By Linda Hyde
Social determinants of health (SDOH) are the economic, social, and behavioral conditions that influence the health, health outcomes, and quality of life of individuals and populations.
The relationship between clinical outcomes and such determinants as economic stability, environmental quality, and food security has been well established for decades. However, the ability to capture this information and integrate it with clinical data and care plans is fairly new.
Today, SDOH have exploded across healthcare. It’s difficult to find a conference, technology solution, or startup that doesn’t extol SDOH as an essential tool for delivering on the promise of whole-person healthcare. And it’s not just hype—across the nation, health systems have launched SDOH initiatives that range from maternal care and childhood asthma to homelessness and PTSD.
For many HIM professionals, the world of SDOH revolves around the ICD-10-CM Z codes, the granular list of 88 categories and subcategories used to capture determinants data. However, the success of these programs depends on a sound data strategy and the ability to:
- Determine what type of data is needed and how is it collected and codified
- Standardize electronic capture and transmission
- Understand how SDOH data should be used to inform public policy, support the appropriate funding necessary to care for individuals and populations, and generate evidence-based data to determine the program’s effectiveness
To truly integrate SDOH into care journeys, health information management (HIM) professionals will need to be fluent in several classifications and terminologies designed to support the four major data concepts relevant to SDOH:
- Screening tools
- Diagnosis/identified need
First, how are individuals identified as having a social risk factor? There are several screening tools that are used to help providers determine if there is an issue that needs to be considered in the patient’s evaluation.
For example, the PRAPARE1 (Protocol for Responding to and Assessing Patient Assets, Risks, and Experiences) tool contains 21 questions designed to flag an individual with specific needs.
PRAPARE is designed to be implemented as part of an electronic health record (EHR), by clinical or non-clinical staff, as a self-assessment according to the needs of the organization implementing the tool. Questions cover areas such as a consistent inability to obtain food, clothing, or utilities and housing status, including homelessness or temporary housing. There are other screeners that focus on a specific issue like food insecurity—for example, the Hunger Vital Signs,2 or the USDA Household Food Security3 screeners.
The LOINC terminology is ideally suited to support codifying screener tools. This terminology supports survey instruments that include assessments and screening tools. Both the PRAPARE and Hunger Vital Signs screeners are currently included in LOINC. Having standard codes that identify the screening tool, questions, and responses facilitates incorporation of the tool into an EHR as well as the exchange of data for coordination of care or other reporting needs.
Clinical review of the screening tool’s results, along with other relevant information from a history and examination of the patient will lead to establishing diagnoses or health needs. A finding of food insecurity can be established as a contributing factor to clinical conditions such as malnutrition or obesity. Homelessness could be identified as an issue resulting from lack of access to care for mental health and substance abuse issues, or as contributing to pregnancy risks.
There are two major classification systems that can be used to code diagnoses or needs: ICD-10-CM and the Systematized Nomenclature of Medicine – Clinical Terms (SNOMED CT).
In ICD-10-CM, Chapter 21, Factors Influencing Health Status and Contact with Health Services (Z00-Z99), contains codes that are used to identify a variety of factors relating to a patient’s health status, encounters for examinations and screening, as well as social needs. Two examples of these types of codes are Z59.0, Homelessness and Z59.4, Lack of adequate food and safe drinking water.
SNOMED CT also supports the collection of findings related to social needs. Similar concepts to the ICD-10-CM examples above include 733423003, Food insecurity (finding) and 32911000, Homeless (finding). SNOMED CT provides for a more granular detail for concepts than ICD-10-CM. While both classifications need to be able to identify SDOH concepts, ICD-10-CM organizes conditions at a more aggregate level and concepts included must fit within the overarching structure of ICD-10 International.
Existing ICD-10-CM codes may need to be modified to clearly identify a specific SDOH factor or to be consistent with current terminology and definitions. For example, the existing code Z59.4, Lack of adequate food and safe drinking water has two concerns. First, combining food and drinking water in one code makes it impossible to identify the specific need. In addition, lack of adequate food does not fully represent the current definition of food insecurity.4 Proposals have been submitted to the ICD-10 Coordination and Maintenance Committee to separate the concepts into individual codes and add a code for food insecurity.
Interventions are the actions needed to address the specific SDOH need. These interventions include referrals, education, counseling, and determining eligibility for various programs. Patients with food insecurity may need an immediate provision of food as well as referral to a specific agency or program. The applicable terminology for these types of concepts is SNOMED CT. Nutrition education 61310001 (procedure) is an example of a type of intervention. SNOMED CT also has codes for more specific types of nutrition education such as content-related education or nutrition-related skills education. There are also federal, state, and local programs that offer support and services to address SDOH issues. Meals on Wheels, food pantry programs, farmers markets, and supplemental nutrition assistance programs (SNAP) are just a few examples. Determining how to represent the interventions needed to treat SDOH needs and including them in SNOMED CT is necessary to close the loop between identifying a need and evaluating which interventions are the most effective.
The final SDOH data concept pertains to goals. What is expected to be achieved to resolve the patient’s identified need. Goals must be measurable and related to the SDOH domain. For a patient identified as food insecure, the ultimate goal would be to return them to a food secure state. There can also be intermediate goals such as a decrease in food insecurity. The LOINC terminology would be used for these concepts.
As the body of literature continues to grow, it is also important to identify and fill any gaps in what is currently available in the various coding systems and terminologies.5 There is also a need to maintain crosswalks between systems such as the mapping for ICD-10-CM and SNOMED CT to support standardization and interoperability. Gaps that are identified will need to be submitted for inclusion in the appropriate code system(s).
One of AHIMA’s 2020-2023 strategic outcomes is “advance and advocate for the creation and use of trusted information across the evolving health continuum.”6 An impact area for this strategy is to “facilitate the optimal sharing of data between providers, consumers, health information networks, and health plans through technology-enabled, secure access to electronic health information (EHI).”
Knowledge of the various classification and terminology systems, understanding of how data is collected, and identifying SDOH concepts that need to be standardized and structured for interoperability are all attributes that will advance this strategic initiative.
- National Association of Community Health Centers. PRAPARE Assessment Tool. http://www.nachc.org/research-and-data/prapare.
- Children’s Health Watch. The Hunger Vital Sign. https://childrenshealthwatch.org/public-policy/hunger-vital-sign/.
- United States Department of Agriculture Economic Research Service. https://www.ers.usda.gov/topics/food-nutrition-assistance/food-security-in-the-us/survey-tools/.
- Centers for Disease Control ICD-10 Coordination and Maintenance Committee Diagnosis Agenda. March 5-6 2019. https://www.cdc.gov/nchs/data/icd/Topic-packet-March-2019-Part-2Vs3.pdf.
- Arons, Abigail et al. “Documenting social determinants of health–related clinical activities using standardized medical vocabularies.” AMIA Open (April 2018): 81-88.
- American Health Information Management Association. 2020-2023 Enterprise Strategic Plan. http://bok.ahima.org/PdfView?oid=302888.
- Gallego, Evelyn. “Why Data Standards Matter for SDOH Integration in Clinical Care: A Trajectory of the Gravity Project.” December 16, 2019. https://www.emiadvisors.net/2019/12/16/why-data-standards-matter-for-sdoh-integration-in-clinical-care-a-trajectory-of-the-gravity-project/.
Linda Hyde is a terminology consultant for the Gravity Project. This multi-focused public collaborative is focused on developing, testing, and validating standardized SDOH data.7
Continuing Education Quiz
Review quiz questions and take the quiz based on this article, available online.
- Quiz ID: Q2029104
- Expiration Date: April 1, 2021
- HIM Domain Area: Clinical Data Management