Evidence map›Paper›PMID 33358138›Full record

ReviewThe Lancet. Digital health2021

Ethical issues in using ambient intelligence in health-care settings.

Nicole Martinez-Martin, Zelun Luo, Amit Kaushal, Ehsan Adeli, Albert Haque, Sara S Kelly, Sarah Wieten, Mildred K Cho, David Magnus, Li Fei-Fei and 2 more

Open access · goldAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in The Lancet. Digital health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
55citing papers in PubMed, 1 pooled it
3.0field-weighted citation impact, top 8% of its field
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

55 citing papers in PubMed, 1 synthesis or guideline pooled it, 147 citations in OpenAlex.

  1. Pooled it
  2. Strengths and Potential Pitfalls of the Use of Artificial Intelligence in Psychiatric Education and Practice.Academic psychiatry : the journal of the American Association of Directors of Psychiatric Residency Training and the Association for Academic Psychiatry · 2026
    Article
  3. Review
  4. Article
  5. The Ethics of AI Scribes as Epistemic Agents.JMIR medical informatics · 2026
    Article
  6. Review
  7. Article
  8. Review
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. From Bytes to Insights: The Promise and Peril of Artificial Intelligence-Powered Psychiatry.Academic psychiatry : the journal of the American Association of Directors of Psychiatric Residency Training and the Association for Academic Psychiatry · 2025
    Article
  19. Article
  20. 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

12 authors at 2 institutions in 1 country.

Nicole Martinez-MartinCenter for Biomedical Ethics, Stanford University, Stanford, CA, USA. Electronic address: nicolemz@stanford.edu.
Zelun LuoDepartment of Computer Science, Stanford University, Stanford, CA, USA.
Amit KaushalDepartment of Bioengineering, Stanford University, Stanford, CA, USA.
Ehsan AdeliDepartment of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA; Department of Computer Science, Stanford University, Stanford, CA, USA.
Albert HaqueDepartment of Computer Science, Stanford University, Stanford, CA, USA.
Sara S KellyClinical Excellence Research Center, Department of Medicine, Stanford University, Stanford, CA, USA.
Sarah WietenCenter for Biomedical Ethics, Stanford University, Stanford, CA, USA.
Mildred K ChoCenter for Biomedical Ethics, Stanford University, Stanford, CA, USA.
David MagnusCenter for Biomedical Ethics, Stanford University, Stanford, CA, USA.
Li Fei-FeiStanford Institute for Human-Centered Artificial Intelligence, Stanford University, Stanford, CA, USA.
Kevin SchulmanClinical Excellence Research Center, Department of Medicine, Stanford University, Stanford, CA, USA.
Arnold MilsteinClinical Excellence Research Center, Department of Medicine, Stanford University, Stanford, CA, USA.
Stanford University · USEthics and Public Policy Center · US

Funding

Integrating Ethics into Machine Learning for Precision MedicineR01HG010476 · NHGRI · STANFORD UNIVERSITY · PI CHO, MILDRED K., SANKAR, PAMELA L · 2019 to 2021
$1.8M
Ethical, Legal and Social Implications in the Use of Digital Technology for Mental Health ApplicationsK01MH118375 · NIMH · STANFORD UNIVERSITY · PI MARTINEZ-MARTIN, NICOLE A · 2019 to 2022
$508k
NHGRI NIH HHS R01 HG010476NIMH NIH HHS K01 MH118375
6 · The paper itself

Abstract

Ambient intelligence is increasingly finding applications in health-care settings, such as helping to ensure clinician and patient safety by monitoring staff compliance with clinical best practices or relieving staff of burdensome documentation tasks. Ambient intelligence involves using contactless sensors and contact-based wearable devices embedded in health-care settings to collect data (eg, imaging data of physical spaces, audio data, or body temperature), coupled with machine learning algorithms to efficiently and effectively interpret these data. Despite the promise of ambient intelligence to improve quality of care, the continuous collection of large amounts of sensor data in health-care settings presents ethical challenges, particularly in terms of privacy, data management, bias and fairness, and informed consent. Navigating these ethical issues is crucial not only for the success of individual uses, but for acceptance of the field as a whole.

Indexed as

Ambient IntelligenceBioethical IssuesAlgorithmsData CollectionData ManagementDigital TechnologyDocumentationHealth PersonnelHumansInformed ConsentMachine LearningPatient CarePatient SafetyPractice Guidelines as TopicPrivacyQuality of Health Care

Identifiers

PMID33358138
PMCPMC8310737
OpenAlexW3117865842

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.