Maintaining patient trust as artificial intelligence’s role in healthcare grows

Patient trust is key to the delivery of healthcare and realisation of artificial intelligence's (AI) benefits in health. Trust in health institutions and the health professionals working within them directly impacts patient engagement with health services and their health outcomes. Patients want to be able to trust the health system and health services to respect, protect and use their data responsibly to minimise any potential harms. Further, when integrating AI within health services, patients want to be able to trust that this is done with good governance, including the correct approvals and processes, to ensure equitable and safe care. Due to the complexity and fast-changing landscape of AI and the varied levels of AI literacy, trust is arguably even more important. Patients need to be able to trust services to use their health information responsibly and integrate AI in care appropriately regardless of whether they fully understand the technology. Through transparency and good AI governance, trust can be built and maintained, but if broken or lost, it will be difficult to repair and will have wider implications. This paper provides recommendations for actions to be taken to build and maintain trust in health institutions within the context of the evolving AI landscape.

Authors

Institutions

Publication Details

Journal
New Zealand Medical Journal
Published
2026-02-10
DOI
https://doi.org/10.26635/6965.7122
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Maintaining patient trust as artificial intelligence’s role in healthcare grows

Rosie Dobson, Melanie Stowell, Robyn Whittaker
New Zealand Medical Journal
Artificial Intelligence in Healthcare and Education
article

Maintaining patient trust as artificial intelligence’s role in healthcare grows

Rosie Dobson, Melanie Stowell, Robyn Whittaker
article en

Abstract

Patient trust is key to the delivery of healthcare and realisation of artificial intelligence's (AI) benefits in health. Trust in health institutions and the health professionals working within them directly impacts patient engagement with health services and their health outcomes. Patients want to be able to trust the health system and health services to respect, protect and use their data responsibly to minimise any potential harms. Further, when integrating AI within health services, patients want to be able to trust that this is done with good governance, including the correct approvals and processes, to ensure equitable and safe care. Due to the complexity and fast-changing landscape of AI and the varied levels of AI literacy, trust is arguably even more important. Patients need to be able to trust services to use their health information responsibly and integrate AI in care appropriately regardless of whether they fully understand the technology. Through transparency and good AI governance, trust can be built and maintained, but if broken or lost, it will be difficult to repair and will have wider implications. This paper provides recommendations for actions to be taken to build and maintain trust in health institutions within the context of the evolving AI landscape.

New Zealand Medical JournalVol. 139(1629)
University of Auckland (NZ), Clinical Trials New Zealand (NZ), Department of Health Services (NP)
Quality Education
Openalex Percentile: Top 63%
Artificial Intelligence in Healthcare and Education
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.