Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/24846
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dc.contributor.authorGrant, Aileenen_UK
dc.contributor.authorDreischulte, Tobiasen_UK
dc.contributor.authorGuthrie, Bruceen_UK
dc.date.accessioned2017-04-20T23:05:07Z-
dc.date.available2017-04-20T23:05:07Z-
dc.date.issued2017-01-07en_UK
dc.identifier.other4en_UK
dc.identifier.urihttp://hdl.handle.net/1893/24846-
dc.description.abstractBackground  Two to 4% of emergency hospital admissions are caused by preventable adverse drug events. The estimated costs of such avoidable admissions in England were £530 million in 2015. The data-driven quality improvement in primary care (DQIP) intervention was designed to prompt review of patients vulnerable from currently prescribed non-steroidal anti-inflammatory drugs (NSAIDs) and anti-platelets and was found to be effective at reducing this prescribing. A process evaluation was conducted parallel to the trial, and this paper reports the analysis which aimed to explore response to the intervention delivered to clusters in relation to participants’ perceptions about which intervention elements were active in changing their practice.  Methods  Data generation was by in-depth interview with key staff exploring participant’s perceptions of the intervention components. Analysis was iterative using the framework technique and drawing on normalisation process theory.  Results  All the primary components of the intervention were perceived as active, but at different stages of implementation: financial incentives primarily supported recruitment; education motivated the GPs to initiate implementation; the informatics tool facilitated sustained implementation. Participants perceived the primary components as interdependent. Intervention subcomponents also varied in whether and when they were active. For example, run charts providing feedback of change in prescribing over time were ignored in the informatics tool, but were motivating in some practices in the regular e-mailed newsletter. The high-risk NSAID and anti-platelet prescribing targeted was accepted as important by all interviewees, and this shared understanding was a key wider context underlying intervention effectiveness.  Conclusions  This was a novel use of process evaluation data which examined whether and how the individual intervention components were effective from the perspective of the professionals delivering changed care to patients. These findings are important for reproducibility and roll-out of the intervention.en_UK
dc.language.isoenen_UK
dc.publisherBioMed Centralen_UK
dc.relationGrant A, Dreischulte T & Guthrie B (2017) Process evaluation of the data-driven quality improvement in primary care (DQIP) trial: active and less active ingredients of a multi-component complex intervention to reduce high-risk primary care prescribing. Implementation Science, 12 (1), Art. No.: 4. https://doi.org/10.1186/s13012-016-0531-2en_UK
dc.rights© The Author(s). 2017 This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.en_UK
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_UK
dc.subjectGeneral practiceen_UK
dc.subjectFamily practiceen_UK
dc.subjectPrescribingen_UK
dc.subjectQuality and safetyen_UK
dc.subjectRandomised controlled trialsen_UK
dc.subjectProcess evaluationen_UK
dc.titleProcess evaluation of the data-driven quality improvement in primary care (DQIP) trial: active and less active ingredients of a multi-component complex intervention to reduce high-risk primary care prescribingen_UK
dc.typeJournal Articleen_UK
dc.identifier.doi10.1186/s13012-016-0531-2en_UK
dc.identifier.pmid28061794en_UK
dc.citation.jtitleImplementation Scienceen_UK
dc.citation.issn1748-5908en_UK
dc.citation.volume12en_UK
dc.citation.issue1en_UK
dc.citation.publicationstatusPublisheden_UK
dc.citation.peerreviewedRefereeden_UK
dc.type.statusVoR - Version of Recorden_UK
dc.contributor.funderScottish Government Chief Scientist Officeen_UK
dc.author.emailaileen.grant@stir.ac.uken_UK
dc.citation.date07/01/2017en_UK
dc.contributor.affiliationHealth Sciences Stirlingen_UK
dc.contributor.affiliationNHS Taysideen_UK
dc.contributor.affiliationUniversity of Dundeeen_UK
dc.identifier.isiWOS:000395704800001en_UK
dc.identifier.scopusid2-s2.0-85010216419en_UK
dc.identifier.wtid537739en_UK
dc.contributor.orcid0000-0001-6146-101Xen_UK
dc.date.accepted2016-12-06en_UK
dcterms.dateAccepted2016-12-06en_UK
dc.date.filedepositdate2017-01-20en_UK
rioxxterms.apcnot requireden_UK
rioxxterms.typeJournal Article/Reviewen_UK
rioxxterms.versionVoRen_UK
local.rioxx.authorGrant, Aileen|0000-0001-6146-101Xen_UK
local.rioxx.authorDreischulte, Tobias|en_UK
local.rioxx.authorGuthrie, Bruce|en_UK
local.rioxx.projectProject ID unknown|Scottish Government Chief Scientist Office|en_UK
local.rioxx.freetoreaddate2017-01-26en_UK
local.rioxx.licencehttp://creativecommons.org/licenses/by/4.0/|2017-01-26|en_UK
local.rioxx.filenameGrant_et_al-2016-DQIP PE Paper 1 Implementation_Science.pdfen_UK
local.rioxx.filecount1en_UK
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