Abstract: FR-OR041
Attitudes and Perception of Artificial Intelligence in Hypertension: Cross-Sectional Survey Among Patients and Clinicians
Session Information
- Hypertension and Cardiorenal Disease: Novel Mechanisms and Therapeutic Targets
November 07, 2025 | Location: Room 332A, Convention Center
Abstract Time: 05:10 PM - 05:20 PM
Category: Hypertension and CVD
- 1602 Hypertension and CVD: Clinical
Authors
- Judge, Conor S., University of Galway College of Medicine Nursing and Health Sciences, Galway, County Galway, Ireland
- Murphy, Paddy, University of Galway College of Medicine Nursing and Health Sciences, Galway, County Galway, Ireland
- Ramirez Batista, Raul Isaac, University of Waterloo, Waterloo, Ontario, Canada
- Rabbitt, Louise, University of Galway College of Medicine Nursing and Health Sciences, Galway, County Galway, Ireland
- Teh, Jia Wei, University of Galway College of Medicine Nursing and Health Sciences, Galway, County Galway, Ireland
- Krewer, Finn, University of Galway College of Medicine Nursing and Health Sciences, Galway, County Galway, Ireland
- O'Donnell, Martin, University of Galway College of Medicine Nursing and Health Sciences, Galway, County Galway, Ireland
- Burns, Catherine, University of Waterloo, Waterloo, Ontario, Canada
- Tripp, Bryan, University of Waterloo, Waterloo, Ontario, Canada
Background
Artificial intelligence clinical decision-support systems (AI-CDSS) show promise for improving blood pressure control, but limited data exist on clinicians' and patients' perceptions. This study explores both groups' views on the use of AI-CDSS in hypertension management.
Methods
We conducted a cross-sectional survey (Aug 2024–Mar 2025) of primary and secondary care clinicians in Ireland, distributed through Nephrology, Hypertension, and General Practice Societies. A parallel patient survey was conducted via hypertension clinics and community networks. Surveys were designed using the Value-Based Adoption Model (perceived risks and benefits) and refined through a Public and Patient Involvement event. Responses were collected using a 5-point Likert scale.
Results
201 clinicians and 304 patients completed surveys. Most clinicians, 84 (42%) were aged 30–39 and most patients, 192 (64%) were ≥60 years. Basic AI understanding was reported by 164 clinicians (83%) and 206 patients (67%). Willingness to use AI-CDSS was high: 138 clinicians (71%) said they would use it, and 223 patients (75%) were comfortable with their doctor using it. The leading concern among clinicians was legal liability: 148 (77%) were worried about responsibility if AI caused harm. For patients, it was lack of regulation, cited by 172 (60%). The most unanimous response was to decision conflict: 290 patients (97%) said they would follow their doctor’s recommendation over AI’s.
Conclusion
Both clinicians and patients are open to AI-CDSS use in hypertension. Patients emphasised the need for stronger regulation and clinicians highlighted liability concerns. Responses strongly affirm that AI must support, not replace clinician judgment.
Funding
- Government Support – Non-U.S.