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Advancing digital health in information systems research: Insights from a text mining analysis

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  • Silke Weissenfels

    (FernUniversität in Hagen, Fakultät Für Wirtschaftswissenschaft, Lehrstuhl Für Betriebswirtschaftslehre, Insb. Betriebliche Anwendungssysteme)

  • Anika Nissen

    (FernUniversität in Hagen, Fakultät Für Wirtschaftswissenschaft, Lehrstuhl Für Betriebswirtschaftslehre, Insb. Betriebliche Anwendungssysteme)

  • Stefan Smolnik

    (FernUniversität in Hagen, Fakultät Für Wirtschaftswissenschaft, Lehrstuhl Für Betriebswirtschaftslehre, Insb. Betriebliche Anwendungssysteme)

Abstract

The advancement and adoption of digital health technologies promise improved healthcare outcomes globally. However, numerous challenges hinder their widespread adoption. Existing IS research offers a plethora of works addressing these challenges, making it difficult to navigate the jungle of health IS research. Thus, we need a structured overview identifying the current knowledge state. Using a text mining approach, we analyze 484 papers from leading IS journals to synthesize health topics across digital health technologies. Our study uncovers key health topics and trends, traces their evolution over time, and identifies knowledge gaps within current IS literature. Our findings underscore the importance of emerging technologies and additional stakeholders in context-sensitive healthcare. We propose a research agenda to extend the scope of health-related IS research and suggest avenues for future exploration. We advocate for IS researchers to collaborate more closely with related fields to stay at the forefront of advancements.

Suggested Citation

  • Silke Weissenfels & Anika Nissen & Stefan Smolnik, 2025. "Advancing digital health in information systems research: Insights from a text mining analysis," Electronic Markets, Springer;IIM University of St. Gallen, vol. 35(1), pages 1-25, December.
    • Handle: RePEc:spr:elmark:v:35:y:2025:i:1:d:10.1007_s12525-025-00768-w
    DOI: 10.1007/s12525-025-00768-w
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    More about this item

    Keywords

    Health IT; E-health; Digital health; Text mining; Topic modeling;
    All these keywords.

    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General

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