Evidence map›Paper›PMID 42382606›Full record

ArticleFuture healthcare journal2026

Digital solutions in acute medicine: Will electronic health records join up the patient journey (soon?).

Christian P Subbe, Anne Kinderlerer, Yogini H Jani

Abstract read
In one paragraph

Article in Future healthcare journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

3 authors.

Christian P SubbeDepartment of Advanced Internal Medicine, Woodlands Hospital, Singapore.
Anne KinderlererChair of Unplanned Care, Kingston Hospital NHS Foundation Trust, Kingston upon Thames, UK.
Yogini H JaniCentre for Medicines Optimisation Research and Education, University College London Hospitals NHS Foundation Trust, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acute medicine provides care to patients during the first 72 h of their hospital stay. Clinicians face unique challenges of complexity in having to care simultaneously for groups of patients with multiple medical conditions and often complex needs. Digital innovation is central to modern clinical practice, yet its capacity to improve quality of care remains contested. This narrative review explores what acute physicians require from electronic health record (EHR) systems, drawing on evidence from usability studies, implementation evaluations and quality frameworks. Despite substantial investment, evidence of benefits for clinical outcomes, cost-effectiveness and user satisfaction remains modest. There is limited research on impact on mortality, efficiency and patient experience. Most research demonstrates inconsistent effects on process and intermediate outcomes such as clinical documentation quality (legibility) or improvements in medication safety. Poor system design based on work as described/imagined, rather than work as actually done, contributes to clinician burnout and undermines system adoption. Despite this, the review identifies good practice examples that show the potential for transformation in this challenging area of medical care. Future progress depends on integrating human factors science, rigorous usability assessment and responsive design. Research will need to evidence equity and sustainability. Acute physicians should 'expect more': systems that provide the right information, in the right context, at the right time - first time.

Indexed as

Acute medicineBurnoutElectronic health recordsImprovement sciencePatient safetyUsability

Identifiers

PMID42382606
PMCPMC13316380

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.