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Explaining clinical behaviors using multiple theoretical models
Authors:Martin P Eccles  Jeremy M Grimshaw  Graeme MacLennan  Debbie Bonetti  Liz Glidewell  Nigel B Pitts  Nick Steen  Ruth Thomas  Anne Walker  Marie Johnston
Institution:1. Tayside Medicines Unit, NHS Tayside, Mackenzie Building, Kirsty Semple Way, Dundee, DD2 4BF, UK
2. Population Health Sciences, Quality, Safety and Informatics Research Group, University of Dundee, Mackenzie Building, Kirsty Semple Way, Dundee, DD2 4BF, UK
3. Dundee Epidemiology and Biostatistics Unit (DEBU), University of Dundee, Mackenzie Building, Kirsty Semple Way, Dundee, DD2 4BF, UK
4. University of Dundee, Perth Rd, Dundee, DD1 4HN, UK
Abstract:

Background

High-risk prescribing of non-steroidal anti-inflammatory drugs (NSAIDs) and antiplatelet agents accounts for a significant proportion of hospital admissions due to preventable adverse drug events. The recently completed PINCER trial has demonstrated that a one-off pharmacist-led information technology (IT)-based intervention can significantly reduce high-risk prescribing in primary care, but there is evidence that effects decrease over time and employing additional pharmacists to facilitate change may not be sustainable.

Methods/design

We will conduct a cluster randomised controlled with a stepped wedge design in 40 volunteer general practices in two Scottish health boards. Eligible practices are those that are using the INPS Vision clinical IT system, and have agreed to have relevant medication-related data to be automatically extracted from their electronic medical records. All practices (clusters) that agree to take part will receive the data-driven quality improvement in primary care (DQIP) intervention, but will be randomised to one of 10 start dates. The DQIP intervention has three components: a web-based informatics tool that provides weekly updated feedback of targeted prescribing at practice level, prompts the review of individual patients affected, and summarises each patient's relevant risk factors and prescribing; an outreach visit providing education on targeted prescribing and training in the use of the informatics tool; and a fixed payment of 350 GBP (560 USD; 403 EUR) up front and a small payment of 15 GBP (24 USD; 17 EUR) for each patient reviewed in the 12 months of the intervention. We hypothesise that the DQIP intervention will reduce a composite of nine previously validated measures of high-risk prescribing. Due to the nature of the intervention, it is not possible to blind practices, the core research team, or the data analyst. However, outcome assessment is entirely objective and automated. There will additionally be a process and economic evaluation alongside the main trial.

Discussion

The DQIP intervention is an example of a potentially sustainable safety improvement intervention that builds on the existing National Health Service IT-infrastructure to facilitate systematic management of high-risk prescribing by existing practice staff. Although the focus in this trial is on Non-steroidal anti-inflammatory drugs and antiplatelets, we anticipate that the tested intervention would be generalisable to other types of prescribing if shown to be effective.

Trial registration

ClinicalTrials.gov, dossier number: NCT01425502
Keywords:
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