On December 22, 2022, the Peking University Global Health and Development Forum 2022 was held with the main theme of Digital Transformation and Development Divides. Co-organized by the Beijing Forum, Asian Development Bank and PKU Institute for Global Health and Development, this Forum brought together world leading scholars, policy researchers and industry leaders from both China and international communities to share their insights and recommendations on the thematic topics, attracted over 10 thousands online viewers participated in the event. Sandro Galea, Dean and Robert A. Knox Professor at Boston University School of Public Health, and a member of the National Academy of Medicine (NAM) delivered a keynote speech at the session of Digital Transformation in Healthcare.
Thank you for the opportunity to speak with you today. As Dean of the School of Public Health at Boston University, I am honored to be part of this meeting, which aims to discuss the use of data for the purpose of improving health and healthcare. My focus today will be on the importance of understanding the determinants of health, and how data can aid in making better decisions to promote longer, healthier lives.
Before delving deeper into this topic, it is essential to understand what causes health. Healthcare, as depicted in the diagram from the Institute for Clinical Systems Improvement, accounts for only 20% of health outcomes. The majority of health outcomes are determined by factors such as tobacco use, diet, alcohol, physical environment, education, job status, family support, income, and community safety.
To fully grasp the impact of these determinants of health, it is essential to note that health outcomes are also shaped by the conditions in which we live. This is evidenced by the data from the Bureau of Labor Statistics in the United States, which shows that most of our time is spent on activities other than healthcare. This highlights the fact that what causes health is much larger than healthcare alone. To truly improve health outcomes, we must also focus on digital approaches that address the broader determinants of health, such as air, housing, and food conditions.
Furthermore, ignoring the broader determinants of health has severe consequences, as is evident in the health disparities and gaps across the globe and within countries such as the United States. These disparities are not due to physiological or genetic differences, but rather, social and economic differences. To illustrate this, we can look at the differences in life expectancy between countries, states, counties, and cities, ranging from 20 to 25 years. Additionally, the disparities in health outcomes between Black and White Americans are directly linked to patterns of differences in social determinants such as unemployment rate, education, income, home ownership, and incarceration.
When considering digital approaches for capturing the conditions that affect our health, such as the air we breathe, the housing we live in, and the food we eat, it is important to take into account the full range of factors known as the "social determinants of health." These include commercial influences, political and governance factors, neighborhood conditions, religious and cultural forces, and individual factors such as social position, assets, income, education, behavior, psychiatry, and genetics.
Ignoring these social determinants of health can lead to significant health disparities and gaps, both globally and within countries. For example, there is a 25-year gap in life expectancy between some countries in sub-Saharan Africa and other Western countries. Similarly, within the United States, there is a 20-year difference in life expectancy across states, counties, and even cities.
These differences in life expectancy are not due to physiological or genetic differences, but rather to social and economic differences. The United States, like many other countries, has paid a high price for this neglect of the social determinants of health, as evidenced by declining health outcomes relative to other high-income countries in the early 1990s. Since the 1990s, the United States has performed worse than other high-income countries with regard to health outcomes. This is a direct result of the social and economic forces that have gone unaddressed. Specific elements of health disparities in the United States include, for example, the black-white gap in health, which is directly linked to patterns of differences in these social determinants. For example, the unemployment rate has historically been higher among Black Americans than among White Americans, and the same is true for educational attainment, household income, and home ownership. Additionally, Black Americans experience higher incarceration rates, which translates into lower life expectancy.
These social determinants are directly linked to health, life expectancy, and quality of life. The COVID-19 pandemic has brought these issues to the forefront, as demonstrated by this graph that shows a decline in life expectancy in many countries over the past two years. In the United States, this decline in life expectancy has not been consistent across all groups, with certain races experiencing disproportionately large drops, including a six-year drop for Native Americans. This decline is directly linked to the imbalances in the social and economic determinants discussed earlier. Furthermore, when looking at COVID-19 deaths, it becomes clear that individuals in certain occupations, such as bus drivers and construction workers, are disproportionately affected, further highlighting the social patterning of deaths due to the pandemic. The consequences of the pandemic extend well beyond COVID-19 deaths themselves, including a 30% increase in deaths due to overdose in the last two years in the United States.
The pattern of vaccination for COVID-19 has been observed among different groups of counties in the United States. The most vulnerable counties have been found to have higher rates of vaccination than the least vulnerable counties. This is due to the fact that social and economic conditions that make these counties more vulnerable also make them less likely to access and receive vaccinations. These social and economic conditions have a significant impact on the health outcomes of individuals and communities, and neglecting them leads to significant health disparities.
The theme of this presentation is data and its role in improving health outcomes. The speaker draws on the work of the Boston University Commission on Data, Social Determinants, and Better Decision-making for Health, which was chaired by the speaker and had 25 members from around the world. The commission believes that there is a wide range of data that should be used to understand social and economic determinants of health. This includes traditional data sources such as census and health assessments, as well as digital consumer footprints and remote sensing data. This data should ultimately be collected and integrated into a web-based ecosystem that allows for a full understanding of the determinants of health.
The commission's report also highlights the need for a more holistic approach to decision-making in health, one that considers a wide range of data and competing priorities. Currently, decision-making on health is often made through a funnel-like approach, where data is narrowed down, and only a select few pieces of information are used for decision-making.
It is then self-evident that the social and economic determinants of health need to be part of any calculation as we think about improving health. And as a result the data to the end of characterizing the social determinants becomes critical and important in order for us to be able to move the health of populations forward. At the same time, when you need a global survey of the commission, our commission, I'm asking people primarily causes their health, which was done in eight countries worldwide, and you see that, people report that it's healthcare that influences their health. See 24.6% say healthcare, and it's a lower proportion of people who say things like education, culture, childhood conditions, matter for health. In fact, politics, only about 3% of people said politics is responsible for their health.
This means that if you subscribe that these things in my talk, and you can listen to talk my say yes, okay, it makes sense, that's actually quite different from our populations’ recognition, which means that we need to make sure that populations do come on board and governments representing populations come on board. The data, by the way, are pretty consistent in countries across the world. We did the study in eight different countries, as you see them here. And you look at healthcare, which is in the bottom row, second front left, healthcare is by far the most commonly reported cause of health everywhere worldwide, education coming in second. And so populations need to be brought along so that we can have the building of trust in the systems that generate help to the end of having those systems empowered to really do their job to create healthier, longer lives.
In essence, what we propose is that decision-making for health in both clinical and societal contexts should be made within an ecosystem that takes into account a comprehensive set of data. This includes data about clinical markers, genetic information, psychiatric history, biomarkers, and environmental and social factors. The commission has outlined six principles to guide this approach.
First, all data resources related to health should be used to inform decisions.
Second, when making decisions in various sectors, the impact on health should be taken into account.
Third, decision-making that affects health populations should prioritize health equity and strive to reduce health disparities. And also it should be noted that sometimes there are trade-offs between short-term and long-term costs and benefits when it comes to health decision-making.
Fourth, all available data resources on the determinants of health should be utilized in decision-making, including both novel and traditional sources.
Fifth, the need for data on the social determinants of health should contribute to more transparent and accountable governance for health. The widening gap in life expectancy among populations highlights the need for greater accountability from those making decisions about health, and utilizing data can aid in closing such gaps and improving health outcomes for all.
Finally, evidence that informs decision-making needs to be participatory and inclusive of multiple perspectives, particularly in regard to the populations whose data is being used to inform decisions about their own health.
The commission also made four recommendations:
First, relevant authorities should collect and make available real-time, quality data on all determinants of health.
Second, transparent systems should be developed to collect data on all determinants of health.
Third, monitoring processes should be put in place to ensure accountability in data collection and interpretation.
Fourth, communities should be involved in both the acquisition and interpretation of data, both domestically and internationally.
In conclusion, addressing the social and economic determinants of health, in both high and low-income countries, is essential in advancing health and health equity on a global scale. It's important to overcome the barriers that impede this progress and harnessing the potential of data collection, analysis and use is one of the way to do that.
As I conclude, I wish to address the question of how to advance health and health equity on a global scale and what barriers currently impede this progress. It is clear that the leading causes of death in both high-income and low-income countries are strongly influenced by social and economic determinants of health. Therefore, it is essential that we consider these factors when striving to improve overall health outcomes.
The data necessary to fully understand and characterize these social determinants is crucial in this endeavor. However, findings from a global survey conducted by our commission revealed that, when asked what primarily influences their health, a majority of people identified healthcare as the primary factor, with relatively lower percentages identifying factors such as education and culture. This discrepancy between expert understanding and public perception highlights the need for greater efforts to educate and engage populations, as well as their representatives in government, in this issue.
The study was conducted in eight countries, and the results were consistent across all of them, with healthcare being identified as the primary influencer of health and education as the second. It's important for the general public to understand the real factors affecting their health and for the government to build trust in the system that will generate solutions and empower them to help improve people's life.
The question of how to build trust in systems that are responsible for generating solutions to public health issues is of paramount importance. Trust is a complex and multi-faceted concept, but in the context of public health, it is a product of three key components: convincing populations that the technical capacity exists to address health concerns, having the political will to act, and engaging and involving communities in the data collection, analysis, and decision-making process.
The COVID-19 pandemic has served as a stark example of the consequences of failing to build and maintain trust in public health systems. In many instances, trust broke down due to a lack of political will, public doubts about the technical capacity of health systems to respond effectively, and inadequate engagement and involvement of communities in the decision-making process.
It's important to keep in mind that, health is determined by a full range of factors, not just one. For example, to understand the disease, treating only the virus or the symptoms is not enough, it's necessary to understand the social, economic, and environmental factors that also contribute to the health of populations.
To end with, the example of the painting of a Kangaroo is a visual representation of how a single force can be perceived and described differently. The image of the Kangaroo can be interpreted based on the limited knowledge of the observer, and without proper data, the image can be inaccurate. In the same way, the perception of health and its determinants can be influenced by our understanding and available data.
In conclusion, it is vital that when making decisions related to health, the full set of data and the broader social and economic factors that contribute to health are taken into account. The COVID-19 pandemic has highlighted the consequences of failing to do so. During this meeting, as we discuss digital approaches and data strategies for improving health outcomes, it is essential that we consider the forces outside of healthcare that play a crucial role in generating health.
I am honored to have been asked to speak here and contribute to this conversation. My thoughts on these issues are further explored in my latest book, which was published last year and is available for reference. Additionally, more information on my writing and research can be found on my website, sandrogalea.org.
Once again, thank you for having me join you. It is a privilege to join this distinguished meeting, and I very much look forward to learning more from watching the other deliberations. I would like to express my appreciation for the opportunity to participate in this distinguished meeting, and I look forward to learning from the discussions and deliberations to come. Thank you very much!
