By Sophia Giebultowicz, Research Associate
We’ve always know that “place matters” when it comes to health. The Greek physician Hippocrates first introduced this concept in his work On Airs, Waters, and Places, and research within the social sciences and public health has long considered how disease is affected by a person’s social, cultural, and physical environment. Yet integrating this approach into primary care practice and research has only recently gained momentum. We continue to understand more and more about Social Determinants of Health, the many non-medical factors that influence people’s lives, such as demographics, education and income. Integrating additional knowledge about communities and neighborhoods that influence well-being in a similar manner is an innovative and critical step forward that can add to our increasingly holistic understanding of population health.
Enter “Community Vital Signs” (CVS), the initiative at OCHIN to integrate community-level data into the Electronic Health Record. This project is a collaborative effort made possible by the PCORI-funded ADVANCE Clinical Research Data Network at OCHIN and our partnership with the Robert Graham Center (RGC) and Health Landscape, both divisions of the American Academy of Family Physicians. The term Community Vital Signs refers specifically to an extensive database of variables linked to geographical areas, such as counties or census tracts. These data are compiled from a variety of sources by RGC and Health Landscape and updated regularly to ensure that the most current figures are available for research purposes. The result is a comprehensive picture of the social and physical environment within every census tract, county, and ZCTA (similar to a ZIP code) across the United States, with figures related to population, poverty, education, crime, migration, health care quality, and other factors that are considered community-level Social Determinants of Health.
The Research Data Warehouse at OCHIN contains the de-identified addresses (both current and historical) of patients in our Electronic Health Record, which we can directly link to these CVS variables. We can then associate each patient with this data on various geographic levels (e.g., Census tract, zip code tabulation area, or county), using it to enrich and inform our analyses and to help better understand the potential relationships between neighborhood-level conditions and health outcomes. Depending on a researcher’s objectives, different variables may be of interest due to a hypothesized effect on certain conditions; for example, asthma studies might utilize air quality data, while research on obesity would consider access to parks and density of fast food restaurants.
Clinicians seeing patients are now also able to access these data, as the Acuere team has integrated CVS variables with their real-time EHR platform. This creates an opportunity for providers to gain a broader, more objective understanding of the day-to-day life of a patient during a visit. Care teams in a clinic could also use this contextual information for targeted outreach and care management purposes.
We live our lives at multiple levels—in our physical body, our physical shelter (or lack thereof), on our street block, and in our community. The exact correlation between individual health and external environment is still unknown, so these CVS data serve as the basis of our research into these elements and their impact and usefulness for clinicians and researchers assessing patients’ health and quality of care. When it comes to health, a comprehensive understanding of causes and conditions is ideal, and OCHIN is taking a two-fold approach by making contextual information easily available to providers in clinics, and to the researchers who use our patient data to seek effective interventions for vulnerable populations.