Evidence map›Paper›PMID 38175688›Full record

ArticleJMIR medical education2024

Generative Language Models and Open Notes: Exploring the Promise and Limitations.

Charlotte Blease, John Torous, Brian McMillan, Maria Hägglund, Kenneth D Mandl

Abstract read
In one paragraph

Article in JMIR medical education, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

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  13. Safety netting in primary care: managing the low incidence, high uncertainty of severe illness.The British journal of general practice : the journal of the Royal College of General Practitioners · 2025
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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

5 authors.

Charlotte BleaseDepartment of Women's and Children's Health, Uppsala University, Uppsala, Sweden.ORCID 0000-0002-0205-1165
John TorousDigital Psychiatry, Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, United States.ORCID 0000-0002-5362-7937
Brian McMillanCentre for Primary Care and Health Services Research, University of Manchester, Manchester, United Kingdom.ORCID 0000-0002-0683-3877
Maria HägglundDepartment of Women's and Children's Health, Uppsala University, Uppsala, Sweden.ORCID 0000-0002-6839-3651
Kenneth D MandlComputational Health Informatics Program, Boston Children's Hospital, Harvard Medical School, Boston, MA, United States.ORCID 0000-0002-9781-0477

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Patients' online record access (ORA) is growing worldwide. In some countries, including the United States and Sweden, access is advanced with patients obtaining rapid access to their full records on the web including laboratory and test results, lists of prescribed medications, vaccinations, and even the very narrative reports written by clinicians (the latter, commonly referred to as "open notes"). In the United States, patient's ORA is also available in a downloadable form for use with other apps. While survey studies have shown that some patients report many benefits from ORA, there remain challenges with implementation around writing clinical documentation that patients may now read. With ORA, the functionality of the record is evolving; it is no longer only an aide memoire for doctors but also a communication tool for patients. Studies suggest that clinicians are changing how they write documentation, inviting worries about accuracy and completeness. Other concerns include work burdens; while few objective studies have examined the impact of ORA on workload, some research suggests that clinicians are spending more time writing notes and answering queries related to patients' records. Aimed at addressing some of these concerns, clinician and patient education strategies have been proposed. In this viewpoint paper, we explore these approaches and suggest another longer-term strategy: the use of generative artificial intelligence (AI) to support clinicians in documenting narrative summaries that patients will find easier to understand. Applied to narrative clinical documentation, we suggest that such approaches may significantly help preserve the accuracy of notes, strengthen writing clarity and signals of empathy and patient-centered care, and serve as a buffer against documentation work burdens. However, we also consider the current risks associated with existing generative AI. We emphasize that for this innovation to play a key role in ORA, the cocreation of clinical notes will be imperative. We also caution that clinicians will need to be supported in how to work alongside generative AI to optimize its considerable potential.

Indexed as

Artificial IntelligenceLanguageCommunicationDocumentationEmpathyHumansChatGPTclinical documentationcommunication tooldocumentationempathygenerative language modelslanguage modellarge language modelsmedical educationonline record accessOpen Notespatient-centered care

Identifiers

PMID38175688
PMCPMC10797501

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.