Evidence map›Paper›PMID 28339805›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2017

Design and evaluation of a pharmacogenomics information resource for pharmacists.

Katrina M Romagnoli, Richard D Boyce, Philip E Empey, Yifan Ning, Solomon Adams, Harry Hochheiser

Abstract readEvaluation Study
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

6 authors.

Katrina M RomagnoliDepartment of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
Richard D BoyceDepartment of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
Philip E EmpeySchool of Pharmacy, University of Pittsburgh.
Yifan NingDepartment of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
Solomon AdamsSchool of Pharmacy, University of Pittsburgh.
Harry HochheiserDepartment of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.

Funding

The internship in Biomedical Research, Informatics, and Computer Science (iBRIC): Biomedical Informatics and Data Science research experiences for students from Minority Serving InstitutionsT15LM007059 · NLM · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI HARRY S HOCHHEISER · 1987 to 2026
$23.9M
Addressing gaps in clinically useful evidence on drug-drug interactionsR01LM011838 · NLM · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI BOYCE, RICHARD DAVID · 2014 to 2017
$1.6M
Improving medication safety for nursing home residents prescribed psychotropic drK01AG044433 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI BOYCE, RICHARD DAVID · 2014 to 2016
$342k
AHRQ HHS K12 HS019461NIA NIH HHS K01 AG044433NLM NIH HHS R01 LM011838NLM NIH HHS T15 LM007059
6 · The paper itself

Abstract

objectiveTo develop and evaluate a pharmacogenomics information resource for pharmacists. MATERIALS AND

methodsWe built a pharmacogenomics information resource presenting Food and Drug Administration (FDA) drug product labelling information, refined it based on feedback from pharmacists, and conducted a comparative usability evaluation, measuring task completion time, task correctness and perceived usability. Tasks involved hypothetical clinical situations requiring interpretation of pharmacogenomics information to determine optimal prescribing for specific patients.

resultsPharmacists were better able to perform certain tasks using the redesigned resource relative to the Pharmacogenomic Knowledgebase (PharmGKB) and the FDA Table of Pharmacogenomic Biomarkers in Drug Labeling. On average, participants completed tasks in 107.5 s using our resource, compared to 188.9 s using PharmGKB and 240.2 s using the FDA table. Using the System Usability Scale, participants rated our resource 79.62 on average, compared to 53.27 for PharmGKB and 50.77 for the FDA table. Participants found the correct answers for 100% of tasks using our resource, compared to 76.9% using PharmGKB and 69.2% using the FDA table. DISCUSSION: We present structured, clinically relevant pharmacogenomic FDA drug product label information with visualizations to help explain the relationships between gene variants, drugs, and phenotypes. The results from our evaluation suggest that user-centered interfaces for pharmacogenomics information can increase ease of access and comprehension.

conclusionA clinician-focused pharmacogenomics information resource can answer pharmacogenomics-related medication questions faster, more correctly, and more easily than widely used alternatives, as perceived by pharmacists.

Indexed as

Databases, FactualDrug LabelingPharmacistsPharmacogeneticsFemaleHumansMaleTask Performance and AnalysisUnited StatesUnited States Food and Drug Administrationclinical decision makingevaluationpharmacistpharmacogenomicsstructured product labelingusability

Identifiers

PMID28339805
PMCPMC6080676

What OpenQuestion holds

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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.