Advances in Artificial Intelligence for Disease Management and Clinical Documentation Improvement

A special issue of Healthcare (ISSN 2227-9032).

Deadline for manuscript submissions: closed (31 December 2025) | Viewed by 7607

Special Issue Editors


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Guest Editor
Department of Health Management and Informatics, University of Central Florida, Orlando, FL, USA
Interests: health informatics; decision support systems; data semantics
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Health Management and Informatics, University of Central Florida, Orlando, FL 32816, USA
Interests: healthcare delivery; healthcare systems; digital health; health informatics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to invite you to contribute to this Special Issue entitled “Advances in Artificial Intelligence for Disease Management and Clinical Documentation Improvement”. This Special Issue focuses on digital health and informatics, leadership and governance, health policy, quality and patient safety, healthcare delivery and access to healthcare, healthcare financing and economics, organizational and cultural change, and the management of health resources. It provides a peer-reviewed forum for the publication of briefings, discussions, applied research, case studies and systematic reviews, expert comments, and empirical analyses regarding applied healthcare research and AI-based applications.

This Special Issue aims to provide healthcare leaders with scientific and evidence-based information to facilitate the development, implementation, and evaluation of complex healthcare interventions in order to enhance the efficiency and effectiveness of healthcare management and policy strategies.

In this Special Issue, original research articles and reviews are welcome. The scope of this Special Issue includes, but is not limited to, the following topics:

  1. E-health, digital health, telemedicine and health informatics;
  2. Clinical and administrative decision support system design and evaluation;
  • Cost-effective and efficient delivery of health services;
  1. Healthcare systems development and reforms;
  2. Healthcare behavioral change and adherence ;
  3. Disease management;
  • Utilization management.

We look forward to receiving your contributions.

Dr. Varadraj Gurupur
Dr. Thomas T. H. Wan
Guest Editors

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 250 words) can be sent to the Editorial Office for assessment.

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. Healthcare is an international peer-reviewed open access semimonthly 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 2700 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

  • e-health
  • digital health
  • healthcare delivery systems
  • clinical documentation improvement
  • disease management
  • health informatics

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Published Papers (1 paper)

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Research

29 pages, 3216 KB  
Article
Integrating Artificial Intelligence, Electronic Health Records, and Wearables for Predictive, Patient-Centered Decision Support in Healthcare
by Deepa Fernandes Prabhu, Varadraj Gurupur, Alexa Stone and Elizabeth Trader
Healthcare 2025, 13(21), 2753; https://doi.org/10.3390/healthcare13212753 - 30 Oct 2025
Cited by 17 | Viewed by 7120 | Correction
Abstract
This study explores how patients and stakeholders envision integrated digital health systems. Background/Objectives: Integrating artificial intelligence (AI), wearable data, electronic health records (EHRs), and patient-reported outcomes could enable proactive and personalized healthcare. However, current solutions remain fragmented and poorly aligned with user expectations. [...] Read more.
This study explores how patients and stakeholders envision integrated digital health systems. Background/Objectives: Integrating artificial intelligence (AI), wearable data, electronic health records (EHRs), and patient-reported outcomes could enable proactive and personalized healthcare. However, current solutions remain fragmented and poorly aligned with user expectations. This study aimed to explore patient and stakeholder needs for AI-driven integration and propose a conceptual framework to inform future system design. Methods: As part of the NSF Innovation Corps (I-Corps) program, we conducted semi-structured interviews with 44 participants representing Health Enthusiasts, Chronic Condition Managers, and Low-Engagement Users. Interviews followed the I-Corps customer discovery framework and were thematically analyzed using a hybrid deductive–inductive approach. Results: Participants highlighted four priorities: (i) interoperability and unification of data from wearables, EHRs, and self-reports; (ii) actionable personalization with predictive insights; (iii) trust and transparency in AI recommendations, often requiring clinician oversight; and (iv) usability through low-friction, intuitive interfaces. Age- and persona-specific differences emerged: younger participants favoring predictive features and older participants emphasizing safety, reassurance, and clinical integration. Conclusions: This exploratory qualitative study identified stakeholder needs that informed a conceptual framework for integrated digital health platforms. While preliminary, the framework provides a blueprint for future technical development and validation of patient- and provider-centered systems. Full article
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