Best practice guidance for antibiotic audit and feedback interventions in primary care: a modified Delphi study from the Joint Programming Initiative on Antimicrobial resistance: Primary Care Antibiotic Audit and Feedback Network (JPIAMR-PAAN).

BACKGROUND: Primary care is a critical partner for antimicrobial stewardship efforts given its high human antibiotic usage. Peer comparison audit and feedback (A&F) is often used to reduce inappropriate antibiotic prescribing. The design and implementation of A&F may impact its effectiveness. There are no best practice guidelines for peer comparison A&F in antibiotic prescribing in primary care. OBJECTIVE: To develop best practice guidelines for peer comparison A&F for antibiotic prescribing in primary care in high income countries by leveraging international expertise via the Joint Programming Initiative on Antimicrobial Resistance-Primary Care Antibiotic Audit and Feedback Network. METHODS: We used a modified Delphi process to achieve convergence of expert opinions on best practice statements for peer comparison A&F based on existing evidence and theory. Three rounds were performed, each with online surveys and virtual meetings to enable discussion and rating of each best practice statement. A five-point Likert scale was used to rate consensus with a median threshold score of 4 to indicate a consensus statement. RESULTS: The final set of guidelines include 13 best practice statements in four categories: general considerations (n = 3), selecting feedback recipients (n = 1), data and indicator selection (n = 4), and feedback delivery (n = 5). CONCLUSION: We report an expert-derived best practice recommendations for designing and evaluating peer comparison A&F for antibiotic prescribing in primary care. These 13 statements can be used by A&F designers to optimize the impact of their quality improvement interventions, and improve antibiotic prescribing in primary care.

Regional and national antimicrobial stewardship activities: a survey from the Joint Programming Initiative on Antimicrobial Resistance-Primary Care Antibiotic Audit and Feedback Network (JPIAMR-PAAN).

Background: Antibiotic overuse and misuse in primary care are common, highlighting the importance of antimicrobial stewardship (AMS) efforts in this setting. Audit and feedback (A&F) interventions can improve professional practice and performance in some settings. Objectives and methods: To leverage the expertise from international members of the Joint Programming Initiative on Antimicrobial Resistance - Primary care Antibiotic Audit and feedback Network (JPIAMR-PAAN). Network members all have experience of designing and delivering A&F interventions to reduce inappropriate antibiotic prescribing in primary care settings. We aim to introduce the network and explore ongoing A&F activities in member regions. An online survey was administered to all network members to collect regional information. Results: Fifteen respondents from 11 countries provided information on A&F activities in their country, and national/regional antibiotic stewardship programmes or policies. Most countries use electronic medical records as the primary data source, antibiotic appropriateness as the main outcome of feedback, and target GPs as the prescribers of interest. Funding sources varied across countries, which could influence the frequency and quality of A&F interventions. Nine out of 11 countries reported having a national antibiotic stewardship programme or policy, which aim to provide systematic support to ongoing AMS efforts and aid sustainability. Conclusions: The survey identified gaps and opportunities for AMS efforts that include A&F across member countries in Europe, Canada and Australia. JPIAMR-PAAN will continue to leverage its members to produce best practice resources and toolkits for antibiotic A&F interventions in primary care settings and identify research priorities.

Clinical presentation, microbiological aetiology and disease course in patients with flu-like illness: a post hoc analysis of randomised controlled trial data.

BACKGROUND: There is little evidence about the relationship between aetiology, illness severity, and clinical course of respiratory tract infections (RTIs) in primary care. Understanding these associations would aid in the development of effective management strategies for these infections. AIM: To investigate whether clinical presentation and illness course differ between RTIs where a viral pathogen was detected and those where a potential bacterial pathogen was found. DESIGN AND SETTING: Post hoc analysis of data from a pragmatic randomised trial on the effects of oseltamivir in patients with flu-like illness in primary care (n = 3266) in 15 European countries. METHOD: Patient characteristics and their signs and symptoms of disease were registered at baseline. Nasopharyngeal (adults) or nasal and pharyngeal (children) swabs were taken for polymerase chain reaction analysis. Patients were followed up until 28 days after inclusion. Regression models and Kaplan-Meier curves were used to analyse the relationship between aetiology, clinical presentation at baseline, and course of disease including complications. RESULTS: Except for a less prominent congested nose (odds ratio [OR] 0.55, 95% confidence interval [CI] = 0.35 to 0.86) and acute cough (OR 0.42, 95% CI = 0.27 to 0.65) in patients with flu-like illness in whom a possible bacterial pathogen was isolated, there were no clear clinical differences in presentations between those with a possible bacterial aetiology compared with those with a viral aetiology. Also, course of disease and complications were not related to aetiology. CONCLUSION: Given current available microbiological tests and antimicrobial treatments, and outside pandemics such as COVID-19, microbiological testing in primary care patients with flu-like illness seems to have limited value. A wait-and-see policy in most of these patients with flu-like illness seems the best option.

Clinical prediction of laboratory-confirmed influenza in adults with influenza-like illness in primary care. A randomized controlled trial secondary analysis in 15 European countries.

BACKGROUND: Clinical findings do not accurately predict laboratory diagnosis of influenza. Early identification of influenza is considered useful for proper management decisions in primary care. OBJECTIVE: We evaluated the diagnostic value of the presence and the severity of symptoms for the diagnosis of laboratory-confirmed influenza infection among adults presenting with influenza-like illness (ILI) in primary care. METHODS: Secondary analysis of patients with ILI who participated in a clinical trial from 2015 to 2018 in 15 European countries. Patients rated signs and symptoms as absent, minor, moderate, or major problem. A nasopharyngeal swab was taken for microbiological identification of influenza and other microorganisms. Models were generated considering (i) the presence of individual symptoms and (ii) the severity rating of symptoms. RESULTS: A total of 2,639 patients aged 18 or older were included in the analysis. The mean age was 41.8 ± 14.7 years, and 1,099 were men (42.1%). Influenza was microbiologically confirmed in 1,337 patients (51.1%). The area under the curve (AUC) of the model for the presence of any of seven symptoms for detecting influenza was 0.66 (95% confidence interval [CI]: 0.65-0.68), whereas the AUC of the symptom severity model, which included eight variables-cough, fever, muscle aches, sweating and/or chills, moderate to severe overall disease, age, abdominal pain, and sore throat-was 0.70 (95% CI: 0.69-0.72). CONCLUSION: Clinical prediction of microbiologically confirmed influenza in adults with ILI is slightly more accurate when based on patient reported symptom severity than when based on the presence or absence of symptoms.

Influenza is usually diagnosed clinically. However, the accuracy of a diagnosis of influenza based on clinical features is limited because symptoms overlap considerably with those caused by other microorganisms. This study examined whether identification of the severity rather than the presence of key signs and symptoms could aid in the diagnosis of influenza, thereby helping clinicians to determine when antiviral agent use is appropriate. The authors used the database of a previous randomized clinical trial on the effectiveness of an antiviral carried out in primary care centers in 15 countries in Europe during three epidemic periods from 2015/2016 to 2017/2018. Participants with influenza symptoms were included and they were asked about the presence and severity of different symptoms during the baseline visit with their doctors and a nasopharyngeal swab was taken for microbiological analysis. Overall, only 51% of the patients aged 18 or older had a confirmed influenza infection. Clinical findings are not particularly useful for confirming or excluding the diagnosis of influenza. However, the results of our study recommend considering how intense the different symptoms are, since key symptoms rated as moderate or severe are slightly better for predicting flu rather than the presence or absence of these symptoms.