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Process evaluation of the Data-driven Quality Improvement in Primary Care (DQIP) trial: quantitative examination of variation between practices in recruitment, implementation and effectiveness.

ABSTRACT: OBJECTIVES:The cluster randomised trial of the Data-driven Quality Improvement in Primary Care (DQIP) intervention showed that education, informatics and financial incentives for general medical practices to review patients with ongoing high-risk prescribing of non-steroidal anti-inflammatory drugs and antiplatelets reduced the primary end point of high-risk prescribing by 37%, where both ongoing and new high-risk prescribing were significantly reduced. This quantitative process evaluation examined practice factors associated with (1) participation in the DQIP trial, (2) review activity (extent and nature of documented reviews) and (3) practice level effectiveness (relative reductions in the primary end point). SETTING/PARTICIPANTS:Invited practices recruited (n=33) and not recruited (n=32) to the DQIP trial in Scotland, UK. OUTCOME MEASURES:(1) Characteristics of recruited versus non-recruited practices. Associations of (2) practice characteristics and 'adoption' (self-reported implementation work done by practices) with documented review activity and (3) of practice characteristics, DQIP adoption and review activity with effectiveness. RESULTS:(1) Recruited practices had lower performance in the quality and outcomes framework than those declining participation. (2) Not being an approved general practitioner training practice and higher self-reported adoption were significantly associated with higher review activity. (3) Effectiveness ranged from a relative increase in high-risk prescribing of 24.1% to a relative reduction of 77.2%. High-risk prescribing and DQIP adoption (but not documented review activity) were significantly associated with greater effectiveness in the final multivariate model, explaining 64.0% of variation in effectiveness. CONCLUSIONS:Intervention implementation and effectiveness of the DQIP intervention varied substantially between practices. Although the DQIP intervention primarily targeted review of ongoing high-risk prescribing, the finding that self-reported DQIP adoption was a stronger predictor of effectiveness than documented review activity supports that reducing initiation and/or re-initiation of high-risk prescribing is key to its effectiveness. TRIAL REGISTRATION NUMBER:NCT01425502; Post-results.

SUBMITTER: Dreischulte T

PROVIDER: S-EPMC5780698 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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Process evaluation of the Data-driven Quality Improvement in Primary Care (DQIP) trial: quantitative examination of variation between practices in recruitment, implementation and effectiveness.

Dreischulte Tobias T Grant Aileen A Hapca Adrian A Guthrie Bruce B

BMJ open 20180105 1

<h4>Objectives</h4>The cluster randomised trial of the Data-driven Quality Improvement in Primary Care (DQIP) intervention showed that education, informatics and financial incentives for general medical practices to review patients with ongoing high-risk prescribing of non-steroidal anti-inflammatory drugs and antiplatelets reduced the primary end point of high-risk prescribing by 37%, where both ongoing and new high-risk prescribing were significantly reduced. This quantitative process evaluati ...[more]

PMID: 29306877

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Project description:BACKGROUND: The European Practice Assessment program provides feedback and outreach visits to primary care practices to facilitate quality improvement in five domains (infrastructure, people, information, finance, and quality and safety). We examined the effectiveness of this program in improving management in primary care practices in Germany, with a focus on the domain of quality and safety. METHODS: In a before-after study, 102 primary care practices completed a practice assessment using the European Practice Assessment instrument at baseline and three years later (intervention group). A comparative group of 102 practices was included that completed their first assessment using this instrument at the time of the intervention group's second assessment. Mean scores were based on the proportion of indicators for which a positive response was achieved by all of the practices, on a scale of 0 to 100. RESULTS: We found significant improvements in all domains between the first and second assessments in the intervention group. In the domain of quality and safety, improvements in scores (mean scores were based on the proportion of indicators for which a positive response was achieved by all of the practices, on a scale of 0 to 100) were observed in the following dimensions: complaint management (from a mean score of 51.2 at first assessment to 80.7 at second assessment); analysis of critical incidents (from 79.1 to 89.6); and quality development, quality policy (from 40.7 to 55.6). Overall scores at the time of the second assessment were significantly higher in the intervention group than in the comparative group. INTERPRETATION: Primary care practices that completed the European Practice Assessment instrument twice over a three-year period showed improvements in practice management. Our findings show the value of the quality-improvement cycle in the context of practice assessment and the use of established organizational standards for practice management with the Europeaen Practice Assessment.

Project description:IntroductionThe coronavirus disease 2019 (COVID-19) pandemic presents unique challenges to frontline healthcare workers. In order to safely care for patients new processes, such as a plan for the airway management of a patient with COVID-19, must be implemented and disseminated in a rapid fashion. The use of in-situ simulation has been used to assist in latent problem identification as part of a Plan-Do-Study-Act cycle. Additionally, simulation is an effective means for training teams to perform high-risk procedures before engaging in the actual procedure. This educational advance seeks to use and study in-situ simulation as a means to rapidly implement a process for airway management in patients with COVID-19.MethodsUsing an airway algorithm developed by the authors, we designed an in-situ simulation scenario to train physicians, nurses, and respiratory therapists in best practices for airway management of patients with COVID-19. Physician participants were surveyed using a five-point Likert scale with regard to their comfort level with various aspects of the airway algorithm both before and after the simulation in a retrospective fashion. Additionally, we obtained feedback from all participants and used it to refine the airway algorithm.ResultsOver a two-week period, 93 physicians participated in the simulation. We received 81 responses to the survey (87%), which showed that the average level of comfort with personal protective equipment procedures increased significantly from 2.94 (95% confidence interval, 2.71-3.17) to 4.36 (4.24-4.48), a difference of 1.42 (1.20-1.63, p < 0.001). There was a significant increase in average comfort level in understanding the physician role with scores increasing from 3.51 (3.26-3.77) to 4.55 (2.71-3.17), a difference of 1.04 (0.82-1.25, p < 0.001). There was also increased comfort in performing procedural tasks such as intubation, from 3.08 (2.80-3.35) to 4.38 (4.23-4.52) after the simulation, a difference of 1.30 points (1.06-1.54, p < 0.001). Feedback from the participants also led to refinement of the airway algorithm.ConclusionWe successfully implemented a new airway management guideline for patients with suspected COVID-19. In-situ simulation is an essential tool for both dissemination and onboarding, as well as process improvement, in the context of an epidemic or pandemic.

Project description:BackgroundA culture of improvement is an important feature of high-quality health care systems. However, health care teams often need support to translate quality improvement (QI) activities into practice. One method of support is consultation from a QI coach. The literature suggests that coaching interventions have a positive impact on clinical outcomes. However, the impact of coaching on specific process outcomes, like adoption of clinical care activities, is unknown. Identifying the process outcomes for which QI coaching is most effective could provide specific guidance on when to employ this strategy.MethodsWe searched multiple databases from inception through July 2021. Studies that addressed the effects of QI coaching on process of care outcomes were included. Two reviewers independently extracted study characteristics and assessed risk of bias. Certainty of evidence was assessed using GRADE.ResultsWe identified 1983 articles, of which 23 cluster-randomized trials met eligibility criteria. All but two took place in a primary care setting. Overall, interventions typically targeted multiple simultaneous processes of care activities. We found that coaching probably has a beneficial effect on composite process of care outcomes (n = 9) and ordering of labs and vital signs (n = 6), and possibly has a beneficial effect on changes in organizational process of care (n = 5), appropriate documentation (n = 5), and delivery of appropriate counseling (n = 3). We did not perform meta-analyses because of conceptual heterogeneity around intervention design and outcomes; rather, we synthesized the data narratively. Due to imprecision, inconsistency, and high risk of bias of the included studies, we judged the certainty of these results as low or very low.ConclusionQI coaching interventions may affect certain processes of care activities such as ordering of labs and vital signs. Future research that advances the identification of when QI coaching is most beneficial for health care teams seeking to implement improvement processes in pursuit of high-quality care will support efficient use of QI resources.Protocol registrationThis study was registered and followed a published protocol (PROSPERO: CRD42020165069).

Project description:PurposeThe purpose of this study was to improve the quality of items on the Korean Nursing Licensing Examination by developing and evaluating case-based items that reflect integrated nursing knowledge.MethodsWe conducted a cross-sectional observational study to develop new case-based items. The methods for developing test items included expert workshops, brainstorming, and verification of content validity. After a mock examination of undergraduate nursing students using the newly developed case-based items, we evaluated the appropriateness of the items through classical test theory and item response theory.ResultsA total of 50 case-based items were developed for the mock examination, and content validity was evaluated. The question items integrated 34 discrete elements of integrated nursing knowledge. The mock examination was taken by 741 baccalaureate students in their fourth year of study at 13 universities. Their average score on the mock examination was 57.4, and the examination showed a reliability of 0.40. According to classical test theory, the average level of item difficulty of the items was 57.4% (80%-100% for 12 items; 60%-80% for 13 items; and less than 60% for 25 items). The mean discrimination index was 0.19, and was above 0.30 for 11 items and 0.20 to 0.29 for 15 items. According to item response theory, the item discrimination parameter (in the logistic model) was none for 10 items (0.00), very low for 20 items (0.01 to 0.34), low for 12 items (0.35 to 0.64), moderate for 6 items (0.65 to 1.34), high for 1 item (1.35 to 1.69), and very high for 1 item (above 1.70). The item difficulty was very easy for 24 items (below -2.0), easy for 8 items (-2.0 to -0.5), medium for 6 items (-0.5 to 0.5), hard for 3 items (0.5 to 2.0), and very hard for 9 items (2.0 or above). The goodness-of-fit test in terms of the 2-parameter item response model between the range of 2.0 to 0.5 revealed that 12 items had an ideal correct answer rate.ConclusionWe surmised that the low reliability of the mock examination was influenced by the timing of the test for the examinees and the inappropriate difficulty of the items. Our study suggested a methodology for the development of future case-based items for the Korean Nursing Licensing Examination.

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Dataset Information

Process evaluation of the Data-driven Quality Improvement in Primary Care (DQIP) trial: quantitative examination of variation between practices in recruitment, implementation and effectiveness.

Publications

Process evaluation of the Data-driven Quality Improvement in Primary Care (DQIP) trial: quantitative examination of variation between practices in recruitment, implementation and effectiveness.

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