As the pandemic shines a harsh light on healthcare disparities – with COVID-19 affecting poor, minority and underserved communities to a significantly disproportionate degree – more attention has been focused on social determinants of health, and how health systems and community groups can better address them to keep these people safe and healthy.

But a major challenge with SDOH information, as has been long documented, appears in the difficulties with managing these different data types and integrating them into clinical care.

In a new article in the Journal of the American Medical Informatics Association, "A Call for Social Informatics," researchers from the University of California, San Francisco describe the challenges and opportunities for a proposed new discipline of health data innovation, and show how it can be formalized into a new domain of study.

Various medical organizations – American Academy of Family Physicians and the National Association of Community Health Centers to name just two – have come out in favor screening patients for SDOH. And federal agencies such as the Office of the National Coordinator for Health IT have thrown their support behind efforts to boost technology systems' ability to integrate SDOH data.

But a broader and more concentrated effort is needed to build momentum, said UCSF researchers.

The good news is there's no shortage of hugely useful socioeconomic data with which to work.

"While data on social conditions, such as lack of access to adequate food, housing, and transportation, may be obtained during clinical encounters, they can also be derived from nonclinical sources such as local and national government datasets," the researchers explain. "Once these data are incorporated into the healthcare system, they facilitate the NASEM report’s recommendation of increasing the health sector’s awareness of social risks of patients and populations."

The challenge has more to do with the shape and structure of these critical data points, and the inadequacy of most systems and processes to accommodate them.

"Regardless of their source, social data are neither uniformly collected nor commonly captured in EHRs in a structured format," according to the report. "As the availability of social data rapidly increases in response to new policy and payment models that incentivize these different awareness strategies, there will be new opportunities to integrate these data into EHRs and implement social care interventions that address identified risks."

And since the onset of the COVID-19 public health emergency, those risks have been borne, to a disproportionate extent, by those with the most SDOH challenges, as this tweet thread from University of St. Andrews infectious disease researcher Muge Cevik shows:

"As evidence of the associations between social factors and health outcomes continues to mount, capturing and acting on social determinants of health in clinical settings has never been more relevant," said the UCSF researchers. "Developing this dedicated subfield of informatics – which we term social informatics – is important to drive research that informs how to approach the unique data, interoperability, execution and ethical challenges involved in integrating social and medical care."

Toward a more rigorous and structured approach to ensuring that important SDOH information is integrated into clinical practice, the UCSF researchers spotlighted five A's, and showed what that could mean for IT and informatics strategies.

Awareness. As care providers identify social risks in their patients and patient populations, a social informatics approach will work on fine-tuning the "collection, linkage, storage, and retrieval of SDOH information – whether collected in clinical settings or imported from community sources – so that it is accessible to inform healthcare practices."

Adjustment. As certain care and treatment decisions may shift in order to address identified social barriers, it's important to engage with "clinical and population health tools within EHRs to incorporate SDOH information into care activities. Improving EHR functionalities to prompt care actions based on social risks."

Assistance. As hospitals and health systems look for ways to reach out and help connect patients with social care and community resources, clinical and EHR workflows should be honed to more efficiently document social assistance that's offered to patients – such as "automating assistance referrals to both healthcare-setting–based (e.g., case manager) and community-based (e.g., housing placement organization) organizations that address social needs."

Alignment. As health networks better understand the social care assets that exist in the community, they should work to organize to facilitate partnerships, synergies and investments – that depends on the creation and facilitation of "electronic linkages between health systems and community-based organizations."

Advocacy. As healthcare organizations collaborate with community social care organizations to "promote policies that facilitate the creation and redeployment of assets or resources to address health and social needs," researchers said, it's key to be able to retrieve population SDOH data to better inform policy decisions.

For all that to happen on a widespread basis, significant challenges related to interoperability, EHR design, and ethics (around analytics, algorithmic bias, resource allocation and more), will need to be addressed, the researchers say. But the benefits of aligning all those imperatives will lead to healthier people, families and communities.

"Creating this new subfield of informatics is necessary to drive research that informs how to approach the unique interoperability, execution, and ethical challenges involved in incorporating social information into health care," the report concludes. "Social informatics will be a new tool in the toolbox for better integrating social and medical care in ways that can improve individual and population health and health equity."

Twitter: @MikeMiliardHITN
Email the writer: mike.miliard@himssmedia.com

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