PerCenAI – Development of Artificial Intelligence to analyse patient stories in the context of Person-Centred Nursing Quality

Introduction:
Person-centredness became a fundamental principle of good healthcare. One way to reflect the quality of care in terms of person-centredness is to use “Key Performance Indicators (KPIs)”. These can be tracked by using a measurement framework, available in an App. Patient stories are a central data source, automatically transcribed in the App.Although nurses categorize and map them to the KIPs. This could be automated using artificial intelligence (AI). The aims of this dissertation are to improve the usability of the App by implementing AI and to explore whether the use of an AI contradicts the philosophical underpinning and principles of person-centredness.

Methods:
The study utilises a multi method approach with a strong focus on user involvement. A valid database of approximately 100 real patient stories is collaboratively created with experts in person-centredness. Workshops are conducted with nursing experts to ensure that the AI's type and functionality meet practice requirements. Following the AI development, a pilot test is conducted: Interrater reliability compares the AI and the human perspective. Focus groups with nurses will address usability, acceptance, and trust in AI. Additionally, discussions about the use of AI in the context of person-centredness
and ethical issues are planned.