Evidence map›Paper›PMID 40417556›Full record

ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2024

Generative AI Demonstrated Difficulty Reasoning on Nursing Flowsheet Data.

Courtney J Diamond, Jennifer Thate, Jennifer B Withall, Rachel Y Lee, Kenrick Cato, Sarah C Rossetti

Abstract read
In one paragraph

Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Courtney J DiamondColumbia University Department of Biomedical Informatics, New York, NY.
Jennifer ThateColumbia University Department of Biomedical Informatics, New York, NY.
Jennifer B WithallColumbia University Department of Biomedical Informatics, New York, NY.
Rachel Y LeeColumbia University School of Nursing, New York, NY.
Kenrick CatoUniversity of Pennsylvania School of Nursing, Philadelphia, PA.
Sarah C RossettiColumbia University Department of Biomedical Informatics, New York, NY.

Funding

Training in Biomedical Informatics at Columbia UniversityT15LM007079 · NLM · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI NOEMIE ELHADAD, GEORGE M HRIPCSAK · 1992 to 2026
$28.9M
Communicating Narrative Concerns Entered by RNs (CONCERN)R01NR016941 · NINR · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Kenrick Dwain Cato, Sarah Collins Rossetti · 2017 to 2026
$6.7M
AHRQ HHS R01 HS028454NINR NIH HHS R01 NR016941NLM NIH HHS T15 LM007079
6 · The paper itself

Abstract

Excessive documentation burden is linked to clinician burnout, thus motivating efforts to reduce burden. Generative artificial intelligence (AI) poses opportunities for burden reduction but requires rigorous assessment. We evaluated the ability of a large language model (LLM) (OpenAI's GPT-4) to interpret various intervention-response relationships presented on nursing flowsheets, assessing performance using MUC-5 evaluation metrics, and compared its assessments to those of nurse expert evaluators. ChatGPT correctly assessed 3 of 14 clinical scenarios, and partially correctly assessed 6 of 14, frequently omitting data from its reasoning. Nurse expert evaluators correctly assessed all relationships and provided additional language reflective of standard nursing practice beyond the intervention-response relationships evidenced in nursing flowsheets. Future work should ensure the training data used for electronic health record (EHR)-integrated LLMs includes all types of narrative nursing documentation that reflect nurses' clinical reasoning, and verification of LLM-based information summarization does not burden end-users.

Indexed as

Artificial IntelligenceDocumentationElectronic Health RecordsNursing RecordsHumansNatural Language Processing

Identifiers

PMID40417556
PMCPMC12099445

What Socratic holds

Textmetadata
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 Socratic graph.