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The Participant-Reported Implementation Update and Score PRIUS: A Novel Method for Capturing Implementation-Related Data Over Time

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Implementers Perspectives on the Routine Use of Artificial Intelligence in Health Services: A Qualitative Study Using

Anna Janssen¹, Kavisha Shah¹, Helena Teede^2,3

¹Faculty of Medicine and Health, The University of Sydney, NSW, Australia.

Health Services Insights

|December 2, 2025

Summary

Implementing Artificial Intelligence (AI) in Australian healthcare faces significant barriers. Key challenges include stakeholder engagement, data access, technical issues, resource constraints, and long implementation timelines, hindering widespread adoption.

Keywords:

artificial intelligence consolidated framework for implementation research digital health ehealth implementation

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Area of Science:

Health Informatics
Artificial Intelligence in Healthcare
Implementation Science

Background:

Growing interest in Artificial Intelligence (AI) for healthcare applications.
AI innovations face challenges in routine clinical practice implementation.
Understanding factors influencing AI implementation in Australian healthcare organizations is crucial.

Purpose of the Study:

To explore the factors influencing the implementation of AI innovations into routine practice.
To gain insights from the perspective of AI implementers in Australian healthcare.

Main Methods:

Qualitative methodology utilizing in-depth research interviews.
Participant identification through environmental scan and snowballing.
Data analysis using inductive coding and deductive categorization via the Consolidated Framework for Implementation Research (CFIR).

Main Results:

Eleven AI innovations and twelve implementers were studied in Australian healthcare.
Implementation factors spanned all five CFIR domains, with emphasis on innovation and implementation process.
Identified barriers include stakeholder engagement, data access, technical hurdles, resource constraints, and lengthy timelines.

Conclusions:

The adoption of Health AI solutions in Australian healthcare is limited compared to research and industry.
The complexity and length of the implementation process, along with identified barriers, contribute to this gap.
Addressing these barriers is essential for successful integration of AI into routine healthcare practice.