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Putting AI into real hospital care is doable but hard, five Kaiser-led projects find

Study title: Can Artificial Intelligence Deliver in Real-World Health Systems? Early Insights From Augmented Intelligence in Medicine and Healthcare Initiative's 5 Funded Projects

The Augmented Intelligence in Medicine and Healthcare Initiative, led by Kaiser Permanente and funded by the Gordon and Betty Moore Foundation, funded five projects to move AI beyond controlled model development into routine care. The projects addressed sepsis management, venous thromboembolism risk, diabetic retinopathy screening, cardiac amyloidosis detection, and pediatric asthma risk prediction, with synthesis of implementation processes and lessons learned.

Read the study abstract

Introduction Artificial intelligence (AI) holds tremendous promise to improve clinical decision-making across diagnosis, risk assessment, and patient care. However, most prior work has focused on model development in controlled settings with limited evidence on real-world implementation. The Augmented Intelligence in Medicine and Healthcare Initiative (AIM-HI), led by Kaiser Permanente and funded by the Gordon and Betty Moore Foundation, was established to evaluate and support integration of AI tools into routin…

By the Truvace desk1 min read1 sourceEvidence: Emerging · 37/100 — Interviews or qualitative study · n = 5 · 1 independent sourcePeer-reviewedTRV-2026-1120· cite & verify
Can Artificial Intelligence Deliver in Real-World Health Systems? Early Insights From Augmented Intelligence in Medicine and Healthcare Initiative's 5 Funded Projects
"Public Health Lab Ribbon Cutting Ceremony" by MDGovpics is licensed under CC BY 2.0. To view a copy of this license, visit https://creativecommons.org/licenses/by/2.0/.

In brief

Early results show feasibility is achievable but not automatic, as deployment hinges on EHR integration, handling data complexity, meeting regulatory requirements, and adapting to workflow variation. The findings matter because they shift evidence from model performance to operational requirements like stakeholder engagement and ongoing monitoring, while uncertainty remains about long-term scalability and performance across sites.

Main points

  1. AIM-HI, led by Kaiser Permanente and funded by the Gordon and Betty Moore Foundation, funded 5 projects via national multistage review using structured scoring rubric.
  2. Projects covered sepsis management, venous thromboembolism risk assessment, diabetic retinopathy screening, cardiac amyloidosis detection, and pediatric asthma risk prediction.
  3. Cross-project synthesis identified stakeholder engagement, local adaptation, quality assurance, and performance monitoring as common implementation themes.

The problem

Authors of five Kaiser Permanente-led AI projects reported that putting the tools into routine care was hard, held back by electronic record integration, data complexity, regulatory requirements and varying clinical workflows.

The rundown

AIM-HI funded 5 projects through a national, multistage review process using a structured scoring rubric, spanning sepsis management, venous thromboembolism risk assessment, diabetic retinopathy screening, cardiac amyloidosis detection, and pediatric asthma risk prediction across diverse health care settings.

Authors synthesized findings on implementation processes, noting that success depended on thoughtful integration, strong partnerships with stakeholders, and sustained evaluation and monitoring, while quality assurance and local adaptation were recurring requirements.

Sources

  1. Peer-reviewedThe Permanente Journal2026-09-16

The debate