Assessments of a health-related matter of interest, importance, or worry to a patient, patient’s family, or patient’s healthcare provider that could identify a need, problem, or condition.
Description (*Please confirm or update this field for the new USCDI version*)
Screening questionnaire-based, structured evaluation for a Social Determinants of Health-related risk.
Examples include but are not limited to food, housing, transportation security, and health literacy.
Applicable Vocabulary Standard(s)
Applicable Standards (*Please confirm or update this field for the new USCDI version*)
Logical Observation Identifiers Names and Codes (LOINC®) version 2.78
SNOMED Clinical Terms® (SNOMED CT®) U.S. Edition, September 2024 Release
Submitted By: Mark Savage for Gravity Project
/ Gravity Project
Data Element Information
Rationale for Separate Consideration
The Assessment is focused on risks specific to SDOH and uses constrained code systems and value sets to express specific risks using the structured assessments. The ability to document and communicate this element is essential to establishing and communicating the exact assessment questions and answers to provide detailed information on the nature of a specific SDOH risk across the various involved entities (e.g., providers, payers, social services, community-based organizations, etc.).
Use Case Description(s)
Use Case Description
• Documentation and exchange SDOH data related to (1) assessments of risks, (2) the declaration of problems/health concerns, problems, and diagnoses, (3) the establishment of specific goals, (4) the identification of interventions, (5) tracking outcomes, and (6) recording and exchanging consent, where needed, to share the SDOH-related data.
• Specifically, the Gravity Project is establishing specific value sets for (1) assessments, (2) problems/health concerns, (3) goals, (4) interventions, (5) outcomes, and (6) consent to facilitate appropriate coding for each with respect to the following SDOH domains: (1) Food Insecurity, (2) Housing Instability and Homelessness, (3) Inadequate Housing, (4) Transportation Insecurity, (5), Financial Strain, (6) Social Isolation, (7) Stress, (8) Interpersonal Violence, (9) Education, (10) Employment, and (11) Veteran Status, in conjunction with the patient encounter
By supporting these data elements and specific domains, we will be able to communicate the SDOH risks of an individual to all of the stakeholders in a structured, unambiguous way that will facilitate interventions to address them and tracking outcomes. https://confluence.hl7.org/display/GRAV/Gravity+Use+Case+Package
Estimate the breadth of applicability of the use case(s) for this data element
Level 2 – elements pertain to most or all patients, providers or requestors.
The list below contains 8 categories of organizations that each represent dozens and in some cases hundreds of stakeholders that would heavily capture, access, use, or exchange the individual data elements in this data class.
This data class (and the 7 elements contained within it) are pertinent to all stakeholders that directly partner with patients toward improving patient health and stakeholders who gather, aggregate and use data to make decisions on policy, programs, and resources toward the improved health of populations.
A qualitative study of EHR vendors making active and current use of SDOH data contains a more in depth description of the stakeholders described below:
Freij, Maysoun et al. “Incorporating Social Determinants of Health in Electronic Health Records: Qualitative Study of Current Practices Among Top Vendors.” JMIR medical informatics vol. 7,2 e13849. 7 Jun. 2019, doi:10.2196/13849
• Providers and provider associations: clinical, community-based, long-term and post-acute, medical homes, accountable care organizations, health systems, and hospitals
• Payers: federal, state, commercial, and employers
• Patients/Beneficiaries
• Patient/Beneficiary advocates: patient/beneficiary representatives and/or delegates, caregivers, family members, and other advocates
• Government agencies, payors, providers, researchers, and policymakers:
o Centers for Disease Control and Prevention, National Center for Health Statistics
o CMS: Office of Minority Health, Center for Medicaid and CHIP Services, Center for Clinical Standards and Quality, CMS Innovation Center
o Department of Defense
o Department of Education
o Department of Housing and Urban Development
o Department of Labor
o Department of Transportation
o Health Resources and Services Administration
o HHS Administration of Children and Families
o HHS Administration of Community Living
o HHS Agency for Healthcare Research & Quality
o HHS Office of the Assistant Secretary for Planning & Evaluation
o HHS Office of the National Coordinator for Health IT
o Indian Health Service
o National Institutes of Health: Office of Minority Health and Health Disparities
o Social Security Administration
o State Medicaid offices, state health and public health departments, and state health information exchange organizations
o Substance Abuse and Mental Health Services Administration
o Veterans Health Administration
• Vendors:
o EHR systems, PHR systems, mobile health systems and apps, health information exchange systems, home- and community-based service information systems, care management and care coordination systems
o Telehealth technologies
o Digital health technologies
o Device manufacturers
o Data warehouse/data mart
• Standards-related organizations: standards developing organizations, vocabulary/terminology organizations
• Privacy and security professionals
Over time, we estimate that virtually all providers, payers, and community-based organizations that provide services to address SDOH risk, and relevant quality and governmental agencies, would capture, access, use or exchange this data class or data elements.
Healthcare Aims
Improving patient experience of care (quality and/or satisfaction)
Improving the health of populations
Reducing the cost of care
Improving provider experience of care
Maturity of Use and Technical Specifications for Data Element
Applicable Standard(s)
Yes, structural standards exist for each of these six elements in current HL7 standards. Specifically, in FHIR, (1) Assessments are Observation resources; (2) Problems/Health Concerns are Condition resources; (3) Goals are Goal resources; (4) Interventions are ServiceRequest and Procedure resources; (5) Outcomes are represented by the status on any of the previously mentioned resources or creation of new Observation resources; and (6) Consent is represented by the Consent resource.
Yes, a vocabulary/terminology standard and/or technical specification exists for each proposed data element.
The technical specifications for value sets under each data element are described below:
• Assessments: LOINC
• Health Concerns/Problems/Diagnoses: SNOMED-CT, ICD-10-CM
• Goals: LOINC
• Procedures/Interventions: SNOMED-CT (clinical), CPT/HCPCS (billing)
• Outcomes: LOINC (NCQA measures)
• Consent (where needed): based on existing HL7 code systems
For the respective SDOH domains:
For (1) Food Insecurity: LOINC, SNOMED-CT, ICD-10-CM, and CPT/HCPCS terminologies are specified by value sets in NLM’s Value Set Authority Center (VSAC).
For (2) Housing Instability and Homelessness, (3) Inadequate Housing, (4) Transportation Insecurity, (5) Financial Strain, (6) Social Isolation, (7) Stress, (8) Interpersonal Violence, (9) Education, (10) Employment, and (11) Veteran Status:
• The corresponding value sets are under development by the Gravity Project.
• The value sets will be complete prior to publishing of USCDI v2.0;
• Even if a particular value set might be incomplete, the value set will be citable.
The details of the domains and specific consensus-approved value sets for each of the activities will be externally maintained as part of a hierarchy of LOINC panels and, where necessary, VSAC value sets referenced by the LOINC panels. The proposed structure is as follows:
Survey (Panel) LOINC code
a. Food Insecurity Domain (Panel) (LOINC code)
i. Food Insecurity Assessment (Panel) (LOINC code)
1. Value set (LOINC codes)
ii. Food Insecurity Health Concerns (Panel) (LOINC code)
1. Value set (SNOMED-CT and ICD-10-CM)
iii. Food Insecurity Goals (Panel) (LOINC code)
1. Value set (LOINC codes)
iv. Food Insecurity Interventions (Panel) (LOINC code)
1. Value set (SNOMED-CT, HCPCS, CPT, LOINC)
v. Food Insecurity Outcomes (Panel) (LOINC code)
1. Value set (LOINC codes)
b. Domain: Housing Instability and Homelessness
c. Etc.
The Gravity Project is currently developing the Implementation Guide as an HL7 Accelerator Project, and the Implementation Guide will be complete and available before ONC publishes the USCDI v2.
Current Use
This data element has been used at scale between multiple different production environments to support the majority of anticipated stakeholders
Supporting Artifacts
Most major EHR vendors collect and record SDOH data elements that are implemented as custom, non-interoperable fields. The lack of a standard creates risks to individual patients by creating gaps in medical histories for patients that move between service providers. The following citations describe examples of how different vendors and health networks have implemented and used these data elements in production, at scale, as part of their routine healthcare operations.
Nicole Friedman & Matthew Banegas, Toward Addressing Social Determinants of Health: A Health Care System Strategy, 22 Permanente J. __ (Oct. 22, 2018) (“The novel electronic health record-based tools developed by KPNW [Kaiser Permanente Northwest] have led to standardized, measurable, and actionable SDH data being used to tailor and target specific resources to meet the identified needs of our patients.”), available at https://doi.org/10.7812/TPP/18-095
Maysoun Freij, Prashila Dullabh, Sarah Lewis, Scott R. Smith, Lauren Hovey, Rina Dhopeshwarkar, Incorporating Social Determinants of Health in Electronic Health Records: Qualitative Study of Current Practices Among Top Vendors, 7 JMIR Med. Inform. e13849 (June 7, 2019) (in a study of EHR vendors with large market shares, “Vendors indicate they are actively developing products to facilitate the collection and use of SDH data for their clients and are seeking solutions to data standardization and interoperability challenges through internal product decisions and collaboration with policymakers. Due to a lack of policy standards around SDH data, product-specific decisions may end up being de facto policies given the market shares of particular vendors. However, commercial vendors appear ready to collaboratively discuss policy solutions such as standards or guidelines with each other, health care systems, and government agencies in order to further promote integration of SDH data into the standard of care for all health systems”), available at https://medinform.jmir.org/2019/2/e13849/.
Freij M, Dullabh P, Lewis S, Smith SR, Hovey L, Dhopeshwarkar R. Incorporating Social Determinants of Health in Electronic Health Records: Qualitative Study of Current Practices Among Top Vendors. JMIR Med Inform. 2019 Jun 7;7(2):e13849. doi: 10.2196/13849. PMID: 31199345; PMCID: PMC6592390, available at https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6592390/.
Extent of exchange
5 or more. This data element has been tested at scale between multiple different production environments to support the majority of anticipated stakeholders.
Supporting Artifacts
The data elements cited have been successfully exchanged in volume between various EHRs, payers and other interested parties. Specifically, there is large scale exchange of these elements with CCDA and FHIR API (specifically Observations, Procedures and Conditions).
Electronic exchange of Social Determinants of Health information is widespread and used at scale as part of routine healthcare operations at many organizations. However, published documentation of standardized electronic exchange is not widespread since there is no standard and vendor customizations that include Social Determinants of Health documentation and exchange interfaces are not typically made public. The examples below demonstrate verifiable exchange between several relevant organizations.
Veterans Affairs provides read-only EHR access to Veteran Service Organizations to facilitate services for veterans that fall outside of typical clinical care. In the absence of standard methods of exchange, this provides organizations insight into custom documentation of Social Determinants of Health conditions that are documented as part of routine clinical care for veteran patients.
• https://www.reginfo.gov/public/do/DownloadDocument?objectID=25768001
OCHIN – non-profit healthcare innovation center that provides EHR services to Community Health Centers nationwide (https://ochin.org/ochin-facts). In particular, the organization supports exchange of Social Determinants of Health Data elements
• Supports 500 organizations nationwide
• Supports 20,000 health care providers
• Serves 105 Federally Qualified Health Centers
• Securely exchanged 151 million clinical summaries across the U.S.
Gold R, Bunce A, Cowburn S, Dambrun K, Dearing M, Middendorf M, Mossman N,
Hollombe C, Mahr P, Melgar G, Davis J, Gottlieb L, Cottrell E. Adoption of
Social Determinants of Health EHR Tools by Community Health Centers. Ann Fam
Med. 2018 Sep;16(5):399-407. doi: 10.1370/afm.2275. PMID: 30201636; PMCID:
PMC6131002.
• Level 1 – exchanged between 2 or 3 different EHR/HIT systems
• This study facilitated exchange between medical clinics and 3 Community Health Centers based on health data collected on 1,130 patients
Gold R, Cottrell E, Bunce A, Middendorf M, Hollombe C, Cowburn S, Mahr P,
Melgar G. Developing Electronic Health Record (EHR) Strategies Related to Health
Center Patients' Social Determinants of Health. J Am Board Fam Med. 2017 Jul-
Aug;30(4):428-447. doi: 10.3122/jabfm.2017.04.170046. PMID: 28720625; PMCID:
PMC5618800.
• Level 1 – exchanged between 2 or 3 different EHR/HIT systems
• Reports development of collection, summary, and referral tools for Community Health Centers supporting conditions arising from Social Determinants.
Potential Challenges
Restrictions on Standardization (e.g. proprietary code)
There are no restriction on the standardization of these data elements. The data elements are open source.
Licensed terminologies:
• CPT: American Medical Association issues licenses for this content. Different pricing models apply to different types of organizations and the intended use of the product.
• ICD-10-CM: World Health Organization owns the copywrite and can grant licenses for the use of ICD-10 worldwide for commercial and non-commercial uses. Commercial users will already be in position of a license to use these codes. Non-commercial entities will be able to register for use of these codes at no charge.
• SNOMED-CT: owned maintained and distrusted by the International Health Terminology Standards Development Organization, a not-for-profit association. SNOMED-CT is distributed at no cost in accordance with the member rights and responsibilities outlined in the IHTSDO’s articles.
Restrictions on Use (e.g. licensing, user fees)
none
Privacy and Security Concerns
o Existing requirements and issues for HIPAA-covered and non-HIPAA-covered entities will apply, as well as any different requirements under state laws.
Estimate of Overall Burden
With minor exception, all Certified EHRs currently need to support collection, use, and exchange of these data elements based on the ONC 21st Century Cures Act Final Rule with the exception Consent and ServiceRequest.
• If this requirement results in any documentation burden for providers across the health care system, this burden would be mitigated by strong evidence that documenting and addressing conditions related to social determinants of health results in a dramatic reduction in hospital readmission rates and improved care coordination among providers.
Burdens avoided
• SDOH reduces hospital readmission. Individuals impacted by SDOH have 25% higher rate of hospital readmission within 30 days than individuals without these factors.
o Fuller, R. L., Atkinson, G., McCullough, E. C. & Hughes, J. S. (2013). Hospital Readmission Rates: The Impacts of Age, Payer, and Mental Health Diagnoses. Journal of Ambulatory Care Management, 36(2), 147–155. doi: 10.1097/JAC.0b013e3182866c1c.
• SDOH reduces hospital costs by 11% due to improved care coordination between medical and social service providers.
o Zachary Pruitt, Nnadozie Emechebe, Troy Quast, Pamme Taylor, and Kristopher Bryant.Population Health Management.Dec 2018.469-476.http://doi.org/10.1089/pop.2017.0199
ONC Evaluation Details Each submitted Data Element has been evaluated based on the following criteria. The overall Level classification is a composite of the maturity based on these individual criteria. This information can be used to identify areas that require additional work to raise the overall classification level and consideration for inclusion in future versions of USCDI
Criterion #1 Maturity - Current Standards
Level 2 - Data element is represented by a terminology standard or SDO-balloted technical specification or implementation guide.
Criterion #2 Maturity - Current Use
Level 1 - Data element is captured, stored, or accessed in at least one production EHR or HIT module.
Criterion #3 Maturity - Current Exchange
Level 1 - Data element is electronically exchanged between two production EHRs or other HIT modules using available interoperability standards.
Criterion #4 Use Case(s) - Breadth of Applicability
Level 2 - Use cases apply to most care settings or specialties.
NACHC Clinical Informatics supports the comment of Ann Phillips / IMO, and firmly believes that the collection of social determinants of health information is critical to support patient access and referral care systems that enable and optimize appropriate closed-loop social interventions.
We strongly support the use of the code systems and codes referenced by the Gravity Project submission to ensure proper representation of PRAPARE and other SDoH assessment screening tools to support interoperability of this data to connect CBOs and CCOs to EHRs.
Please see attached document for a detailed summary of our comments on SDoH
IMO supports the inclusion of SDOH Assessment in the Assessment and Plan of Treatment Data Class in USCDI V3 and recommends that the Applicable Vocabulary Standard(s) category be expanded to include ICD-10-CM Z codes recently developed for Social Determinants of Health.
However, we strongly caution against the inclusion of specific value sets to represent SDOH assessments without alignment to SDOH screening tools by domain that have a history of implementation in clinical care environments.
Submitted by RUy on
NACHC Clinical Informatics…
NACHC Clinical Informatics supports the comment of Ann Phillips / IMO, and firmly believes that the collection of social determinants of health information is critical to support patient access and referral care systems that enable and optimize appropriate closed-loop social interventions.
We strongly support the use of the code systems and codes referenced by the Gravity Project submission to ensure proper representation of PRAPARE and other SDoH assessment screening tools to support interoperability of this data to connect CBOs and CCOs to EHRs.
Please see attached document for a detailed summary of our comments on SDoH
2022-04-30 NACHC USCDIv3 Letter of Support.pdf