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Interprofessional collaboration between general practitioners (GPs) and community pharmacists (CPs) is central to implement antimicrobial stewardship (AMS) programmes in primary care. This study aimed to design a GP/pharmacist antimicrobial stewardship (GPPAS) model for primary care in Australia. An exploratory study design was followed that included seven studies conducted from 2017 to 2021 for the development of the GPPAS model. We generated secondary and primary evidence through a systematic review, a scoping review, a rapid review, nationwide surveys of Australian GPs and CPs including qualitative components, and a pilot study of a GPPAS submodel. All study evidence was synthesised, reviewed, merged, and triangulated to design the prototype GPPAS model using a Systems Engineering Initiative for Patient Safety theoretical framework. The secondary evidence provided effective GPPAS interventions, and the primary evidence identified GP/CP interprofessional issues, challenges, and future needs for implementing GPPAS interventions. The framework of the GPPAS model informed five GPPAS implementation submodels to foster implementation of AMS education program, antimicrobial audits, diagnostic stewardship, delayed prescribing, and routine review of antimicrobial prescriptions, through improved GP–CP collaboration. The GPPAS model could be used globally as a guide for GPs and CPs to collaboratively optimise antimicrobial use in primary care. Implementation studies on the GPPAS model and submodels are required to integrate the GPPAS model into GP/pharmacist interprofessional care models in Australia for improving AMS in routine primary care.

Abstract Background Clinical studies and mathematical simulation suggest that active surveillance with contact isolation is associated with reduced vancomycin-resistant enterococci (VRE) prevalence compared to passive surveillance. Models using pre- and post-intervention data that account for the imperfect observation and serial dependence of VRE transmission events can better estimate the effectiveness of active surveillance and subsequent contact isolation; however, such analyses have not been performed. Methods A mathematical model was fitted to surveillance data collected pre- and post-implementation of active surveillance with contact isolation in the haematology-oncology ward. We developed a Hidden Markov Model to describe undetected and observed VRE colonisation/infection status based on the detection activities in the ward. Bayesian inference was used to estimate transmission rates. The effectiveness of active surveillance was assumed to be via increased detection and subsequent contact isolation of VRE positive patients. Results We estimated that 31% (95% credible interval: 0.33–85%) of the VRE transmissions were due to cross-transmission between patients. The ratio of transmission rates from patients with contact isolation versus those without contact isolation was 0.33 (95% credible interval: 0.050–1.22). Conclusions The majority of the VRE acquisitions in the haematology-oncology ward was estimated to be due to background rates of VRE, rather than within ward patient to patient acquisition. The credible interval for cross-transmission was wide which results in a large degree of uncertainty in the estimates. Factors that could account for background VRE acquisition include endogenous acquisition from antibiotic selection pressure and VRE in the environment. Contact isolation was not significantly associated with reduced VRE transmission in settings where the majority of VRE acquisition was due to background acquisition, emphasising the need to identify and address the source of acquisition. As the credible interval for the ratio of VRE transmission in contact isolated versus non-contact isolated patients crossed 1, there is a probability that the transmission rate in contact isolation was not lower. Our finding highlights the need to optimise infection control measures other than active surveillance for VRE and subsequent contact isolation to reduce VRE transmission. Such measures could include antimicrobial stewardship, environmental cleaning, and hand hygiene.

Abstract Background There are limited published data on the types and appropriateness of oral and intravenous (IV) antibiotics prescribed to patients receiving haemodialysis. This information is critical to optimise antibiotic prescribing. Therefore this study aims to describe the patterns of use and the appropriateness of oral and IV antibiotics prescribed to patients receiving haemodialysis. Methods This was a prospective, observational study across four community and two hospital inpatient haemodialysis units in Melbourne, Australia. Data were collected from July 2014 to January 2015 from participants. Antibiotic regimens prescribed were compared with nationally available antibiotic guidelines and then classified as being either appropriate, inappropriate or not assessable by an expert multidisciplinary team using the National Antimicrobial Prescribing Survey tool. Results Overall, 114 participants consented to this study where 55.3% (63/114) received antibiotics and 235 antibiotic regimens were prescribed at a rate of 69.1 antibiotic regimens/100 patient-months. The most common oral antibiotics prescribed were amoxycillin/clavulanic acid and cephalexin. The most common IV antibiotics prescribed were vancomycin, piperacillin/tazobactam, cephazolin and ceftriaxone. The percentage of inappropriate antibiotic regimens prescribed were 34.9% (15/43) in the community setting and 22.1% (40/181) in the hospital setting. Furthermore, 29.4% (30/102) of oral and 20.5% (25/122) of IV antibiotic regimens were inappropriate with incorrect dosing as the primary reason. Conclusion Although this study is limited by the sample size, it describes the high antibiotic exposure that patients receiving haemodialysis experience. Of concern is inappropriate dose and frequency being a major issue. This requires interventions focused on the quality use of medicines and antimicrobial stewardship aspects of prescribing in this population.

Setting up an interprofessional team for antimicrobial stewardship (AMS) to improve the quality and safety of antimicrobial use in primary care is essential but challenging. This study aimed to investigate the convergent and divergent attitudes and views of general practitioners (GPs) and community pharmacists (CPs) about AMS implementation and their perceived challenges of collaboration to design a GP–pharmacist collaborative AMS (GPPAS) model. Nationwide surveys of GPs and CPs across Australia were conducted January-October 2019. Chi square statistics and a theoretical framework were used for comparative analyses of quantitative and qualitative data, respectively. In total, 999 participants responded to the surveys with 15.4% (n = 386) response rates for GPs and 30.7% (n = 613) for CPs. GPs and CPs were aware about AMS however their interprofessional perceptions varied to the benefits of AMS programs. CPs indicated that they would need AMS training; significantly higher than GPs (GP vs. CP; 46.4% vs. 76.5%; p < 0.0001). GPs’ use of the Therapeutic Guideline Antibiotic was much higher than CPs (83.2% vs. 45.5%; p < 0.0001). No interprofessional difference was found in the very-limited use of patient information leaflets (p < 0.1162) and point-of-care tests (p < 0.7848). While CPs were more willing (p < 0.0001) to collaborate with GPs, both groups were convergent in views that policies that support GP–CP collaboration are needed to implement GPPAS strategies. GP–pharmacist collaborative group meetings (54.9% vs. 82.5%) and antimicrobial audit (46.1% vs. 86.5%) models were inter-professionally supported to optimise antimicrobial therapy, but an attitudinal divergence was significant (p < 0.001). The challenges towards GP–CP collaboration in AMS were identified by both at personal, logistical and organisational environment level. There are opportunities for GP–CP collaboration to improve AMS in Australian primary care. However, strengthening GP–pharmacy collaborative system structure and practice agreements is a priority to improve interprofessional trust, competencies, and communications for AMS and to establish a GPPAS model in future.

Implementing antimicrobial stewardship (AMS) programs is central to optimise antimicrobial use in primary care. This study aims to assess general practitioners’ (GPs’) awareness of AMS, uptake of AMS strategies, attitudes towards GP–pharmacist collaboration in AMS and future AMS improvement strategies. A paper-based survey of nationally representative GPs across Australia was conducted in 2019. Of 386 respondent GPs, 68.9% were familiar with AMS. Respondents most frequently used the Therapeutic Guidelines (TG) (83.2%, 321/385) and delayed antimicrobial prescribing (72.2%, 278/385) strategies, whereas few utilised point-of-care tests (18.4%, 71/382), patient information leaflets (20.2%, 78/384), peer prescribing reports (15.5%, 60/384) and audit and feedback (9.8%, 38/384). GPs were receptive to pharmacists’ recommendations on the choice (50.5%, 192/381) and dose (63%, 241/382) of antimicrobials, and more than 60% (235/381) supported a policy fostering increased GP–pharmacist collaboration. Most GPs agreed to have AMS training (72%, 278/386), integration of electronic TG (eTG) with prescribing software (88.3%, 341/386) and policies limiting the prescribing of selected antimicrobials (74.4%, 287/386) in the future. Conclusively, GPs are aware of the importance of judicious antimicrobial prescribing but inadequately uptake evidence-based AMS strategies. The majority of GPs support GP–pharmacist collaborative AMS approaches to optimise antimicrobial use. Developing a feasible GP–pharmacist collaborative AMS implementation model and facilitating stewardship resources and training could foster AMS activities in primary care.

Little is known about the transmission dynamics of Acinetobacter baumannii in hospitals, despite such information being critical for designing effective infection control measures. In the absence of comprehensive epidemiological data, mathematical modelling is an attractive approach to understanding transmission process. The statistical challenge in estimating transmission parameters from infection data arises from the fact that most patients are colonised asymptomatically and therefore the transmission process is not fully observed. Hidden Markov models (HMMs) can overcome this problem. We developed a continuous-time structured HMM to characterise the transmission dynamics, and to quantify the relative importance of different acquisition sources of A. baumannii in intensive care units (ICUs) in three hospitals in Melbourne, Australia. The hidden states were the total number of patients colonised with A. baumannii (both detected and undetected). The model input was monthly incidence data of the number of detected colonised patients (observations). A Bayesian framework with Markov chain Monte Carlo algorithm was used for parameter estimations. We estimated that 96-98% of acquisition in Hospital 1 and 3 was due to cross-transmission between patients; whereas most colonisation in Hospital 2 was due to other sources (sporadic acquisition). On average, it takes 20 and 31 days for each susceptible individual in Hospital 1 and Hospital 3 to become colonised as a result of cross-transmission, respectively; whereas it takes 17 days to observe one new colonisation from sporadic acquisition in Hospital 2. The basic reproduction ratio (R0) for Hospital 1, 2 and 3 was 1.5, 0.02 and 1.6, respectively. Our study is the first to characterise the transmission dynamics of A. baumannii using mathematical modelling. We showed that HMMs can be applied to sparse hospital infection data to estimate transmission parameters despite unobserved events and imperfect detection of the organism. Our results highlight the need to optimise infection control in ICUs.