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Exploring consensus across sectors for measuring the social determinants of health.

ABSTRACT: The importance of social determinants of health (SDOH) -such as affordable housing, stable employment, consistent transportation, healthy food access, and quality schools-is well-established as a key component of chronic disease prevention and health promotion. Increasingly, practitioners within and beyond public health are collaborating to implement such strategies, part of which involves measuring their impacts over time. This study assesses the current state of SDOH measurement across sectors by systematically identifying how many and what kinds of tools exist and whether there is consensus around SDOH categories and indicators selected. This study revealed that while numerous SDOH measurement resources exist, relatively few are tools for measuring the SDOH. Although the SDOH categories being measured could be readily summarized across tools, there was wide variation in the particular SDOH categories included in each tool. Finally, remarkably little consensus exists for the specific indicators used to measure SDOH categories. While complete consensus across tools may not be possible, learning how different sectors measure SDOH and more systematically aligning SDOH categories and indicators being measured will enable greater collaboration and deepen the impacts of place-based interventions to improve community health and well-being.

SUBMITTER: Elias RR

PROVIDER: S-EPMC6484213 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Exploring consensus across sectors for measuring the social determinants of health.

Elias Renee Roy RR Jutte Douglas P DP Moore Alison A

SSM - population health 20190409

The importance of social determinants of health (SDOH) -such as affordable housing, stable employment, consistent transportation, healthy food access, and quality schools-is well-established as a key component of chronic disease prevention and health promotion. Increasingly, practitioners within and beyond public health are collaborating to implement such strategies, part of which involves measuring their impacts over time. This study assesses the current state of SDOH measurement across sectors ...[more]

PMID: 31049390

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Project description:ObjectiveExisting research on social determinants of health (SDoH) predominantly focuses on physician notes and structured data within electronic medical records. This study posits that social work notes are an untapped, potentially rich source for SDoH information. We hypothesize that clinical notes recorded by social workers, whose role is to ameliorate social and economic factors, might provide a complementary information source of data on SDoH compared to physician notes, which primarily concentrate on medical diagnoses and treatments. We aimed to use word frequency analysis and topic modeling to identify prevalent terms and robust topics of discussion within a large cohort of social work notes including both outpatient and in-patient consultations.Materials and methodsWe retrieved a diverse, deidentified corpus of 0.95 million clinical social work notes from 181 644 patients at the University of California, San Francisco. We conducted word frequency analysis related to ICD-10 chapters to identify prevalent terms within the notes. We then applied Latent Dirichlet Allocation (LDA) topic modeling analysis to characterize this corpus and identify potential topics of discussion, which was further stratified by note types and disease groups.ResultsWord frequency analysis primarily identified medical-related terms associated with specific ICD10 chapters, though it also detected some subtle SDoH terms. In contrast, the LDA topic modeling analysis extracted 11 topics explicitly related to social determinants of health risk factors, such as financial status, abuse history, social support, risk of death, and mental health. The topic modeling approach effectively demonstrated variations between different types of social work notes and across patients with different types of diseases or conditions.DiscussionOur findings highlight LDA topic modeling's effectiveness in extracting SDoH-related themes and capturing variations in social work notes, demonstrating its potential for informing targeted interventions for at-risk populations.ConclusionSocial work notes offer a wealth of unique and valuable information on an individual's SDoH. These notes present consistent and meaningful topics of discussion that can be effectively analyzed and utilized to improve patient care and inform targeted interventions for at-risk populations.

Project description:ObjectiveTo propose and evaluate a novel approach for measuring hospital-level disparities according to the effect of a continuous, polysocial risk factor on those outcomes.Study settingOur cohort consisted of Medicare Fee-for-Service (FFS) patients 65 years and older admitted to acute care hospitals for one of six common conditions or procedures. Medicare administrative claims data for six hospital readmission measures including hospitalizations from July 2015 to June 2018 were used.Study designWe adapted existing methodologies that were developed to report hospital-level disparities using dichotomous social risk factors (SRFs). The existing methods report disparities within and across hospitals; we developed and tested modified approaches for both methods using the Agency for Healthcare Research and Quality Socioeconomic Status Index. We applied the adapted methodologies to six 30-day hospital readmission measures included in the Centers for Medicare & Medicaid Services Hospital Readmissions Reduction Program measures. We compared the within- and across-hospital results for each to those obtained from using the original methods and dichotomizing the AHRQ SES Index into "low" and "high" scores.Data collectionWe used Medicare FFS administrative claims data linked to U.S. Census data.Principal findingsFor all six readmission measures we find that, when compared with the existing methods, the methods for continuous SRFs provide disparity results for more facilities though across a narrower range of values. Measures of disparity based on this approach are moderately to highly correlated with those based on a dichotomous version of the same risk factor, while reflecting a fuller spectrum of risk. This approach represents an opportunity for detection of provider-level results that more closely align with underlying social risk.ConclusionWe have demonstrated the feasibility and utility of estimating hospital disparities of care using a continuous, polysocial risk factor. This approach expands the potential for reporting hospital-level disparities while better accounting for the multifactorial nature of social risk on hospital outcomes.

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Exploring consensus across sectors for measuring the social determinants of health.

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Exploring consensus across sectors for measuring the social determinants of health.

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