scholarly journals Physician Assessment of Social Determinants of Health: A Necessary Component in Improving Care of Patients

2021 ◽  
Vol 11 (S1) ◽  
Author(s):  
Emaan Chaudry

The importance of building a therapeutic relationship between a physician and a patient is taught early on in a medical student's training, specifically through the practice of obtaining a patient history. This process consists of gathering information in four main categories: the history of the present illness, personal social history, past medical history, and family history. Each piece of information obtained within these categories is vital in ensuring a patient receives appropriate and effective care. Specifically, a social history consists of asking about a patient's relationship status, support system, home environment, interests, exercise, nutritional habits, substance use, and sexual history. To complete a successful and full social history, one should try to address the social determinants of health. As per the Government of Canada’s website, social determinants of health “refer to a specific group of social and economic factors within the broader determinants of health. These relate to an individual’s place in society such as income, education or employment” [1]. Consequently, a critical component of a complete social history interview should be investigating a patients socioeconomic status. Low socioeconomic status (LSES) has been found to play a role in incidence and susceptibility to a variety of health conditions. As such, I believe that screening for and asking questions pertaining to the socioeconomic status of a patient should be considered a vital and essential component of every patient assessment.

2020 ◽  
pp. 1-12
Author(s):  
Steven S. Coughlin ◽  
Steven S. Coughlin ◽  
Lufei Young

Social determinants of health that have been examined in relation to myocardial infarction incidence and survival include socioeconomic status (income, education), neighbourhood disadvantage, immigration status, social support, and social network. Other social determinants of health include geographic factors such as neighbourhood access to health services. Socioeconomic factors influence risk of myocardial infarction. Myocardial infarction incidence rates tend to be inversely associated with socioeconomic status. In addition, studies have shown that low socioeconomic status is associated with increased risk of poorer survival. There are well-documented disparities in myocardial infarction survival by socioeconomic status, race, education, and census-tract-level poverty. The results of this review indicate that social determinants such as neighbourhood disadvantage, immigration status, lack of social support, and social isolation also play an important role in myocardial infarction risk and survival. To address these social determinants and eliminate disparities, effective interventions are needed that account for the social and environmental contexts in which heart attack patients live and are treated.


2021 ◽  
Vol 42 (Supplement_1) ◽  
pp. S151-S152
Author(s):  
Luis H Quiroga ◽  
Tomer Lagziel ◽  
Mohammed Asif ◽  
Raymond Fang ◽  
Grace F Rozycki ◽  
...  

Abstract Introduction To our knowledge, no studies have been conducted assessing the social determinants of health and the impact on the outcomes for burn patients. Such studies are needed considering burn injuries are associated with high costs, severe psychological impact, and a high burden placed on the healthcare systems. The burden is hypothesized to be aggravated by the increasing amount of diabetes and obesity seen in the general population which put patients at increased risk for developing chronic wounds. Studies have shown that several socioeconomic status (SES) factors are associated with increased risk of burns, but none have documented the outcomes of burn patients based on their social determinants of health. In our study, we will be comparing patients in the burn ICU (BICU) to patients in the surgical ICU (SICU). The purpose of this comparison is to evaluate whether the same social determinants of health have similar influences in both groups. Methods We performed a retrospective analysis of population group data from patients admitted to the BICU and SICU from January 1, 2016, to November 18, 2019. The primary outcomes were length-of-stay (LOS), mortality, 30-day-readmission, and hospital charges. Pearson’s chi-square test for categorical variables and t-test for continuous variables were used to compare population health groups. Results We analyzed a total of 487 burn and 510 surgical patients. When comparing BICU and SICU patients, we observed significantly higher mean hospital charges and LOS in burn patients with a history of mental health (mean difference: $42,756.04, p=0.013 and 7.12 days, p=0.0085), ESRD ($57,8124.7, p=0.0047 and 78.62 days, p=0.0104), sepsis ($168,825.19, p=< 0.001 and 20.68 days, p=0.0043), and VTE ($63,9924.1, p=< 0.001 and 72.9 days, p=0.002). Also, higher mortality was observed in burn patients with ESRD, STEMI, sepsis, VTE, and diabetes mellitus. Burn patients with a history of mental health, drug dependence, heart failure, and diabetes mellitus also had greater 30-day-readmissions rates. Conclusions This study sheds new knowledge on the considerable variability that exists between the different population health groups in terms of outcomes for each cohort of critically ill patients. It demonstrates the impacts of population health group on outcomes. These population groups and social determinants have different effects on BICU versus SICU patients and this study provides supporting evidence for the need to identify and develop new strategies to decrease overspending in healthcare. Further research to develop relevant and timely interventions that can improve these outcomes.


Author(s):  
Jessica Wallace ◽  
Erica Beidler ◽  
Johna K. Register-Mihalik ◽  
Tamaria Hibbler ◽  
Abigail Bretzin ◽  
...  

Abstract Context: There is limited research concerning the relationship between social determinants of health, including race, healthcare access, socioeconomic status (SES), and physical environment; and, concussion nondisclosure in college-athletes. However, in high school athletes, disparities have been noted, with Black athletes attending under-resourced schools and lacking access to an athletic trainer (AT) disclosing fewer concussions. Objective: To investigate whether concussion nondisclosure disparities exist by 1) race, 2) SES, and 3) AT healthcare access prior to college; and to understand the differential reasons for concussion nondisclosure between Black and White college-athletes. Design: Cross-sectional Setting: College athletics Participants: 735 college-athletes (84.6% White, 15.4% Black) Main Outcome Measures: Participants completed a questionnaire that directly assessed concussion nondisclosure, including reasons for not reporting a suspected concussion. With the premise of investigating social determinants of health, race was the primary exposure of interest. The outcome of interest, nondisclosure, was assessed with a binary (yes/no) question, “Have you ever sustained a concussion that you did not report to your coach, athletic trainer, parent, teammate, or anyone else?” Results: Overall, among White and Black athletes 15.6% and 17.7% respectively reported a history of concussion nondisclosure. No significant differences were found by race for distributions of history of concussion nondisclosure (p=0.57). Race was not associated with concussion nondisclosure when evaluated as an effect modification measure or confounder; and, no significant associations were noted by SES or high school AT access. Differences by race for reported reasons for nondisclosure were found for: “At the time I did not think it was a concussion” (p=0.045) and “I thought my teammates would think I am weak” (p=0.03) with Black athletes reporting these more frequently than White athletes. Conclusions: These data help to contextualize race and its intersection with other social determinants of health that could influence concussion nondisclosure outcomes in college-athletes.


Author(s):  
Ruth Cross ◽  
Simon Rowlands ◽  
Sally Foster

Abstract This book chapter seeks to: (i) explore concepts of 'health' held by lay people and health promoters; (ii) introduce recent work on the social determinants of health; (iii) introduce certain threshold concepts including salutogenesis, social models of health and upstream thinking; (iv) establish the value base of health promotion; (v) introduce the disciplinary foundations of health promotion; (vi) outline in more detail 'empowerment' as a key value in health promotion; and (vii) describe the key WHO conferences, which provide the milestones in the development of health promotion. This chapter has provided a foundation upon which to base further study; it has presented the key values and principles of health promotion; emphasized the need to tackle the social determinants of health; presented a history of health promotion's development through the WHO-led conferences; introduced some threshold concepts; introduced the disciplines that contribute to health promotion; outlined professional and lay concepts of health; and suggested that empowerment approaches are the essence of health promotion.


Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Kristie Bauman ◽  
Shashank Agarwal ◽  
Shadi Yaghi ◽  
Ariane Lewis ◽  
Aaron Lord ◽  
...  

Introduction: The association between race and white matter hyperintensities (WMH) and cerebral microbleeds in patients with intracerebral hemorrhage (ICH) is controversial. We examined the relationship between race and social determinants of health with WMH and microbleeds in ICH. Methods: We performed a retrospective study of patients at a tertiary care hospital between 2013 and 2020 who presented with ICH and underwent MRI of the brain. MRIs were evaluated for the presence of microbleeds and WMH severity (defined by the Fazekas scale; severe WMH defined as Fazekas 3). We assessed for an association of sex, race, ethnicity, employment status, median household income by zip code, education level, and insurance status with the severity of WMH or presence of microbleeds. Results: We identified 105 patients (median age 65.5 (IQR 53-76); 51% females; 13.2% Black) with ICH who had an MRI of the brain. Median ICH score was 1 [IQR 0-2] and median hematoma size was 15.9 ml (SD 19.7). High school graduation was the highest education level in 13.2%, and 57.5% had private insurance. Median income by zip code was $87,667 (IQR $65,900-$117,923). Severe WMH was observed in 19.8% and 52.8% of patients had microbleeds. There was no significant difference in sex, insurance status or median income for patients with or without severe WMH nor those with or without microbleeds. Severe WMH was more common among older patients (p=0.001), Black patients (p=0.03), patients with hypertension (p=0.03), and those with lower levels of education (p=0.03). In multivariable analyses, Black race was associated with severe WMH when adjusting for age and history of hypertension (OR 6.13 95% CI 1.14-25.98, p=0.01) but the effect size attenuated and the association disappears when adding education level to the model (OR 3.38 95% CI 0.48-23.76, p = 0.2). Age and history of hypertension were associated with presence of microbleeds (p<0.01 for both), but there was no association between presence of microbleeds and Black race or education level. Conclusion: Although Black race was associated with severe WMH, this association did not remain after adjusting for level of education. Our findings suggest that social determinants of health can modify the association between race and imaging biomarkers of ICH.


2021 ◽  
Vol 2 (2) ◽  
pp. 119-121
Author(s):  
Hiroshi Bando

Diabetes mellitus has become a medical and social problem. For better diabetic management and improvement of the health care system, the concept of social determinants of health (SDOH) and socioeconomic status (SES) would be required. SES includes adequate diabetes care, medical cost, health condition, and regular access to care and cure. World Health Organization (WHO) has continued the prevention and management of diabetes and proposed the Global Diabetes Compact in last 2020 [1]. The purpose of the Compact includes several items, such as i) to leverage present capacities in the healthcare system, ii) to meet people’s needs more holistic way, iii) to promote efforts to prevent diabetes especially the young generation, and others. A successful key would be the combined action among public, private, and philanthropic associations. Diabetes mellitus has been a growing medical and social problem in all countries and districts worldwide [2]. The socio economic gradient for diabetic prevalence is shown in high income countries [3]. Further, this gradient seems to be continued for a long despite the improvement of the health care system in those countries [4,5]. In this paper, we describe the social determinants of health (SDOH) and socioeconomic status (SES), among other axes of symmetry for diabetes. In medical practice and health care, population based and value based care have been emphasized. Then, the concept of social determinants of health (SDOH) has been gradually known for an intervention target for estimating health equity [6]. Recently, some comments for SDOH were proposed from medical associations, such as the Society of General Internal Medicine, the American College of Physicians, and other organizations [7]. Moreover, the action perspectives tend to focus on the determinants for individuals and policy [8,9]. In diabetic practice, some basic matters exist including prevalence, incidence, adequate therapy, and economic problems [10]. ADA presented a comment about socio ecological determinants of diabetes. Successively, ADA had an advanced health improvement project for the diabetes writing committee. It has the goal of clarifying diabetic risk and outcomes, academic literature for SDOH [11]. From previous literature, SDOH covers certain areas as follows [6]: i) social context (social support, relationship, and capital, social relationship), ii) health care (quality, accessibility, affordability), iii) local and physical circumstance (residence condition, building environment), iv) food environment (insecurity for food, accessibility for food) and v) socio economic condition (occupation, education, income). According to academic reports, the health disparities for diabetes have been present in the light of adverse influence [12]. Social and environmental factors have been summarized as SDOH in WHO [13]. Among them, social environments seem to be rather main factors. They include societal and community context [14], social capital, social cohesion, and social elements [15]. Health care has been found as an SDOH in the Healthy People 2020, WHO, County health rankings models, associated with accessible factors. WHO regards the health system as one of the SDOH which can give a message of determinants of several health outcomes [15]. On the other hand, it is socioeconomic status (SES) that may influence all related aspects of diabetic treatment in the clinical practice [16]. Actually, lower SES diabetic cases are likely to have some barriers to adequate diabetes care, including medical cost, unsatisfactory health condition, and regular access to care and cure [17]. SES has revealed the multidimensional construct, associated with the occupational, economic, and educational situation [18]. SES has been related to all factors of SDOH [13]. They include medical care, health care, nutrition, social resources, housing, transportation, and so on. The factors of SES and diabetes were investigated for observational studies [19]. It included 28 investigations including diabetic complications, retinopathy, cardiopathy, and others. In summary, SDOH and SES concerning diabetes were introduced. This information will be hopefully useful for developing a bio psycho social perspective in clinical practice.


PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0241868
Author(s):  
Zachary D. Rethorn ◽  
Alessandra N. Garcia ◽  
Chad E. Cook ◽  
Oren N. Gottfried

Objectives Our objective was to analyze the collective effect of social determinants of health (SDoH) on lumbar spine surgery outcomes utilizing two different statistical methods of combining variables. Methods This observational study analyzed data from the Quality Outcomes Database, a nationwide United States spine registry. Race/ethnicity, educational attainment, employment status, insurance payer, and gender were predictors of interest. We built two models to assess the collective influence of SDoH on outcomes following lumbar spine surgery—a stepwise model using each number of SDoH conditions present (0 of 5, 1 of 5, 2 of 5, etc) and a clustered subgroup model. Logistic regression analyses adjusted for age, multimorbidity, surgical indication, type of lumbar spine surgery, and surgical approach were performed to identify the odds of failing to demonstrate clinically meaningful improvements in disability, back pain, leg pain, quality of life, and patient satisfaction at 3- and 12-months following lumbar spine surgery. Results Stepwise modeling outperformed individual SDoH when 4 of 5 SDoH were present. Cluster modeling revealed 4 distinct subgroups. Disparities between the younger, minority, lower socioeconomic status and the younger, white, higher socioeconomic status subgroups were substantially wider compared to individual SDoH. Discussion Collective and cluster modeling of SDoH better predicted failure to demonstrate clinically meaningful improvements than individual SDoH in this cohort. Viewing social factors in aggregate rather than individually may offer more precise estimates of the impact of SDoH on outcomes.


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