Enterprise AI Analysis
A multidimensional framework for mapping social need to electronic health records in people with multimorbidity
Leveraging cutting-edge AI to extract and integrate social determinants of health from EHRs, revolutionising integrated care for multimorbidity.
Executive Impact Summary
This groundbreaking study introduces a novel, multidimensional framework designed to systematically map social needs to electronic health records (EHR) within a large multimorbidity population. The framework identifies eight critical domains of social needs and demonstrates their significant association with multimorbidity burden. Its application to a national cohort of 7.2 million individuals in England reveals a disproportionate burden of social needs among older females with higher multimorbidity, underscoring the urgent need for integrated care solutions. This research provides a foundational tool for healthcare systems to quantify and integrate social needs into clinical care, ultimately improving patient outcomes.
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Individuals in Study Cohort
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% with at Least One Social Need
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Social Need Domains Identified
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% Increase in Social Need Odds per Additional LTC (Unadjusted)
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
Multidimensional Framework Development Workflow
Scoping Review
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Qualitative Interviews
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Delphi Prioritisation Exercise
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Domain Grouping & Data Mapping
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Iterative Data Mapping & Validation
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Testing with CPRD Data
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| Identification of Social Needs |
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Percentage of individuals with multimorbidity reporting at least one social need.
Demographic Burden of Social Needs
The study cohort of 7,290,716 individuals with multimorbidity revealed significant demographic disparities in social need prevalence. Approximately 37% (2,694,488 individuals) reported at least one social need, with 15.8% (1,148,247 individuals) reporting two or more. Individuals with social needs tended to be older (average age 77 years vs. 70 years without social needs) and were more frequently female (57.2% vs. 55.3%). Regional variations were also noted, with the highest proportions in the Northwest, South Central, and West Midlands. These findings highlight vulnerable subgroups where targeted interventions integrating social care could yield substantial benefits.
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Increase in social need units for each additional long-term condition (LTC).
The Compounded Burden: LTCs and Social Needs
A statistically significant linear association was found between the number of Long-Term Conditions (LTCs) and the number of social needs. Each additional LTC corresponded to an increase of 0.060 units in social need (p < 0.001), even after adjusting for sociodemographic variables. The logistic regression analysis showed that each additional LTC was associated with a 24% increase in the odds of having at least one social need in the unadjusted model, and a 21% increase in the adjusted model. This underscores the intricate and compounded burden faced by individuals with multimorbidity, where clinical complexities are often exacerbated by unmet social needs. The strongest associations were observed for residential, mobility, and community care needs.
Calculate Your Potential Impact
Estimate the cost savings and reclaimed hours by integrating social needs mapping into your healthcare system.
Estimated Annual Cost Savings
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Estimated Annual Hours Reclaimed
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Your 6-Month Implementation Roadmap
A phased approach to integrating the multidimensional social needs framework into your enterprise operations.
Phase 1: Discovery & Customisation (Month 1)
Conduct a detailed audit of existing EHR data and social care workflows. Identify relevant SNOMED/READ codes within your system. Customise the framework's domains and indicators to align with local population needs and available data.
Phase 2: Data Integration & Mapping (Month 2)
Implement automated scripts for extracting and mapping social need variables from EHRs using the customised framework. Establish data validation routines to ensure accuracy and completeness of social need profiles.
Phase 3: Pilot Program Launch (Month 3)
Launch a pilot program in a selected primary care setting or patient cohort. Train clinical and social care staff on using the new framework for social need identification and intervention planning.
Phase 4: Feedback & Iteration (Month 4)
Collect feedback from pilot participants and stakeholders. Analyse initial data to identify areas for framework refinement and process optimisation. Iterate on the framework and integration methods.
Phase 5: Scaled Deployment & Training (Month 5)
Begin scaled deployment across additional clinics or regions. Provide comprehensive training and support to all relevant staff, ensuring widespread adoption and consistent application of the framework.
Phase 6: Performance Monitoring & Reporting (Month 6+)
Establish continuous monitoring of framework effectiveness in identifying social needs and its impact on patient outcomes. Develop dashboards for tracking key metrics and generating reports for ongoing evaluation and improvement.
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