Evidence map›Paper›PMID 22401330›Full record

ArticleJournal of diabetes science and technology2012

Interface design and human factors considerations for model-based tight glycemic control in critical care.

Logan Ward, James Steel, Aaron Le Compte, Alicia Evans, Chia-Siong Tan, Sophie Penning, Geoffrey M Shaw, Thomas Desaive, J Geoffrey Chase

Abstract readEvaluation Study
In one paragraph

Article in Journal of diabetes science and technology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Accuracy of Blood Glucose Measurement and Blood Glucose Targets.Journal of diabetes science and technology · 2020
    Review
  2. Article
  3. The benefits of tight glycemic control in critical illness: Sweeter than assumed?Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine · 2014
    Review
  4. 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

9 authors.

Logan WardDepartment of Mechanical Engineering, Centre for Bio-Engineering, University of Canterbury, Christchurch, New Zealand.
James Steel
Aaron Le Compte
Alicia Evans
Chia-Siong Tan
Sophie Penning
Geoffrey M Shaw
Thomas Desaive
J Geoffrey Chase

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionTight glycemic control (TGC) has shown benefits but has been difficult to implement. Model-based methods and computerized protocols offer the opportunity to improve TGC quality and compliance. This research presents an interface design to maximize compliance, minimize real and perceived clinical effort, and minimize error based on simple human factors and end user input.

methodThe graphical user interface (GUI) design is presented by construction based on a series of simple, short design criteria based on fundamental human factors engineering and includes the use of user feedback and focus groups comprising nursing staff at Christchurch Hospital. The overall design maximizes ease of use and minimizes (unnecessary) interaction and use. It is coupled to a protocol that allows nurse staff to select measurement intervals and thus self-manage workload.

resultsThe overall GUI design is presented and requires only one data entry point per intervention cycle. The design and main interface are heavily focused on the nurse end users who are the predominant users, while additional detailed and longitudinal data, which are of interest to doctors guiding overall patient care, are available via tabs. This dichotomy of needs and interests based on the end user's immediate focus and goals shows how interfaces must adapt to offer different information to multiple types of users.

conclusionsThe interface is designed to minimize real and perceived clinical effort, and ongoing pilot trials have reported high levels of acceptance. The overall design principles, approach, and testing methods are based on fundamental human factors principles designed to reduce user effort and error and are readily generalizable.

Indexed as

Models, TheoreticalResearch DesignUser-Computer InterfaceBlood GlucoseClinical ProtocolsComputer GraphicsCritical CareCritical IllnessData CollectionHealth Plan ImplementationHumansInformation Storage and RetrievalModels, BiologicalMonitoring, PhysiologicStochastic ProcessesBlood Glucose

Identifiers

PMID22401330
PMCPMC3320829

What OpenQuestion holds

Textmetadata
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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.