the question has not yet been adequately answered. Of course, the analysis today would be different, as deaths from chronic diseases have replaced the impact of infectious diseases of that period, which they showed in Figure 3, and “managing” these diseases may now be more important than “eliminating” them. But, in what I consider to be the seminal paper in the modern field of population health science, only one italicized sentence regarding the contribution of medical measures appeared: “A society that spends so much on health care that it cannot or will not spend adequately on other health enhancing activities may actually be reducing the health of its population.”3 The authors, however, made no empiric estimate regarding what this adequate fraction should be.
For many years, I taught a session of my population health course featuring the two contemporary papers that frame what we know today—the first by McGinnis and colleagues,4 based on CDC surveys, argues that medical care is responsible for about 10% of preventable mortality, and the second an econometric analysis by David Cutler5 argues that medical care was responsible for 50% improvement in certain causes of mortality over the period of 1960 to 2000. When students are shocked by this range, I remind them that, in a world that still predominantly assumes the pre‐McKinlay reality of medical care being close to fully responsible for preventing or curing disease and death, it is still a profound statement to many that much more than medical care goes into the production of health.
In a 2007 Milbank Quarterly article, I asserted that “the overriding population health question is, What is the optimal balance of investments (e.g., dollars, time, policies) in the multiple determinants of health (e.g., behavior, environment, socioeconomic status, medical care, genetics) over the life course that will maximize overall health outcomes and minimize health inequities at the population level?” This is a significant challenge that will require decades of attention by scholars and policymakers.”6
One of my major disappointments at age 80 is that more policy relevant answers have not emerged. Progress can be made even with current understanding, as shown by the impact of the County Health Rankings model (https://www.countyhealthrankings.org) that uses as a starting point a 20% weight for medical care impact on a broad health outcome mix of mortality and morbidity. It may be that our methods and especially robust longitudinal data are inadequate for more complete causal understanding. From this perspective, Greg Stoddart in 1995 called it the Fantasy Equation, arguing that “at present we but vaguely understand the relative magnitude of the coefficients on the independent variables that would inform specific policies rather than broad directions, even if we are beginning to see the variables themselves more clearly“7,8(p344) and that more careful context‐specific studies are required. But I refuse to accept that increased and badly needed policy relevant results would not emerge from much more significant investment in data infrastructure rather than having wasted and ineffective medical care dollars consume those resources,9 such as that recently shown by Milstein and Homer.10
It should be noted that some anti‐vaccine advocates have used the McKinlays’ paper as scientific support for their views. To this, the McKinlays reply that “we consider this an egregious misinterpretation of our research. Effective vaccines clearly have an important role in the ongoing containment of a disease after its prevalence has been reduced. Measles provides an excellent current example of the resurgence of a previously contained infectious disease following reduction in measles vaccination interventions.” However, they add, in supporting basic public health measures, that “if the current coronavirus follows the established course of the several infectious diseases of the past that we examined, then promising therapeutics or vaccines will have little effect on any overall decline in the disease.”
The question they posed in 1977 is still fundamental to modern population health scholarship. I would add now a second applied question: once pieces of the Fantasy Equation are better understood, how can we create financial and other incentives for effective health enhancing cross‐sectoral collaboration and reinvestment? The November 2020 special issue of the American Journal of Public Health features substantial analysis and commentary on the challenges for achieving the 2012 Institute of Medicine recommendation to reach parity with other OECD nations in both health outcomes and health expenditures to improve the public’s health.11
In conclusion, I remain grateful for the McKinlays’ ahead‐of‐its‐time article and for its ongoing relevance. But my hope (and concern) is that it doesn’t take another 40 years for significant scholarship and policy progress to be made on this most critical population health challenge.
1. McKinlay JB, McKinlay SM. The Questionable Contribution of Medical Measures to the Decline of Mortality in the United States in the Twentieth Century. Milbank Q. 1977;55(3):405-428. 2. McKeown T, Record RG, Turner RD. An interpretation of the decline of mortality in England and Wales during the twentieth century. Population Studies. 1975;29:391. 3. Evans R, Stoddart GC. Consuming healthcare, producing health. Soc Sci Med. 1990;33:1347-1363. 4. McGinnis M, Williams-Russo P, Knickman J. The case for more active policy attention to health promotion. Health Aff (Millwood). 2002; 21(2):78-93. 5. Cutler DM, Rosen AB, Vijan S. The value of medical spending in the United States, 1960–2000. N Engl J Med. 2006;355:920-927. 6. Kindig DA. Understanding population health terminology. Milbank Q. 2007;85(1):139-161. 7. Stoddart G. The challenge of producing health in modern economies. Centre for Health Economics and Policy Analysis Working Paper Series 1995-15, Centre for Health Economics and Policy Analysis (CHEPA), McMaster University, Hamilton, Canada; 1995. 8. Stoddart GL, Eyles JD, Lavis JN, Chaulk PC. Reallocating resources across public sectors to improve population health. In: Societies: From Analysis to Action. Oxford University Press; 2006:327-347. 9. Kindig D, Mullahy J. Comparative effectiveness-of what? Evaluating strategies to improve population health. JAMA. 2010;304(8):901-902. 10. Milstein B, Homer J. Which priorities for health and well-being stand out after accounting for tangled threats and costs? Simulating potential intervention portfolios in large urban counties. Milbank Q. 2020;98(2):372-398. 11. McCullough JM, Spee, M, Magnan S, et al. Reduction in US Health Care Spending Required toMeet the Institute of Medicine’s 2030 Target. Am J Public Health. In press.
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David A. Kindig, MD, PhD, is emeritus professor of population health sciences and emeritus vice-chancellor for health sciences at the University of Wisconsin–Madison School of Medicine. He currently is cochair of the Institute of Medicine Roundtable on Population Health Improvement and codirects the Wisconsin site of the Robert Wood Johnson Foundation (RWJF) Health & Society Scholars Program. He was an initial co-principal investigator on the RWJF MATCH grant under which the County Health Rankings were developed and was the founder of the RWJF Roadmaps to Health Prize. He received a BA from Carleton College and MD and PhD degrees from the University of Chicago School of Medicine.
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