New Data Resources, Linkages, and Infrastructure for Cancer Health Economics Research: Main Topics From a Panel Discussion

Realizing the potential of social determinants data in EHR systems: A scoping review of approaches for screening, linkage, extraction, analysis, and interventions

Background

Social determinants of health (SDoH), such as socioeconomics and neighborhoods, strongly influence health outcomes. However, the current state of standardized SDoH data in electronic health records (EHRs) is lacking, a significant barrier to research and care quality.

Methods

We conducted a PubMed search using "SDOH" and "EHR" Medical Subject Headings terms, analyzing included articles across five domains: 1) SDoH screening and assessment approaches, 2) SDoH data collection and documentation, 3) Use of natural language processing (NLP) for extracting SDoH, 4) SDoH data and health outcomes, and 5) SDoH-driven interventions.

Results

Of 685 articles identified, 324 underwent full review. Key findings include implementation of tailored screening instruments, census and claims data linkage for contextual SDoH profiles, NLP systems extracting SDoH from notes, associations between SDoH and healthcare utilization and chronic disease control, and integrated care management programs. However, variability across data sources, tools, and outcomes underscores the need for standardization.

Discussion

Despite progress in identifying patient social needs, further development of standards, predictive models, and coordinated interventions is critical for SDoH-EHR integration. Additional database searches could strengthen this scoping review. Ultimately, widespread capture, analysis, and translation of multidimensional SDoH data into clinical care is essential for promoting health equity.

Realizing the Potential of Social Determinants Data: A Scoping Review of Approaches for Screening, Linkage, Extraction, Analysis and Interventions

Background

Social determinants of health (SDoH) like socioeconomics and neighborhoods strongly influence outcomes, yet standardized SDoH data is lacking in electronic health records (EHR), limiting research and care quality.

Methods

We searched PubMed using keywords "SDOH" and "EHR", underwent title/abstract and full-text screening. Included records were analyzed under five domains: 1) SDoH screening and assessment approaches, 2) SDoH data collection and documentation, 3) Use of natural language processing (NLP) for extracting SDoH, 4) SDoH data and health outcomes, and 5) SDoH-driven interventions.

Results

We identified 685 articles, of which 324 underwent full review. Key findings include tailored screening instruments implemented across settings, census and claims data linkage providing contextual SDoH profiles, rule-based and neural network systems extracting SDoH from notes using NLP, connections found between SDoH data and healthcare utilization/chronic disease control, and integrated care management programs executed. However, considerable variability persists across data sources, tools, and outcomes.

Discussion

Despite progress identifying patient social needs, further development of standards, predictive models, and coordinated interventions is critical to fulfill the potential of SDoH-EHR integration. Additional database searches could strengthen this scoping review. Ultimately widespread capture, analysis, and translation of multidimensional SDoH data into clinical care is essential for promoting health equity.

Enhancing Cancer Economic Data Resources: The Interagency Consortium to Promote Health Economics Research on Cancer (HEROiC)

BACKGROUND

Cancer diagnosis and treatment can substantially affect health and financial outcomes for patients and families. Research in health care delivery across the cancer control continuum includes diverse activities led by multiple government and private sector organizations. Assessing the economic drivers and influencing factors associated with costs across this continuum is challenging as organizations leading research efforts often do not have forums to share data, develop linkages, and explore collaborative opportunities.

OBJECTIVE

To describe the objectives, activities, and goals of the Interagency Consortium to Promote Health Economics Research on Cancer (HEROiC) to strengthen data resources and capacity for collaborative patient-focused cancer health economics research.

MAIN ARGUMENT

HEROiC's goals include assessing the economic burden of cancer; examining the effects of policies, health care setting/system factors, and health service delivery approaches across the cancer control continuum; and enhancing collaborations among researchers and organizations.

CONCLUSIONS

Data resources to study economic outcomes associated with cancer control are highly fragmented; HEROIC provides a forum to collaboratively develop, enhance, and utilize data resources and infrastructure for patient-centered cancer health economics research. This includes sharing data resources, developing linkages, identifying new data collection venues, and creating and supporting the dissemination of evidence-based information to diverse stakeholders. These efforts provide critical information to address the economic burden of cancer.

RELEVANCE TO THE SPECIAL ISSUE

Cancer diagnosis and treatment affect patient health and financial outcomes. This commentary describes how HEROiC will enhance research data infrastructure and collaborations to support patient-centered research with the goal of reducing the economic burden of cancer.