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.

scholarly journals Adverse Childhood Experiences among Adults in North Carolina, USA: Influences on Risk Factors for Poor Health across the Lifespan and Intergenerational Implications

2020 ◽  
Vol 17 (22) ◽  
pp. 8548
Author(s):  
Adam Hege ◽  
Erin Bouldin ◽  
Manan Roy ◽  
Maggie Bennett ◽  
Peyton Attaway ◽  
...  
Keyword(s):  
Risk Factors ◽  
North Carolina ◽  
Health Risk ◽  
Food Insecurity ◽  
Social Determinants Of Health ◽  
Social Determinants ◽  
Adverse Childhood Experiences ◽  
Health Risk Factors ◽  
Childhood Experiences ◽  
Adverse Childhood

Adverse childhood experiences (ACEs) are a critical determinant and predictor of health across the lifespan. The Appalachian region of the United States, particularly the central and southern portions, experiences worse health outcomes when compared to the rest of the nation. The current research sought to understand the cross-sectional relationships between ACEs, social determinants of health and other health risk factors in one southcentral Appalachian state. Researchers used the 2012 and 2014 North Carolina Behavioral Risk Factor Surveillance System (BRFSS) for analyses. An indicator variable of Appalachian county (n = 29) was used to make comparisons against non-Appalachian counties (n = 71). Analyses further examined the prevalence of ACEs in households with and without children across Appalachian and non-Appalachian regions, and the effects of experiencing four or more ACEs on health risk factors. There were no statistically significant differences between Appalachian and non-Appalachian counties in the prevalence of ACEs. However, compared with adults in households without children, those with children reported a higher percentage of ACEs. Reporting four or more ACEs was associated with higher prevalence of smoking (prevalence ratio [PR] = 1.56), heavy alcohol consumption (PR = 1.69), overweight/obesity (PR = 1.07), frequent mental distress (PR = 2.45), and food insecurity (PR = 1.58) in adjusted models and with fair or poor health only outside Appalachia (PR = 1.65). Residence in an Appalachian county was independently associated with higher prevalence of food insecurity (PR = 1.13). Developing programs and implementing policies aimed at reducing the impact of ACEs could improve social determinants of health, thereby helping to reduce health disparities.

scholarly journals Mining 100 million notes to find homelessness and adverse childhood experiences: 2 case studies of rare and severe social determinants of health in electronic health records

2017 ◽  
Vol 25 (1) ◽  
pp. 61-71 ◽  
Author(s):  
Cosmin A Bejan ◽  
John Angiolillo ◽  
Douglas Conway ◽  
Robertson Nash ◽  
Jana K Shirey-Rice ◽  
...  
Keyword(s):  
Electronic Health Records ◽  
Social Determinants Of Health ◽  
Social Determinants ◽  
Adverse Childhood Experiences ◽  
Determinants Of Health ◽  
Homeless Population ◽  
Health Records ◽  
Childhood Experiences ◽  
Adverse Childhood ◽  
Electronic Health

Abstract Objective Understanding how to identify the social determinants of health from electronic health records (EHRs) could provide important insights to understand health or disease outcomes. We developed a methodology to capture 2 rare and severe social determinants of health, homelessness and adverse childhood experiences (ACEs), from a large EHR repository. Materials and Methods We first constructed lexicons to capture homelessness and ACE phenotypic profiles. We employed word2vec and lexical associations to mine homelessness-related words. Next, using relevance feedback, we refined the 2 profiles with iterative searches over 100 million notes from the Vanderbilt EHR. Seven assessors manually reviewed the top-ranked results of 2544 patient visits relevant for homelessness and 1000 patients relevant for ACE. Results word2vec yielded better performance (area under the precision-recall curve [AUPRC] of 0.94) than lexical associations (AUPRC = 0.83) for extracting homelessness-related words. A comparative study of searches for the 2 phenotypes revealed a higher performance achieved for homelessness (AUPRC = 0.95) than ACE (AUPRC = 0.79). A temporal analysis of the homeless population showed that the majority experienced chronic homelessness. Most ACE patients suffered sexual (70%) and/or physical (50.6%) abuse, with the top-ranked abuser keywords being “father” (21.8%) and “mother” (15.4%). Top prevalent associated conditions for homeless patients were lack of housing (62.8%) and tobacco use disorder (61.5%), while for ACE patients it was mental disorders (36.6%–47.6%). Conclusion We provide an efficient solution for mining homelessness and ACE information from EHRs, which can facilitate large clinical and genetic studies of these social determinants of health.

Advocacy and Ac­tion in Appalachia Aimed at Adverse Childhood Experiences

2020 ◽  
pp. 125-148
Author(s):  
Adam Hege ◽  
Denise Presnell ◽  
Kellie B. Reed-Ashcraft ◽  
Karen Caldwell ◽  
Damiana Gibbons Pyles ◽  
...  
Keyword(s):  
Social Determinants Of Health ◽  
Social Determinants ◽  
Adverse Childhood Experiences ◽  
Academic Research ◽  
Social Determinant ◽  
Determinants Of Health ◽  
Childhood Experiences ◽  
Adverse Childhood ◽  
Community Initiative ◽  
Rural Appalachia

Rural Appalachia faces extreme poverty-linked hardships, often referred to as ‘social determinants of health'. One social determinant of health often linked with rural poverty is adverse childhood experiences (ACEs). ACEs refer to numerous experiences (e.g., forms of abuse and maltreatment, a dysfunctional household, mental illness in the household, etc.) that one encounters before the age of 18. Local leaders of a county in the heart of Appalachia in northwestern North Carolina (Watauga) embarked on a community level initiative (Watauga Compassionate Community Initiative) aimed at preventing and treating the effects of ACEs and building resiliency. This chapter delves into the academic research related to ACEs and poverty and details the background and ongoing story of the Watauga Compassionate Community Initiative, concluding with lessons learned and insights into what other rural communities can focus on when addressing ACEs, poverty, and other social determinants of health.

scholarly journals Assessing the Social Determinants of Health and Adverse Childhood Experiences in Patients Attending a Children's Hospital Cleft Palate-Craniofacial Program

2021 ◽  
pp. 105566562110487
Author(s):  
Ethan Ponton ◽  
Rebecca Courtemanche ◽  
Tanjot K. Singh ◽  
Damian Duffy ◽  
Douglas J. Courtemanche ◽  
...  
Keyword(s):  
Cleft Palate ◽  
Social Determinants Of Health ◽  
Social Determinants ◽  
Adverse Childhood Experiences ◽  
Determinants Of Health ◽  
Childhood Experiences ◽  
Children's Hospital ◽  
Adverse Childhood ◽  
The Social ◽  
Children’S Hospital

This study aimed to describe the social determinants of health (SDoH) for patients receiving multidisciplinary team care in a Cleft Palate-Craniofacial program, develop responsive and consistent processes to include trauma-informed psychosocial histories, promote discussions about additional “non-medical” factors influencing health and surgical outcomes, and demonstrate that these activities are feasible in the context of multidisciplinary patient-provider interactions. Single-site, cross-sectional study using a questionnaire. Participants were recruited from a provincial quaternary care Cleft Palate-Craniofacial program at British Columbia Children's Hospital in Vancouver, BC, Canada. 290 families completed the questionnaire. 34% of families experience significant barriers to accessing primary health care, 51% struggle financially, and 11% scored four or more on the Adverse Childhood Experiences scale. Furthermore, 47% reported not having adequate social support in their lives, and 5% reported not feeling resilient at the time of the survey. Patients with cleft and craniofacial anomalies have complex needs that extend beyond the surgical and medical care they receive. It is critical that all Cleft and Craniofacial teams incorporate social histories into their clinic workflow and be responsive to these additional needs. Discussions surrounding SDoH and adversity are welcomed by families; being involved in the care and decision-making plans is highly valued. Healthcare providers can and should ask about SDoH and advocate for universal access to responsive, site-based, social work support for their patients.

scholarly journals Structural and Social Determinants of Health Factors Associated with County-Level Variation in Non-Adherence to Antihypertensive Medication Treatment

2020 ◽  
Vol 17 (18) ◽  
pp. 6684
Author(s):  
Macarius M. Donneyong ◽  
Teng-Jen Chang ◽  
John W. Jackson ◽  
Michael A. Langston ◽  
Paul D. Juarez ◽  
...  
Keyword(s):  
Food Insecurity ◽  
Social Determinants Of Health ◽  
Social Determinants ◽  
Antihypertensive Medication ◽  
Social Supports ◽  
Determinants Of Health ◽  
P Value ◽  
County Level ◽  
Medication Treatment ◽  
Factors Associated

Background: Non-adherence to antihypertensive medication treatment (AHM) is a complex health behavior with determinants that extend beyond the individual patient. The structural and social determinants of health (SDH) that predispose populations to ill health and unhealthy behaviors could be potential barriers to long-term adherence to AHM. However, the role of SDH in AHM non-adherence has been understudied. Therefore, we aimed to define and identify the SDH factors associated with non-adherence to AHM and to quantify the variation in county-level non-adherence to AHM explained by these factors. Methods: Two cross-sectional datasets, the Centers for Disease Control and Prevention (CDC) Atlas of Heart Disease and Stroke (2014–2016 cycle) and the 2016 County Health Rankings (CHR), were linked to create an analytic dataset. Contextual SDH variables were extracted from the CDC-CHR linked dataset. County-level prevalence of AHM non-adherence, based on Medicare fee-for-service beneficiaries’ claims data, was extracted from the CDC Atlas dataset. The CDC measured AHM non-adherence as the proportion of days covered (PDC) with AHM during a 365 day period for Medicare Part D beneficiaries and aggregated these measures at the county level. We applied confirmatory factor analysis (CFA) to identify the constructs of social determinants of AHM non-adherence. AHM non-adherence variation and its social determinants were measured with structural equation models. Results: Among 3000 counties in the U.S., the weighted mean prevalence of AHM non-adherence (PDC < 80%) in 2015 was 25.0%, with a standard deviation (SD) of 18.8%. AHM non-adherence was directly associated with poverty/food insecurity (β = 0.31, P-value < 0.001) and weak social supports (β = 0.27, P-value < 0.001), but inversely with healthy built environment (β = −0.10, P-value = 0.02). These three constructs explained one-third (R2 = 30.0%) of the variation in county-level AHM non-adherence. Conclusion: AHM non-adherence varies by geographical location, one-third of which is explained by contextual SDH factors including poverty/food insecurity, weak social supports and healthy built environments.

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 Identification of factors related to food insecurity and the implications for social determinants of health screenings

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ashley R. Banks ◽  
Bethany A. Bell ◽  
David Ngendahimana ◽  
Milen Embaye ◽  
Darcy A. Freedman ◽  
...  
Keyword(s):  
Food Insecurity ◽  
Social Determinants Of Health ◽  
Social Determinants ◽  
Supplemental Nutrition Assistance Program ◽  
Determinants Of Health ◽  
Healthy Foods ◽  
Supplemental Nutrition ◽  
Assistance Program ◽  
And Behaviors ◽  
Nutrition Assistance

Abstract Background Food insecurity and other social determinants of health are increasingly being measured at routine health care visits. Understanding the needs and behaviors of individuals or families who screen positive for food insecurity may inform the types of resources they need. The goal of this research was to identify modifiable characteristics related to endorsement of two food insecurity screener questions to better understand the resources necessary to improve outcomes. Methods Analysis was conducted focusing on cross-sectional survey data collected in 2015–2016 from participants (N = 442) living in urban neighborhoods in Ohio with limited access to grocery stores. Food insecurity was assessed by the endorsement of at least one of two items. These were used to categorize participants into two groups: food insecure(N = 252) or food secure (N = 190). Using logistic regression, we estimated the association between several variables and the food insecure classification. Results Those that used their own car when shopping for food had lower odds of reporting food insecurity, as did those with affirmative attitudes related to the convenience of shopping for and ease of eating healthy foods. As shopping frequency increased, the odds of food insecurity increased. Food insecurity also increased with experience of a significant life event within the past 12 months. There was an 81% increase in the odds of reporting food insecurity among participants who received Supplemental Nutrition Assistance Program benefits compared to those not receiving Supplemental Nutrition Assistance Program benefits. Conclusions Along with referrals to SNAP, clinicians can further address screening-identified food insecurity through provision of transportation supports and linkages to other social services while collaborating on community initiatives to promote convenient and easy access to healthy foods. The needs and behaviors associated with screens indicating food insecurity also have implications for impacting other SDH, and thus, health outcomes.

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