Evidence map›Paper›PMID 34269680›Full record

ArticleJMIR medical informatics2021

A Tool for Evaluating Medication Alerting Systems: Development and Initial Assessment.

Wu Yi Zheng, Bethany Van Dort, Romaric Marcilly, Richard Day, Rosemary Burke, Sepehr Shakib, Young Ku, Hannah Reid-Anderson, Melissa Baysari

Abstract read
In one paragraph

Article in JMIR medical informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
–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

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

9 authors.

Wu Yi ZhengBlack Dog Institute, Randwick, NSW, Australia.ORCID https://orcid.org/0000-0002-1159-4700
Bethany Van DortThe University of Sydney, Faculty of Medicine and Health, School of Medical Sciences, Biomedical Informatics and Digital Health, Sydney, Australia.ORCID https://orcid.org/0000-0003-0052-6400
Romaric MarcillyUniv Lille, CHU Lille, ULR 2694, METRICS: Évaluation des Technologies de santé des Pratiques médicales, Lille, France.ORCID https://orcid.org/0000-0002-7077-7267
Richard DayUniversity of New South Wales, Randwick, Australia.ORCID https://orcid.org/0000-0002-6045-6937
Rosemary BurkeSydney Local Health District, Sydney, Australia.ORCID https://orcid.org/0000-0002-5396-8977
Sepehr ShakibRoyal Adelaide Hospital, Adelaide, Australia.ORCID https://orcid.org/0000-0002-7199-5733
Young KuHunter New England Local Health District, Newcastle, Australia.ORCID https://orcid.org/0000-0002-6962-4431
Hannah Reid-AndersonMacquarie University Hospital, Sydney, Australia.ORCID https://orcid.org/0000-0001-5287-4154
Melissa BaysariThe University of Sydney, Faculty of Medicine and Health, School of Medical Sciences, Biomedical Informatics and Digital Health, Sydney, Australia.ORCID https://orcid.org/0000-0003-1645-9126

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIt is well known that recommendations from electronic medication alerts are seldom accepted or acted on by users. Key factors affecting the effectiveness of medication alerts include system usability and alert design. Thus, human factors principles that apply knowledge of human capabilities and limitations are increasingly used in the design of health technology to improve the usability of systems.

objectiveThis study aims to evaluate a newly developed evidence-based self-assessment tool that allows the valid and reliable evaluation of computerized medication alerting systems. This tool was developed to be used by hospital staff with detailed knowledge of their hospital's computerized provider order entry system and alerts to identify and address potential system deficiencies. In this initial assessment, we aim to determine whether the items in the tool can measure compliance of medication alerting systems with human factors principles of design, the tool can be consistently used by multiple users to assess the same system, and the items are easy to understand and perceived to be useful for assessing medication alerting systems.

methodsThe Tool for Evaluating Medication Alerting Systems (TEMAS) was developed based on human factors design principles and consisted of 66 items. In total, 18 staff members recruited across 6 hospitals used the TEMAS to assess their medication alerting systems. Data collected from participant assessments were used to evaluate the validity, reliability, and usability of the TEMAS. Validity was assessed by comparing the results of the TEMAS with those of prior in-house evaluations. Reliability was measured using Krippendorff α to determine agreement among assessors. A 7-item survey was used to determine usability.

resultsThe participants reported mostly negative (n=8) and neutral (n=7) perceptions of alerts in their medication alerting system. However, the validity of the TEMAS could not be directly tested, as participants were unaware of any results from prior in-house evaluations. The reliability of the TEMAS, as measured by Krippendorff α, was low to moderate (range 0.26-0.46); however, participant feedback suggests that individuals' knowledge of the system varied according to their professional background. In terms of usability, 61% (11/18) of participants reported that the TEMAS items were generally easy to understand; however, participants suggested the revision of 22 items to improve clarity.

conclusionsThis initial assessment of the TEMAS allowed the identification of its components that required modification to improve usability and usefulness. It also revealed that for the TEMAS to be effective in facilitating a comprehensive assessment of a medication alerting system, it should be completed by a multidisciplinary team of hospital staff from both clinical and technical backgrounds to maximize their knowledge of systems.

Indexed as

assessment tooldecision supporthuman factorsmedication alertsusability flaws

Identifiers

PMID34269680
PMCPMC8325080

What OpenQuestion holds

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LicenceCC BY
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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.