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Mobile Health and Big Data in Cardiovascular Disease Management: Focused on Prevention, Cardiac Rehabilitation, and Education

Call for Papers

Mobile health has been defined as medical and public health practice supported by mobile devices, such as mobile phones, patient monitoring devices, and personal digital assistants. Cardiovascular mobile health includes simple strategies, such as the use of short message service (SMS) or text messages in successful short-term smoking cessation, weight loss, and diabetes management programs for reducing multiple cardiovascular risk factors. Mobile health can also involve more complex strategies, such as smartphone applications (apps), global positioning system (GPS), and Bluetooth technologies. More recently, the use of sensors to monitor and provide feedback to patients and healthcare providers has been explored. With almost two billion people currently owning smartphones and 50% of adults (globally) predicted to own one by 2018, mobile health provides the prospect of delivering efficient, affordable healthcare services to widespread populations both locally and globally. In particular, it has the potential to reduce socioeconomic disparity and alleviate the burden of cardiovascular disease. In addition, according to a report, 90 percent of the data in the world today were created in the past two years. This statistic is not surprising given the explosion of mobile phones and other devices that generate data, the Internet of Things (e.g., smart refrigerators), and metadata (data about data). Big Data analytics in healthcare is evolving into a promising field for providing insight from very large datasets and improving outcomes while reducing costs. In practice, the electronic health records, free open data, and the “quantified self” offer new perspectives for data analytics. Regarding analytics, significant advances have been made in information extraction from text data, which unlocks a lot of data from clinical documentation for analytic purposes. At the same time, medicine and healthcare are lagging behind in the adoption of Big Data approaches. This can be traced to particular problems regarding data complexity and organizational, legal, and ethical challenges.

There is now a need to rethink traditional health service structures and bioengineering capacity, to ensure mobile health systems are also safe, secure, and robust. The potential for Big Data analytics to improve cardiovascular quality of care and patient outcomes is tremendous. However, the application of Big Data in healthcare is at a nascent stage, and the evidence to date demonstrating that Big Data analytics will improve care and outcomes is scant.

This special issue is intended to present and discuss mobile healthcare in the management of cardiovascular diseases. This topic will focus on what can be done now (across regions with different network resources and local regulations to handle individual patient data), what should be done in the future, how the data can be handled in each country or region, and so forth.

Potential topics include but are not limited to the following:

  • Mobile healthcare in primary prevention such as exercise, nutrition, and stress management
  • Mobile healthcare in hypertension, diabetes, and dyslipidemia management
  • Mobile healthcare in cardiac rehabilitation
  • Mobile healthcare in patient education
  • Mobile medicine across regions which as different network resources, local regulations to handle individual patient data, etc

Authors can submit their manuscripts through the Manuscript Tracking System at https://mts.hindawi.com/submit/journals/bmri/cardiology/mhbd/.

Submission DeadlineFriday, 31 August 2018
Publication DateJanuary 2019

Papers are published upon acceptance, regardless of the Special Issue publication date.

Lead Guest Editor

  • Kyoung I. Cho, Kosin University School of Medicine, Busan, Republic of Korea

Guest Editors

  • Patrick Then, Swinburne University of Technology Sarawak Campus, Sarawak, Malaysia
  • Alan Fong, Sarawak Heart Centre, Sarawak, Malaysia
  • Jung J. Park, Pusan National University, Busan, Republic of Korea