Evidence map›Paper›PMID 25943590›Full record

ReviewBMC medicine2015

Smartphone apps for calculating insulin dose: a systematic assessment.

Kit Huckvale, Samanta Adomaviciute, José Tomás Prieto, Melvin Khee-Shing Leow, Josip Car

Open access · goldAbstract readReview
In one paragraph

Review in BMC medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 82 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
82citing papers in PubMed, 5 pooled it
51.8field-weighted citation impact, top 1% of its field
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

82 citing papers in PubMed, 5 syntheses or guidelines pooled it, 210 citations in OpenAlex.

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  17. Ideal automation for insulin management - with interpretation of risk ratio.The Lancet regional health. Western Pacific · 2023
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22 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 4 institutions in 3 countries.

Kit HuckvaleGlobal eHealth Unit, Imperial College London, Reynolds Building, St Dunstans Road, London, W6 8RP, UK. c.huckvale@imperial.ac.uk.
Samanta AdomaviciuteGlobal eHealth Unit, Imperial College London, Reynolds Building, St Dunstans Road, London, W6 8RP, UK. samanta.adomaviciute@gmail.com.
José Tomás PrietoCRG, École polytechnique, Palaiseau, France. jose-tomas.prieto@polytechnique.edu.
Melvin Khee-Shing LeowDepartment of Endocrinology, Tan Tock Seng Hospital, Singapore, Singapore. melvin.leow@sics.a-star.edu.org.
Josip CarGlobal eHealth Unit, Imperial College London, Reynolds Building, St Dunstans Road, London, W6 8RP, UK. josip.car@imperial.ac.uk.
Imperial College London · GBDuke-NUS Medical School · SGÉcole Polytechnique · FRNanyang Technological University · SG

Funding

Department of Health IPF-12-09
6 · The paper itself

Abstract

backgroundMedical apps are widely available, increasingly used by patients and clinicians, and are being actively promoted for use in routine care. However, there is little systematic evidence exploring possible risks associated with apps intended for patient use. Because self-medication errors are a recognized source of avoidable harm, apps that affect medication use, such as dose calculators, deserve particular scrutiny. We explored the accuracy and clinical suitability of apps for calculating medication doses, focusing on insulin calculators for patients with diabetes as a representative use for a prevalent long-term condition.

methodsWe performed a systematic assessment of all English-language rapid/short-acting insulin dose calculators available for iOS and Android.

resultsSearches identified 46 calculators that performed simple mathematical operations using planned carbohydrate intake and measured blood glucose. While 59% (n = 27/46) of apps included a clinical disclaimer, only 30% (n = 14/46) documented the calculation formula. 91% (n = 42/46) lacked numeric input validation, 59% (n = 27/46) allowed calculation when one or more values were missing, 48% (n = 22/46) used ambiguous terminology, 9% (n = 4/46) did not use adequate numeric precision and 4% (n = 2/46) did not store parameters faithfully. 67% (n = 31/46) of apps carried a risk of inappropriate output dose recommendation that either violated basic clinical assumptions (48%, n = 22/46) or did not match a stated formula (14%, n = 3/21) or correctly update in response to changing user inputs (37%, n = 17/46). Only one app, for iOS, was issue-free according to our criteria. No significant differences were observed in issue prevalence by payment model or platform.

conclusionsThe majority of insulin dose calculator apps provide no protection against, and may actively contribute to, incorrect or inappropriate dose recommendations that put current users at risk of both catastrophic overdose and more subtle harms resulting from suboptimal glucose control. Healthcare professionals should exercise substantial caution in recommending unregulated dose calculators to patients and address app safety as part of self-management education. The prevalence of errors attributable to incorrect interpretation of medical principles underlines the importance of clinical input during app design. Systemic issues affecting the safety and suitability of higher-risk apps may require coordinated surveillance and action at national and international levels involving regulators, health agencies and app stores.

Indexed as

Cell PhoneMobile ApplicationsBlood GlucoseDiabetes MellitusHumansInsulinsSelf CareBlood GlucoseInsulins

Identifiers

PMID25943590
PMCPMC4433091
OpenAlexW1554470992

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.