Detecting Dissonance in Clinical and Research Workflow for Translational Psychiatric Registries

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dc.contributorSistema FMUSP-HC: Faculdade de Medicina da Universidade de São Paulo (FMUSP) e Hospital das Clínicas da FMUSP
dc.contributor.authorCOFIEL, Luciana
dc.contributor.authorBASSI, Debora U.
dc.contributor.authorRAY, Ryan Kumar
dc.contributor.authorPIETROBON, Ricardo
dc.contributor.authorBRENTANI, Helena
dc.date.accessioned2014-01-28T22:26:34Z
dc.date.available2014-01-28T22:26:34Z
dc.date.issued2013
dc.description.abstractBackground: The 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 Methods: In 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. Results: We 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. Conclusion: The 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.
dc.description.indexMEDLINE
dc.description.sponsorshipFAPESP [2009/454220-6, 2011/05481-1]
dc.identifier.citationPLOS ONE, v.8, n.9, article ID e75167, 14p, 2013
dc.identifier.doi10.1371/journal.pone.0075167
dc.identifier.issn1932-6203
dc.identifier.urihttps://observatorio.fm.usp.br/handle/OPI/4210
dc.language.isoeng
dc.publisherPUBLIC LIBRARY SCIENCE
dc.relation.ispartofPlos One
dc.rightsopenAccess
dc.rights.holderCopyright PUBLIC LIBRARY SCIENCE
dc.subject.otherresearch data-collection
dc.subject.otherdata capture
dc.subject.othertechnology
dc.subject.otherautism
dc.subject.othercare
dc.subject.wosMultidisciplinary Sciences
dc.titleDetecting Dissonance in Clinical and Research Workflow for Translational Psychiatric Registries
dc.typearticle
dc.type.categoryoriginal article
dc.type.versionpublishedVersion
dspace.entity.typePublication
hcfmusp.affiliation.countryEstados Unidos
hcfmusp.affiliation.countryisous
hcfmusp.author.externalCOFIEL, Luciana:Univ Sao Paulo, Sch Med, Dept Psychiat, Sao Paulo, Brazil
hcfmusp.author.externalBASSI, Debora U.:Univ Sao Paulo, Sch Med, Dept Psychiat, Sao Paulo, Brazil
hcfmusp.author.externalRAY, Ryan Kumar:Univ Texas Sch Publ Hlth, Dept Management Policy & Community Hlth, Houston, TX USA
hcfmusp.author.externalPIETROBON, Ricardo:Duke Univ, Med Ctr, Dept Surg, Durham, NC 27710 USA
hcfmusp.citation.scopus5
hcfmusp.contributor.author-fmusphcHELENA PAULA BRENTANI
hcfmusp.description.articlenumbere75167
hcfmusp.description.issue9
hcfmusp.description.volume8
hcfmusp.origemWOS
hcfmusp.origem.pubmed24073246
hcfmusp.origem.scopus2-s2.0-84884494230
hcfmusp.origem.wosWOS:000324768000055
hcfmusp.publisher.citySAN FRANCISCO
hcfmusp.publisher.countryUSA
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