Evidence map›Paper›PMID 41033694›Full record

ArticleBMJ health & care informatics2025

Developing clinical informatics to support direct care and population health management: the VIEWER story.

Robert Harland, Tao Wang, David Codling, Catherine Polling, Matthew Broadbent, Holly Newton, Yamiko Joseph Msosa, Daisy Kornblum, Claire Delaney-Pope, Barbara Arroyo and 8 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMJ health & care informatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
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

18 authors.

Robert HarlandSouth London and Maudsley NHS Foundation Trust, London, UK.
Tao WangInstitute of Psychiatry Psychology & Neuroscience, King's College London, London, UK tao.wang@kcl.ac.uk.ORCID http://orcid.org/0000-0002-0437-0557
David CodlingSouth London and Maudsley NHS Foundation Trust, London, UK.
Catherine PollingSouth London and Maudsley NHS Foundation Trust, London, UK.
Matthew BroadbentSouth London and Maudsley NHS Foundation Trust, London, UK.
Holly NewtonSouth London and Maudsley NHS Foundation Trust, London, UK.
Yamiko Joseph MsosaInstitute of Psychiatry Psychology & Neuroscience, King's College London, London, UK.
Daisy KornblumSouth London and Maudsley NHS Foundation Trust, London, UK.
Claire Delaney-PopeSouth London and Maudsley NHS Foundation Trust, London, UK.
Barbara ArroyoSouth London and Maudsley NHS Foundation Trust, London, UK.
Stuart MacLellanSouth London and Maudsley NHS Foundation Trust, London, UK.
Zoe KeddieSouth London and Maudsley NHS Foundation Trust, London, UK.
Mary Jane DochertySouth London and Maudsley NHS Foundation Trust, London, UK.
Angus RobertsInstitute of Psychiatry Psychology & Neuroscience, King's College London, London, UK.
Derek TracySouth London and Maudsley NHS Foundation Trust, London, UK.
Philip McguireInstitute of Psychiatry Psychology & Neuroscience, King's College London, London, UK.
Richard J B DobsonInstitute of Psychiatry Psychology & Neuroscience, King's College London, London, UK.
Robert StewartSouth London and Maudsley NHS Foundation Trust, London, UK.ORCID http://orcid.org/0000-0002-4435-6397

Funding

Wellcome Trust
6 · The paper itself

Abstract

Electronic health records (EHRs) provide comprehensive patient data, which could be better used to enhance informed decision-making, resource allocation and coordinated care, thereby optimising healthcare delivery. However, in mental healthcare, critical information, such as on risk factors, precipitants and treatment responses, is often embedded in unstructured text, limiting the ability to automate at scale measures to identify and prioritise local populations and patients, which potentially hinders timely prevention and intervention. We describe the development and proof-of-concept implementation of Visual & Interactive Engagement With Electronic Records, a clinical informatics platform designed to enhance direct patient care and population health management by improving the accessibility and usability of EHR data. We further outline strategies that were employed in this work to foster informatics innovation through interdisciplinary and cross-organisational collaboration to support integrated, personalised care and detail how these advancements were piloted and implemented within a large UK mental health National Health Service Foundation Trust to improve patient outcomes at an individual patient, clinician, clinical team and organisational level.

Indexed as

Electronic Health RecordsMedical InformaticsMental Health ServicesPopulation Health ManagementHumansState MedicineUnited KingdomBMJ Health InformaticsDecision Support Systems, ClinicalElectronic Health Records

Identifiers

PMID41033694
PMCPMC12496044

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.