Food Insecurity

Data Element

Food Insecurity

Description

Uncertain, limited, or unstable access to food that is: adequate in quantity and in nutritional quality; culturally acceptable; safe and acquired in socially acceptable ways. (Gravity Project.)

Submitted By: Mark Savage for Gravity Project / Gravity Project
Data Element Information
Use Case Description(s)
Use Case Description	• Document SDOH data relevant to (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 • Document and track SDOH-related interventions related to (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 to completion • Gather and aggregate SDOH data related to (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 for uses beyond the point of care
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 eleven data 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 decsions 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.
Link to use case project page	https://confluence.hl7.org/display/GRAV/Gravity+Use+Case+Package
Supporting Attachments	Gravity Project to ONC on SDOH Data Class for USCDI v2 (10-23-2020).pdf
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, a vocabulary/terminology standard and/or technical specification exists for each proposed data element. The Gravity Project attaches a letter with an overview. For (1) Food Insecurity: LOINC, SNOMED-CT, ICD-10-CM, and CPT/HCPCS terminologies are specified by value set 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 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 https://www.vsac.org/
Additional Specifications	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 SDOH 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 wide spread 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 docuemented 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 posetion 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 distrubted by the International Health Terminolology 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	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 through the social, psychological, and behavioral data module in the 2015 Edition of Certified Health IT. • 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
Other Implementation Challenges	This can include concepts such as regulatory impact analysis, development burden/cost, cultural barriers, etc. Again, it may not be fully known to the submitter.

Comment

Submitted by RUy on 2024-04-16

NACHC supports CDC's comment, and for all SDOH data elements!

With the SNAP, WIC, and HFFI programs supporting millions of people in the United States, NACHC recommends reassessment of this data element's level, and agrees with CDC's April 2024 comment.

Submitted by nedragarrett_CDC on 2024-04-15

CDC's Comment for draft USCDI v5

The Centers for Disease Control and Prevention strongly recommends inclusion of Food Insecurity data elements in USCDI core dataset under the Health Status Assessments data class:

Food insecurity - worried food will run out, and
Food insecurity - not enough food.
In addition, use cases that contain these elements should be used for EHR certification purposes.

These data elements align with health care and government priorities and are of key importance. As stated in the American Medical Association policy (adopted 2022):  “Our AMA adopts the position that electronic health records should integrate and display information on social determinants of health and social risk so that such information is actionable by physicians to intervene and mitigate the impacts of social factors on health outcomes;”  The Hunger Vital Sign are increasingly used in various healthcare settings to identify households at risk for food insecurity, an important social determinant of health. The Hunger Vital Sign consists of two questions derived from the U.S. Household Food Security Survey module, which is a well-validated tool used to assess food insecurity. These questions are designed to be simple, quick, and easily integrated into the workflow of healthcare settings, making them an efficient method for screening patients for food insecurity. Examples of how the hunger as vital sign are used include:

Primary Care and Pediatric Practices: These settings are among the most common places where the Hunger Vital Sign is used. Pediatricians and primary care providers screen patients during routine visits, recognizing that food insecurity can significantly impact children's physical and cognitive development, as well as overall family health.
Hospitals and Emergency Departments: Some hospitals and emergency departments incorporate food insecurity screening into their patient intake process, especially in communities with high rates of poverty and food insecurity. Identifying food insecurity in these settings can help healthcare providers offer more holistic care and connect patients with necessary resources upon discharge.
Community Health Centers: These centers often serve underserved populations who are at a higher risk for food insecurity. Screening for food insecurity allows community health workers and other healthcare professionals to address a key aspect of their patients' social determinants of health.
Specialty Clinics: Clinics focused on chronic diseases such as diabetes, heart disease, and obesity may use the Hunger Vital Sign to understand how food insecurity impacts their patients' ability to manage their conditions, adhere to dietary recommendations, and achieve optimal health outcomes.
Maternal and Child Health Programs: Programs focused on the health of pregnant women, infants, and young children may use this tool to ensure that families have the resources they need for healthy pregnancies and child development.
Integrated Care Models: In models where behavioral health and social services are integrated with primary medical care, such as in some Accountable Care Organizations (ACOs) or Patient-Centered Medical Homes (PCMHs), screening for food insecurity is part of a comprehensive approach to patient wellness.
Telehealth Services: With the expansion of telehealth, especially highlighted during the COVID-19 pandemic, some providers have started incorporating social determinants of health screenings, including the Hunger Vital Sign, into their virtual consultations.
Public Health Initiatives and Research: Beyond clinical settings, the Hunger Vital Sign is used in public health research and initiatives aimed at understanding and addressing food insecurity at the community and population levels.

The use of the Hunger Vital Sign across these diverse settings highlights the growing recognition of food insecurity as a critical factor affecting health outcomes. By identifying individuals and households at risk, healthcare providers and community programs can connect them with resources such as food assistance programs, nutritional counseling, and other support services, addressing a fundamental need that impacts overall health and well-being.

All of government has been working to address food insecurity and other health-related social needs (HRSNs) through a variety of strategies, recognizing the importance of these factors in overall health outcomes. Advancing data collection and interoperability among health care, public health, social care services, and other data systems is central to both the White House’ U.S. Playbook to Address Social Determinants of Health and HHS’s Call to Action to Address Health Related Social Needs. Assistant Secretary for Planning and Evaluation’s report from April 1, 2022 highlights successful examples of evidence-based strategies and breadth of current federal efforts to address health-related social needs (HRSNs) and Social Determinants of Health (SDOH).

In addition, as part of its commitment to advance health equity and whole-person care, the Centers for Medicare & Medicaid Services (CMS) is prioritizing the collection of social drivers/determinants of health (SDOH) data, including food insecurity, across programs and health care settings. This includes adoption of quality measures focused on screening for social drivers of health and the positivity rate for those screened social drivers in multiple quality reporting programs, including the Hospital Inpatient Quality Reporting program and Merit-Based Incentive Payment System Program.

ONC’s prioritization criteria for The United States Core Data for Interoperability (USCDI) includes : Healthcare disparities and inequities, Underserved communities, and public health. USCDI incorporates SDOH/ HRSN data elements, but the way these elements are integrated within USCDI poses limitations on their utilization for integration, analysis, and management of critical SDOH/ HRSN data in healthcare settings. The current structure in USCDI categorizes SDOH data into "domains" based on assessments, goals, diagnoses, and interventions. Each specific aspect or domain of SDOH, such as food insecurity or social connectedness, is regarded as a subset or a "specialized use" within the broader SDOH USCDI domains. This approach hampers the ability to establish precise standards or code-sets for vital SDOH elements like food insecurity.

For an effective assessment of food insecurity, a minimum of two distinct data elements is required: "Food insecurity - worried food will run out" and "Food insecurity - not enough food" (represented by LOINC codes 99122-7 and 88123-5, respectively). However, the current USCDI framework allows healthcare systems to employ different questions related to food insecurity or proprietary value sets that do not necessarily align with best practices or the evidence base.

Submitted by RUy on 2023-09-21

Reaffirming support for SDOH data elements

The National Association of Community Health Centers (NACHC) remains steadfast in its commitment to advocating for and prioritizing Social Determinants of Health (SDOH) data elements. Recognizing the critical role that these factors play in shaping the clinical outcomes of community health center patients, NACHC continues to emphasize the need for comprehensive, accurate, and interoperable SDOH data. By reaffirming our support for these essential elements, we aim to drive informed decision-making, policy development, and targeted interventions that address the root causes of health disparities. This underscores NACHC's belief in the transformative potential of SDOH data in building healthier, more equitable communities.

2023-09-20 NACHC USCDIv5 Letter of Support_1.pdf

Submitted by RUy on 2023-04-17

Food Insecurity as a key SDOH data element

Given the significant impact of food insecurity on an individual's health and well-being, it is crucial that healthcare providers have access to this information in a standardized and interoperable format. This would allow for a more comprehensive assessment of patients' health needs and enable healthcare providers to provide targeted interventions to address food insecurity.

An example of representing food insecurity as a concept would be ICD-10-CM code Z59.4 ("Lack of adequate food or safe drinking water").

Incorporating food insecurity as a required data element for USCDI would not only improve the quality of care provided to patients but also enable the identification of food insecurity at a population level, which can inform public health interventions and policy.

Submitted by RUy on 2022-09-30

Food Insecurity as SDOH data element under USCDI or ISA

NACHC would like to resupport this data element for consideration / inclusion to USCDIv3.

All federally qualified health centers (FQHCs) gather SDOH data, which includes a focus on this data element through the PRAPARE screening tool. This data is relevant to and encompasses in 2019 29 million patients at 1400+ FQHCs with more than 13000 health care delivery sites.

If this data element is not considered for addition to USCDI, we would like to comment on it's addition to ISA as a coded data element under SDOH, with applicable standards and representation accross ICD-10-CM, SNOMED-CT and LOINC.