Artificial Intelligence-supported digital health utilization in primary care in the Netherlands
Abstract
Background: General practices continue to report high workloads while administrative burdens steadily increase. Emerging digital health technologies, such as Artificial Intelligence (AI), may help alleviate some of this pressure. However, the current level of adoption and the perceived need for AI-supported digital health applications in general practices remain unclear. In addition, little is known about the barriers to implementing AI applications.
Methods: Since 2024, the annual Nivel General Practice Survey measures among Dutch general practices their use of AI-supported digital health applications and their need for such tools. In 2025, additional questions were incorporated to explore why practices may not have a need for AI-supported digital health and to identify barriers that hinder its adoption.
Results: The proportion of general practices (n = 827) using AI-supported digital health applications increased in 2025 compared with 2024, particularly for speech-based reporting (2024: 14%; 2025: 36%). Between one-third and half of the practices report a need for AI applications, especially for preventive care and triage. Practices without this need report limited added value, insufficient reliability, and the perceived loss of personal care due to AI. In general, practices see barriers for AI adoption because of limited familiarity with AI-supported applications, suboptimal quality, high costs, insufficient time, and inadequate integration with existing information systems.
Conclusions: This study provides empirical insight into the use of AI-supported digital health applications in general practices in the Netherlands. The high level of demand by practices suggests continued growth in adoption but many barriers are perceived as well. The identified barriers, that are likely to be internationally relevant, offer actionable directions for policymakers to support sustainable implementation of AI-supported digital health applications in primary care.
Key messages: • The high level of demand for AI-supported digital health applications by general practices suggests continued growth in adoption, but trends cannot be clearly observed yet.
• The identified barriers for the adoption and use of AI by general practices offer actionable directions for policymakers to support sustainable implementation.
Related
- An assisted telemedicine model with digital diagnostics and artificial intelligence-supported clinical decision in hard-to-reach rural communities: a community-based mixed-methods study from Rajasthan, India
- Digital, Mobile and Artificial Intelligence‐Supported Interventions for Pressure Injury Prevention and Management: A Systematic Review of Clinical, Workflow and Implementation Outcomes
- Artificial intelligence-supported diabetic retinopathy screening in Tanzania: a randomised controlled trial
- Personalized Remote Patient Management in Heart Failure : From Implanted Hemodynamic Monitoring Toward an Artificial Intelligence-Supported Adaptive Care Cycle.
- Exploring nursing students' communication experiences with artificial intelligence-supported virtual patients: a qualitative study.
BibTeX
@article{keuper2026artificial,
title = {{Artificial Intelligence-supported digital health utilization in primary care in the Netherlands}},
author = {JJ Keuper and RS Batenburg and LHD Van Tuyl},
journal = {The European Journal of Public Health},
year = {2026},
month = oct,
doi = {10.1093/eurpub/ckag169.400},
url = {https://doi.org/10.1093/eurpub/ckag169.400},
note = {CC BY-NC 4.0},
}
RIS
TY - JOUR
TI - Artificial Intelligence-supported digital health utilization in primary care in the Netherlands
AU - JJ Keuper
AU - RS Batenburg
AU - LHD Van Tuyl
PY - 2026
DA - 2026/10/01
JO - The European Journal of Public Health
DO - 10.1093/eurpub/ckag169.400
UR - https://doi.org/10.1093/eurpub/ckag169.400
AB - Background: General practices continue to report high workloads while administrative burdens steadily increase. Emerging digital health technologies, such as Artificial Intelligence (AI), may help alleviate some of this pressure. However, the current level of adoption and the perceived need for AI-supported digital health applications in general practices remain unclear. In addition, little is known about the barriers to implementing AI applications. Methods: Since 2024, the annual Nivel General Practice Survey measures among Dutch general practices their use of AI-supported digital health applications and their need for such tools. In 2025, additional questions were incorporated to explore why practices may not have a need for AI-supported digital health and to identify barriers that hinder its adoption. Results: The proportion of general practices (n = 827) using AI-supported digital health applications increased in 2025 compared with 2024, particularly for speech-based reporting (2024: 14%; 2025: 36%). Between one-third and half of the practices report a need for AI applications, especially for preventive care and triage. Practices without this need report limited added value, insufficient reliability, and the perceived loss of personal care due to AI. In general, practices see barriers for AI adoption because of limited familiarity with AI-supported applications, suboptimal quality, high costs, insufficient time, and inadequate integration with existing information systems. Conclusions: This study provides empirical insight into the use of AI-supported digital health applications in general practices in the Netherlands. The high level of demand by practices suggests continued growth in adoption but many barriers are perceived as well. The identified barriers, that are likely to be internationally relevant, offer actionable directions for policymakers to support sustainable implementation of AI-supported digital health applications in primary care. Key messages: • The high level of demand for AI-supported digital health applications by general practices suggests continued growth in adoption, but trends cannot be clearly observed yet. • The identified barriers for the adoption and use of AI by general practices offer actionable directions for policymakers to support sustainable implementation.
SN - 1101-1262
SN - 1464-360X
ER -