Evidence map›Paper›PMID 24073246›Full record

ArticlePloS one2013

Detecting dissonance in clinical and research workflow for translational psychiatric registries.

Luciana Cofiel, Débora U Bassi, Ryan Kumar Ray, Ricardo Pietrobon, Helena Brentani

Abstract read
In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
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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

5 authors.

Luciana CofielDepartment of Psychiatry, University of São Paulo Medical School, São Paulo, São Paulo, Brazil.
Débora U Bassi
Ryan Kumar Ray
Ricardo Pietrobon
Helena Brentani

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe interplay between the workflow for clinical tasks and research data collection is often overlooked, ultimately making it ineffective. QUESTIONS/PURPOSES: To the best of our knowledge, no previous studies have developed standards that allow for the comparison of workflow models derived from clinical and research tasks toward the improvement of data collection processes.

methodsIn this study we used the term dissonance for the occurrences where there was a discord between clinical and research workflows. We developed workflow models for a translational research study in psychiatry and the clinic where its data collection was carried out. After identifying points of dissonance between clinical and research models we derived a corresponding classification system that ultimately enabled us to re-engineer the data collection workflow. We considered (1) the number of patients approached for enrollment and (2) the number of patients enrolled in the study as indicators of efficiency in research workflow. We also recorded the number of dissonances before and after the workflow modification.

resultsWe identified 22 episodes of dissonance across 6 dissonance categories: actor, communication, information, artifact, time, and space. We were able to eliminate 18 episodes of dissonance and increase the number of patients approached and enrolled in research study trough workflow modification.

conclusionThe classification developed in this study is useful for guiding the identification of dissonances and reveal modifications required to align the workflow of data collection and the clinical setting. The methodology described in this study can be used by researchers to standardize data collection process.

Indexed as

PsychiatryWorkflowAmbulatory Care FacilitiesAutistic DisorderData CollectionHumansModels, TheoreticalRegistriesResearch DesignResearch SubjectsTranslational Research, Biomedical

Identifiers

PMID24073246
PMCPMC3779159

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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.