Evidence map›Paper›PMID 39049318›Full record

ArticleStudies in health technology and informatics2024

Using Generative AI to Translate Administrative Claims Data into Narrative Summaries for Palliative Care Needs Assessment: A Case Study.

Kathryn H Bowles, Carlin Brickner, Elizabeth A Luth

Abstract read
In one paragraph

Article in Studies in health technology and informatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

3 authors.

Kathryn H BowlesUniversity of Pennsylvania School of Nursing, Philadelphia, PA, USA.
Carlin BricknerScience and Technology, Center for Home Care Policy and Research, VNS Health, New York, NY, USA.
Elizabeth A LuthRutgers University and Robert Wood Johnson School of Medicine, New Brunswick, NJ., USA.

Funding

New Jersey Alliance for Clinical Translational Science: NJ ACTSUL1TR003017 · NCATS · RUTGERS BIOMEDICAL/HEALTH SCIENCES-RBHS · PI PANETTIERI, REYNOLD ALEXANDER · 2019 to 2023
$28.9M
NCATS NIH HHS UL1 TR003017
6 · The paper itself

Abstract

Community-based palliative care is a useful, but underutilized service to support seriously ill older adults to remain safely at home and improve quality of life. Clinical decision support tools can assist palliative care need assessments if presented in a way that is useful to clinicians. This case study explores the potential for generative artificial intelligence (AI) to translate diagnostic and billing codes from administrative data into a narrative format to facilitate clinical decision-making regarding palliative care need. Informatics structures for protecting patient confidentiality are described. Generative AI has the potential to support clinical decision-making but requires additional testing, validation, and refinement.

Indexed as

Artificial IntelligenceNeeds AssessmentPalliative CareDecision Support Systems, ClinicalHumansInsurance Claim ReviewNarrationNatural Language Processingclinical decision supportgenerative AIMachine learningnursing informaticspalliative care

Identifiers

PMID39049318
PMCPMC12869425

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.