scholarly journals An Urban Population Health Observatory System to Support COVID-19 Pandemic Preparedness, Response, and Management: Design and Development Study (Preprint)

2021 ◽  
Author(s):  
Whitney S Brakefield ◽  
Nariman Ammar ◽  
Olufunto A Olusanya ◽  
Arash Shaban-Nejad
Keyword(s):  
Public Health ◽  
Social Determinants Of Health ◽  
Population Health ◽  
Social Determinants ◽  
Urban Population ◽  
Data Science ◽  
Determinants Of Health ◽  
Case Scenario ◽  
Effective Interventions ◽  
Novel Approach

BACKGROUND COVID-19 is impacting people worldwide and is currently a leading cause of death in many countries. Underlying factors, including Social Determinants of Health (SDoH), could contribute to these statistics. Our prior work has explored associations between SDoH and several adverse health outcomes (eg, asthma and obesity). Our findings reinforce the emerging consensus that SDoH factors should be considered when implementing intelligent public health surveillance solutions to inform public health policies and interventions. OBJECTIVE This study sought to redefine the Healthy People 2030’s SDoH taxonomy to accommodate the COVID-19 pandemic. Furthermore, we aim to provide a blueprint and implement a prototype for the Urban Population Health Observatory (UPHO), a web-based platform that integrates classified group-level SDoH indicators to individual- and aggregate-level population health data. METHODS The process of building the UPHO involves collecting and integrating data from several sources, classifying the collected data into drivers and outcomes, incorporating data science techniques for calculating measurable indicators from the raw variables, and studying the extent to which interventions are identified or developed to mitigate drivers that lead to the undesired outcomes. RESULTS We generated and classified the indicators of social determinants of health, which are linked to COVID-19. To display the functionalities of the UPHO platform, we presented a prototype design to demonstrate its features. We provided a use case scenario for 4 different users. CONCLUSIONS UPHO serves as an apparatus for implementing effective interventions and can be adopted as a global platform for chronic and infectious diseases. The UPHO surveillance platform provides a novel approach and novel insights into immediate and long-term health policy responses to the COVID-19 pandemic and other future public health crises. The UPHO assists public health organizations and policymakers in their efforts in reducing health disparities, achieving health equity, and improving urban population health.

scholarly journals Social determinants of health in the Big Data mode of population health risk calculation

2021 ◽  
Vol 8 (2) ◽  
pp. 205395172110628
Author(s):  
Rachel Rowe
Keyword(s):  
Public Health ◽  
Big Data ◽  
Social Determinants Of Health ◽  
Population Health ◽  
Social Determinants ◽  
Determinants Of Health ◽  
Individual Risk ◽  
Risk Calculation ◽  
Health And Illness ◽  
The Usa

Amidst the climate of crisis surrounding the rise in opioid-related overdose in the USA, early in 2019, Google and Deloitte launched ‘Opioid360’. Here came a platform combining browser histories, credit, insurance, social media, and traditional survey data to sell the service of risk calculation in population health. Opioid360's approach to automating risk calculation not only promised to identify persons ‘at risk’ of opioid dependence, but also paved the way for broader applications anticipating common chronic diseases and coordinating logistical operations involved in pandemic response. Beginning with this experimental platform, this paper develops an analysis of the Big Data mode of risk calculation - an epistemological and political shift that involves technology companies, investors, insurers, governments, and public health institutions. The analysis focuses on the re-emergence of ‘social determinants of health’ (SDOH) in the rhetoric accompanying novel analytic platforms that estimate, calculate, and compute individual health risks. While the treatment of SDOH has always been a site of political contestation within the discipline of public health, powerful interests are crystallising around the concept and instrumentalising it in platforms that sell algorithmic prediction. Silicon Valley's breed of asset-oriented technoscience appears not only to be amplifying the behaviouralist elements of public health. Among the stakes of the Big Data mode is the paradoxical retreat from changing social conditions that contribute to the prevalence of health and illness in populations; and instead, the promotion of an apparatus for pricing and exchanging individual risk or excluding from services those who bear risk most acutely.

scholarly journals Public and Population Health Informatics: The Bridging of Big Data to Benefit Communities

2018 ◽  
Vol 27 (01) ◽  
pp. 199-206 ◽  
Author(s):  
Roland Gamache ◽  
Hadi Kharrazi ◽  
Jonathan Weiner
Keyword(s):  
Public Health ◽  
Big Data ◽  
Social Determinants Of Health ◽  
Population Health ◽  
Social Determinants ◽  
Information Exchange ◽  
Health Informatics ◽  
Determinants Of Health ◽  
Geographical Information ◽  
Care Providers

Objective: To summarize the recent public and population health informatics literature with a focus on the synergistic “bridging” of electronic data to benefit communities and other populations. Methods: The review was primarily driven by a search of the literature from July 1, 2016 to September 30, 2017. The search included articles indexed in PubMed using subject headings with (MeSH) keywords “public health informatics” and “social determinants of health”. The “social determinants of health” search was refined to include articles that contained the keywords “public health”, “population health” or “surveillance”. Results: Several categories were observed in the review focusing on public health's socio-technical infrastructure: evaluation of surveillance practices, surveillance methods, interoperable health information infrastructure, mobile health, social media, and population health. Common trends discussing socio-technical infrastructure included big data platforms, social determinants of health, geographical information systems, novel data sources, and new visualization techniques. A common thread connected these categories of workforce, governance, and sustainability: using clinical resources and data to bridge public and population health. Conclusions: Both medical care providers and public health agencies are increasingly using informatics and big data tools to create and share digital information. The intent of this “bridging” is to proactively identify, monitor, and improve a range of medical, environmental, and social factors relevant to the health of communities. These efforts show a significant growth in a range of population health-centric information exchange and analytics activities.

scholarly journals Integrating Social Determinants of Health to Precision Medicine through Digital Transformation: An Exploratory Roadmap

2021 ◽  
Vol 18 (9) ◽  
pp. 5018
Author(s):  
Ik-Whan G. Kwon ◽  
Sung-Ho Kim ◽  
David Martin
Keyword(s):  
Precision Medicine ◽  
Social Determinants Of Health ◽  
Population Health ◽  
Social Determinants ◽  
Information Technologies ◽  
Healthcare Delivery ◽  
Healthcare Providers ◽  
Determinants Of Health ◽  
Collaborative Tools ◽  
High Level

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.

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 ◽  
...  
Keyword(s):  
Mental Health ◽  
Diabetes Mellitus ◽  
Social Determinants Of Health ◽  
Population Health ◽  
Social Determinants ◽  
Determinants Of Health ◽  
Hospital Charges ◽  
Burn Patients ◽  
Increased Risk ◽  
History Of

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.

scholarly journals Public Health capacities for action on the social determinants of health in Europe

2013 ◽  
Vol 23 (suppl_1) ◽  
Author(s):  
S van den Broucke ◽  
C Aluttis ◽  
K Michelsen ◽  
H Brand ◽  
C Chiotan ◽  
...  
Keyword(s):  
Public Health ◽  
Social Determinants Of Health ◽  
Social Determinants ◽  
Determinants Of Health ◽  
The Social

A public health model of the social determinants of health

2003 ◽  
Vol 48 (4) ◽  
pp. 242-251 ◽  
Author(s):  
Zahid Ansari ◽  
Norman J. Carson ◽  
Michael J. Ackland ◽  
Loretta Vaughan ◽  
Adrian Serraglio
Keyword(s):  
Public Health ◽  
Social Determinants Of Health ◽  
Social Determinants ◽  
Determinants Of Health ◽  
Public Health Model ◽  
The Social ◽  
Health Model

scholarly journals Aiming for Health Equity: The role of Public Health Policy and Primary Healthcare Comment on "Universal Health Coverage for Non-Communicable Diseases and Health Equity: Lessons From Australian Primary Healthcare"

2021 ◽  
Author(s):  
Bo Burström
Keyword(s):  
Public Health ◽  
Social Determinants Of Health ◽  
Healthcare System ◽  
Health Equity ◽  
Social Determinants ◽  
Primary Healthcare ◽  
Communicable Diseases ◽  
Determinants Of Health ◽  
Non Communicable Diseases

This commentary refers to the article by Fisher et al on lessons from Australian primary healthcare (PHC), which highlights the role of PHC to reduce non-communicable diseases (NCDs) and promote health equity. This commentary discusses important elements and features when aiming for health equity, including going beyond the healthcare system and focusing on the social determinants of health in public health policies, in PHC and in the healthcare system as a whole, to reduce NCDs. A wider biopsychosocial view on health is needed, recognizing the importance of social determinants of health, and inequalities in health. Public funding and universal access to care are important prerequisites, but regulation is needed to ensure equitable access in practice. An example of a PHC reform in Sweden indicates that introducing market solutions in a publicly funded PHC system may not benefit those with greater needs and may reduce the impact of PHC on population health.

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