The public forum is dominated by discussions surrounding access to medical care. In part, calls for expanded “health care” abound with the term often a misnomer. There is no doubt that modern medical advances extend life and cure or make chronic diseases that once held little hope possible. This progress restores individuals to their baseline if not better. Methods for prevention are also amplified and monitored. But, a new study in the Annals of Family Medicine suggests the lion’s share of curtailing or curbing premature death in a population may not rest with sick care (or “health care”) alone, but instead with behavioral factors.
The researchers found their data “produced estimates ranging from 0% to 17% of premature mortality attributable to deficiencies in health care access or delivery. Estimates of the effect of behavioral factors ranged from 16% to 65%.”
In an effort to clarify an age-old argument over where investments should be deployed to make the most positive contribution to population health and life expectancy, researchers decided to “review 4 different estimates of the contributions of health care to premature mortality and other health outcomes.” Resources are often considered best directed to medical services. But, that is only one piece of the story, as much evidence shows how influential social determinants of health are to outcomes and promoting longevity.
To understand what actually is incorporated into this concept of premature mortality, consider, for example, a fatal motor vehicle accident where excessive alcohol intake was the cause. Or, death from lung cancer due to cigarette smoking. These eventualities would be categorized more by behavioral factors. There is much work done on trying to link variations in health care use with morbidity and mortality, and debate surrounding how to direct resources tends to focus on medical services when any number of avenues warrant attention. The investigators here sought to determine how much the prior data collected on this topic actually does or does not tell us about the weighted contribution of health behaviors (eg tobacco use, poor diet, sedentary lifestyle, substance abuse), medical care albeit access to it or level of its quality, environmental exposures (eg toxins, air quality), or socioeconomic influences (eg income, support structures, safety of community, education) when it comes to health outcomes.
There are many more estimates that have made their way to the literature over the years. So, more exists than was examined in this work. It is a monstrous challenge to assess the effect of medical treatment in this manner and the limitations to doing so abound. For instance, stratifying by disease state will be more beneficial to understanding the genuine impact of a therapy than one number for an entire population’s life expectancy. As poignantly evidenced by the authors,
“For example, successful treatment of women with cervical cancer could add 21 years to the life expectancy of a particular patient. The condition affects about 13,000 women annually, therefore the estimated gain in total US population life expectancy for treatment of cervical cancer is only 1 week. Similarly, successful treatment of colorectal cancer could add 12 years of life to as many as 155,000 adults. But on a population-wide basis, it contributes only about 1 week to average life expectancy. Likewise, treatments for appendicitis, pneumonia, and influenza, although successful for many individuals, on average have a negligible effect on population life expectancy.”
So, understanding that even life expectancy as a term has refined meaning when put into context is critical to its actual interpretation. This is why comparing countries by infant mortality rates is also an incredibly flawed endeavor. For example, some countries define it differently and include first breath, while others do not. Some track till the first year, others do not. The notion it is a uniform, standard value is a false premise.
Here’s the rub. When it comes to longevity, in general, and metrics like life expectancy, they are often flawed and idealized. What benefits a population or the aggregate, may not be in the best interest of the individual as there is tremendous variability in genetics, disease, clinical status and beyond. Practicing medicine offers unique insights into how people manage risk. Intellectually, for most, knowing that 90% do well following a particular path is calming until you fall into the 10% group. Then, that potential for poor outcome becomes 100% to you. And, the meaning shifts dramatically. This is why making sweeping generalizations rarely moves the needle in improving health care delivery. Understanding the nuances of geography, populations, medical histories, behavior, biopsychosocial spheres etc is essential to compelling genuine change for the better - and for the most people.
One thing is clear, to say a population’s life expectancy rates are exclusively correlated with the availability and quality of healthcare services is overly simplistic and does not begin to address the complexity of factors involved. As inconvenient as it is, the multifaceted nature of what contributes to overall longevity is unique to individuals within a population and can have much variability by region, genetic influences, occupation, lifestyle, clinical status, education and so on.
This report’s analysis conveys “social and behavioral factors account for a much higher percentage of the variation in premature mortality than health care does.” Now, that doesn’t mean that investing in health care isn’t worthwhile. Don’t forget, these metrics don’t emphasize or address new treatments and modalities that are extending life and converting once ominous disease to more chronic conditions. There is great value in funding research and optimizing health care delivery. This piece simply reminds us that there is also value to consider that extends beyond the hospital bed and exam room. Also investing in communities and social determinants of health will improve quality of life in a multi-prong fashion, and this, too, can yield great dividends to a population - in daily life and in terms of longevity.
The take home message of this study is to diversify. Recognizing access to and the quality of medical services is one crucial component to enhancing longevity is important - especially for the individual. Factoring in the others adds value too.
This publication reinforces (and rides the current wave on) the importance of social determinants of health already underway.
For instance, in the not-so-new realm of nontraditional health coverage, the Centers for Medicare and Medicaid Services (CMS) is expanding their Medicare Advantage plan to include benefits that meet patients “unique health needs” and improve “their quality of life.” Behavioral economics is currently in full swing and now being put to the test by this recent roll out set to take effect this year. Based on the premise that social determinants can drive poor health outcomes and increase costs, equalizing these factors through non-emergent medical transportation (NEMT, read here) as a means to reduce barriers thereby improving care access, providing air conditioners for high risk populations and specific foods for those with diabetes could impact healthcare spending with a hope of yielding overall savings. Read more here and also learn about spending by other countries on social services compared to the United States.
Robert M. Kaplan, PhD and Arnold Milstein, MD, MPH. Contributions of Health Care to Longevity: A Review of 4 Estimation Methods. Ann Fam Med May/June 2019 vol. 17 no. 3 267-272. doi: 10.1370/afm.2362, see here.
The authors are from Stanford University School of Medicine's Clinical Excellence Research Center (CERC). I recently attended a conference (unrelated to this journal article) in Chicago organized by Stanford's CERC on "Reducing the Cost of Great Care: Pathways to Value."
Originally posted May 22, 2019 on www.acsh.org