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ORIGINAL RESEARCH article

Front. Med.

Sec. Regulatory Science

Volume 12 - 2025 | doi: 10.3389/fmed.2025.1575195

From Data to Medical Context: The Power of Categorization in Healthcare

Provisionally accepted
  • 1Université du Québec à Chicoutimi, Chicoutimi, Canada
  • 2Université du Québec à Rimouski, Rimouski, Quebec, Canada
  • 3Lebanese University, Beirut, Lebanon

The final, formatted version of the article will be published soon.

In the rapidly evolving healthcare domain, the ability to structure and interpret contextual medical data is crucial for delivering personalized and efficient patient care. While many existing studies attempt to define medical context through diverse categorizations, they often lack completeness or applicability in the real-world healthcare domain. This paper introduces a novel and comprehensive context categorization model composed of fifteen well-defined categories, bridging the gap between theoretical models and practical requirements in telemonitoring systems for chronic disease management. By incorporating important but often overlooked components such as social determinants, Service Level Agreements (SLAs), and environmental factors our model enhances clarity and strengthens decision-making in clinical settings. We validate the applicability of this framework through detailed case studies on asthma, COPD, and cardiovascular diseases, demonstrating its utility in enhancing telehealth solutions and aiding early intervention strategies.In the rapidly evolving healthcare domain, the ability to structure and interpret contextual medical data is crucial for delivering personalized and efficient patient care. While many existing studies attempt to define medical context through diverse categorizations, they often lack completeness or applicability in the realworld healthcare domain. This paper introduces a novel and comprehensive context categorization model composed of fifteen well-defined categories, bridging the gap between theoretical models and practical requirements in telemonitoring systems for chronic disease management. By incorporating important but often overlooked components such as social determinants, Service Level Agreements (SLAs), and environmental factors our model enhances clarity and strengthens decision-making in clinical settings. We validate the applicability of this framework through detailed case studies on asthma, COPD, and cardiovascular diseases, demonstrating its utility in enhancing telehealth solutions and aiding early intervention strategies.

Keywords: Context categorization, context of healthcare domain, Telemedicine, Chronic Disease, Clinical support

Received: 12 Feb 2025; Accepted: 28 Apr 2025.

Copyright: © 2025 Msheik, Mcheick, Hariri, Adda and Dbouk. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Batoul Msheik, Université du Québec à Chicoutimi, Chicoutimi, Canada

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.