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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
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    References listed on IDEAS

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    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.
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