Evidence map›Paper›PMID 32785904›Full record

ArticleApplied clinical informatics2020

Usability Testing a Potentially Inappropriate Medication Dashboard: A Core Component of the Dashboard Development Process.

Regina Richter Lagha, Zachary Burningham, Brian C Sauer, Jianwei Leng, Celena Peters, Tina Huynh, Shardool Patel, Ahmad S Halwani, B Josea Kramer

Open access · hybridAbstract read
In one paragraph

Article in Applied clinical informatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 3 pooled it
5.4field-weighted citation impact, top 5% 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

17 citing papers in PubMed, 3 syntheses or guidelines pooled it, 30 citations in OpenAlex.

  1. Pooled it
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  4. From Data to Decision: Design and Evaluation of a Patient Safety Dashboard.Medical journal of the Islamic Republic of Iran · 2025
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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 at 4 institutions in 1 country.

Regina Richter LaghaVeterans Affairs Greater Los Angeles Medical Center, Geriatric Research Education and Clinical Center, Los Angeles, California, United States.
Zachary BurninghamDivision of Epidemiology, Department of Internal Medicine, University of Utah, Salt Lake City, Utah, United States.
Brian C SauerDivision of Epidemiology, Department of Internal Medicine, University of Utah, Salt Lake City, Utah, United States.
Jianwei LengDivision of Epidemiology, Department of Internal Medicine, University of Utah, Salt Lake City, Utah, United States.
Celena PetersDivision of Epidemiology, Department of Internal Medicine, University of Utah, Salt Lake City, Utah, United States.
Tina HuynhDivision of Epidemiology, Department of Internal Medicine, University of Utah, Salt Lake City, Utah, United States.
Shardool PatelDivision of Epidemiology, Department of Internal Medicine, University of Utah, Salt Lake City, Utah, United States.
Ahmad S HalwaniSalt Lake City Veterans Affairs Medical Center, Health Services Research and Development Center, Salt Lake City, Utah, United States.
B Josea KramerVeterans Affairs Greater Los Angeles Medical Center, Geriatric Research Education and Clinical Center, Los Angeles, California, United States.
University of Utah · USHealth Services Research & Development · USGeriatric Research Education and Clinical Center · USLos Angeles Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWith the increased usage of dashboard reporting systems to monitor and track patient panels by clinical users, developers must ensure that the information displays they produce are accurate and intuitive. When evaluating usability of a clinical dashboard among potential end users, developers oftentimes rely on methods such as questionnaires as opposed to other, more time-intensive strategies that incorporate direct observation.

objectivesPrior to release of the potentially inappropriate medication (PIM) clinical dashboard, designed to facilitate completion of a quality improvement project by clinician scholars enrolled in the Veterans Affairs (VA) workforce development Geriatric Scholars Program (GSP), we evaluated the usability of the system. This article describes the process of usability testing a dashboard reporting system with clinicians using direct observation and think-aloud moderating techniques.

methodsWe developed a structured interview protocol that combines virtual observation, think-aloud moderating techniques, and retrospective questioning of the overall user experience, including use of the System Usability Scale (SUS). Thematic analysis was used to analyze field notes from the interviews of three GSP alumni.

resultsOur structured approach to usability testing identified specific functional problems with the dashboard reporting system that were missed by results from the SUS. Usability testing lead to overall improvements in the intuitive use of the system, increased data transparency, and clarification of the dashboard's purpose.

conclusionReliance solely on questionnaires and surveys at the end stages of dashboard development can mask potential functional problems that will impede proper usage and lead to misinterpretation of results. A structured approach to usability testing in the developmental phase is an important tool for developers of clinician friendly systems for displaying easily digested information and tracking outcomes for the purpose of quality improvement.

Indexed as

Potentially Inappropriate Medication ListData DisplayElectronic Health RecordsFeasibility StudiesHumansQuality ControlSurveys and QuestionnairesUser-Computer Interface

Identifiers

PMID32785904
PMCPMC7425799
OpenAlexW3048581229

What OpenQuestion holds

Textmetadata
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.