Collecting Social Determinants of Health Data in the Clinical Setting: Findings from National PRAPARE Implementation

2020 ◽  
Vol 31 (2) ◽  
pp. 1018-1035 ◽  
Author(s):  
Rosy Chang Weir ◽  
Michelle Proser ◽  
Michelle Jester ◽  
Vivian Li ◽  
Carlyn M. Hood-Ronick ◽  
...  
Keyword(s):  
Social Determinants Of Health ◽  
Social Determinants ◽  
Clinical Setting ◽  
Health Data ◽  
Determinants Of Health

scholarly journals Linking Health and Social Data to Assess the Performance of High Dimensional Propensity Scores

2020 ◽  
Vol 5 (5) ◽  
Author(s):  
Naomi Hamm ◽  
Deepa Singal ◽  
Matthew Dahl ◽  
Dan Chateau ◽  
Marni Brownell
Keyword(s):  
School Readiness ◽  
Social Determinants Of Health ◽  
Social Determinants ◽  
Social Factors ◽  
Propensity Scores ◽  
Health Data ◽  
Determinants Of Health ◽  
Income Quintile ◽  
Social Data ◽  
Income Assistance

IntroductionHigh dimensional propensity scores (HDPS) aim to account for unmeasured confounding. However, it is unclear to what extent HDPS are able to attain this. Objectives and ApproachThis study aimed to test how well HDPS can account for confounding due to social determinants of health when using only health data. A retrospective cohort study was used to examine the effect of exposure to prescription opioids in utero on childhood outcomes (ADHD, school readiness, NICU admission, and hospitalization within the first year of life). Administrative health and social data were linked at the individual level and HDPS for each outcome were calculated using the mothers’ health data. Exposed and unexposed mother-child dyads were then matched. Standardized differences of mothers’ social factors (history of teen birth, lowest income quintile, ever received income assistance (i.e., welfare), ever lived in social housing, history with child protection services, residential mobility, and contact with the justice system) were compared before and after matching to determine to what degree the HDPS could account for differences in social determinants of health. Additional HDPS analyses were performed with social factors included in the HDPS with the health data. ResultsBefore matching, standardized differences between exposed and unexposed groups for the social factors ranged between 0.40-0.75. Income assistance and lowest income quintile consistently had the greatest and smallest standardized difference for all outcomes, respectively. After matching, using health data only, standardized differences decreased considerably, ranging from 0.05-0.27. When including social factors into the HDPS, the addition of income assistance produced the smallest standardized differences with a range of 0.01-0.13 for all outcomes. ConclusionsUsing the HDPS with health data only can reduce confounding due to social factors. If data are available, including income assistance in the HDPS may further reduce confounding for all social determinants of health.

scholarly journals Using simulation to increase resident comfort discussing social determinants of health

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
John M Morrison ◽  
Sarah M. Marsicek ◽  
Akshata M Hopkins ◽  
Robert A Dudas ◽  
Kimberly R Collins
Keyword(s):  
Food Insecurity ◽  
Social Determinants Of Health ◽  
Social Determinants ◽  
Clinical Setting ◽  
Comfort Level ◽  
Determinants Of Health ◽  
Childhood Experiences ◽  
Curricular Intervention ◽  
Adverse Childhood ◽  
A Prospective Study

Abstract Background Social determinants of health (SDoH) play an important role in pediatric health outcomes. Trainees receive little to no training on how to identify, discuss and counsel families in a clinical setting. The aim of this study was to determine if a simulation-based SDoH training activity would improve pediatric resident comfort with these skills. Methods We performed a prospective study of a curricular intervention involving simulation cases utilizing standardized patients focused on four social determinants (food insecurity, housing insecurity, barriers to accessing care, and adverse childhood experiences [ACEs]). Residents reported confidence levels with discussing each SDoH and satisfaction with the activity in a retrospective pre-post survey with five-point Likert style questions. Select residents were surveyed again 9–12 months after participation. Results 85% (33/39) of residents expressed satisfaction with the simulation activity. More residents expressed comfort discussing each SDoH after the activity (Δ% 38–47%; all p < .05), with the greatest effect noted in post-graduate-year-1 (PGY-1) participants. Improvements in comfort were sustained longitudinally during the academic year. More PGY-1 participants reported engaging in ≥ 2 conversations in a clinical setting related to food insecurity (43% vs. 5%; p = .04) and ACEs (71% vs. 20%; p = .02). Discussion Simulation led to an increased resident comfort with discussing SDoH in a clinical setting. The greatest benefit from such a curriculum is likely realized early in training. Future efforts should investigate if exposure to the simulations and increased comfort level with each topic correlate with increased likelihood to engage in these conversations in the clinical setting.

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