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Exploring a Large Language Model-Based Chatbot Use in Data Analysis: A Case Study of the Problems Related to the Do

Kaija Saranto1, Eija Kivekäs2, Hanna Kuusisto1,3

  • 1University of Eastern Finland.

Studies in Health Technology and Informatics
|May 23, 2026
PubMed
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This study explored how artificial intelligence (AI) impacts healthcare professionals

Area of Science:

  • Medical Ethics
  • Artificial Intelligence in Healthcare
  • Clinical Decision-Making

Background:

  • Healthcare professionals (HCPs) navigate complex ethical decisions in critical medical contexts.
  • The integration of artificial intelligence (AI), specifically large language models (LLMs), presents new dynamics in trust and authority.
  • Understanding these dynamics is crucial for ethically sensitive clinical decision-making (DM).

Purpose of the Study:

  • To explore and test the integration of Microsoft Copilot® LLM chatbot into ethically sensitive clinical decision-making (DM).
  • To identify challenges faced by HCPs in do-not-attempt-resuscitation (DNAR) order-making.
  • To pinpoint key areas for development in AI-assisted medical DM.

Main Methods:

  • Qualitative content analysis of 100 healthcare professionals' (HCPs) views.
Keywords:
Artificial IntelligenceData analysisDecision makingDo not attempt resuscitation (DNAR) Orders

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  • Utilized an interpretative framework to analyze AI, HCPs, and researchers' construction of meaning, trust, and authority.
  • AI-driven thematic analysis identified 15 categories related to DNAR protocols and DM.

    • Main Results:

    • AI identified key themes in DNAR order-making, particularly regarding patient/family roles and practical issues.
    • AI's interpretations showed higher frequency in practical and patient-centered categories compared to researchers.
    • Researchers' analysis emphasized communication and documentation in DNAR decision-making.

    Conclusions:

    • AI, like Microsoft Copilot®, can identify critical issues in DNAR decision-making processes.
    • AI's role in interpreting ethical medical contexts requires further exploration regarding trust and authority.
    • Future developments should focus on AI's practical application and communication support for HCPs in sensitive DM.