Evidence map›Paper›PMID 41737440›Full record

ArticleHealth science reports2026

Mobile Applications for Sepsis-Related Healthcare: A Systematic Search and Evaluation Within App Stores.

Jacky Kao, Khalia Ackermann, Vincent Lam, Ling Li

Abstract read
In one paragraph

Article in Health science reports, 2026. 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

4 authors.

Jacky KaoFaculty of Medicine, Health, and Human Sciences Macquarie University New South Wales Australia.
Khalia AckermannCenter for Health Systems and Safety Research, Australian Institute of Health Innovation Macquarie University New South Wales Australia.ORCID https://orcid.org/0000-0001-9868-9456
Vincent LamFaculty of Medicine, Health, and Human Sciences Macquarie University New South Wales Australia.
Ling LiCenter for Health Systems and Safety Research, Australian Institute of Health Innovation Macquarie University New South Wales Australia.ORCID https://orcid.org/0000-0002-1642-142X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Aims: Sepsis is a life-threatening condition that poses a significant global health challenge. The rapid development and use of mobile phone technology has led to an increase in mobile health (mHealth) applications (apps). This review aimed to evaluate free and publicly available mHealth apps for sepsis-related healthcare, focusing on app features, quality, and clinical calculator accuracy. Methods: mHealth apps were identified by searching Results: Out of 317 identified apps, 16 met the inclusion criteria. These apps predominantly targeted healthcare professionals and supported many functions, such as education, diagnosis, management, clinical decision support, and clinical calculators. The mean MARS score of all apps was 3.25 out of 5 (SD 0.45), signifying acceptable app quality overall. The highest-scoring domain was information (mean 3.79, SD 0.59), and the lowest was engagement (mean 2.45, SD 0.43). Of 10 apps with clinical calculators, three (30%) had a calculation error. Conclusion: Most sepsis-related mHealth apps currently available are designed for clinicians' use as clinical decision-support tools. While overall app quality was acceptable, errors in the calculator function were identified, highlighting the crucial need for better mHealth regulatory guidelines and quality control.

Indexed as

clinical decision support systemsmHealthmobile applicationspatient safetysepsis

Identifiers

PMID41737440
PMCPMC12928056

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Registered trials

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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.