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Digital Health and the Learning Healthcare System
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Digital Health and the Learning Healthcare System

A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Digital Health".

Deadline for manuscript submissions: closed (25 August 2022) | Viewed by 4543

Special Issue Editor

Dr. Clair Sullivan

E-Mail Website
Guest Editor
Digital Health Research Network, Centre for Health Services Research, Faculty of Medicine, University of Queensland, Brisbane, QLD 4102, Australia
Interests: digital health; clinical informatics; data and analytics; translation of new technology into healthcare practice

Special Issue Information

Dear Colleagues,

The current methods of healthcare delivery are no longer sustainable. Global pandemics and an aging population are creating significant demands for new models of healthcare, and in order to evolve new models of care, a learning healthcare system is required. A learning healthcare system is a digitally connected network, where routinely collected data are re-invested and re-used to create new knowledge and drive iterative quality improvement. Digital health is the enabler for new models of healthcare delivery; however, little is known about how to develop a safe and effective digital learning healthcare system. This issue examines how digital health contributes to a learning healthcare system, particularly along three digital health horizons:

1. Digital foundations: How are effective digital health workflows established? How is effective digital transformation in healthcare achieved? How is digital disruption best managed?

2. Data and analytics: How is the data cycle managed effectively in healthcare? How can data be leveraged for acute care, public health and healthcare promotion? How is the full spectrum of analytics (descriptive, predictive and prescriptive) deployed effectively to improve health?

3. Transforming healthcare: How can digital workflows and data and analytics be leveraged to create new models of care? Can we shift from traditional break–fix health care to predict–prevent? How do we evaluate and improve new models of care? How do healthcare providers and consumers navigate the change driven by new healthcare models?

Dr. Clair Sullivan
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Environmental Research and Public Health is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • digital health
  • clinical informatics
  • data and analytics
  • innovation
  • quality improvement
  • clinical redesign

Published Papers (2 papers)

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Research

16 pages, 1620 KiB  
Article
PREVIDE: A Qualitative Study to Develop a Decision-Making Framework (PREVention decIDE) for Noncommunicable Disease Prevention in Healthcare Organisations
by Oliver J. Canfell, Kamila Davidson, Clair Sullivan, Elizabeth E. Eakin and Andrew Burton-Jones
Int. J. Environ. Res. Public Health 2022, 19(22), 15285; https://doi.org/10.3390/ijerph192215285 - 18 Nov 2022
Viewed by 1707
Abstract
Noncommunicable diseases (NCDs), including obesity, remain a significant global public health challenge. Prevention and public health innovation are needed to effectively address NCDs; however, understanding of how healthcare organisations make prevention decisions is immature. This study aimed to (1) explore how healthcare organisations [...] Read more.
Noncommunicable diseases (NCDs), including obesity, remain a significant global public health challenge. Prevention and public health innovation are needed to effectively address NCDs; however, understanding of how healthcare organisations make prevention decisions is immature. This study aimed to (1) explore how healthcare organisations make decisions for NCD prevention in Queensland, Australia (2) develop a contemporary decision-making framework to guide NCD prevention in healthcare organisations. Cross-sectional and qualitative design, comprising individual semi-structured interviews. Participants (n = 14) were recruited from two organisations: the state public health care system (CareQ) and health promotion/disease prevention agency (PrevQ). Participants held executive, director/manager or project/clinical lead roles. Data were analysed in two phases (1) automated content analysis using machine learning (Leximancer v4.5) (2) researcher-led interpretation of the text analytics. Final themes were consolidated into a proposed decision-making framework (PREVIDE, PREvention decIDE) for NCD prevention in healthcare organisations. Decision-making was driven by four themes: Data, Evidence, Ethics and Health, i.e., data, its quality and the story it tells; traditional and non-traditional sources of evidence; ethical grounding in fairness and equity; and long-term value generated across multiple determinants of health. The strength of evidence was directly proportional to confidence in the ethics of a decision. PREVIDE can be adapted by public health practitioners and policymakers to guide real-world policy, practice and investment decisions for obesity prevention and with further validation, other NCDs and priority settings (e.g., healthcare). Full article
(This article belongs to the Special Issue Digital Health and the Learning Healthcare System)
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18 pages, 3576 KiB  
Article
Decentralized Patient-Centric Report and Medical Image Management System Based on Blockchain Technology and the Inter-Planetary File System
by Syed Agha Hassnain Mohsan, Abdul Razzaq, Shahbaz Ahmed Khan Ghayyur, Hend Khalid Alkahtani, Nouf Al-Kahtani and Samih M. Mostafa
Int. J. Environ. Res. Public Health 2022, 19(22), 14641; https://doi.org/10.3390/ijerph192214641 - 8 Nov 2022
Cited by 6 | Viewed by 2173
Abstract
Several academicians have been actively contributing to establishing a practical solution to storing and distributing medical images and test reports in the research domain of health care in recent years. Current procedures mainly rely on cloud-assisted centralized data centers, which raise maintenance expenditure, [...] Read more.
Several academicians have been actively contributing to establishing a practical solution to storing and distributing medical images and test reports in the research domain of health care in recent years. Current procedures mainly rely on cloud-assisted centralized data centers, which raise maintenance expenditure, necessitate a large amount of storage space, and raise privacy concerns when exchanging data across a network. As a result, it is critically essential to provide a framework that allows for the efficient exchange and storage of large amounts of medical data in a secure setting. In this research, we describe a unique proof-of-concept architecture for a distributed patient-centric test report and image management (PCRIM) system that aims to facilitate patient privacy and control without the need for a centralized infrastructure. We used an Ethereum blockchain and a distributed file system technology called the Inter-Planetary File System in this system (IPFS). Then, to secure a distributed and trustworthy access control policy, we designed an Ethereum smart contract termed the patient-centric access control protocol. The IPFS allows for the decentralized storage of medical metadata, such as images, with worldwide accessibility. We demonstrate how the PCRIM system design enables hospitals, patients, and image requestors to obtain patient-centric data in a distributed and secure manner. Finally, we tested the proposed framework in the Windows environment by deploying a smart contract prototype on an Ethereum TESTNET blockchain. The findings of the study indicate that the proposed strategy is both efficient and practicable. Full article
(This article belongs to the Special Issue Digital Health and the Learning Healthcare System)
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