Era Of Digital Health Research Articles

Opinion leader empowered patients about the era of digital health: a qualitative study

ObjectivesWe aimed to explore the opinion leader empowered patients’ relationship with their medical professionals, their experiences and beliefs about technologies, and how they see the future. We also attempted to...

Bridging the Global Digital Health Divide for Cardiovascular Disease.

Big data approaches have been lauded as game changers in health care. Exponential growth of telecommunications and mobile phone ownership have presented new possibilities for digital health (use of data to drive health care), e-health (use of electronic processes in health care), and m-health (use of mobile technologies in health care). From machine learning and natural language processing to genomics and metabolomics, advanced analytics are being developed to improve health outcomes. Health inequalities are well documented within and across countries, and the role of social determinants is increasingly recognized as an important factor driving these differences. Could digital technologies and their associated healthcare strategies improve these health inequalities by making information and expertise more scalable and widely available? Or will they perpetuate or even worsen these widespread differences? Cardiovascular diseases (CVD), the cause of greatest morbidity and mortality worldwide, are the ideal lens through which to explore these issues and the future of global health in the era of digital health. According to the GBD study (Global Burden of Disease),1 which celebrated its 20th anniversary in October, CVD disproportionately affects low- and middle-income countries (LMICs), but technologies are widely transforming societal trends across many LMICs. In this article, the potential associations between digital health and inequalities in CVD are reviewed. There have been several calls for greater attention and action for the CVD epidemic, recognizing the disparities between countries and within countries at every stage of the patient journey. In terms of diagnosis, individuals from lower socioeconomic status and from LMICs have less access to screening programs and testing, whether laboratory, imaging, or interventional-based. Preventive strategies, from lifestyle to medical interventions, are less likely to be implemented in these settings. Evidence-based treatment, including drugs and invasive therapies such as surgery, are less widely available and less likely to be …

Behavioral health workforce development challenges in the digital health era.

This column describes challenges for hiring, training, and supervising psychiatric rehabilitation service providers for positions that involve the use of digital health technology. Adoption and implementation of any new technology or technique requires workforce development. This article outlines considerations for policymakers, funders, and service agency administrators as digital health technologies become more widespread. The article discusses issues based on professional experience of the authors and available literature. The literature on adoption of innovations in general, and the adoption of psychiatric evidence-based practices in particular, indicates that funding and adoption of new techniques and technologies are not adequate to ensure full and sustained implementation. The use of any new treatment or technology requires training and other supports to ensure that users have the competencies needed to make it work and that the workplace supports its use. As new digital health technologies become available, considerations of their cost and effectiveness need to include an examination of the required competencies of the service providers who will use them and the added cost of developing, enhancing, and maintaining those competencies. Specific attitudes, knowledge, and skills will be relevant to hiring decisions. Relevant preservice and on-the-job training opportunities, technical assistance, and supervision will be needed. Implementation needs to be monitored, not assumed, and the rights of the people who use technology-supported services must be fully protected. (PsycINFO Database Record

Hemodynamic monitoring in the era of digital health.

Digital innovations are changing medicine, and hemodynamic monitoring will not be an exception. Five to ten years from now, we can envision a world where clinicians will learn hemodynamics with simulators and serious games, will monitor patients with wearable or implantable sensors in the hospital and after discharge, will use medical devices able to communicate and integrate the historical, clinical, physiologic and biological information necessary to predict adverse events, propose the most rationale therapy and ensure it is delivered properly. Considerable intellectual and financial investments are currently made to ensure some of these new ideas and products soon become a reality.

A Tap on the Shoulder: The Disciplinary Techniques and Logics of Anti-Pokie Apps

A Tap on the Shoulder: The Disciplinary Techniques and Logics of Anti-Pokie Apps

The digitally engaged patient: Self-monitoring and self-care in the digital health era

The phenomenon of digital health has emerged as a key dimension of contemporary healthcare policy and delivery in many countries. This review article focuses on one aspect of digital health discourses: the concept of patient engagement that encourages patients to take up the new digital media technologies to engage in self-monitoring and self-care, or what I term ‘the digitally engaged patient’. A critical approach is adopted to examine the sociocultural dimensions of eliciting patients to become ‘digitally engaged’ in their own medical care and preventive health efforts. It is argued that the techno-utopian discourses articulated in the mainstream healthcare policy literature concerning the possibilities and potentialities afforded by digital health technologies do not acknowledge the complexities and ambivalences that are part of using self-monitoring and self-care technologies for monitoring health and illness states, both for patients and for healthcare providers. These include the surveillance and disciplinary dimensions of using these technologies, the emotions and resistances they provoke, their contribution to the burden of self-care and the invisible work on the part of healthcare workers that they require to operate.