How to gather technology and apply Social Determinants of Health (SDOH) information into a patient's Electronic Health Record (EHR)?

How to Gather and Apply SDOH Information into Patient Electronic Health Records

Implement the Health Level 7 (HL7) Gravity Project's standardized FHIR-based framework to systematically capture, code, and exchange SDOH data within your EHR system, using structured screening tools and standardized terminology to enable actionable clinical documentation. 1

Technology Infrastructure and Standards

Core Framework Implementation

• Deploy HL7 FHIR Release 4 application programming interfaces to enable structured SDOH data capture and bidirectional exchange between clinical settings, community services, and social care platforms 1

• Utilize standardized SDOH value sets from the National Library of Medicine's Value Set Authority Center, which align with US Core Data for Interoperability Version 2 data elements covering screening, diagnosis, goals, and interventions 1

• Implement technology-agnostic, open-source solutions from the Gravity Project that provide consensus-based data standards specifically designed for SDOH documentation across diverse care settings 1

Structured Data Collection Methods

• Integrate validated screening tools directly into EHR workflows, such as the Protocol for Responding to and Assessing Patients' Assets, Risks, and Experiences (PRAPARE) or the CMS Accountable Health Communities Model screening tool 1, 2, 3

• Configure EHR systems to capture five core CMS-recommended domains: housing instability, food insecurity, transportation difficulties, utility assistance needs, and interpersonal safety 2

• Enable all care team members (nurses, social workers, community health workers, care managers, and pharmacists) to document SDOH using ICD-10-CM Z codes, as authorized since February 2018 2

Comprehensive SDOH Domains to Capture

Individual-Level Data Elements

• Document demographic and social identity factors including race (with specific cultural subgroups beyond broad categories), ethnicity, sex, sexual orientation, gender identity, primary language spoken, and immigration/acculturation status—all derived from patient self-identification 1, 2

• Capture health literacy and digital access metrics including broadband internet access, availability of digital devices, digital health literacy levels, and ability to navigate patient portals and telemedicine platforms 1, 2

• Record economic indicators such as income level, employment status, educational attainment, and financial barriers to care 1, 2

• Assess dietary quality and food security status using standardized questions about household-level access to adequate food 1, 2

Interpersonal and Community-Level Factors

• Document social connection networks, experiences of interpersonal discrimination, disparate healthcare quality, and psychosocial stress 2

• Capture community-level determinants including housing quality, transportation access, walkability, proximity to healthcare services, and community education/employment rates 2

• Link geographic data (county, zip code, census tract) to Agency for Healthcare Research and Quality SDOH databases covering social context, economic context, education, physical infrastructure, and healthcare context 1

Practical Implementation Strategies

Workflow Integration

• Embed SDOH screening at multiple touchpoints: during ambulatory clinic visits, emergency department encounters, hospital admissions, and annual wellness visits 3, 4

• Implement phased rollout approaches to streamline screening and referral processes, allowing for workflow optimization and staff education 4

• Configure EHR systems to automatically measure user experience metrics (clicks, time spent, data transferred without manual review) rather than requiring clinicians to manually document system effectiveness 1

Data Capture Optimization

• Leverage natural language processing to extract SDOH information from unstructured clinical notes, social history sections, and social work documentation, which often contain more comprehensive details about status, severity, and temporality than structured fields alone 5, 6

• Establish three key measurement approaches: (1) documented during encounter (DDE), (2) documented by discharge (DBD), and (3) reviewed during encounter (RDE) to track real-world SDOH data utilization patterns 6

• Address data quality issues by minimizing missingness through mandatory field completion for high-priority domains and implementing data validation rules 3, 6

Critical Pitfalls to Avoid

• Do not rely solely on newly added structured SDOH fields without user education and workflow integration, as real-world data shows these fields have extremely low utilization rates (0.03% documented during encounters) compared to free-text social history fields (12.1%) 6

• Recognize that two-thirds of patients with cost-related medication non-adherence never discuss this with physicians, necessitating systematic screening rather than passive documentation 2

• Ensure adolescent privacy protections by implementing adequate technology to restrict access to protected laboratory results, diagnoses, and clinical information when guardians have proxy access to pediatric EHRs 1

• Avoid using area-level SDOH data from external sources as primary documentation, since 79% of studies show minimal contribution to predictive model performance, whereas individual-level SDOH data consistently improves risk prediction for outcomes like readmissions and medication adherence 7

Interoperability and Data Exchange

Platform Integration

• Connect EHR systems with community referral platforms such as Unite Us or Findhelp using FHIR-based APIs to enable closed-loop referrals and track intervention outcomes 1

• Establish bidirectional mapping between healthcare data standards and social care data systems (211 services, homeless management information systems) to coordinate care across sectors 1

• Integrate smartphone and web-based applications that use FHIR APIs to allow patients to report SDOH information directly and access community resources 1

Security and Privacy Considerations

• Use only HIPAA-compliant, ONC-certified EHR technology for SDOH communication and data exchange to protect patient information 1

• Implement secure platforms that enable closed-loop communication, ensuring confirmation of receipt and comprehension when sharing SDOH-related information with patients 1

• Maintain confidentiality for minors accessing care for sensitive conditions by configuring EHR access controls that comply with state-specific laws regarding adolescent privacy 1

Actionable Clinical Use

Resource Allocation and Referrals

• Use collected SDOH data to trigger automatic social work referrals when specific risk factors are identified (homelessness, food insecurity, transportation barriers) 3, 4

• Allocate resources to targeted patient populations based on community-specific SDOH patterns identified through systematic screening 4

• Track intervention outcomes by monitoring whether identified social needs are addressed and measuring impact on health outcomes and healthcare utilization 3, 4

Quality Improvement

• Monitor SDOH screening rates as a quality metric, with successful implementations achieving 95% increases in screening rates over 2-year periods 4

• Analyze patterns of SDOH documentation across different data types (structured fields, problem lists, nursing questions, free-text notes) to identify gaps and optimize collection strategies 6

• Recognize that emergency department patients report significantly higher proportions of suboptimal SDOH, requiring targeted screening and intervention protocols in acute care settings 3