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Background: In 2014, nursing home administration and government officials were facing increasing public and media scrutiny around the variation of antipsychotic medication (APM) prescribing across Ontario nursing homes. In response, policy makers partnered to test an academic detailing (AD) intervention to address appropriate prescribing of APM in nursing homes in a cluster-randomized trial. This mixed-methods study aimed to explore how and why the AD intervention may have resulted in changes in the nursing home context. The objectives were to understand how the intervention was implemented, explore contextual factors associated with implementation, and examine impact of the intervention on prescribing.Methods: Administrative data for the primary outcome of the full randomized trial will not be available for a minimum of 1 year. Therefore, this paper reports the findings of a planned, quantitative interim trial analysis assessed mean APM dose and prescribing prevalence at baseline and 3 and 6 months across 40 nursing homes (18 intervention, 22 control). Patient-level administrative data regarding prescribing were analyzed using generalized linear mixed effects regression. Semi-structured interviews were conducted with nursing home staff from the intervention group to explore opinions and experiences of the AD intervention. Interviews were analyzed using the framework method, with constructs from the Consolidated Framework for Implementation Research (CFIR) applied as pre-defined deductive codes. Open coding was applied when emerging themes did not align with CFIR constructs. Qualitative and quantitative findings were triangulated to examine points of divergence to understand how the intervention may work and to identify areas for future opportunities and areas for improvement.Results: No significant differences were observed in prescribing outcomes. A total of 22 interviews were conducted, including four academic detailers and 18 nursing home staff. Constructs within the CFIR domains of Outer Setting, Inner Setting, and Characteristics of Individuals presented barriers to antipsychotic prescribing. Intervention Source, Evidence Strength and Quality, and Adaptability explained participant engagement in the AD intervention; nursing homes that exhibited a Tension for Change and Leadership Engagement reported positive changes in processes and communication.Conclusions: Participants described their experiences with the intervention against the backdrop of a range of factors that influence APM prescribing in nursing homes that exist at the system, facility, provider, and resident levels. In this context, the perceived credibility and flexibility of the intervention were critical features that explained engagement with and potential impact of the intervention. Development of a common language across the team to enable communication was reported as a proximal outcome that may eventually have an effect on APM prescribing rates. Process evaluations may be useful during early stages of evaluation to understand how the intervention is working and how it might work better. Qualitative results suggest the lack of early changes observed in prescribing may reflect the number of upstream factors that need to change for APM rates to decrease.Trial Registration: ClinicalTrials.gov, NCT02604056. [ABSTRACT FROM AUTHOR]

Background: 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.Trial Registration: ClinicalTrials.gov, NCT01425502 . [ABSTRACT FROM AUTHOR]

Background: Intentions play a central role in numerous empirically supported theories of behavior and behavior change and have been identified as a potentially important antecedent to successful evidence-based treatment (EBT) implementation. Despite this, few measures of mental health clinicians' EBT intentions exist and available measures have not been subject to thorough psychometric evaluation or testing. This paper evaluates the psychometric properties of the evidence-based treatment intentions (EBTI) scale, a new measure of mental health clinicians' intentions to adopt EBTs.Methods: The study evaluates the reliability and validity of inferences made with the EBTI using multi-method, multi-informant criterion variables collected over 12 months from a sample of 197 mental health clinicians delivering services in 13 mental health agencies. Structural, predictive, and discriminant validity evidence is assessed.Results: Findings support the EBTI's factor structure (χ (2) = 3.96, df = 5, p = .556) and internal consistency reliability (α = .80). Predictive validity evidence was provided by robust and significant associations between EBTI scores and clinicians' observer-reported attendance at a voluntary EBT workshop at a 1-month follow-up (OR = 1.92, p < .05), self-reported EBT adoption at a 12-month follow-up (R (2) = .17, p < .001), and self-reported use of EBTs with clients at a 12-month follow-up (R (2) = .25, p < .001). Discriminant validity evidence was provided by small associations with clinicians' concurrently measured psychological work climate perceptions of functionality (R (2) = .06, p < .05), engagement (R (2) = .06, p < .05), and stress (R (2) = .00, ns).Conclusions: The EBTI is a practical and theoretically grounded measure of mental health clinicians' EBT intentions. Scores on the EBTI provide a basis for valid inferences regarding mental health clinicians' intentions to adopt EBTs. Discussion focuses on research and practice applications. [ABSTRACT FROM AUTHOR]

Background: Health system guidance (HSG) provides recommendations aimed to address health system challenges. However, there is a paucity of methods to direct, appraise, and report HSG. Earlier research identified 30 candidate criteria (concepts) that can be used to evaluate the quality of HSG and guide development and reporting requirements. The objective of this paper was to describe two studies aimed at evaluating the importance of these 30 criteria, design a draft HSG appraisal tool, and test its usability.Methods: This study involved a two-step survey process. In step 1, respondents rated the 30 concepts for appropriateness to, relevance to, and priority for health system decisions and HSG. This led to a draft tool. In step 2, respondents reviewed HSG documents, appraised them using the tool, and answered a series of questions. Descriptive analyses were computed.Results: Fifty participants were invited in step 1, and we had a response rate of 82 %. The mean response rates for each concept within each survey question were universally favorable. There was also an overall agreement about the need for a high-quality tool to systematically direct the development, appraisal, and reporting of HSG. Qualitative feedback and a consensus process by the team led to refinements to some of the concepts and the creation of a beta (draft) version of the HSG tool. In step 2, 35 participants were invited and we had a response rate of 74 %. Exploratory analyses showed that the quality of the HSGs reviewed varied as a function of the HSG item and the specific document assessed. A favorable consensus was reached with participants agreeing that the HSG items were easy to understand and easy to apply. Moreover, the overall agreement was high for the usability of the tool to systematically direct the development (85 %), appraisal (92 %), and reporting (81 %) of HSG. From this process, version 1.0 of the HSG appraisal tool was generated complete with 32 items (and their descriptions) and 4 domains.Conclusions: The final tool, named the Appraisal of Guidelines for Research and Evaluation for Health Systems (AGREE-HS) (version 1), defines expectations of HSG and facilitates informed decisions among policymakers on health system delivery, financial, and governance arrangements. [ABSTRACT FROM AUTHOR]

Background: The translation of healthcare research into practice is typically challenging and limited in effectiveness. The Theoretical Domains Framework (TDF) identifies 12 domains of behaviour determinants which can be used to understand the principles of behavioural change, a key factor influencing implementation. The Accelerated Chest pain Risk Evaluation (ACRE) project has successfully translated research into practice, by implementing an intervention to improve the assessment of low to intermediate risk patients presenting to emergency departments (EDs) with chest pain. The aims of this paper are to describe use of the TDF to determine which factors successfully influenced implementation and to describe use of the TDF as a tool to evaluate implementation efforts and which domains are most relevant to successful implementation.Methods: A 30-item questionnaire targeting clinicians was developed using the TDF as a guide. Questions encompassed ten of the domains of the TDF: Knowledge; Skills; Social/professional role and identity; Beliefs about capabilities; Optimism; Beliefs about consequences; Intentions; Memory, attention and decision processes; Environmental context and resources; and Social influences.Results: Sixty-three of 176 stakeholders (36 %) responded to the questionnaire. Responses for all scales showed that respondents were highly favourable to all aspects of the implementation. Scales with the highest mean responses were Intentions, Knowledge, and Optimism, suggesting that initial education and awareness strategies around the ACRE project were effective. Scales with the lowest mean responses were Environmental context and resources, and Social influences, perhaps highlighting that implementation planning could have benefitted from further consideration of the factors underlying these scales.Conclusions: The ACRE project was successful, and therefore, a perfect case study for understanding factors which drive implementation success. The overwhelmingly positive response suggests that it was a successful programme and likely that each of these domains was important for the implementation. However, a lack of variance in the responses hampered us from concluding which factors were most influential in driving the success of the implementation. The TDF offers a useful framework to conceptualise and evaluate factors impacting on implementation success. However, its broad scope makes it necessary to tailor the framework to allow evaluation of specific projects. [ABSTRACT FROM AUTHOR]