Evidence map›Paper›PMID 33962988›Full record

ArticleBMJ health & care informatics2021

User testing of a diagnostic decision support system with machine-assisted chart review to facilitate clinical genomic diagnosis.

Alanna Kulchak Rahm, Nephi A Walton, Lynn K Feldman, Conner Jenkins, Troy Jenkins, Thomas N Person, Joeseph Peterson, Jonathon C Reynolds, Peter N Robinson, Makenzie A Woltz and 2 more

Abstract read
In one paragraph

Article in BMJ health & care informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 2 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

4 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  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

12 authors.

Alanna Kulchak RahmGenomic Medicine Institute, Geisinger Health System, Danville, Pennsylvania, USA akrahm@geisinger.edu.ORCID http://orcid.org/0000-0003-2513-9298
Nephi A WaltonIntermountain Precision Genomics, Intermountain Healthcare, St. George, Utah, USA.
Lynn K FeldmanSimulConsult, Inc, Chestnut Hill, Massachusetts, USA.
Conner JenkinsUniversity of Utah, Salt Lake City, Utah, USA.
Troy JenkinsUniversity of Utah, Salt Lake City, Utah, USA.
Thomas N PersonGenomic Medicine Institute, Geisinger Health System, Danville, Pennsylvania, USA.
Joeseph PetersonUniversity of Utah, Salt Lake City, Utah, USA.
Jonathon C ReynoldsGenomic Medicine Institute, Geisinger Health System, Danville, Pennsylvania, USA.
Peter N RobinsonJackson Laboratory for Genomic Medicine, Farmington, Connecticut, USA.
Makenzie A WoltzGenomic Medicine Institute, Geisinger Health System, Danville, Pennsylvania, USA.
Marc S WilliamsGenomic Medicine Institute, Geisinger Health System, Danville, Pennsylvania, USA.
Michael M SegalSimulConsult, Inc, Chestnut Hill, Massachusetts, USA.

Funding

A Genotype-Phenotype Archiving and Communication SystemR43HG010322 · NHGRI · PHENOSOLVE, LLC · PI SEGAL, MICHAEL M, WILLIAMS, MARC S. · 2018 to 2018
$300k
NHGRI NIH HHS R43 HG010322
6 · The paper itself

Abstract

objectivesThere is a need in clinical genomics for systems that assist in clinical diagnosis, analysis of genomic information and periodic reanalysis of results, and can use information from the electronic health record to do so. Such systems should be built using the concepts of human-centred design, fit within clinical workflows and provide solutions to priority problems.

methodsWe adapted a commercially available diagnostic decision support system (DDSS) to use extracted findings from a patient record and combine them with genomic variant information in the DDSS interface. Three representative patient cases were created in a simulated clinical environment for user testing. A semistructured interview guide was created to illuminate factors relevant to human factors in CDS design and organisational implementation.

resultsSix individuals completed the user testing process. Tester responses were positive and noted good fit with real-world clinical genetics workflow. Technical issues related to interface, interaction and design were minor and fixable. Testers suggested solving issues related to terminology and usability through training and infobuttons. Time savings was estimated at 30%-50% and additional uses such as in-house clinical variant analysis were suggested for increase fit with workflow and to further address priority problems.

conclusionThis study provides preliminary evidence for usability, workflow fit, acceptability and implementation potential of a modified DDSS that includes machine-assisted chart review. Continued development and testing using principles from human-centred design and implementation science are necessary to improve technical functionality and acceptability for multiple stakeholders and organisational implementation potential to improve the genomic diagnosis process.

Indexed as

Decision Support Systems, ClinicalElectronic Health RecordsGenomicsHumansNatural Language ProcessingTerminology as TopicTime FactorsUser-Centered Designhealth carepatient care

Identifiers

PMID33962988
PMCPMC8108675

What OpenQuestion holds

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LicenceCC BY-NC
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.