by Gulzar H. Shah, PhD, MStat, MS, and Wu Xu, MS, PhD

---

Introducing Health Informatics Innovations and Applications, a new series that highlights ways that health informatics innovations and applications are supporting stakeholders in public health practice and policy to advance their mission of improved population health. The series will also highlight innovations in health care informatics.

Last week, my co-author Dr. Wu Xu and I met after a decade or so of occasional path-crossing at conferences to participate in the reunion of graduates of the Yun Kim Population Research Lab, Utah State University to celebrate its 50^th. We were both surprised that despite entirely different titles of our talks, we ended up making a case for the importance of three aspects of public health in promoting population health: social determinants of health (SDoH), Health in All Policies (HiAP), and health informatics.

On second thought, it should not have been surprising given that we both were trained in demography. Also, we had made health informatics our primary professional interest in the mid-1990s, much before the term became a buzzword and even before we realized that our work constituted health informatics. During the mid-1990s, we both found ourselves on an interdisciplinary team engaged in public health informatics projects as employees of the Utah State Department of Health (DH). In 2002, we parted our professional pathways, with Wu staying with the Utah DH and myself venturing into several positions in academia and public health practice.

After our presentations at the reunion, we decided to share our thoughts on the interconnectivity of the SDoH and health informatics via this blog post. The coincidence of our overlapping presentations dictated that SDoH should be the focus of this blog, although we were fully aware that health informatics has implications for many other aspects of public health. Considering the increasing recent recognition of the importance of SDoH, and with health informatics being our defining career interests, we decided to outline the potential role of health informatics in assisting public health practice agencies in leveraging SDoH. Here are some salient points we discussed:

Let the Data Talk

The thought that we were being recognized among the successful graduates of the Yun Kim Lab during the 50-year celebration could not escape our minds. Hindsight being 20/20, we both agreed that betting on making a career out of “letting the data talk” back in the 1990s was not a bad career choice at all. True, given that skills in data and information sciences are still highly sought after, as made evident in the recent Bloomberg article by Michael Sasso about data science, titled “This Is America’s Hottest Job.”  Dr. Xu recalled a mentor’s advice, “If you can make data talk, you have a career regardless of which field.”

Tracing the Influence of SDOH on Health Is Not New

We recalled that SDoH were not a focus of public health practice back in the 1990s. So a holistic view of health was not common in public health practice. The public health practice emphasis was on individual health behaviors and clinical care. A renewed emphasis on SDoH is rooted in the notion that population health is not simply an outcome of health care, public health, and an individual’s characteristics and behaviors. Instead, unequal or unjust distribution of a broad array of socioeconomic, legal, and other resources and conditions influence individual and group differences in health status. I also brought up that the practice of social medicine, the mother of the social determinants of health paradigm, is not new. Origins of linking SDoH to health outcomes can be traced back to the work of a 19^th Century pathologist, public health activist, and social reformer Rudolf Virchow, who in 1848 determined that social conditions led to the epidemic of typhus, an infectious disease caused by rickettsial bacteria. Initial progress in social medicine and social illness did not become mainstream in public health until after the 1990s as the practice focus became the provision of essential public health services.

Health Informatics Is Relatively New

Health informatics in the contemporary sense of its meaning is relatively a new kid on the block, although evidence-based public health is not a new tradition, as it goes way back to the John Snow’s cholera outbreak investigation of 1854 in Soho, London. To our knowledge, the term “public health informatics” appeared the very first time in 1995 in the title of a peer-reviewed journal article, “Public Health Informatics: How Information-age Technology Can Strengthen Public Health.”

The Future of SDoH in the Age of Big Data

In the current public health landscape, big data generated from healthcare and other community partners are ready to talk about SDoH and their impact on health. For the big data to talk, greater expertise in public health is needed for data management, underscoring the need for training and recruitment of data scientists in public health. Given that population health is increasingly considered a byproduct of SDoH, interdisciplinary perspective is also becoming indispensable in contemporary public health practice. So are data-driven decision making and measurement of population health based on much more than simple summary indices, such as life expectancy and disease rates. As public health practice continues to move forward to make a paradigm shift to “Public Health 3.0,” community partners will be sharing location-specific data on social and economic environmental factors, which will in turn allow assessment of community-specific health disparities and inequities as well as identifying the SDoH contributing to those disparities.

Health care informatics and an emphasis on SDoH are beginning to change the traditional health care focus on cure based primarily on individual characteristics. For instance, PCORnet has acknowledged the need for data on SDoH to adequately address the health care needs of many population subgroups affected by SDoH.

Data linkage science has also matured, allowing probabilistic inking of health care and SDoH data from community information systems, without utilization of unique identifiers and thus averting the risk of individuals’ data disclosure. Availability of big data on SDoH and improvements in geographic information systems (GIS) science allowing geospatial coding of data present tremendous potential for improved precision of linkages between SDoH and health outcomes. Specific details about the role of health informatics in linking SDoH with population health are desirable, and therefore a more in-depth discussion is needed. Perhaps a future blog in this new series will attempt that.

Share This Post on Social Media

Tweet this! 

Drs. @GshahGSU and Wu Xu outline the potential role of health informatics in assisting #publichealth practice agencies in leveraging social determinants of #health. #SDoH  https://wp.me/p7l72S-3nm

Post this on Facebook! 

JPHMP Consulting Editor of Biostatistics Dr. Gulzar Shah and colleague Dr. Wu Xu look at social determinants of health in the age of big data in this new series highlighting health informatics innovations and applications. https://wp.me/p7l72S-3nm 

---

Gulzar H. Shah, PhD, MStat, MS, currently serves as a Professor of Health Policy and Management and the Department Chair, Health Policy and Community Health, at the Jiann-Ping Hsu College of Public Health (JPHCOPH), Georgia Southern University. He served the JPHCOPH as an Associate Dean for Research before accepting the Department Chair position in 2017. Prior to moving into academia, Dr. Shah spent over 17 years serving in public health practice, first at the Utah State Department of Health, and subsequently at the National Association of Health Data Organizations (NAHDO) and National Association of County and City Health Officials (NACCHO). [Full bio.]

 

Wu Xu, PhD, is the retired Director of the Center for Health Data and Informatics at the Utah Department of Health and adjunct faculty at the University of Utah Departments of Sociology, Internal Medicine-Epidemiology, and Bio-medical Informatics.