IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v20y2023i19p6836-d1248310.html
   My bibliography  Save this article

Advancing the Management of Long COVID by Integrating into Health Informatics Domain: Current and Future Perspectives

Author

Listed:
  • Radha Ambalavanan

    (The Self Research Institute, Broken Arrow, OK 74011, USA)

  • R Sterling Snead

    (The Self Research Institute, Broken Arrow, OK 74011, USA)

  • Julia Marczika

    (The Self Research Institute, Broken Arrow, OK 74011, USA)

  • Karina Kozinsky

    (The Self Research Institute, Broken Arrow, OK 74011, USA)

  • Edris Aman

    (The Self Research Institute, Broken Arrow, OK 74011, USA)

Abstract

The ongoing COVID-19 pandemic has profoundly affected millions of lives globally, with some individuals experiencing persistent symptoms even after recovering. Understanding and managing the long-term sequelae of COVID-19 is crucial for research, prevention, and control. To effectively monitor the health of those affected, maintaining up-to-date health records is essential, and digital health informatics apps for surveillance play a pivotal role. In this review, we overview the existing literature on identifying and characterizing long COVID manifestations through hierarchical classification based on Human Phenotype Ontology (HPO). We outline the aspects of the National COVID Cohort Collaborative (N3C) and Researching COVID to Enhance Recovery (RECOVER) initiative in artificial intelligence (AI) to identify long COVID. Through knowledge exploration, we present a concept map of clinical pathways for long COVID, which offers insights into the data required and explores innovative frameworks for health informatics apps for tackling the long-term effects of COVID-19. This study achieves two main objectives by comprehensively reviewing long COVID identification and characterization techniques, making it the first paper to explore incorporating long COVID as a variable risk factor within a digital health informatics application. By achieving these objectives, it provides valuable insights on long COVID’s challenges and impact on public health.

Suggested Citation

  • Radha Ambalavanan & R Sterling Snead & Julia Marczika & Karina Kozinsky & Edris Aman, 2023. "Advancing the Management of Long COVID by Integrating into Health Informatics Domain: Current and Future Perspectives," IJERPH, MDPI, vol. 20(19), pages 1-21, September.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:19:p:6836-:d:1248310
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/20/19/6836/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/20/19/6836/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Stefania Fugazzaro & Angela Contri & Otmen Esseroukh & Shaniko Kaleci & Stefania Croci & Marco Massari & Nicola Cosimo Facciolongo & Giulia Besutti & Mauro Iori & Carlo Salvarani & Stefania Costi, 2022. "Rehabilitation Interventions for Post-Acute COVID-19 Syndrome: A Systematic Review," IJERPH, MDPI, vol. 19(9), pages 1-24, April.
    2. Nicole H. Goldhaber & Jordan N. Kohn & William Scott Ogan & Amy Sitapati & Christopher A. Longhurst & Angela Wang & Susan Lee & Suzi Hong & Lucy E. Horton, 2022. "Deep Dive into the Long Haul: Analysis of Symptom Clusters and Risk Factors for Post-Acute Sequelae of COVID-19 to Inform Clinical Care," IJERPH, MDPI, vol. 19(24), pages 1-13, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Durita Viderø Gunnarsson & Kamilla Woznica Miskowiak & Johanna Kølle Pedersen & Henrik Hansen & Daria Podlekareva & Stine Johnsen & Christian Have Dall, 2023. "Physical Function and Association with Cognitive Function in Patients in a Post-COVID-19 Clinic—A Cross-Sectional Study," IJERPH, MDPI, vol. 20(10), pages 1-16, May.
    2. Olivier Van Hove & Alexis Gillet & Jérôme Tack & Gregory Reychler & Magda Guatteri & Asuncion Ballarin & Justine Thomas & Rolando Espinoza & Frédéric Bonnier & Michelle Norrenberg & Pauline Daniel & M, 2022. "Development of a Medium Care Unit Using an Inexperienced Respiratory Staff: Lessons Learned during the COVID-19 Pandemic," IJERPH, MDPI, vol. 19(12), pages 1-13, June.
    3. Janet L. Larson & Weijiao Zhou & Philip T. Veliz & Sheree Smith, 2023. "Symptom Clusters in Adults with Post-COVID-19: A Cross-Sectional Survey," Clinical Nursing Research, , vol. 32(8), pages 1071-1080, November.
    4. Sarah Houben & Bruno Bonnechère, 2022. "The Impact of COVID-19 Infection on Cognitive Function and the Implication for Rehabilitation: A Systematic Review and Meta-Analysis," IJERPH, MDPI, vol. 19(13), pages 1-21, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:20:y:2023:i:19:p:6836-:d:1248310. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.