Evidence map›Paper›PMID 40382095›Full record

ReviewCritical care nursing clinics of North America2025

Applying an Agile Science Roadmap to Integrate and Evaluate Ethical Frameworks Throughout the Lifecycle and Use of Artificial Intelligence Tools in the Intensive Care Unit.

Heidi Lindroth, Juhi Sahajwani, Mark Hudson, Laura Heier, Andrew A Gonzalez, Anirban Bhattacharyya, Zhi Zheng, Malaz Boustani, Vitaly Herasevich, Michelle McGowan and 1 more

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Critical care nursing clinics of North America, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. A pragmatic risk-stratified framework for using large language models in intensive care medicine: A narrative review.Critical care and resuscitation : journal of the Australasian Academy of Critical Care Medicine · 2026
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Heidi LindrothDivision of Nursing Research, Department of Nursing, Mayo Clinic, Rochester, MN, USA; Center for Aging Research, Regenstrief Institute, School of Medicine, Indiana University, Indianapolis, IN, USA; Center for Health Innovation and Implementation Science, School of Medicine, Indiana University, Indianapolis, IN, USA. Electronic address: Lindroth.heidi@mayo.edu.
Juhi SahajwaniDepartment of Critical Care Medicine, Mayo Clinic, Jacksonville, FL, USA.
Mark HudsonSchool of Psychology and Counselling, The Open University, Milton Keynes, UK.
Laura HeierDepartment of Graduate Nursing, Viterbo University, La Crosse, WI, USA; Department of Neurosurgery, Mayo Clinic, Rochester, MN, USA.
Andrew A GonzalezCenter for Health Services Research, Regenstrief Institute, School of Medicine, Indiana University, Indianapolis, IN, USA; Surgical Outcomes and Quality Improvement Center, Department of Surgery, School of Medicine, Indiana University, Indianapolis, IN, USA.
Anirban BhattacharyyaDepartment of Critical Care Medicine, Mayo Clinic, Jacksonville, FL, USA.
Zhi ZhengDepartment of Electrical Engineering, University of Notre Dame, Notre Dame, IN, USA.
Malaz BoustaniCenter for Aging Research, Regenstrief Institute, School of Medicine, Indiana University, Indianapolis, IN, USA; Center for Health Innovation and Implementation Science, School of Medicine, Indiana University, Indianapolis, IN, USA.
Vitaly HerasevichDepartment of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN, USA.
Michelle McGowanBiomedical Ethics, Departments of Quantitative Health Sciences and Artificial Intelligence and Informatics, Biomedical Ethics Research Program, Mayo Clinic, Rochester, MN, USA.
Barbara BarryKern Center Mayo Clinic, Rochester, MN, USA.

Funding

Harnessing the Power of Technology to Transform Delirium Severity Measurement in the ICUK23AG076662 · NIA · MAYO CLINIC ROCHESTER · PI Heidi Lindroth · 2022 to 2026
$815k
NIA NIH HHS K23 AG076662
6 · The paper itself

Abstract

This article summarizes existing ethical frameworks for healthcare artificial intelligence (AI) and ambient sensing technology, such as computer vision, and examines their application to improve patient outcomes in the intensive care unit (ICU). Integrating ethical considerations such as privacy, fairness, and autonomy into the lifecycle of an AI tool is necessary to fully harvest AI's potential to deliver safe, high-quality, personalized, and low-cost healthcare services that provide positive experiences for patients, families, and clinicians while improving health outcomes. Drawing from agile science, the article proposes a practical roadmap for clinician and researcher use to identify, integrate, and monitor ethical considerations throughout the lifecycle of an AI tool with the intention to improve patient care. A use case illustrates the application of the agile science-informed roadmap that details the development of a passive digital marker for delirium severity.

Indexed as

Artificial IntelligenceIntensive Care UnitsHumansAgile scienceAI toolsArtificial intelligenceComputer visionDelirium severityEthical frameworks for health care AIICUPassive digital marker

Identifiers

PMID40382095
PMCPMC13016272

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.