The Utility of the Brokamp Area Deprivation Index as a Prescreen for Social Risk in Primary Care

Nguyen, Cam; Popescu, Filoteia; Sommer, Evan C.; Adams, LauraBeth; Barkin, Shari L.

doi:10.1016/j.jpeds.2022.06.028

Cited by 7 publications

(9 citation statements)

References 25 publications

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“…Lastly, our model showed a minimally increased risk of social needs in association with characteristics of the neighborhood of residence, presented as the ADI measure. This finding was similar to the results of the study by Nguyen et al [ 39 ], where they identified a small statistically significant association between the ADI and total score on social needs from the Health Leads Social Needs Survey among pediatric patients‘ families receiving primary care at a large academic institution. A review by Chen et al [ 21 ] also indicated the low success of the integration of population-level data for predictive modeling and risk stratification purposes, including the prediction of social-related service referrals [ 13 ], in contrast to the performance of models using individual-level data in referrals to a social worker [ 40 ].…”

Section: Discussionsupporting

confidence: 91%

Development of a Social Risk Score in the Electronic Health Record to Identify Social Needs Among Underserved Populations: Retrospective Study

Hatef,

Chang,

Richards

et al. 2024

JMIR Form Res

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Background Patients with unmet social needs and social determinants of health (SDOH) challenges continue to face a disproportionate risk of increased prevalence of disease, health care use, higher health care costs, and worse outcomes. Some existing predictive models have used the available data on social needs and SDOH challenges to predict health-related social needs or the need for various social service referrals. Despite these one-off efforts, the work to date suggests that many technical and organizational challenges must be surmounted before SDOH-integrated solutions can be implemented on an ongoing, wide-scale basis within most US-based health care organizations. Objective We aimed to retrieve available information in the electronic health record (EHR) relevant to the identification of persons with social needs and to develop a social risk score for use within clinical practice to better identify patients at risk of having future social needs. Methods We conducted a retrospective study using EHR data (2016-2021) and data from the US Census American Community Survey. We developed a prospective model using current year-1 risk factors to predict future year-2 outcomes within four 2-year cohorts. Predictors of interest included demographics, previous health care use, comorbidity, previously identified social needs, and neighborhood characteristics as reflected by the area deprivation index. The outcome variable was a binary indicator reflecting the likelihood of the presence of a patient with social needs. We applied a generalized estimating equation approach, adjusting for patient-level risk factors, the possible effect of geographically clustered data, and the effect of multiple visits for each patient. Results The study population of 1,852,228 patients included middle-aged (mean age range 53.76-55.95 years), White (range 324,279/510,770, 63.49% to 290,688/488,666, 64.79%), and female (range 314,741/510,770, 61.62% to 278,488/448,666, 62.07%) patients from neighborhoods with high socioeconomic status (mean area deprivation index percentile range 28.76-30.31). Between 8.28% (37,137/448,666) and 11.55% (52,037/450,426) of patients across the study cohorts had at least 1 social need documented in their EHR, with safety issues and economic challenges (ie, financial resource strain, employment, and food insecurity) being the most common documented social needs (87,152/1,852,228, 4.71% and 58,242/1,852,228, 3.14% of overall patients, respectively). The model had an area under the curve of 0.702 (95% CI 0.699-0.705) in predicting prospective social needs in the overall study population. Previous social needs (odds ratio 3.285, 95% CI 3.237-3.335) and emergency department visits (odds ratio 1.659, 95% CI 1.634-1.684) were the strongest predictors of future social needs. Conclusions Our model provides an opportunity to make use of available EHR data to help identify patients with high social needs. Our proposed social risk score could help identify the subset of patients who would most benefit from further social needs screening and data collection to avoid potentially more burdensome primary data collection on all patients in a target population of interest.

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Section: Discussionsupporting

confidence: 91%

Development of a Social Risk Score in the Electronic Health Record to Identify Social Needs Among Underserved Populations: Retrospective Study

Hatef,

Chang,

Richards

et al. 2024

JMIR Form Res

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“…A developing body of research is examining the relationship between population-level social indices and health outcomes. The role of social indices has been proposed as part of a prescreening process or as a proxy for screening for SDOH when individual screening is not feasible [75] or encounters limitations [76,77]. Social indices are scores produced from geocoded population-level surveillance of indicators that are considered factorial SDOH domains.…”

Section: The Role Of Individual Versus Population Datamentioning

confidence: 99%

“…There are currently few studies correlating social indices to individually identified patient specific needs. Nguyen et al [75] performed a study comparing family completed Health Leads Social Needs (HLSN) survey responses to the Area Deprivation Index and found a small but statistically significant association with the SDOH domains of housing instability, childcare, transportation, and health literacy. Ho et al showed a three-fold greater odds ratio of being food insecure (based off the two-item Hunger Vital Sign) for patients living in low/very-low child opportunity areas compared with high opportunity areas [84].…”

Section: The Role Of Individual Versus Population Datamentioning

confidence: 99%

Social determinants of health screening in pediatric healthcare settings

Nerlinger

Kopsombut

2022

Current Opinion in Pediatrics

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Purpose of reviewThis article outlines updates in social determinants of health (SDOH) screening practices in pediatric healthcare and community settings. The transition to value-based care and the COVID-19 pandemic have both had significant impacts on screening practices, with implications for providers, communities, and policymakers.Recent findingsThe COVID-19 pandemic has exacerbated social needs for vulnerable patients and families, resulting in increased recognition by healthcare teams through screening. Policy frameworks like value-based care that aim to deliver whole-child care in the community are reorienting the logistics of screening, including screening in acute-care settings and community settings. Recent studies on family and provider perspectives should be integrated into screening practices.SummaryDespite significant advances in and expansion of SDOH screening in the pediatric healthcare setting, there remain limitations and future research needs. More data is needed to evaluate social need screeners and interventions, and determine how healthcare systems, communities, and states can spread and scale such interventions based on outcomes and value measurements. Population-based social indices have the potential to augment individual patient screening, but this remains a future research need.

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“… 39 Similarly, community-level SDoH assessments can be incorporated into the medical health record to stratify patient risk in a multitude of health care settings such as inpatient or outpatient. 40 , 41 With most children surviving a primary malignancy, assessments that focus on childhood cancer survivorship is increasingly more relevant due to a higher incidence of not only secondary malignant neoplasms 42 but also cardiovascular complications 43 in this population. Both general and subspecialty medical health care providers have a valuable role in both risk-based surveillance and preventative medicine.…”

Section: Discussionmentioning

confidence: 99%

Impact of social disparities on 10 year survival rates in paediatric cancers: a cohort study

Chalfant

Riveros

Bradfield

et al. 2023

The Lancet Regional Health - Americas

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The Utility of the Brokamp Area Deprivation Index as a Prescreen for Social Risk in Primary Care

Cited by 7 publications

References 25 publications

Development of a Social Risk Score in the Electronic Health Record to Identify Social Needs Among Underserved Populations: Retrospective Study

Development of a Social Risk Score in the Electronic Health Record to Identify Social Needs Among Underserved Populations: Retrospective Study

Social determinants of health screening in pediatric healthcare settings

Impact of social disparities on 10 year survival rates in paediatric cancers: a cohort study

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