Changing antibiotic prescribing practices in outpatient primary care settings in China: Study protocol for a health information system-based cluster-randomised crossover controlled trial

Background The overuse and abuse of antibiotics is a major risk factor for antibiotic resistance in primary care settings of China. In this study, the effectiveness of an automatically-presented, privacy-protecting, computer information technology (IT)-based antibiotic feedback intervention will be evaluated to determine whether it can reduce antibiotic prescribing rates and unreasonable prescribing behaviours. Methods We will pilot and develop a cluster-randomised, open controlled, crossover, superiority trial. A total of 320 outpatient physicians in 6 counties of Guizhou province who met the standard will be randomly divided into intervention group and control group with a primary care hospital being the unit of cluster allocation. In the intervention group, the three components of the feedback intervention included: 1. Artificial intelligence (AI)-based real-time warnings of improper antibiotic use; 2. Pop-up windows of antibiotic prescription rate ranking; 3. Distribution of educational manuals. In the control group, no form of intervention will be provided. The trial will last for 6 months and will be divided into two phases of three months each. The two groups will crossover after 3 months. The primary outcome is the 10-day antibiotic prescription rate of physicians. The secondary outcome is the rational use of antibiotic prescriptions. The acceptability and feasibility of this feedback intervention study will be evaluated using both qualitative and quantitative assessment methods. Discussion This study will overcome limitations of our previous study, which only focused on reducing antibiotic prescription rates. AI techniques and an educational intervention will be used in this study to effectively reduce antibiotic prescription rates and antibiotic irregularities. This study will also provide new ideas and approaches for further research in this area. Trial registration ISRCTN, ID: ISRCTN13817256. Registered on 11 January 2020.

Positive parenting in foster care: A video-feedback intervention to promote positive parenting – theory and practice

Foster children are known to be at high risk for developing attachment problems. Moreover, their associated behavioural problems can be a burden for the foster family and increase the risk of placement breakdown. A sensitive parenting style promotes a secure attachment which, in turn, can reduce the chance of difficulties arising and protect against placement disruption. Interventions using video-feedback of parent–child interactions offer a method of increasing parental sensitivity and improving the quality of the parent–child attachment. The intervention discussed in this article was part of a wider initiative, Video-feedback Intervention to promote Positive Parenting and Sensitive Discipline (VIPP-SD), fashioned to promote sensitive parenting, secure attachment and a reduction in children’s behavioural problems. Its effectiveness has been shown for a variety of target groups. A variant of the approach was developed specifically for foster and adopted children, Video-feedback Intervention to promote Positive Parenting and Sensitive Discipline – Foster Care/Adoption (VIPP-FC/A). This article discusses the design and delivery of the intervention and illustrates these with case material.

Performance feedback on the quality of care in hospitals performing thrombectomy for ischemic stroke (PERFEQTOS): protocol of a stepped wedge cluster randomized trial

Background Although the provision of performance feedback to healthcare professionals based on data from quality registries is common practice in many fields of medicine, observational studies of its effect on the quality of care have shown mixed results. The objective of this study is to evaluate the effect of performance feedback on the quality of care for acute ischemic stroke. Methods PERFEQTOS is a stepped wedge cluster randomized trial in 13 hospitals in the Netherlands providing endovascular thrombectomy for ischemic stroke. The primary outcome is the hospital’s door-to-groin time. The study starts with a 6-month period in which none of the hospitals receives the performance feedback intervention. Subsequently, every 6 months, three or four hospitals are randomized to cross over from the control to the intervention conditions, until all hospitals receive the feedback intervention. The feedback intervention consists of a dashboard with quarterly reports on patient characteristics, structure, process, and outcome indicators related to patients with ischemic stroke treated with endovascular thrombectomy. Hospitals can compare their present performance with their own performance in the past and with other hospitals. The performance feedback is provided to local quality improvement teams in each hospital, who define their own targets on specific indicators and develop performance improvement plans. The impact of the performance feedback and improvement plans will be evaluated by comparing the primary outcome before and after the intervention. Discussion This study will provide evidence on the effectiveness of performance feedback to healthcare providers. The results will be actively disseminated through peer-reviewed journals, conference presentations, and various stakeholder engagement activities. Trial registration Netherlands Trial Register NL9090. Registered on December 3, 2020

571Effect of a computer network-based feedback program on antibiotic prescription rates of primary care physicians

Background Antibiotic overuse is one of the major prescription problems in rural China and a major risk factor for antibiotic resistance. Low antibiotic prescription rates can effectively reduce the risk of antibiotic resistance. Methods A cluster randomized crossover open controlled trial was conducted in 31 hospitals. These hospitals were randomly allocated to two groups to receive the intervention for three months followed by no intervention for three months in a random sequence. The feedback intervention information, which displayed the physicians’ antibiotic prescription rates and ranking, was updated every 10 days. The primary outcome was the 10-day antibiotic prescription rate of the physicians. Results There were 82 physicians in group 1 (intervention first followed by control) and 81 in group 2 (control first followed by intervention). Baseline comparison showed no significant difference in antibiotic prescription rate between the two groups (30.8% vs 35.2%, P-value = 0.07). At the crossover point, the relative reduction in antibiotic prescription rate was significantly higher among physicians in the intervention group than in the control group (33.1% vs 20.3%, P-value < 0.001). After a further 3 months, the rate of decline in antibiotic prescriptions was also significantly greater in the intervention group compared to the control group (14.2% vs 4.6%, P-value < 0.001). Conclusions A computer network-based feedback intervention can significantly reduce the antibiotic prescription rates of primary care outpatient physicians. Key messages The feedback intervention continuously affected their prescription behavior for up to six months.

1086Methodological challenges using routine aggregated data in a primary care implementation trial on opioid prescribing

Focus of Presentation There is international concern over rising trends in opioid prescribing, largely attributed to prescribing for chronic non-cancer pain. We conducted a controlled interrupted time series study on anonymised, aggregated practice data to evaluate the effect of the Campaign to Reduce Opioid Prescribing (CROP) in reducing the number of patients taking opioid medication in West Yorkshire UK practices targeted by the feedback intervention, compared to practices outside of West Yorkshire. We will discuss the methodological challenges addressed in the collection and analysis of these data, and the implications for using routine data in trials. Findings Primary care data sources for feedback interventions include large-scale databases (General Practice Research Database), high-level nationally gathered databases (OpenPrescribing.com) or data extracted directly from electronic health records (EHR). We will discuss the implications of the different sources of data and compare the results from each, in understanding the impact of the feedback intervention of reducing opioid prescribing over time. The consequences of the heterogeneity of the data sources on the interrupted time series analysis undertaken will also be discussed and solutions outlined. Conclusions/Implications Routine data are heterogeneous, with different purposes, structures and collection methods, which have considerable implications on their use, analysis and interpretation. Researchers need to understand that the utility of routine data sources have implications (both practically and methodologically) in conducting pragmatic trials, which should be considered when planning and conducting future studies using routine data.

PP24 Prehospital feedback in the United Kingdom: protocol for a review of current practice using a realist approach

BackgroundPrehospital feedback is increasingly receiving attention from clinicians, managers and researchers. The effectiveness of feedback in changing professional behaviour and improving clinical performance is strongly evidenced across a range of healthcare settings, but this has not yet been replicated within the prehospital context. Without a firmer evidence base, development in practice relies on isolated initiatives with no clear intervention model or evaluative framework. The aim of this study is to understand how UK ambulance services are currently meeting the challenge of providing prehospital feedback and generate an explanatory programme theory.MethodsThis mixed methods study will follow a realist evaluation methodology framework with an explanatory case study research design. A realist approach was selected as it will facilitate development of programme theory by exploring context, mechanisms and outcomes. The study will consist of three phases: a pilot case study, a national survey and three in-depth case studies. Phase 1 and 3 of the study will involve semi-structured qualitative interviews and site visits, whilst phase 2 will consist of a cross-sectional survey sent out to leads of UK prehospital feedback initiatives. This study will draw upon a range of existing theories to aid understanding such as the Consolidated Framework for Implementation Research, Normalisation Process Theory and Clinical Performance Feedback Intervention Theory.Results and ConclusionThe three phases of this study will allow for cyclical development, testing and refinement of programme theory by describing existing prehospital feedback intervention types and variations in implementation, as well as evaluating their causal mechanisms and outcomes. Study findings will facilitate an understanding of the extent and limitations of current initiatives, with a view towards identifying opportunities for intervention.