The added value of the artificial intelligence patient-reported experience measure (AI-PREM tool) in clinical practise: Deployment in a vestibular schwannoma care pathway

Abstract

Objectives: Patient-reported experience measures (PREMs) can be used for the improvement of quality of care. In this study, the outcome of an open-ended question PREM combined with computer-assisted analysis is compared to the outcome of a closed-ended PREM questionnaire. Methods: This survey study assessed the outcome of the open-ended questionnaire PREM and a close-ended question PREM of patients with unilateral vestibular schwannoma in a tertiary vestibular schwannoma expert centre. Results: The open-ended questions PREM, consisting of five questions, was completed by 507 participants and resulted in 1508 positive and 171 negative comments, categorised into 27 clusters. The close-ended questions PREM results were mainly positive (overall experience graded as 8/10), but did not identify specific action points. Patients who gave high overall scores (>8) on the close-ended question provided points for improvement in the open-ended question PREM, which would have been missed using the close-ended questions only. Conclusions: Compared to the close-ended question PREM, the open-ended question PREM provides more detailed and specific information about the patient experience in the vestibular schwannoma care pathway. Innovation: Automated analysis of feedback with the open-ended question PREM revealed relevant insights and identified topics for targeted quality improvement, whereas the close-ended PREM did not.

Keywords

• Patient experience
• Quality of care
• Patient centredness
• Artificial intelligence
• Vestibular schwannoma