Evidence map›Paper›PMID 36013262›Full record

ArticleJournal of personalized medicine2022

A Mixed-Methods Protocol to Identify Best Practices for Implementing Pharmacogenetic Testing in Clinical Settings.

Nina R Sperber, Deborah Cragun, Megan C Roberts, Lisa M Bendz, Parker Ince, Sarah Gonzales, Susanne B Haga, R Ryanne Wu, Natasha J Petry, Laura Ramsey and 1 more

Abstract read
In one paragraph

Article in Journal of personalized medicine, 2022. 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

11 authors.

Nina R SperberDepartment of Population Health Sciences, School of Medicine, Duke University, Durham, NC 27701, USA.ORCID 0000-0001-6640-2510
Deborah CragunCollege of Public Health, University of South Florida, Tampa, FL 33612, USA.
Megan C RobertsUNC Eshelman School of Pharmacy, University of North Carolina-Chapel Hill, Chapel Hill, NC 27599, USA.
Lisa M BendzCenter for Medication Policy and Drug Information, Department of Pharmacy, Duke University Hospital, Durham, NC 27710, USA.
Parker InceDepartment of Population Health Sciences, School of Medicine, Duke University, Durham, NC 27701, USA.
Sarah GonzalesDepartment of Population Health Sciences, School of Medicine, Duke University, Durham, NC 27701, USA.ORCID 0000-0002-7860-3341
Susanne B HagaDepartment of Medicine, Duke University, Durham, NC 27701, USA.
R Ryanne WuDurham VA Health Care System, Durham, NC 27705, USA.ORCID 0000-0002-7655-3096
Natasha J PetrySchool of Pharmacy, North Dakota State University/Sanford Health Imagenetics, Fargo, ND 58108, USA.ORCID 0000-0001-5089-9286
Laura RamseyDepartment of Pediatrics, Divisions of Clinical Pharmacology and Research in Patient Services, University of Cincinnati College of Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA.ORCID 0000-0001-6417-3961
Ryley UberCenter for Pharmacy Innovation and Outcomes, Geisinger, Danville, CA 17822, USA.

Funding

Implementing Pharmacogenomics in Diverse Health Care SystemsR21HG011337 · NHGRI · DUKE UNIVERSITY · PI SPERBER, NINA · 2021 to 2021
$455k
HSRD VA CIN 13-410NHGRI NIH HHS R21 HG011337NIH HHS 1R21-HG011337-01A1
6 · The paper itself

Abstract

Using a patient's genetic information to inform medication prescriptions can be clinically effective; however, the practice has not been widely implemented. Health systems need guidance on how to engage with providers to improve pharmacogenetic test utilization. Approaches from the field of implementation science may shed light on the complex factors affecting pharmacogenetic test use in real-world settings and areas to target to improve utilization. This paper presents an approach to studying the application of precision medicine that utilizes mixed qualitative and quantitative methods and implementation science frameworks to understand which factors or combinations consistently account for high versus low utilization of pharmocogenetic testing. This approach involves two phases: (1) collection of qualitative and quantitative data from providers-the cases-at four clinical institutions about their experiences with, and utilization of, pharmacogenetic testing to identify salient factors; and (2) analysis using a Configurational Comparative Method (CCM), using a mathematical algorithm to identify the minimally necessary and sufficient factors that distinguish providers who have higher utilization from those with low utilization. Advantages of this approach are that it can be used for small to moderate sample sizes, and it accounts for conditions found in real-world settings by demonstrating how they coincide to affect utilization.

Indexed as

coincidence analysisconfigurational comparative methodshealth services researchimplementation sciencemixed methodspharmacogenomics

Identifiers

PMID36013262
PMCPMC9410119

What OpenQuestion holds

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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.