Evidence map›Paper›PMID 27025648›Full record

ArticleJMIR human factors2015

Assessing the Usability of Six Data Entry Mobile Interfaces for Caregivers: A Randomized Trial.

Frederic Ehrler, Guy Haller, Evelyne Sarrey, Magali Walesa, Rolf Wipfli, Christian Lovis

Abstract read
In one paragraph

Article in JMIR human factors, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

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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

6 authors.

Frederic EhrlerDivision of Medical Information Sciences, Department of medical imaging and medical information sciences, University Hospitals of Geneva, Geneva, Switzerland. frederic.ehrler@hcuge.ch.ORCID http://orcid.org/0000-0001-9734-3242

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere is an increased demand in hospitals for tools, such as dedicated mobile device apps, that enable the recording of clinical information in an electronic format at the patient's bedside. Although the human-machine interface design on mobile devices strongly influences the accuracy and effectiveness of data recording, there is still a lack of evidence as to which interface design offers the best guarantee for ease of use and quality of recording. Therefore, interfaces need to be assessed both for usability and reliability because recording errors can seriously impact the overall level of quality of the data and affect the care provided.

objectiveIn this randomized crossover trial, we formally compared 6 handheld device interfaces for both speed of data entry and accuracy of recorded information. Three types of numerical data commonly recorded at the patient's bedside were used to evaluate the interfaces.

methodsIn total, 150 health care professionals from the University Hospitals of Geneva volunteered to record a series of randomly generated data on each of the 6 interfaces provided on a smartphone. The interfaces were presented in a randomized order as part of fully automated data entry scenarios. During the data entry process, accuracy and effectiveness were automatically recorded by the software.

resultsVarious types of errors occurred, which ranged from 0.7% for the most reliable design to 18.5% for the least reliable one. The length of time needed for data recording ranged from 2.81 sec to 14.68 sec, depending on the interface. The numeric keyboard interface delivered the best performance for pulse data entry with a mean time of 3.08 sec (SD 0.06) and an accuracy of 99.3%.

conclusionsOur study highlights the critical impact the choice of an interface can have on the quality of recorded data. Selecting an interface should be driven less by the needs of specific end-user groups or the necessity to facilitate the developer's task (eg, by opting for default solutions provided by commercial platforms) than by the level of speed and accuracy an interface can provide for recording information. An important effort must be made to properly validate mobile device interfaces intended for use in the clinical setting. In this regard, our study identified the numeric keyboard, among the proposed designs, as the most accurate interface for entering specific numerical values. This is an important step toward providing clearer guidelines on which interface to choose for the appropriate use of handheld device interfaces in the health care setting.

Indexed as

computers, handhelddata collectionmobile applicationspatient safetyuser-computer interfacevital signs

Identifiers

PMID27025648
PMCPMC4802909

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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.