600 Social Determinants and Their Impact on Burn Surgery Outcomes

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):  
Ik-Whan G. Kwon ◽  
Sung-Ho Kim ◽  
David Martin

The COVID-19 pandemic has altered healthcare delivery platforms from traditional face-to-face formats to online care through digital tools. The healthcare industry saw a rapid adoption of digital collaborative tools to provide care to patients, regardless of where patients or clinicians were located, while mitigating the risk of exposure to the coronavirus. Information technologies now allow healthcare providers to continue a high level of care for their patients through virtual visits, and to collaborate with other providers in the networks. Population health can be improved by social determinants of health and precision medicine working together. However, these two health-enhancing constructs work independently, resulting in suboptimal health results. This paper argues that artificial intelligence can provide clinical–community linkage that enhances overall population health. An exploratory roadmap is proposed.


2019 ◽  
Vol 26 (8-9) ◽  
pp. 895-899 ◽  
Author(s):  
Joseph J Deferio ◽  
Scott Breitinger ◽  
Dhruv Khullar ◽  
Amit Sheth ◽  
Jyotishman Pathak

Abstract Social determinants of health (SDOH) are known to influence mental health outcomes, which are independent risk factors for poor health status and physical illness. Currently, however, existing SDOH data collection methods are ad hoc and inadequate, and SDOH data are not systematically included in clinical research or used to inform patient care. Social contextual data are rarely captured prospectively in a structured and comprehensive manner, leaving large knowledge gaps. Extraction methods are now being developed to facilitate the collection, standardization, and integration of SDOH data into electronic health records. If successful, these efforts may have implications for health equity, such as reducing disparities in access and outcomes. Broader use of surveys, natural language processing, and machine learning methods to harness SDOH may help researchers and clinical teams reduce barriers to mental health care.


2013 ◽  
Vol 32 (1) ◽  
pp. 43-57 ◽  
Author(s):  
Shawn R. Currie ◽  
Kirsten Fiest ◽  
Lindsay Guyn

The effect of social determinants of health on depression prevalence and treatment access was examined using community survey and administrative data on mental health service users in the Calgary Health Region (CHR). Consistent with national prevalence data, depression was significantly associated with female gender, younger age, and health risk factors such as smoking, hypertension, and obesity. The prevalence of depression causing interference in daily functioning across 19 social districts (subregions within the CHR) was significantly related to community-level indicators of single-parent status, low-income families, and low educational achievement in each district. Disparities in treatment access were also found with persons living in the most impoverished districts having the lowest rates of accessing professional mental health services.


2019 ◽  
Vol 34 (s1) ◽  
pp. s95-s95
Author(s):  
Joseph Cuthbertson ◽  
Frank Archer ◽  
Jose Rodriguez-llanes ◽  
Andrew Robertson

Introduction:The rationale for undertaking this study was to investigate how characteristics of population health relate to and impact disaster risk, resilience, vulnerability, impact, and recovery. The multi-disciplinary environment that contextualizes disaster practice can influence determinants of health. Robust health determinants, or lack thereof, may influence the outcomes of disaster events affecting an individual or a community.Aim:To investigate how the social determinants of health inform community perceptions of disaster risk.Methods:Community perception of disaster risk in reference to the social determinants of health was assessed in this study. Individual interviews with participants from a community were conducted, all of whom were permanent community residents. Thematic analysis was conducted using narrative inquiry to gather firsthand insights on their perceptions of how characteristics of population health relate to and impact an individual’s disaster risk.Results:Analysis demonstrated commonality between interviewees in perceptions of the influence of the social determinants of health on individual disaster risk by determinant type. Interviewees sensed a strong correlation between low community connection and disaster risk vulnerability. Specific populations thought to have low community connection were perceived to be socially isolated, resulting in low knowledge or awareness of the surrounding disaster risks, or how to prepare and respond to disasters. In addition, they had reduced access to communication and support in time of need.Discussion:The importance of a strong social community connection was a feature of this research. Further research on how health determinants can enable disaster risk awareness and disaster risk communication is warranted.


2022 ◽  
Vol 21 (1) ◽  
pp. 179-202
Author(s):  
Mariel Heredia ◽  
Esther Carlota Gallegos Cabriales

Objective: Describe the relationship between social determinants of health and risk of type 2 diabetes mellitus in Mexican population.Methods: This was a cross-sectional descriptive correlational study of a sample of 256 individuals from a rural community in Sinaloa, Mexico. Data collection was carried out from October 2020 to February 2021. A snowball non-probability sampling method was used. The Instruments used were the International Physical Activity Questionnaire (IPAQ), short version, the IPAQ-A for adults, the IPAQ-C for children, and a sociodemographic, anthropometric, and clinical data sheet.Results: The most frequent risk indicators for T2DM for adults are hypertension (81.7%) and overweight/obesity (68.6%); in children, it was overweight/obesity (34.9%). The risk of T2DM increased according to age (r = .560, p < .01) but decreased as education level increased (r = −.127, p < .05)Conclusions: The approach to T2DM risk factors from the perspective of social determinants of health allows strategic healthcare planning that considers the contextual factors associated with a lifestyle that reinforces the actions of healthcare providers. Objetivo: Describir la relación de los determinantes sociales de salud con el riesgo de DMT2 en población mexicana.Métodos: Estudio descriptivo correlacional transversal, con una muestra de 256 individuos de una comunidad rural de Sinaloa, México. La recolección de datos se realizó durante octubre de 2020 y febrero de 2021. El muestreo fue no probabilístico por bola de nieve. Los instrumentos utilizados fueron el cuestionario internacional de actividad física (IPAQ) versión corta, IPAQ-A, IPAQ-C y una hoja de registro datos sociodemográficos, antropométricos y clínicos.Resultados: Los indicadores de riesgo de DMT2 con mayor frecuencia para adultos fue padecer hipertensión arterial (81.7%) y SP/OB (68.6%) y para menores de edad fue tener SP/OB (34.9%). Resultó que el riesgo de DMT2 se acrecentaba según lo hacía la edad (r = .560, p < .01) pero disminuía al aumentar la escolaridad de las personas (r = -.127, p < .05).Conclusiones: El abordaje de factores de riesgo de DMT2 bajo la perspectiva de los DSS brinda la oportunidad de plantear estrategias de salud que contemplen factores contextuales simultáneos al estilo de vida que refuercen las acciones del personal de salud para contribuir a la reducción de los índices de morbimortalidad causados por la DMT2.


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.


2019 ◽  
Author(s):  
Yunning Liu ◽  
Thomas Astell-Burt ◽  
Xiaoqi Feng ◽  
Fan Mao ◽  
Ruiming Liang ◽  
...  

Abstract Background: The aim of this study was to enhance capability in research on social determinants of health in China by linking and analyzing routinely-collected death records over 5 years with national population health surveillance.Methods: Linkage of 98 058 participants in the 2010 China Chronic Disease and Risk Factor Surveillance (CCDRFS) to records in the national death surveillance data from 2011 to 2015 was conducted through a matching program involving identification numbers, name, gender and residential address, followed by a structured checking process. Multilevel regressions were used to investigate five-year odds of all-cause, non-communicable disease (NCD), infectious disease and injury mortality in relation to person- and county-level factors.Results: A total of 3,365 deaths were observed in the linked mortality and population health surveillance. Cross-checks and comparisons with national mortality distributions provided assurance that the linkage was reasonable. Geographic variation in mortality was observed via age and gender adjusted median odds ratios for all-cause mortality (>1.30), infectious disease (>2.01), NCD (>1.24) and injury (>1.12). Increased odds of all-cause and all three cause-specific mortality outcomes were higher with age and among men. Low educational attainment was a predictor of all-cause, NCD and injury mortality. Longer mean years of education at the county-level was only associated with lower injury mortality. Divorcees had a higher odd of all-cause and NCD mortality than singletons. Rurality was a predictor of all-cause and NCD mortality.Conclusion: The results of this study provide utility for future investigations of social determinants of health and mortality using linked data in China.


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