healthcare technology

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.

access the study at https://publichealth.jmir.org/2021/6/e28269/

As Web-based social media are growing in popularity, the number of people who share their experiences or ask for support in health-related social media has also increased. A study found that 41% of e-patients have read someone else’s commentary or experience about health on a Web-based news group, website, or blog.

Another study reported that more than 60 million Americans read or contribute to Health 2.0 apps, in which they consider these apps as their first source when gathering data and opinions. About 40% of Americans doubt a professional opinion when it conflicted with what they form from Web-based health social media.

One of the key benefits of health-related Web-based social media reported by researchers is the increased access to information to various demographic groups, regardless of age, education, income, or location. However, previous work has mainly relied on user surveys to study the effect of the use of social media to health-related factors such as psychological distress. In addition, previous work does not reveal granular information on what disorders or other health topics are mostly discussed in the Internet by each demographic group, which would allow health care providers to create targeted and effective educational campaigns.

In this work, we conducted the first, to our best knowledge, large-scale data-driven comparative analysis of the content of health-related social media across various demographic dimensions—gender, age, ethnicity, location, and writing level. For each demographic group, we study the content of the posts across the following dimensions: sentiment, popular terms (keywords), and medical concepts (particularly disorders and drugs). Concepts refer to entries in the Unified Medical Language System (UMLS) vocabulary, whereas terms are just words from the posts’ text that may or may not belong to any UMLS concept.

We report results for 3 types of social media:

(1) general Web-Based Social Networks, namely Google+ and Twitter,

(2) drug review websites, and

(3) health Web forums.

The selection of social media types was based on their popularity and on our study of the literature on health-related social content.

The objective of this study was to identify which health topics are discussed in which social media by which demographic groups, to better guide educational outreach and research activities.

read the whole study at http://www.jmir.org/2016/6/e148/

eHealth literacy was conceptualized in 2006 as the ability of internet users to locate, evaluate, and act upon web-based health information.

Now, advances in eHealth technology have cultivated transactional opportunities for patients to access, share, and monitor health information. However, empirical evidence shows that existing models and measures of eHealth literacy have limited theoretical underpinnings that reflect the transactional capabilities of eHealth.

This paper describes a conceptual model based on the Transactional Model of Communication (TMC), in which eHealth literacy is described as an intrapersonal skillset hypothesized as being dynamic; reciprocal; and shaped by social, relational, and cultural contexts.

The objective of this study was to systematically examine eHealth literacy definitions, models, and measures to propose a refined conceptual and operational definition based on the TMC.

Systematic review evidence revealed incongruity between operational eHealth literacy included in definitions compared with literacies included within models and measures. Theoretical underpinnings of eHealth literacy also remain dismal.

Despite the transactional capabilities of eHealth, the role of “communication” in eHealth literacy remains underdeveloped and does not account for physical and cognitive processing abilities necessary for multiway transactions.

read the full study at https://www.jmir.org/2018/10/e10175/