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Khatiwada, Pankaj ; Yang, Bian ; Lin, Jia-Chun ; Blobel, Bernd

Patient-Generated Health Data (PGHD): Understanding, Requirements, Challenges, and Existing Techniques for Data Security and Privacy

Khatiwada, Pankaj, Yang, Bian, Lin, Jia-Chun und Blobel, Bernd (2024) Patient-Generated Health Data (PGHD): Understanding, Requirements, Challenges, and Existing Techniques for Data Security and Privacy. Journal of Personalized Medicine 14 (3), S. 282.

Veröffentlichungsdatum dieses Volltextes: 07 Jan 2025 09:59
Artikel
DOI zum Zitieren dieses Dokuments: 10.5283/epub.74577


Zusammenfassung

The evolution of Patient-Generated Health Data (PGHD) represents a major shift in healthcare, fueled by technological progress. The advent of PGHD, with technologies such as wearable devices and home monitoring systems, extends data collection beyond clinical environments, enabling continuous monitoring and patient engagement in their health management. Despite the growing prevalence of PGHD, ...

The evolution of Patient-Generated Health Data (PGHD) represents a major shift in healthcare, fueled by technological progress. The advent of PGHD, with technologies such as wearable devices and home monitoring systems, extends data collection beyond clinical environments, enabling continuous monitoring and patient engagement in their health management. Despite the growing prevalence of PGHD, there is a lack of clear understanding among stakeholders about its meaning, along with concerns about data security, privacy, and accuracy. This article aims to thoroughly review and clarify PGHD by examining its origins, types, technological foundations, and the challenges it faces, especially in terms of privacy and security regulations. The review emphasizes the role of PGHD in transforming healthcare through patient-centric approaches, their understanding, and personalized care, while also exploring emerging technologies and addressing data privacy and security issues, offering a comprehensive perspective on the current state and future directions of PGHD. The methodology employed for this review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and Rayyan, AI-Powered Tool for Systematic Literature Reviews. This approach ensures a systematic and comprehensive coverage of the available literature on PGHD, focusing on the various aspects outlined in the objective. The review encompassed 36 peer-reviewed articles from various esteemed publishers and databases, reflecting a diverse range of methodologies, including interviews, regular articles, review articles, and empirical studies to address three RQs exploratory, impact assessment, and solution-oriented questions related to PGHD. Additionally, to address the future-oriented fourth RQ for PGHD not covered in the above review, we have incorporated existing domain knowledge articles. This inclusion aims to provide answers encompassing both basic and advanced security measures for PGHD, thereby enhancing the depth and scope of our analysis.



Beteiligte Einrichtungen


Details

DokumentenartArtikel
Titel eines Journals oder einer ZeitschriftJournal of Personalized Medicine
Verlag:MDPI
Band:14
Nummer des Zeitschriftenheftes oder des Kapitels:3
Seitenbereich:S. 282
Datum3 März 2024
InstitutionenMedizin > Zentren des Universitätsklinikums Regensburg > EHealth Competence Center
Identifikationsnummer
WertTyp
10.3390/jpm14030282DOI
Stichwörter / KeywordsPGHD; health data; security; privacy; patient-generated health data
Dewey-Dezimal-Klassifikation000 Informatik, Informationswissenschaft, allgemeine Werke > 004 Informatik
600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin
StatusVeröffentlicht
BegutachtetJa, diese Version wurde begutachtet
An der Universität Regensburg entstandenJa
URN der UB Regensburgurn:nbn:de:bvb:355-epub-745771
Dokumenten-ID74577

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