@Article{info:doi/10.2196/63983, author="Lee, Heonyi and Kim, Yi-Jun and Kim, Jin-Hong and Kim, Soo-Kyung and Jeong, Tae-Dong", title="Optimizing Initial Vancomycin Dosing in Hospitalized Patients Using Machine Learning Approach for Enhanced Therapeutic Outcomes: Algorithm Development and Validation Study", journal="J Med Internet Res", year="2025", month="Mar", day="31", volume="27", pages="e63983", keywords="algorithm", keywords="machine learning", keywords="therapeutic drug monitoring", keywords="vancomycin", keywords="area under curve", keywords="pharmacokinetics", keywords="vancomycin dosing", abstract="Background: Vancomycin is commonly dosed using standard weight--based methods before dose adjustments are made through therapeutic drug monitoring (TDM). However, variability in initial dosing can lead to suboptimal therapeutic outcomes. A predictive model that personalizes initial dosing based on patient-specific pharmacokinetic factors prior to administration may enhance target attainment and minimize the need for subsequent dose adjustments. Objective: This study aimed to develop and evaluate a machine learning (ML)--based algorithm to predict whether an initial vancomycin dose falls within the therapeutic range of the 24-hour area under the curve to minimum inhibitory concentration, thereby optimizing the initial vancomycin dosage. Methods: A retrospective cohort study was conducted using hospitalized patients who received intravenous vancomycin and underwent pharmacokinetic TDM consultation (n=415). The cohort was randomly divided into training and testing datasets in a 7:3 ratio, and multiple ML techniques were used to develop an algorithm for optimizing initial vancomycin dosing. The optimal algorithm, referred to as the OPTIVAN algorithm, was selected and validated using an external cohort (n=268). We evaluated the performance of 4 ML models: gradient boosting machine, random forest (RF), support vector machine (SVM), and eXtreme gradient boosting (XGB). Additionally, a web-based clinical support tool was developed to facilitate real-time vancomycin TDM application in clinical practice. Results: The SVM algorithm demonstrated the best predictive performance, achieving an area under the receiver operating characteristic curve (AUROC) of 0.832 (95\% CI 0.753-0.900) for the training dataset and 0.720 (95\% CI 0.654-0.783) for the external validation dataset. The gradient boosting machine followed closely with AUROC scores of 0.802 (95\% CI 0.667-0.857) for the training dataset and 0.689 (95\% CI 0.596-0.733) for the validation dataset. In contrast, both XGB and RF exhibited relatively lower performance. XGB achieved AUROC values of 0.769 (95\% CI 0.671-0.853) for the training set and 0.707 (95\% CI 0.644-0.772) for the validation set, while RF recorded AUROC scores of 0.759 (95\% CI 0.656-0.846) for the test dataset and 0.693 (95\% CI 0.625-0.757) for the external validation set. The SVM model incorporated 7 covariates: age, BMI, glucose, blood urea nitrogen, estimated glomerular filtration rate, hematocrit, and daily dose per body weight. Subgroup analyses demonstrated consistent performance across different patient categories, such as renal function, sex, and BMI. A web-based TDM analysis tool was developed using the OPTIVAN algorithm. Conclusions: The OPTIVAN algorithm represents a significant advancement in personalized initial vancomycin dosing, addressing the limitations of current TDM practices. By optimizing the initial dose, this algorithm may reduce the need for subsequent dosage adjustments. The algorithm's web-based app is easy to use, making it a practical tool for clinicians. This study highlights the potential of ML to enhance the effectiveness of vancomycin treatment. ", doi="10.2196/63983", url="https://www.jmir.org/2025/1/e63983" } @Article{info:doi/10.2196/60831, author="Gao, Yu and Magin, Parker and Tapley, Amanda and Holliday, Elizabeth and Dizon, Jason and Fisher, Katie and van Driel, Mieke and Davis, S. Joshua and Davey, Andrew and Ralston, Anna and Fielding, Alison and Moad, Dominica and Mulquiney, Katie and Clarke, Lisa and Turner, Alexandria", title="Prevalence of Antibiotic Prescribing for Acute Respiratory Tract Infection in Telehealth Versus Face-to-Face Consultations: Cross-Sectional Analysis of General Practice Registrars' Clinical Practice", journal="J Med Internet Res", year="2025", month="Mar", day="13", volume="27", pages="e60831", keywords="antimicrobial resistance", keywords="antibiotics stewardship", keywords="telehealth", keywords="general practice", keywords="registrars", keywords="acute respiratory tract infection", keywords="antibiotics", keywords="prescription", keywords="respiratory tract infection", keywords="RTIs", keywords="Australia", keywords="consultations", keywords="teleconsultation", keywords="teleconsult", keywords="bronchitis", keywords="sore throat", keywords="acute otitis", keywords="sinusitis", keywords="in-consultation", keywords="upper respiratory tract infection", abstract="Background: Antimicrobial resistance is a global threat. Australia has high antibiotic prescribing rates with the majority of antibiotics prescribed by general practitioners (GPs) for self-limiting acute respiratory tract infection (ARTIs). Australian GP trainees' (registrars') prescribing for ARTIs may have been affected by the introduction of remunerated telehealth consultations in 2020. Understanding of the impact of telehealth on antibiotic stewardship may inform registrar educational programs. Objective: This study aimed to compare the prevalence of antibiotic prescribing by GP registrars in telehealth versus face-to-face (F2F) consultations for common cold (upper respiratory tract infection [URTI]), bronchitis, sore throat, acute otitis media, and sinusitis. Methods: A cross-sectional analysis of data from the Registrar Clinical Encounters in Training (ReCEnT) study, a multicenter inception cohort study of registrars' in-consultation clinical and educational experiences. Analysis used univariable and multivariable logistic regression using 2020-2023 ReCEnT data. The outcome variable was ``antibiotic prescribed'' for new presentations of URTI, acute sore throat, acute bronchitis, acute sinusitis, and acute otitis media. The study factor was consultation type (telehealth or F2F). Results: A total of 2392 registrars participated (response rate=93.4\%). The proportions of diagnoses that were managed via telehealth were 25\% (5283/21384) overall, 19\% (641/3327) for acute sore throat, 29\% (3733/12773) for URTI, 21\% (364/1772), for acute bronchitis, 4.1\% (72/1758) for acute otitis media, and 27\% (473/1754) for acute sinusitis. Antibiotics were prescribed for 51\% (1685/3327) of sore throat diagnoses, 6.9\% (880/12773) of URTI diagnoses, 64\% (1140/1772) of bronchitis diagnoses, 61\% (1067/1754) of sinusitis diagnoses, and 73\% (1278/1758) of otitis media diagnoses. On multivariable analysis, antibiotics were less often prescribed in telehealth than F2F consultations for sore throat (adjusted odds ratio [OR] 0.69, 95\% CI 0.55-0.86; P=.001), URTI (adjusted OR 0.64, 95\% CI 0.51-0.81; P<.001), and otitis media (adjusted OR 0.47, 95\% CI 0.26-0.84; P=.01). There were no significant differences for acute bronchitis (adjusted OR 1.07, 95\% CI 0.79-1.45; P=.66) or acute sinusitis (adjusted OR 1, 95\% CI 0.76-1.32; P=.99). Conclusions: GP registrars are less likely to prescribe antibiotics for sore throat, URTI, and otitis media when seeing patients by telehealth versus F2F. Understanding the reason for this difference is essential to help guide educational efforts aimed at decreasing antibiotic prescribing by GPs for conditions such as ARTIs where they are of little to no benefit. There was no evidence in this study that telehealth consultations were associated with greater registrar antibiotic prescribing for ARTIs. Therefore, there is no deleterious effect on antibiotic stewardship. ", doi="10.2196/60831", url="https://www.jmir.org/2025/1/e60831" } @Article{info:doi/10.2196/66699, author="D{\"u}vel, Andrea Juliane and Lampe, David and Kirchner, Maren and Elkenkamp, Svenja and Cimiano, Philipp and D{\"u}sing, Christoph and Marchi, Hannah and Schmiegel, Sophie and Fuchs, Christiane and Cla{\ss}en, Simon and Meier, Kirsten-Laura and Borgstedt, Rainer and Rehberg, Sebastian and Greiner, Wolfgang", title="An AI-Based Clinical Decision Support System for Antibiotic Therapy in Sepsis (KINBIOTICS): Use Case Analysis", journal="JMIR Hum Factors", year="2025", month="Mar", day="4", volume="12", pages="e66699", keywords="CDSS", keywords="use case analysis", keywords="technology acceptance", keywords="sepsis", keywords="infection", keywords="infectious disease", keywords="antimicrobial resistance", keywords="clinical decision support system", keywords="decision-making", keywords="clinical support", keywords="machine learning", keywords="ML", keywords="artificial intelligence", keywords="AI", keywords="algorithm", keywords="model", keywords="analytics", keywords="predictive models", keywords="deep learning", keywords="early warning", keywords="early detection", abstract="Background: Antimicrobial resistances pose significant challenges in health care systems. Clinical decision support systems (CDSSs) represent a potential strategy for promoting a more targeted and guideline-based use of antibiotics. The integration of artificial intelligence (AI) into these systems has the potential to support physicians in selecting the most effective drug therapy for a given patient. Objective: This study aimed to analyze the feasibility of an AI-based CDSS pilot version for antibiotic therapy in sepsis patients and identify facilitating and inhibiting conditions for its implementation in intensive care medicine. Methods: The evaluation was conducted in 2 steps, using a qualitative methodology. Initially, expert interviews were conducted, in which intensive care physicians were asked to assess the AI-based recommendations for antibiotic therapy in terms of plausibility, layout, and design. Subsequently, focus group interviews were conducted to examine the technology acceptance of the AI-based CDSS. The interviews were anonymized and evaluated using content analysis. Results: In terms of the feasibility, barriers included variability in previous antibiotic administration practices, which affected the predictive ability of AI recommendations, and the increased effort required to justify deviations from these recommendations. Physicians' confidence in accepting or rejecting recommendations depended on their level of professional experience. The ability to re-evaluate CDSS recommendations and an intuitive, user-friendly system design were identified as factors that enhanced acceptance and usability. Overall, barriers included low levels of digitization in clinical practice, limited availability of cross-sectoral data, and negative previous experiences with CDSSs. Conversely, facilitators to CDSS implementation were potential time savings, physicians' openness to adopting new technologies, and positive previous experiences. Conclusions: Early integration of users is beneficial for both the identification of relevant context factors and the further development of an effective CDSS. Overall, the potential of AI-based CDSSs is offset by inhibiting contextual conditions that impede its acceptance and implementation. The advancement of AI-based CDSSs and the mitigation of these inhibiting conditions are crucial for the realization of its full potential. ", doi="10.2196/66699", url="https://humanfactors.jmir.org/2025/1/e66699" } @Article{info:doi/10.2196/66184, author="Ram, Sharan and Corbin, Marine and 't Mannetje, Andrea and Eng, Amanda and Kvalsvig, Amanda and Baker, G. Michael and Douwes, Jeroen", title="Antibiotic Use In Utero and Early Life and Risk of Chronic Childhood Conditions in New Zealand: Protocol for a Data Linkage Retrospective Cohort Study", journal="JMIR Res Protoc", year="2025", month="Feb", day="28", volume="14", pages="e66184", keywords="early childhood", keywords="chronic childhood conditions", keywords="antibiotics", keywords="data linkage", keywords="study protocol", keywords="routine data", abstract="Background: The incidence of many common chronic childhood conditions has increased globally in the past few decades, which has been suggested to be potentially attributed to antibiotic overuse leading to dysbiosis in the gut microbiome. Objective: This linkage study will assess the role of antibiotic use in utero and in early life in the development of type 1 diabetes (T1D), attention-deficit/hyperactive disorder (ADHD), and inflammatory bowel disease. Methods: The study design involves several retrospective cohort studies using linked administrative health and social data from Statistics New Zealand's Integrated Data Infrastructure. It uses data from all children who were born in New Zealand between October 2005 and December 2010 (N=334,204) and their mothers. Children's antibiotic use is identified for 4 time periods (at pregnancy, at ?1 year, at ?2 years, and at ?5 years), and the development of T1D, ADHD, and inflammatory bowel disease is measured from the end of the antibiotic use periods until death, emigration, or the end of the follow-up period (2021), whichever came first. Children who emigrated or died before the end of the antibiotic use period are excluded. Cox proportional hazards regression models are used while adjusting for a range of potential confounders. Results: As of September 2024, data linkage has been completed, involving the integration of antibiotic exposure and outcome variables for 315,789 children. Preliminary analyses show that both prenatal and early life antibiotic consumption is associated with T1D. Full analyses for all 3 outcomes will be completed by the end of 2025. Conclusions: This series of linked cohort studies using detailed, complete, and systematically collected antibiotic prescription data will provide critical new knowledge regarding the role of antibiotics in the development of common chronic childhood conditions. Thus, this study has the potential to contribute to the development of primary prevention strategies through, for example, targeted changes in antibiotic use. International Registered Report Identifier (IRRID): DERR1-10.2196/66184 ", doi="10.2196/66184", url="https://www.researchprotocols.org/2025/1/e66184", url="http://www.ncbi.nlm.nih.gov/pubmed/40053783" } @Article{info:doi/10.2196/57457, author="Iera, Jessica and Isonne, Claudia and Seghieri, Chiara and Tavoschi, Lara and Ceparano, Mariateresa and Sciurti, Antonio and D'Alisera, Alessia and Sane Schepisi, Monica and Migliara, Giuseppe and Marzuillo, Carolina and Villari, Paolo and D'Ancona, Fortunato and Baccolini, Valentina", title="Availability and Key Characteristics of National Early Warning Systems for Emerging Profiles of Antimicrobial Resistance in High-Income Countries: Systematic Review", journal="JMIR Public Health Surveill", year="2025", month="Jan", day="15", volume="11", pages="e57457", keywords="early warning system", keywords="surveillance", keywords="emerging AMR", keywords="high-income countries", keywords="antimicrobial resistance", abstract="Background: The World Health Organization (WHO) recently advocated an urgent need for implementing national surveillance systems for the timely detection and reporting of emerging antimicrobial resistance (AMR). However, public information on the existing national early warning systems (EWSs) is often incomplete, and a comprehensive overview on this topic is currently lacking. Objective: This review aimed to map the availability of EWSs for emerging AMR in high-income countries and describe their main characteristics. Methods: A systematic review was performed on bibliographic databases, and a targeted search was conducted on national websites. Any article, report, or web page describing national EWSs in high-income countries was eligible for inclusion. EWSs were identified considering the emerging AMR-reporting WHO framework. Results: We identified 7 national EWSs from 72 high-income countries: 2 in the East Asia and Pacific Region (Australia and Japan), 3 in Europe and Central Asia (France, Sweden, and the United Kingdom), and 2 in North America (the United States and Canada). The systems were established quite recently; in most cases, they covered both community and hospital settings, but their main characteristics varied widely across countries in terms of the organization and microorganisms under surveillance, with also different definitions of emerging AMR and alert functioning. A formal system assessment was available only in Australia. Conclusions: A broader implementation and investment of national surveillance systems for the early detection of emerging AMR are still needed to establish EWSs in countries and regions lacking such capabilities. More standardized data collection and reporting are also advisable to improve cooperation on a global scale. Further research is required to provide an in-depth analysis of EWSs, as this study is limited to publicly available data in high-income countries. ", doi="10.2196/57457", url="https://publichealth.jmir.org/2025/1/e57457" } @Article{info:doi/10.2196/60535, author="Jeanmougin, Pauline and Larramendy, St{\'e}phanie and Fournier, Jean-Pascal and Gaultier, Aur{\'e}lie and Rat, C{\'e}dric", title="Effect of a Feedback Visit and a Clinical Decision Support System Based on Antibiotic Prescription Audit in Primary Care: Multiarm Cluster-Randomized Controlled Trial", journal="J Med Internet Res", year="2024", month="Dec", day="18", volume="26", pages="e60535", keywords="antibacterial agents", keywords="feedback", keywords="clinical decision support system", keywords="prescriptions", keywords="primary health care", keywords="clinical decision", keywords="antibiotic prescription", keywords="antimicrobial", keywords="antibiotic stewardship", keywords="interventions", keywords="health insurance", keywords="systematic antibiotic prescriptions", abstract="Background: While numerous antimicrobial stewardship programs aim to decrease inappropriate antibiotic prescriptions, evidence of their positive impact is needed to optimize future interventions. Objective: This study aimed to evaluate 2 multifaceted antibiotic stewardship interventions for inappropriate systemic antibiotic prescription in primary care. Methods: An open-label, cluster-randomized controlled trial of 2501 general practitioners (GPs) working in western France was conducted from July 2019 to January 2021. Two interventions were studied: the standard intervention, consisting of a visit by a health insurance representative who gave prescription feedback and provided a leaflet for treating cystitis and tonsillitis; and a clinical decision support system (CDSS)--based intervention, consisting of a visit with prescription feedback and a CDSS demonstration on antibiotic prescribing. The control group received no intervention. Data on systemic antibiotic dispensing was obtained from the National Health Insurance System (Syst{\`e}me National d'Information Inter-R{\'e}gimes de l'Assurance Maladie) database. The overall antibiotic volume dispensed per GP at 12 months was compared between arms using a 2-level hierarchical analysis of covariance adjusted for annual antibiotic prescription volume at baseline. Results: Overall, 2501 GPs were randomized (n=1099, 43.9\% women). At 12 months, the mean volume of systemic antibiotics per GP decreased by 219.2 (SD 61.4; 95\% CI ?339.5 to ?98.8; P<.001) defined daily doses in the CDSS-based visit group compared with the control group. The decrease in the mean volume of systemic antibiotics dispensed per GP was not significantly different between the standard visit group and the control group (?109.7, SD 62.4; 95\% CI ?232.0 to 12.5 defined daily doses; P=.08). Conclusions: A visit by a health insurance representative combining feedback and a CDSS demonstration resulted in a 4.4\% (-219.2/4930) reduction in the total volume of systemic antibiotic prescriptions in 12 months. Trial Registration: ClinicalTrials.gov NCT04028830; https://clinicaltrials.gov/study/NCT04028830 ", doi="10.2196/60535", url="https://www.jmir.org/2024/1/e60535", url="http://www.ncbi.nlm.nih.gov/pubmed/39693139" } @Article{info:doi/10.2196/58140, author="Hope, Mackline and Kiggundu, Reuben and Byonanebye, M. Dathan and Mayito, Jonathan and Tabajjwa, Dickson and Lwigale, Fahad and Tumwine, Conrad and Mwanja, Herman and Kambugu, Andrew and Kakooza, Francis", title="Progress of Implementation of World Health Organization Global Antimicrobial Resistance Surveillance System Recommendations on Priority Pathogen-Antibiotic Sensitivity Testing in Africa: Protocol for a Scoping Review", journal="JMIR Res Protoc", year="2024", month="Nov", day="15", volume="13", pages="e58140", keywords="antimicrobial resistance", keywords="antibiotic sensitivity testing", keywords="global antimicrobial resistance surveillance system", keywords="GLASS implementation", keywords="AMR Surveillance", keywords="Africa", abstract="Background: Antimicrobial resistance (AMR) is a major global public health concern, particularly in low- and middle-income countries where resources and infrastructure for an adequate response are limited. The World Health Organization (WHO) Global Antimicrobial Resistance Surveillance System (GLASS) was introduced in 2016 to address these challenges, outlining recommendations for priority pathogen-antibiotic combinations. Despite this initiative, implementation in Africa remains understudied. This scoping review aims to assess the current state of implementing WHO GLASS recommendations on antimicrobial sensitivity testing (AST) in Africa. Objective: The primary objective of this study is to determine the current state of implementing the WHO GLASS recommendations on AST for priority pathogen-antimicrobial combinations. The review will further document if the reporting of AST results is according to ``susceptible,'' ``intermediate,'' and ``resistant'' recommendations according to GLASS. Methods: Following the methodological framework by Arksey and O'Malley, studies published between January 2016 and November 2023 will be included. Search strategies will target electronic databases, including MEDLINE, Scopus, CINAHL, and Embase. Eligible studies will document isolates tested for antimicrobial sensitivity, focusing on WHO-priority specimens and pathogens. Data extraction will focus on key study characteristics, study context, population, and adherence to WHO GLASS recommendations on AST. Descriptive statistics involving summarizing the quantitative data extracted through measures of central tendency and variation will be used. Covidence and Microsoft Excel software will be used. This study will systematically identify, collate, and analyze relevant studies and data sources based on clear inclusion criteria to provide a clear picture of the progress achieved in the implementation of the WHO GLASS recommendations. Areas for further improvement will be documented to inform future efforts to strengthen GLASS implementation for enhanced AMR surveillance in Africa. Results: The study results are expected in August 2024. Conclusions: To our knowledge, this scoping review will be the first to comprehensively examine the implementation of WHO GLASS recommendations in Africa, shedding light on the challenges and successes of AMR surveillance in the region. Addressing these issues aims to contribute to global efforts to combat AMR. International Registered Report Identifier (IRRID): PRR1-10.2196/58140 ", doi="10.2196/58140", url="https://www.researchprotocols.org/2024/1/e58140" } @Article{info:doi/10.2196/58116, author="Mayito, Jonathan and Tumwine, Conrad and Galiwango, Ronald and Nuwamanya, Elly and Nakasendwa, Suzan and Hope, Mackline and Kiggundu, Reuben and Byonanebye, M. Dathan and Dhikusooka, Flavia and Twemanye, Vivian and Kambugu, Andrew and Kakooza, Francis", title="Combating Antimicrobial Resistance Through a Data-Driven Approach to Optimize Antibiotic Use and Improve Patient Outcomes: Protocol for a Mixed Methods Study", journal="JMIR Res Protoc", year="2024", month="Nov", day="8", volume="13", pages="e58116", keywords="antimicrobial resistance", keywords="AMR database", keywords="AMR", keywords="machine learning", keywords="antimicrobial use", keywords="artificial intelligence", keywords="antimicrobial", keywords="data-driven", keywords="mixed-method", keywords="patient outcome", keywords="drug-resistant infections", keywords="drug resistant", keywords="surveillance data", keywords="economic", keywords="antibiotic", abstract="Background: It is projected that drug-resistant infections will lead to 10 million deaths annually by 2050 if left unabated. Despite this threat, surveillance data from resource-limited settings are scarce and often lack antimicrobial resistance (AMR)--related clinical outcomes and economic burden. We aim to build an AMR and antimicrobial use (AMU) data warehouse, describe the trends of resistance and antibiotic use, determine the economic burden of AMR in Uganda, and develop a machine learning algorithm to predict AMR-related clinical outcomes. Objective: The overall objective of the study is to use data-driven approaches to optimize antibiotic use and combat antimicrobial-resistant infections in Uganda. We aim to (1) build a dynamic AMR and antimicrobial use and consumption (AMUC) data warehouse to support research in AMR and AMUC to inform AMR-related interventions and public health policy, (2) evaluate the trends in AMR and antibiotic use based on annual antibiotic and point prevalence survey data collected at 9 regional referral hospitals over a 5-year period, (3) develop a machine learning model to predict the clinical outcomes of patients with bacterial infectious syndromes due to drug-resistant pathogens, and (4) estimate the annual economic burden of AMR in Uganda using the cost-of-illness approach. Methods: We will conduct a study involving data curation, machine learning--based modeling, and cost-of-illness analysis using AMR and AMU data abstracted from procurement, human resources, and clinical records of patients with bacterial infectious syndromes at 9 regional referral hospitals in Uganda collected between 2018 and 2026. We will use data curation procedures, FLAIR (Findable, Linkable, Accessible, Interactable and Repeatable) principles, and role-based access control to build a robust and dynamic AMR and AMU data warehouse. We will also apply machine learning algorithms to model AMR-related clinical outcomes, advanced statistical analysis to study AMR and AMU trends, and cost-of-illness analysis to determine the AMR-related economic burden. Results: The study received funding from the Wellcome Trust through the Centers for Antimicrobial Optimisation Network (CAMO-Net) in April 2023. As of October 28, 2024, we completed data warehouse development, which is now under testing; completed data curation of the historical Fleming Fund surveillance data (2020-2023); and collected retrospective AMR records for 599 patients that contained clinical outcomes and cost-of-illness economic burden data across 9 surveillance sites for objectives 3 and 4, respectively. Conclusions: The data warehouse will promote access to rich and interlinked AMR and AMU data sets to answer AMR program and research questions using a wide evidence base. The AMR-related clinical outcomes model and cost data will facilitate improvement in the clinical management of AMR patients and guide resource allocation to support AMR surveillance and interventions. International Registered Report Identifier (IRRID): PRR1-10.2196/58116 ", doi="10.2196/58116", url="https://www.researchprotocols.org/2024/1/e58116" } @Article{info:doi/10.2196/58039, author="Jian, Ming-Jr and Lin, Tai-Han and Chung, Hsing-Yi and Chang, Chih-Kai and Perng, Cherng-Lih and Chang, Feng-Yee and Shang, Hung-Sheng", title="Pioneering Klebsiella Pneumoniae Antibiotic Resistance Prediction With Artificial Intelligence-Clinical Decision Support System--Enhanced Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry: Retrospective Study", journal="J Med Internet Res", year="2024", month="Nov", day="7", volume="26", pages="e58039", keywords="Klebsiella pneumoniae", keywords="multidrug resistance", keywords="AI-CDSS", keywords="quinolone", keywords="ciprofloxacin", keywords="levofloxacin", abstract="Background: The rising prevalence and swift spread of multidrug-resistant gram-negative bacteria (MDR-GNB), especially Klebsiella pneumoniae (KP), present a critical global health threat highlighted by the World Health Organization, with mortality rates soaring approximately 50\% with inappropriate antimicrobial treatment. Objective: This study aims to advance a novel strategy to develop an artificial intelligence-clinical decision support system (AI-CDSS) that combines machine learning (ML) with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), aiming to significantly improve the accuracy and speed of diagnosing antibiotic resistance, directly addressing the grave health risks posed by the widespread dissemination of pan drug-resistant gram-negative bacteria across numerous countries. Methods: A comprehensive dataset comprising 165,299 bacterial specimens and 11,996 KP isolates was meticulously analyzed using MALDI-TOF MS technology. Advanced ML algorithms were harnessed to sculpt predictive models that ascertain resistance to quintessential antibiotics, particularly levofloxacin and ciprofloxacin, by using the amassed spectral data. Results: Our ML models revealed remarkable proficiency in forecasting antibiotic resistance, with the random forest classifier emerging as particularly effective in predicting resistance to both levofloxacin and ciprofloxacin, achieving the highest area under the curve of 0.95. Performance metrics across different models, including accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and F1-score, were detailed, underlining the potential of these algorithms in aiding the development of precision treatment strategies. Conclusions: This investigation highlights the synergy between MALDI-TOF MS and ML as a beacon of hope against the escalating threat of antibiotic resistance. The advent of AI-CDSS heralds a new era in clinical diagnostics, promising a future in which rapid and accurate resistance prediction becomes a cornerstone in combating infectious diseases. Through this innovative approach, we answered the challenge posed by KP and other multidrug-resistant pathogens, marking a significant milestone in our journey toward global health security. ", doi="10.2196/58039", url="https://www.jmir.org/2024/1/e58039" } @Article{info:doi/10.2196/57285, author="Abejew, Agalu Asrat and Wubetu, Yismaw Gizachew and Fenta, Gedif Teferi", title="Antibiotic Prescribing Behavior of Physicians in Outpatient Departments in Hospitals in Northwest Ethiopia: Structural Equation Modeling Approach", journal="Interact J Med Res", year="2024", month="Oct", day="23", volume="13", pages="e57285", keywords="antibiotic prescribing behavior", keywords="Ethiopia", keywords="outpatient departments", keywords="physicians", keywords="SEM", keywords="TPB", abstract="Background: Antibiotic resistance, fueled by irrational prescribing, is a global threat associated with health, social, and economic consequences. Understanding antibiotic prescribing behavior and associated factors is important to promote good prescribing practice. Objective: This study aimed to determine the factors affecting antibiotic prescribing behaviors of physicians based on the theory of planned behavior in hospitals in northwest Ethiopia in 2022. Methods: A cross-sectional study was conducted from September 2022 to October 2022. A total of 185 health professionals were included, and a self-administered questionnaire was used to collect data. A structural equation model based on the modified theory of planned behavior was used to determine factors affecting antibiotic prescribing behavior. The percentages of physicians' estimated prescriptions for patients with upper respiratory tract infections (URTIs) and during weekly outpatient visits were used to predict antibiotic prescribing behavior and finally linked with behavioral constructs. A P value <.05 was considered significant. Results: Physicians estimated that they prescribed antibiotics for 54.8\% (9896/18,049) of weekly outpatient encounters, and 178 (96.2\%) of the 185 physicians estimated they prescribed antibiotics for patients who presented with symptoms of a URTI. Physicians aged ?30 years were less likely to prescribe antibiotics (48/100, 48\%) for patients who presented with a URTI than physicians older than 30 years (51/100, 51\%; P=.004), and general practitioners were less likely to prescribe antibiotics (47/100, 47\%) for patients who presented with a URTI than residents (51/100, 51\%; P=.03). Similarly, during outpatient visits, physicians ?30 years old were less likely to prescribe antibiotics (54/100, 54\%) than physicians older than 30 years (57/100, 57\%; P<.001), male physicians were less likely to prescribe antibiotics (53/100, 53\%) than female physicians (64/100, 64\%; P=.03), and general practitioners were less likely to prescribe antibiotics (53/100, 53\%) than residents (57/100, 57\%; P=.02). Physicians with good knowledge were less affected by perceived social pressure (mean 4.4, SD 0.6) than those with poor knowledge (mean 4.0, SD 0.9; P<.001) and felt it was easy to make rational decisions (mean 4.1, SD 1.1) compared with those with poor knowledge (mean 3.8, SD 1; P<.001). However, intentions to reduce and prescribe antibiotics were not affected by attitudes, subjective norms, or perceived behavioral control, and perceived antibiotic prescribing behavior was not related to intentions to reduce or prescribe antibiotics. Conclusions: Antibiotic prescribing behavior was not under the volitional control of physicians. This calls for a systematic approach to change antibiotic prescribing practices in hospital. ", doi="10.2196/57285", url="https://www.i-jmr.org/2024/1/e57285", url="http://www.ncbi.nlm.nih.gov/pubmed/39441643" } @Article{info:doi/10.2196/53828, author="Zhu, Jiayue Nina and Weldegiorgis, Misghina and Carter, Emma and Brown, Colin and Holmes, Alison and Aylin, Paul", title="Economic Burden of Community-Acquired Antibiotic-Resistant Urinary Tract Infections: Systematic Review and Meta-Analysis", journal="JMIR Public Health Surveill", year="2024", month="Oct", day="9", volume="10", pages="e53828", keywords="cost-effectiveness", keywords="urinary tract infection", keywords="antibiotic resistance", keywords="mortality", keywords="hospital length of stay", abstract="Background: Antibiotic resistance (ABR) poses a major burden to global health and economic systems. ABR in community-acquired urinary tract infections (CA-UTIs) has become increasingly prevalent. Accurate estimates of ABR's clinical and economic burden are needed to support medical resource prioritization and cost-effectiveness evaluations of urinary tract infection (UTI) interventions. Objective: This study aims to systematically synthesize the evidence on the economic costs associated with ABR in CA-UTIs, using published studies comparing the costs of antibiotic-susceptible and antibiotic-resistant cases. Methods: We searched the PubMed, Ovid MEDLINE and Embase, Cochrane Review Library, and Scopus databases. Studies published in English from January 1, 2008, to January 31, 2023, reporting the economic costs of ABR in CA-UTI of any microbe were included. Independent screening of titles/abstracts and full texts was performed based on prespecified criteria. A quality assessment was performed using the Integrated Quality Criteria for Review of Multiple Study Designs (ICROMS) tool. Data in UTI diagnosis criteria, patient characteristics, perspectives, resource costs, and patient and health economic outcomes, including mortality, hospital length of stay (LOS), and costs, were extracted and analyzed. Monetary costs were converted into 2023 US dollars. Results: This review included 15 studies with a total of 57,251 CA-UTI cases. All studies were from high- or upper-middle-income countries. A total of 14 (93\%) studies took a health system perspective, 13 (87\%) focused on hospitalized patients, and 14 (93\%) reported UTI pathogens. Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa are the most prevalent organisms. A total of 12 (80\%) studies reported mortality, of which, 7 reported increased mortality in the ABR group. Random effects meta-analyses estimated an odds ratio of 1.50 (95\% CI 1.29-1.74) in the ABR CA-UTI cases. All 13 hospital-based studies reported LOS, of which, 11 reported significantly higher LOS in the ABR group. The meta-analysis of the reported median LOS estimated a pooled excess LOS ranging from 1.50 days (95\% CI 0.71-4.00) to 2.00 days (95\% CI 0.85-3.15). The meta-analysis of the reported mean LOS estimated a pooled excess LOS of 2.45 days (95\% CI 0.51?4.39). A total of 8 (53\%) studies reported costs in monetary terms---none discounted the costs. All 8 studies reported higher medical costs spent treating patients with ABR CA-UTI in hospitals. The highest excess cost was observed in UTIs caused by carbapenem-resistant Enterobacterales. No meta-analysis was performed for monetary costs due to heterogeneity. Conclusions: ABR was attributed to increased mortality, hospital LOS, and economic costs among patients with CA-UTI. The findings of this review highlighted the scarcity of research in this area, particularly in patient morbidity and chronic sequelae and costs incurred in community health care. Future research calls for a cost-of-illness analysis of infections, standardizing therapy-pathogen combination comparators, medical resources, productivity loss, intangible costs to be captured, and data from community sectors and low-resource settings and countries. ", doi="10.2196/53828", url="https://publichealth.jmir.org/2024/1/e53828" } @Article{info:doi/10.2196/45122, author="Peiffer-Smadja, Nathan and Descousse, Sophie and Courr{\`e}ges, Elsa and Nganbou, Audrey and Jeanmougin, Pauline and Birgand, Gabriel and L{\'e}naud, S{\'e}verin and Beaumont, Anne-Lise and Durand, Claire and Delory, Tristan and Le Bel, Josselin and Bouvet, Elisabeth and Lariven, Sylvie and D'Ortenzio, Eric and Konat{\'e}, Issa and Bouyou-Akotet, Karine Marielle and Ouedraogo, Abdoul-Salam and Kouakou, Affoue Gis{\`e}le and Poda, Armel and Akpovo, Corinne and Lescure, Fran{\c{c}}ois-Xavier and Tanon, Aristophane", title="Implementation of a Clinical Decision Support System for Antimicrobial Prescribing in Sub-Saharan Africa: Multisectoral Qualitative Study", journal="J Med Internet Res", year="2024", month="Oct", day="7", volume="26", pages="e45122", keywords="antimicrobial resistance", keywords="implementation research", keywords="Consolidated Framework for Implementation Research", keywords="CDSS", keywords="mobile health", keywords="mHealth", keywords="eHealth", keywords="mobile phone", abstract="Background: Suboptimal use of antimicrobials is a driver of antimicrobial resistance in West Africa. Clinical decision support systems (CDSSs) can facilitate access to updated and reliable recommendations. Objective: This study aimed to assess contextual factors that could facilitate the implementation of a CDSS for antimicrobial prescribing in West Africa and Central Africa and to identify tailored implementation strategies. Methods: This qualitative study was conducted through 21 semistructured individual interviews via videoconference with health care professionals between September and December 2020. Participants were recruited using purposive sampling in a transnational capacity-building network for hospital preparedness in West Africa. The interview guide included multiple constructs derived from the Consolidated Framework for Implementation Research. Interviews were transcribed, and data were analyzed using thematic analysis. Results: The panel of participants included health practitioners (12/21, 57\%), health actors trained in engineering (2/21, 10\%), project managers (3/21, 14\%), antimicrobial resistance research experts (2/21, 10\%), a clinical microbiologist (1/21, 5\%), and an anthropologist (1/21, 5\%). Contextual factors influencing the implementation of eHealth tools existed at the individual, health care system, and national levels. At the individual level, the main challenge was to design a user-centered CDSS adapted to the prescriber's clinical routine and structural constraints. Most of the participants stated that the CDSS should not only target physicians in academic hospitals who can use their network to disseminate the tool but also general practitioners, primary care nurses, midwives, and other health care workers who are the main prescribers of antimicrobials in rural areas of West Africa. The heterogeneity in antimicrobial prescribing training among prescribers was a significant challenge to the use of a common CDSS. At the country level, weak pharmaceutical regulations, the lack of official guidelines for antimicrobial prescribing, limited access to clinical microbiology laboratories, self-medication, and disparity in health care coverage lead to inappropriate antimicrobial use and could limit the implementation and diffusion of CDSS for antimicrobial prescribing. Participants emphasized the importance of building a solid eHealth ecosystem in their countries by establishing academic partnerships, developing physician networks, and involving diverse stakeholders to address challenges. Additional implementation strategies included conducting a local needs assessment, identifying early adopters, promoting network weaving, using implementation advisers, and creating a learning collaborative. Participants noted that a CDSS for antimicrobial prescribing could be a powerful tool for the development and dissemination of official guidelines for infectious diseases in West Africa. Conclusions: These results suggest that a CDSS for antimicrobial prescribing adapted for nonspecialized prescribers could have a role in improving clinical decisions. They also confirm the relevance of adopting a cross-disciplinary approach with participants from different backgrounds to assess contextual factors, including social, political, and economic determinants. ", doi="10.2196/45122", url="https://www.jmir.org/2024/1/e45122", url="http://www.ncbi.nlm.nih.gov/pubmed/39374065" } @Article{info:doi/10.2196/60099, author="Garc{\'i}a-Sangen{\'i}s, Ana and Modena, Daniela and Jensen, Nygaard Jette and Chalkidou, Athina and Antsupova, S. Valeria and Marloth, Tina and Theut, Marie Anna and Gonz{\'a}lez L{\'o}pez-Valc{\'a}rcel, Beatriz and Raynal, Fabiana and Vallejo-Torres, Laura and Lykkegaard, Jesper and Hansen, Plejdrup Malene and S{\o}ndergaard, Jens and Olsen, Kanstrup Jonas and Munck, Anders and Balint, Andr{\'a}s and Benko, Ria and Petek, Davorina and Sodja, Nina and Kowalczyk, Anna and Godycki-Cwirko, Maciej and Glasov{\'a}, Helena and Glasa, Jozef and Radzeviciene Jurgute, Ruta and Jaruseviciene, Lina and Lionis, Christos and Anastasaki, Marilena and Angelaki, Agapi and Petelos, Elena and Alvarez, Laura and Ricart, Marta and Briones, Sergi and Ruppe, Georg and Monf{\`a}, Ramon and Bjerrum, Anders and Llor, Carl", title="Improving Antibiotic Use in Nursing Homes by Infection Prevention and Control and Antibiotic Stewardship (IMAGINE): Protocol for a Before-and-After Intervention and Implementation Study", journal="JMIR Res Protoc", year="2024", month="Sep", day="16", volume="13", pages="e60099", keywords="antimicrobial stewardship", keywords="medical audit", keywords="hygiene", keywords="antibacterial agents", keywords="quality improvement", keywords="nursing homes", keywords="health personnel", keywords="drug resistance, microbial", keywords="frail elderly", abstract="Background: Despite the extensive use of antibiotics and the growing challenge of antimicrobial resistance, there has been a lack of substantial initiatives aimed at diminishing the prevalence of infections in nursing homes and enhancing the detection of urinary tract infections (UTIs). Objective: This study aims to systematize and enhance efforts to prevent health care--associated infections, mainly UTIs and reduce antibiotic inappropriateness by implementing a multifaceted intervention targeting health care professionals in nursing homes. Methods: A before-and-after intervention study carried out in a minimum of 10 nursing homes in each of the 8 European participating countries (Denmark, Greece, Hungary, Lithuania, Poland, Slovakia, Slovenia, and Spain). A team of 4 professionals consisting of nurses, doctors, health care assistants, or health care helpers are actively involved in each nursing home. Over the initial 3-month period, professionals in each nursing home are registering information on UTIs as well as infection and prevention control measures by means of the Audit Project Odense method. The audit will be repeated after implementing a multifaceted intervention. The intervention will consist of feedback and discussion of the results from the first registration, training on the implementation of infection and prevention control techniques provided by experts, appropriateness of the diagnostic approach and antibiotic prescribing for UTIs, and provision of information materials on infection control and antimicrobial stewardship targeted to staff, residents, and relatives. We will compare the pre- and postintervention audit results using chi-square test for prescription appropriateness and Student t test for implemented hygiene elements. Results: A total of 109 nursing homes have participated in the pilot study and the first registration audit. The results of the first audit registration are expected to be published in autumn of 2024. The final results will be published by the end of 2025. Conclusions: This is a European Union--funded project aimed at contributing to the battle against antimicrobial resistance through improvement of the quality of management of common infections based on evidence-based interventions tailored to the nursing home setting and a diverse range of professionals. We expect the intervention to result in a significant increase in the number of hygiene activities implemented by health care providers and residents. Additionally, we anticipate a marked reduction in the number of inappropriately managed UTIs, as well as a substantial decrease in the overall incidence of infections following the intervention. International Registered Report Identifier (IRRID): DERR1-10.2196/60099 ", doi="10.2196/60099", url="https://www.researchprotocols.org/2024/1/e60099", url="http://www.ncbi.nlm.nih.gov/pubmed/39284176" } @Article{info:doi/10.2196/54044, author="Ito, Genta and Yada, Shuntaro and Wakamiya, Shoko and Aramaki, Eiji", title="Predictive Model for Extended-Spectrum $\beta$-Lactamase--Producing Bacterial Infections Using Natural Language Processing Technique and Open Data in Intensive Care Unit Environment: Retrospective Observational Study", journal="JMIR Form Res", year="2024", month="Jul", day="10", volume="8", pages="e54044", keywords="predictive modeling", keywords="MIMIC-3 dataset", keywords="natural language processing", keywords="NLP", keywords="QuickUMLS", keywords="named entity recognition", keywords="ESBL-producing bacterial infections", abstract="Background: Machine learning has advanced medical event prediction, mostly using private data. The public MIMIC-3 (Medical Information Mart for Intensive Care III) data set, which contains detailed data on over 40,000 intensive care unit patients, stands out as it can help develop better models including structured and textual data. Objective: This study aimed to build and test a machine learning model using the MIMIC-3 data set to determine the effectiveness of information extracted from electronic medical record text using a named entity recognition, specifically QuickUMLS, for predicting important medical events. Using the prediction of extended-spectrum $\beta$-lactamase (ESBL)--producing bacterial infections as an example, this study shows how open data sources and simple technology can be useful for making clinically meaningful predictions. Methods: The MIMIC-3 data set, including demographics, vital signs, laboratory results, and textual data, such as discharge summaries, was used. This study specifically targeted patients diagnosed with Klebsiella pneumoniae or Escherichia coli infection. Predictions were based on ESBL-producing bacterial standards and the minimum inhibitory concentration criteria. Both the structured data and extracted patient histories were used as predictors. In total, 2 models, an L1-regularized logistic regression model and a LightGBM model, were evaluated using the receiver operating characteristic area under the curve (ROC-AUC) and the precision-recall curve area under the curve (PR-AUC). Results: Of 46,520 MIMIC-3 patients, 4046 were identified with bacterial cultures, indicating the presence of K pneumoniae or E coli. After excluding patients who lacked discharge summary text, 3614 patients remained. The L1-penalized model, with variables from only the structured data, displayed a ROC-AUC of 0.646 and a PR-AUC of 0.307. The LightGBM model, combining structured and textual data, achieved a ROC-AUC of 0.707 and a PR-AUC of 0.369. Key contributors to the LightGBM model included patient age, duration since hospital admission, and specific medical history such as diabetes. The structured data-based model showed improved performance compared to the reference models. Performance was further improved when textual medical history was included. Compared to other models predicting drug-resistant bacteria, the results of this study ranked in the middle. Some misidentifications, potentially due to the limitations of QuickUMLS, may have affected the accuracy of the model. Conclusions: This study successfully developed a predictive model for ESBL-producing bacterial infections using the MIMIC-3 data set, yielding results consistent with existing literature. This model stands out for its transparency and reliance on open data and open-named entity recognition technology. The performance of the model was enhanced using textual information. With advancements in natural language processing tools such as BERT and GPT, the extraction of medical data from text holds substantial potential for future model optimization. ", doi="10.2196/54044", url="https://formative.jmir.org/2024/1/e54044" } @Article{info:doi/10.2196/55228, author="Wallman, Andy and Sv{\"a}rdsudd, Kurt and Bobits, Kent and Wallman, Thorne", title="Antibiotic Prescribing by Digital Health Care Providers as Compared to Traditional Primary Health Care Providers: Cohort Study Using Register Data", journal="J Med Internet Res", year="2024", month="Jun", day="26", volume="26", pages="e55228", keywords="telehealth prescribing", keywords="physical-primary health care", keywords="internet-primary health care", keywords="antibiotics", keywords="prescription", keywords="infectious disease", keywords="antibiotic", keywords="prescriptions", keywords="prescribing", keywords="telehealth", keywords="health care", keywords="traditional", keywords="digital", keywords="telemedicine", keywords="virtual care", keywords="Swedish", keywords="Sweden", keywords="primary care", keywords="quality of care", keywords="online setting", keywords="ePrescription", keywords="ePrescriptions", keywords="ePrescribing", keywords="eHealth", keywords="compare", keywords="comparison", keywords="online consultation", keywords="digital care", keywords="patient record", keywords="patient records", keywords="mobile phone", abstract="Background: ?``Direct-to-consumer (DTC) telemedicine'' is increasing worldwide and changing the map of primary health care (PHC). Virtual care has increased in the last decade and with the ongoing COVID-19 pandemic, patients' use of online care has increased even further. In Sweden, online consultations are a part of government-supported health care today, and there are several digital care providers on the Swedish market, which makes it possible to get in touch with a doctor within a few minutes. The fast expansion of this market has raised questions about the quality of primary care provided only in an online setting without any physical appointments. Antibiotic prescribing is a common treatment in PHC. Objective: ?This study aimed to compare antibiotic prescribing between digital PHC providers (internet-PHC) and traditional physical PHC providers (physical-PHC) and to determine whether prescriptions for specific diagnoses differed between internet-PHC and physical-PHC appointments, adjusted for the effects of attained age at the time of appointment, gender, and time relative to the COVID-19 pandemic. Methods: ?Antibiotic prescribing data based on Anatomical Therapeutic Chemical (ATC) codes were obtained for Region S{\"o}rmland residents from January 2020 until March 2021 from the Regional Administrative Office. In total, 160,238 appointments for 68,332 S{\"o}rmland residents were included (124,398 physical-PHC and 35,840 internet-PHC appointments). Prescriptions issued by internet-PHC or physical-PHC physicians were considered. Information on the appointment date, staff category serving the patient, ICD-10 (International Statistical Classification of Diseases, Tenth Revision) diagnosis codes, ATC codes of prescribed medicines, and patient-attained age and gender were used. Results: ?A total of 160,238 health care appointments were registered, of which 18,433 led to an infection diagnosis. There were large differences in gender and attained age distributions among physical-PHC and internet-PHC appointments. Physical-PHC appointments peaked among patients aged 60-80 years while internet-PHC appointments peaked at 20-30 years of age for both genders. Antibiotics with the ATC codes J01A-J01X were prescribed in 9.3\% (11,609/124,398) of physical-PHC appointments as compared with 6.1\% (2201/35,840) of internet-PHC appointments. In addition, 61.3\% (6412/10,454) of physical-PHC infection appointments resulted in antibiotic prescriptions, as compared with only 25.8\% (2057/7979) of internet-PHC appointments. Analyses of the prescribed antibiotics showed that internet-PHC followed regional recommendations for all diagnoses. Physical-PHC also followed the recommendations but used a wider spectrum of antibiotics. The odds ratio of receiving an antibiotic prescription (after adjustments for attained age at the time of appointment, patient gender, and whether the prescription was issued before or during the COVID-19 pandemic) during an internet-PHC appointment was 0.23-0.39 as compared with a physical-PHC appointment. Conclusions: ?Internet-PHC appointments resulted in a significantly lower number of antibiotics prescriptions than physical-PHC appointments, adjusted for the large differences in the characteristics of patients who consult internet-PHC and physical-PHC. Internet-PHC prescribers showed appropriate prescribing according to guidelines. ", doi="10.2196/55228", url="https://www.jmir.org/2024/1/e55228" } @Article{info:doi/10.2196/54996, author="Stevens, R. Elizabeth and Xu, Lynn and Kwon, JaeEun and Tasneem, Sumaiya and Henning, Natalie and Feldthouse, Dawn and Kim, Ji Eun and Hess, Rachel and Dauber-Decker, L. Katherine and Smith, D. Paul and Halm, Wendy and Gautam-Goyal, Pranisha and Feldstein, A. David and Mann, M. Devin", title="Barriers to Implementing Registered Nurse--Driven Clinical Decision Support for Antibiotic Stewardship: Retrospective Case Study", journal="JMIR Form Res", year="2024", month="May", day="23", volume="8", pages="e54996", keywords="integrated clinical prediction rules", keywords="EHR", keywords="electronic health record", keywords="implementation", keywords="barriers", keywords="acute respiratory infections", keywords="antibiotics", keywords="CDS", keywords="clinical decision support", keywords="decision support", keywords="antibiotic", keywords="prescribe", keywords="prescription", keywords="acute respiratory infection", keywords="barrier", keywords="effectiveness", keywords="registered nurse", keywords="RN", keywords="RN-driven intervention", keywords="personnel availability", keywords="workflow variability", keywords="infrastructure", keywords="infrastructures", keywords="law", keywords="laws", keywords="policy", keywords="policies", keywords="clinical-care setting", keywords="clinical setting", keywords="electronic health records", keywords="RN-driven", keywords="antibiotic stewardship", keywords="retrospective analysis", keywords="Consolidated Framework for Implementation Research", keywords="CFIR", keywords="CDS-based intervention", keywords="urgent care", keywords="New York", keywords="chart review", keywords="interview", keywords="interviews", keywords="staff change", keywords="staff changes", keywords="RN shortage", keywords="RN shortages", keywords="turnover", keywords="health system", keywords="nurse", keywords="nurses", keywords="researcher", keywords="researchers", abstract="Background: Up to 50\% of antibiotic prescriptions for upper respiratory infections (URIs) are inappropriate. Clinical decision support (CDS) systems to mitigate unnecessary antibiotic prescriptions have been implemented into electronic health records, but their use by providers has been limited. Objective: As a delegation protocol, we adapted a validated electronic health record--integrated clinical prediction rule (iCPR) CDS-based intervention for registered nurses (RNs), consisting of triage to identify patients with low-acuity URI followed by CDS-guided RN visits. It was implemented in February 2022 as a randomized controlled stepped-wedge trial in 43 primary and urgent care practices within 4 academic health systems in New York, Wisconsin, and Utah. While issues were pragmatically addressed as they arose, a systematic assessment of the barriers to implementation is needed to better understand and address these barriers. Methods: We performed a retrospective case study, collecting quantitative and qualitative data regarding clinical workflows and triage-template use from expert interviews, study surveys, routine check-ins with practice personnel, and chart reviews over the first year of implementation of the iCPR intervention. Guided by the updated CFIR (Consolidated Framework for Implementation Research), we characterized the initial barriers to implementing a URI iCPR intervention for RNs in ambulatory care. CFIR constructs were coded as missing, neutral, weak, or strong implementation factors. Results: Barriers were identified within all implementation domains. The strongest barriers were found in the outer setting, with those factors trickling down to impact the inner setting. Local conditions driven by COVID-19 served as one of the strongest barriers, impacting attitudes among practice staff and ultimately contributing to a work infrastructure characterized by staff changes, RN shortages and turnover, and competing responsibilities. Policies and laws regarding scope of practice of RNs varied by state and institutional application of those laws, with some allowing more clinical autonomy for RNs. This necessitated different study procedures at each study site to meet practice requirements, increasing innovation complexity. Similarly, institutional policies led to varying levels of compatibility with existing triage, rooming, and documentation workflows. These workflow conflicts were compounded by limited available resources, as well as an implementation climate of optional participation, few participation incentives, and thus low relative priority compared to other clinical duties. Conclusions: Both between and within health care systems, significant variability existed in workflows for patient intake and triage. Even in a relatively straightforward clinical workflow, workflow and cultural differences appreciably impacted intervention adoption. Takeaways from this study can be applied to other RN delegation protocol implementations of new and innovative CDS tools within existing workflows to support integration and improve uptake. When implementing a system-wide clinical care intervention, considerations must be made for variability in culture and workflows at the state, health system, practice, and individual levels. Trial Registration: ClinicalTrials.gov NCT04255303; https://clinicaltrials.gov/ct2/show/NCT04255303 ", doi="10.2196/54996", url="https://formative.jmir.org/2024/1/e54996", url="http://www.ncbi.nlm.nih.gov/pubmed/38781006" } @Article{info:doi/10.2196/50588, author="Katumba, Godfrey and Mwanja, Herman and Mayito, Jonathan and Mbolanyi, Betty and Isaasi, Fred and Kibombo, Daniel and Namumbya, Judith and Musoke, David and Kabazzi, Jonathan and Sekamatte, Musa and Idrakua, Lillian and Walwema, Richard and Lamorde, Mohammed and Kakooza, Francis and Etimu, Simon", title="Establishing Antimicrobial Resistance Surveillance in the Water and Environment Sector in a Resource-Limited Setting: Methodical Qualitative and Quantitative Description of Uganda's Experience From 2021 to 2023", journal="JMIRx Bio", year="2024", month="May", day="7", volume="2", pages="e50588", keywords="antimicrobial resistance", keywords="surveillance system", keywords="water and environment sector", abstract="Background: Antimicrobial irrational use and poor disposal in the human and animal sectors promote antimicrobial resistance (AMR) in the environment as these antimicrobials and their active ingredients, coupled with resistant microbes, are released into the environment. While AMR containment programs in the human and animal sectors are well established in Uganda, those in the water and environment sector still need to be established and strengthened. Therefore, the Ministry of Water and Environment set out to establish an AMR surveillance program to bolster the One Health efforts for the containment of AMR under the National Action Plan 2018-2023. Objective: This study aims to describe Uganda's experience in establishing AMR surveillance in the water and environment sector. Methods: A methodical qualitative and quantitative description of the steps undertaken between August 2021 and March 2023 to establish an AMR surveillance system in the water and environment sector is provided. The Uganda Ministry of Water and Environment used a stepwise approach. Governance structures were streamlined, and sector-specific AMR surveillance guiding documents were developed, pretested, and rolled out. The National Water Quality Reference Laboratory infrastructure and microbiology capacity were enhanced to aid AMR detection and surveillance using conventional culture-based methods. A passive and targeted active surveillance hybrid was used to generate AMR data. Passive surveillance used remnants of water samples collected routinely for water quality monitoring while targeted active surveys were done at selected sites around the Kampala and Wakiso districts. Excel and Stata 15 statistical software were used for data analysis. Results: A sector-specific technical working group of 10 members and focal persons is in place, providing strategic direction and linkage to the national AMR surveillance program. The National Water Quality Reference Laboratory is now at biosafety level 2 and conducting microbiology testing using conventional culture-based techniques. Up to 460 water samples were processed and 602 bacterial isolates were recovered, of which 399 (66.3\%) and 203 (33.7\%) were priority pathogens and nonpriority pathogens, respectively. Of the 399 priority pathogens, 156 (39.1\%), 140 (35.1\%), 96 (24.1\%), and 7 (1.8\%) were Escherichia coli, Klebsiella species, Enterococcus species, and Salmonella species, respectively. E coli showed resistance to ampicillin (79\%), ciprofloxacin (29\%), and ceftriaxone (29\%). Similarly, Klebsiella species showed resistance to ampicillin (100\%), ciprofloxacin (17\%), and ceftriaxone (18\%). Enterococcus species showed resistance to ciprofloxacin (52\%), vancomycin (45\%), and erythromycin (56\%). Up to 254 (63.7\%) of the priority pathogens recovered exhibited multiple and extensive resistance to the different antibiotics set. Conclusions: Initial efforts to establish and implement AMR surveillance in the water and environment sector have succeeded in streamlining governance and laboratory systems to generate AMR data using conventional culture-based methods. ", doi="10.2196/50588", url="https://bio.jmirx.org/2024/1/e50588" } @Article{info:doi/10.2196/51326, author="?lhanl?, Nevruz and Park, Yoon Se and Kim, Jaewoong and Ryu, An Jee and Yard?mc?, Ahmet and Yoon, Dukyong", title="Prediction of Antibiotic Resistance in Patients With a Urinary Tract Infection: Algorithm Development and Validation", journal="JMIR Med Inform", year="2024", month="Feb", day="29", volume="12", pages="e51326", keywords="antibiotic resistance", keywords="machine learning", keywords="urinary tract infections", keywords="UTI", keywords="decision support", abstract="Background: The early prediction of antibiotic resistance in patients with a urinary tract infection (UTI) is important to guide appropriate antibiotic therapy selection. Objective: In this study, we aimed to predict antibiotic resistance in patients with a UTI. Additionally, we aimed to interpret the machine learning models we developed. Methods: The electronic medical records of patients who were admitted to Yongin Severance Hospital, South Korea were used. A total of 71 features extracted from patients' admission, diagnosis, prescription, and microbiology records were used for classification. UTI pathogens were classified as either sensitive or resistant to cephalosporin, piperacillin-tazobactam (TZP), carbapenem, trimethoprim-sulfamethoxazole (TMP-SMX), and fluoroquinolone. To analyze how each variable contributed to the machine learning model's predictions of antibiotic resistance, we used the Shapley Additive Explanations method. Finally, a prototype machine learning--based clinical decision support system was proposed to provide clinicians the resistance probabilities for each antibiotic. Results: The data set included 3535, 737, 708, 1582, and 1365 samples for cephalosporin, TZP, TMP-SMX, fluoroquinolone, and carbapenem resistance prediction models, respectively. The area under the receiver operating characteristic curve values of the random forest models were 0.777 (95\% CI 0.775-0.779), 0.864 (95\% CI 0.862-0.867), 0.877 (95\% CI 0.874-0.880), 0.881 (95\% CI 0.879-0.882), and 0.884 (95\% CI 0.884-0.885) in the training set and 0.638 (95\% CI 0.635-0.642), 0.630 (95\% CI 0.626-0.634), 0.665 (95\% CI 0.659-0.671), 0.670 (95\% CI 0.666-0.673), and 0.721 (95\% CI 0.718-0.724) in the test set for predicting resistance to cephalosporin, TZP, carbapenem, TMP-SMX, and fluoroquinolone, respectively. The number of previous visits, first culture after admission, chronic lower respiratory diseases, administration of drugs before infection, and exposure time to these drugs were found to be important variables for predicting antibiotic resistance. Conclusions: The study results demonstrated the potential of machine learning to predict antibiotic resistance in patients with a UTI. Machine learning can assist clinicians in making decisions regarding the selection of appropriate antibiotic therapy in patients with a UTI. ", doi="10.2196/51326", url="https://medinform.jmir.org/2024/1/e51326", url="http://www.ncbi.nlm.nih.gov/pubmed/38421718" } @Article{info:doi/10.2196/50417, author="Attal, Hersh and Huang, Zhilian and Kuan, Sen Win and Weng, Yanyi and Tan, Yee Hann and Seow, Eillyne and Peng, Lee Li and Lim, Chin Hoon and Chow, Angela", title="N-of-1 Trials of Antimicrobial Stewardship Interventions to Optimize Antibiotic Prescribing for Upper Respiratory Tract Infection in Emergency Departments: Protocol for a Quasi-Experimental Study", journal="JMIR Res Protoc", year="2024", month="Feb", day="21", volume="13", pages="e50417", keywords="antibiotic resistance", keywords="emergency department", keywords="upper respiratory tract infection", keywords="N-of-1 trials", keywords="prescribing feedback", keywords="feedback", keywords="emergency", keywords="upper respiratory tract", keywords="respiratory", keywords="antibiotic", keywords="antimicrobial stewardship", keywords="antimicrobials", keywords="antibiotics", keywords="hospital", keywords="experimental study", keywords="antibiotic therapy", keywords="URTI", keywords="evidence-based intervention", keywords="evidence-based", keywords="patient education", keywords="prescribing rates", keywords="patient literacy", keywords="Singapore", keywords="regression analysis", keywords="regression", abstract="Background: Antimicrobial stewardship programs attempting to optimize antibiotic therapy and clinical outcomes mainly focus on inpatient and outpatient settings. The lack of antimicrobial stewardship program studies in the emergency department (ED) represents a gap in tackling the problem of antimicrobial resistance as EDs treat a substantial number of upper respiratory tract infection cases throughout the year. Objective: We intend to implement two evidence-based interventions: (1) patient education and (2) providing physician feedback on their prescribing rates. We will incorporate evidence from a literature review and contextualizing the interventions based on findings from a local qualitative study. Methods: Our study uses a quasi-experimental design to evaluate the effects of interventions over time in the EDs of 4 public hospitals in Singapore. We will include an initial control period of 18 months. In the next 6 months, we will randomize 2 EDs to receive 1 intervention (ie, patient education) and the other 2 EDs to receive the alternative intervention (ie, physician feedback). All EDs will receive the second intervention in the subsequent 6 months on top of the ongoing intervention. Data will be collected for another 6 months to assess the persistence of the intervention effects. The information leaflets will be handed to patients at the EDs before they consult with the physician, while feedback to individual physicians by senior doctors is in the form of electronic text messages. The feedback will contain the physicians' antibiotic prescribing rate compared with the departments' overall antibiotic prescribing rate and a bite-size message on good antibiotic prescribing practices. Results: We will analyze the data using segmented regression with difference-in-difference estimation to account for concurrent cluster comparisons. Conclusions: Our proposed study assesses the effectiveness of evidence-based, context-specific interventions to optimize antibiotic prescribing in EDs. These interventions are aligned with Singapore's national effort to tackle antimicrobial resistance and can be scaled up if successful. Trial Registration: ClinicalTrials.gov NCT05451863; https://clinicaltrials.gov/study/NCT05451836 International Registered Report Identifier (IRRID): DERR1-10.2196/50417 ", doi="10.2196/50417", url="https://www.researchprotocols.org/2024/1/e50417", url="http://www.ncbi.nlm.nih.gov/pubmed/38381495" } @Article{info:doi/10.2196/46938, author="Hoang, Uy and Williams, Alice and Smylie, Jessica and Aspden, Carole and Button, Elizabeth and Macartney, Jack and Okusi, Cecilia and Byford, Rachel and Ferreira, Filipa and Leston, Meredith and Xie, Xuan Charis and Joy, Mark and Marsden, Gemma and Clark, Tristan and de Lusignan, Simon", title="The Impact of Point-of-Care Testing for Influenza on Antimicrobial Stewardship (PIAMS) in UK Primary Care: Protocol for a Mixed Methods Study", journal="JMIR Res Protoc", year="2023", month="Jun", day="16", volume="12", pages="e46938", keywords="medical records systems, computerized", keywords="influenza point-of-care systems", keywords="general practice", keywords="RSV", keywords="implementation", keywords="outcome assessment", keywords="health care", keywords="antimicrobial stewardship", keywords="acute respiratory infection", keywords="antimicrobial", keywords="influenza", keywords="primary care", keywords="respiratory symptom", abstract="Background: Molecular point-of-care testing (POCT) used in primary care can inform whether a patient presenting with an acute respiratory infection has influenza. A confirmed clinical diagnosis, particularly early in the disease, could inform better antimicrobial stewardship. Social distancing and lockdowns during the COVID-19 pandemic have disturbed previous patterns of influenza infections in 2021. However, data from samples taken in the last quarter of 2022 suggest that influenza represents 36\% of sentinel network positive virology, compared with 24\% for respiratory syncytial virus. Problems with integration into the clinical workflow is a known barrier to incorporating technology into routine care. Objective: This study aims to report the impact of POCT for influenza on antimicrobial prescribing in primary care. We will additionally describe severe outcomes of infection (hospitalization and mortality) and how POCT is integrated into primary care workflows. Methods: The impact of POCT for influenza on antimicrobial stewardship (PIAMS) in UK primary care is an observational study being conducted between December 2022 and May 2023 and involving 10 practices that contribute data to the English sentinel network. Up to 1000 people who present to participating practices with respiratory symptoms will be swabbed and tested with a rapid molecular POCT analyzer in the practice. Antimicrobial prescribing and other study outcomes will be collected by linking information from the POCT analyzer with data from the patient's computerized medical record. We will collect data on how POCT is incorporated into practice using data flow diagrams, unified modeling language use case diagrams, and Business Process Modeling Notation. Results: We will present the crude and adjusted odds of antimicrobial prescribing (all antibiotics and antivirals) given a POCT diagnosis of influenza, stratifying by whether individuals have a respiratory or other relevant diagnosis (eg, bronchiectasis). We will also present the rates of hospital referrals and deaths related to influenza infection in PIAMS study practices compared with a set of matched practices in the sentinel network and the rest of the network. We will describe any difference in implementation models in terms of staff involved and workflow. Conclusions: This study will generate data on the impact of POCT testing for influenza in primary care as well as help to inform about the feasibility of incorporating POCT into primary care workflows. It will inform the design of future larger studies about the effectiveness and cost-effectiveness of POCT to improve antimicrobial stewardship and any impact on severe outcomes. International Registered Report Identifier (IRRID): DERR1-10.2196/46938 ", doi="10.2196/46938", url="https://www.researchprotocols.org/2023/1/e46938", url="http://www.ncbi.nlm.nih.gov/pubmed/37327029" } @Article{info:doi/10.2196/37863, author="Cresswell, Kathrin and Hinder, Susan and Sheikh, Aziz and Pontefract, Sarah and Watson, W. Neil and Price, David and Heed, Andrew and Coleman, Jamie and Ennis, Holly and Beggs, Jillian and Chuter, Antony and Williams, Robin", title="ePrescribing-Based Antimicrobial Stewardship Practices in an English National Health Service Hospital: Qualitative Interview Study Among Medical Prescribers and Pharmacists", journal="JMIR Form Res", year="2023", month="Jun", day="6", volume="7", pages="e37863", keywords="antimicrobial resistance", keywords="antimicrobial stewardship", keywords="electronic prescribing", keywords="hospitals", abstract="Background: Antimicrobial resistance, the ability of microorganisms to survive antimicrobial drugs, is a public health emergency. Although electronic prescribing (ePrescribing)--based interventions designed to reduce unnecessary antimicrobial usage exist, these often do not integrate effectively with existing workflows. As a result, ePrescribing-based interventions may have limited impact in addressing antimicrobial resistance. Objective: We sought to understand the existing ePrescribing-based antimicrobial stewardship (AMS) practices in an English hospital preceding the implementation of functionality designed to improve AMS. Methods: We conducted 18 semistructured interviews with medical prescribers and pharmacists with varying levels of seniority exploring current AMS practices and investigating potential areas for improvement. Participants were recruited with the help of local gatekeepers. Topic guides sought to explore both formal and informal practices surrounding AMS, and challenges and opportunities for ePrescribing-based intervention. We coded audio-recorded and transcribed data with the help of the Technology, People, Organizations, and Macroenvironmental factors framework, allowing emerging themes to be added inductively. We used NVivo 12 (QSR International) to facilitate coding. Results: Antimicrobial prescribing and review processes were characterized by competing priorities and uncertainty of prescribers and reviewers around prescribing decisions. For example, medical prescribers often had to face trade-offs between individual patient benefit and more diffuse population health benefits, and the rationale for prescribing decisions was not always clear. Prescribing involved a complex set of activities carried out by various health care practitioners who each only had a partial and temporary view of the whole process, and whose relationships were characterized by deeply engrained hierarchies that shaped interactions and varied across specialties. For example, newly qualified doctors and pharmacists were hesitant to change a consultant's prescribing decision when reviewing prescriptions. Multidisciplinary communication, collaboration, and coordination promoted good AMS practices by reducing uncertainty. Conclusions: Design of ePrescribing-based interventions to improve AMS needs to take into account the multitude of actors and organizational complexities involved in the prescribing and review processes. Interventions that help reduce prescriber or reviewer uncertainty and improve multidisciplinary collaboration surrounding initial antimicrobial prescribing and subsequent prescription review are most likely to be effective. Without such attention, interventions are unlikely to fulfill their goal of improving patient outcomes and combatting antimicrobial resistance. ", doi="10.2196/37863", url="https://formative.jmir.org/2023/1/e37863", url="http://www.ncbi.nlm.nih.gov/pubmed/37279044" } @Article{info:doi/10.2196/39022, author="Bakon, Karen Sophia and Mohamad, Asrah Zuraifah and Jamilan, Azerulazree Mohd and Hashim, Hazimah and Kuman, Yazid Mohamed and Shaharudin, Rafiza and Ahmad, Norazah and Muhamad, Asiah Nor", title="Prevalence of Antibiotic-Resistant Pathogenic Bacteria and Level of Antibiotic Residues in Hospital Effluents in Selangor, Malaysia: Protocol for a Cross-sectional Study", journal="JMIR Res Protoc", year="2023", month="May", day="29", volume="12", pages="e39022", keywords="ESKAPE", keywords="antimicrobial resistance", keywords="hospital effluent", keywords="antibiotics", keywords="health care", keywords="antibiotic resistance", keywords="antimicrobial", keywords="hospital setting", keywords="antibiotic residues", keywords="wastewater", abstract="Background: Antimicrobial resistance (AMR) has emerged as a major global public health challenge due to the overuse and misuse of antibiotics for humans and animals. Hospitals are among the major users of antibiotics, thereby having a large contribution to AMR. Objective: The aim of this study is to determine the prevalence of antibiotic-resistant pathogenic bacteria and the level of antibiotic residues in the hospital effluents in Selangor, Malaysia. Methods: A cross-sectional study will be performed in the state of Selangor, Malaysia. Tertiary hospitals will be identified based on the inclusion and exclusion criteria. The methods are divided into three phases: sample collection, microbiological analysis, and chemical analysis. Microbiological analyses will include the isolation of bacteria from hospital effluents by culturing on selective media. Antibiotic sensitivity testing will be performed on the isolated bacteria against ceftriaxone, ciprofloxacin, meropenem, vancomycin, colistin, and piperacillin/tazobactam. The identification of bacteria will be confirmed using 16S RNA polymerase chain reaction (PCR) and multiplex PCR will be performed to detect resistance genes (ermB, mecA, blaNDM-L, blaCTX-M, blaOXA-48, blaSHV, VanA, VanB, VanC1, mcr-1, mcr-2, mcr-3, Intl1, Intl2, and qnrA). Finally, the level of antibiotic residues will be measured using ultrahigh-performance liquid chromatography. Results: The expected outcomes will be the prevalence of antibiotic-resistant Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter (ESKAPE) bacterial species from the hospital effluents, the occurrence of antibiotic resistance genes (ARGs) from the isolated ESKAPE bacteria, and the level of antibiotic residues that may be detected from the effluent. Sampling has been conducted in three hospitals. Data analysis from one hospital showed that as of July 2022, 80\% (8/10) of E. faecium isolates were resistant to vancomycin and 10\% (1/10) were resistant to ciprofloxacin. Further analysis will be conducted to determine if the isolates harbor any ARGs and effluent samples are being analyzed to detect antibiotic residues. Sampling activities will be resumed after being suspended due to the COVID-19 pandemic and are scheduled to end by December 2022. Conclusions: This study will provide the first baseline information to elucidate the current status of AMR of highly pathogenic bacteria present in hospital effluents in Malaysia. International Registered Report Identifier (IRRID): DERR1-10.2196/39022 ", doi="10.2196/39022", url="https://www.researchprotocols.org/2023/1/e39022", url="http://www.ncbi.nlm.nih.gov/pubmed/37247207" } @Article{info:doi/10.2196/45109, author="Florea, Ana and Casey, A. Joan and Nachman, Keeve and Price, B. Lance and Pomichowski, E. Magdalena and Takhar, S. Harpreet and Quinlivan, Vanessa and Childs, D. Lee and Davis, F. Meghan and Wei, Rong and Hong, Vennis and Ku, H. Jennifer and Liu, M. Cindy and Pressman, Alice and Robinson, Sarah and Bruxvoort, J. Katia and Salas, Bianca S. and Tartof, Y. Sara", title="Impact of California's Senate Bill 27 on Antimicrobial-Resistant Escherichia coli Urinary Tract Infection in Humans: Protocol for a Study of Methods and Baseline Data", journal="JMIR Res Protoc", year="2023", month="May", day="5", volume="12", pages="e45109", keywords="AMR", keywords="antimicrobial resistance", keywords="E coli", keywords="Escherichia coli", keywords="urinary tract infection", keywords="UTI", abstract="Background: Overuse of antibiotics contributes to antimicrobial resistance (AMR) and is a growing threat to human health worldwide. Previous work suggests a link between antimicrobial use in poultry and human AMR extraintestinal pathogenic Escherichia coli (E coli) urinary tract infections (UTIs). However, few US-based studies exist, and none have comprehensively assessed both foodborne and environmental pathways using advanced molecular and spatial epidemiologic methods in a quasi-experimental design. Recently, California enacted Senate Bill 27 (SB27), which changed previous policy to require a veterinarian's prescription for the use of antibiotic drugs, and which banned antibiotic use for disease prevention in livestock. This provided an opportunity to evaluate whether SB27 will result in a reduction in antimicrobial-resistant infections in humans. Objective: We describe in detail the methods implemented to achieve the overarching objective of this study to evaluate the impact of SB27 on downstream antibiotic resistance rates in human UTIs. Methods: A summary of the overall approach and the partnerships between Columbia University, George Washington University (GWU), Johns Hopkins Bloomberg School of Public Health, Kaiser Permanente Southern California (KPSC) Research and Evaluation, the Natural Resources Defense Council, Sanger Institute at Stanford University, Sutter Health Center for Health Systems Research, the University of Cambridge, and the University of Oxford is presented. The collection, quality control testing, and shipment of retail meat and clinical samples are described. Retail meat (chicken, beef, turkey, and pork) was purchased from stores throughout Southern California from 2017 to 2021. After processing at KPSC, it was shipped to GWU for testing. From 2016 to 2021, after clinical specimens were processed for routine clinical purposes and immediately before discarding, those with isolated colonies of E coli, Campylobacter, and Salmonella from KPSC members were collected and processed to be shipped for testing at GWU. Detailed methods of the isolation and testing as well as the whole-genome sequencing of the meat and clinical samples at GWU are described. KPSC electronic health record data were used to track UTI cases and AMR patterns among the cultured specimens. Similarly, Sutter Health electronic health record data were used to track UTI cases in its Northern California patient population. Results: From 2017 to 2021, overall, 12,616 retail meat samples were purchased from 472 unique stores across Southern California. In addition, 31,643 positive clinical cultures were collected from KPSC members during the same study period. Conclusions: Here, we presented data collection methods for the study, which was conducted to evaluate the impact of SB27 on downstream antibiotic resistance rates in human UTI. To date, it is one of the largest studies of its kind to be conducted. The data collected during this study will be used as the foundation for future analyses specific to the various objectives of this large body of work. International Registered Report Identifier (IRRID): DERR1-10.2196/45109 ", doi="10.2196/45109", url="https://www.researchprotocols.org/2023/1/e45109", url="http://www.ncbi.nlm.nih.gov/pubmed/37145842" } @Article{info:doi/10.2196/42978, author="Yoon, Ho Chang and Nolan, Imogen and Humphrey, Gayl and Duffy, J. Eamon and Thomas, G. Mark and Ritchie, R. Stephen", title="Long-Term Impact of a Smartphone App on Prescriber Adherence to Antibiotic Guidelines for Adult Patients With Community-Acquired Pneumonia: Interrupted Time-Series Study", journal="J Med Internet Res", year="2023", month="May", day="2", volume="25", pages="e42978", keywords="app", keywords="antimicrobial stewardship", keywords="antibiotic adherence", keywords="community", keywords="pneumonia", keywords="smartphone", keywords="mobile health", keywords="mHealth", keywords="antibiotic", keywords="behavior", keywords="adults", keywords="diagnosis", keywords="pulmonary", keywords="patient", abstract="Background: Mobile health platforms like smartphone apps that provide clinical guidelines are ubiquitous, yet their long-term impact on guideline adherence remains unclear. In 2016, an antibiotic guidelines app, called SCRIPT, was introduced in Auckland City Hospital, New Zealand, to provide local antibiotic guidelines to clinicians on their smartphones. Objective: We aimed to assess whether the provision of antibiotic guidelines in a smartphone app resulted in sustained changes in antibiotic guideline adherence by prescribers. Methods: We analyzed antibiotic guideline adherence rates during the first 24 hours of hospital admission in adults diagnosed with community-acquired pneumonia using an interrupted time-series study with 3 distinct periods post app implementation (ie, 3, 12, and 24 months). Results: Adherence increased from 23\% (46/200) at baseline to 31\% (73/237) at 3 months and 34\% (69/200) at 12 months, reducing to 31\% (62/200) at 24 months post app implementation (P=.07 vs baseline). However, increased adherence was sustained in patients with pulmonary consolidation on x-ray (9/63, 14\% at baseline; 23/77, 30\% after 3 months; 32/92, 35\% after 12 month; and 32/102, 31\% after 24 months; P=.04 vs baseline). Conclusions: An antibiotic guidelines app increased overall adherence, but this was not sustained. In patients with pulmonary consolidation, the increased adherence was sustained. ", doi="10.2196/42978", url="https://www.jmir.org/2023/1/e42978", url="http://www.ncbi.nlm.nih.gov/pubmed/37129941" } @Article{info:doi/10.2196/45833, author="Huang, Zhilian and Tang, Ee Wern and Guo, Huiling and Natarajan, Karthiga and Lee, Hong Tau and Yeo, Wen Tsin and Chow, Angela", title="An Evidence-Based Serious Game App for Public Education on Antibiotic Use and Antimicrobial Resistance: Protocol of a Randomized Controlled Trial", journal="JMIR Res Protoc", year="2023", month="Mar", day="28", volume="12", pages="e45833", keywords="antibiotic resistance", keywords="antibiotic use", keywords="app development", keywords="development", keywords="educational intervention", keywords="health education", keywords="public education", keywords="randomized controlled trial", keywords="serious games", keywords="user engagement", keywords="user satisfaction", abstract="Background: The misuse and overuse of antibiotics contribute to the acceleration of antimicrobial resistance (AMR), but public knowledge on appropriate antibiotic use and AMR remained low despite ongoing health promotion efforts. App gamification has gained traction in recent years for health promotion and to affect change in health behaviors. Hence, we developed an evidence-based serious game app ``SteWARdS Antibiotic Defence'' to educate the public on appropriate antibiotic use and AMR and address knowledge gaps. Objective: We aim to evaluate the effectiveness of the ``SteWARdS Antibiotic Defence'' app in improving the knowledge of, attitude toward, and perception (KAP) of appropriate antibiotic use and AMR among the public. The primary objective is to assess the changes in KAP of antibiotic use and AMR in our participants, while the secondary objectives are to assess the extent of user engagement with the app and the level of user satisfaction in using the app. Methods: Our study is a parallel 2-armed randomized controlled trial with a 1:1 allocation. We plan to recruit 400 participants (patients or their caregivers) aged 18-65 years from government-funded primary care clinics in Singapore. Participants are randomized in blocks of 4 and into the intervention or control group. Participants in the intervention group are required to download the ``SteWARdS Antibiotic Defence'' app on their smartphones and complete a game quest within 2 weeks. Users will learn about appropriate antibiotic use and effective methods to recover from uncomplicated upper respiratory tract infections by interacting with the nonplayer characters and playing 3 minigames in the app. The control group will not receive any intervention. Results: The primary study outcome is the change in participants' KAP toward antibiotic use and AMR 6-10 weeks post intervention or 6-10 weeks from baseline for the control group (web-based survey). We will also assess the knowledge level of participants immediately after the participant completes the game quest (in the app). The secondary study outcomes are the user engagement level (tracked by the app) and satisfaction level of playing the game (via the immediate postgame survey). The satisfaction survey will also collect participants' feedback on the game app. Conclusions: Our proposed study provides a unique opportunity to assess the effectiveness of a serious game app in public health education. We anticipate possible ceiling effects and selection bias in our study and have planned to perform subgroup analyses to adjust for confounding factors. The app intervention will benefit a larger population if it is proven to be effective and acceptable to users. Trial Registration: ClinicalTrials.gov NCT05445414; https://clinicaltrials.gov/ct2/show/NCT05445414 International Registered Report Identifier (IRRID): DERR1-10.2196/45833 ", doi="10.2196/45833", url="https://www.researchprotocols.org/2023/1/e45833", url="http://www.ncbi.nlm.nih.gov/pubmed/36976619" } @Article{info:doi/10.2196/45121, author="Chan, Y. Isaac H. and Gofine, Miriam and Arora, Shitij and Shaikh, Ahmed and Balsari, Satchit", title="Technology, Training, and Task Shifting at the World's Largest Mass Gathering in 2025: An Opportunity for Antibiotic Stewardship in India", journal="JMIR Public Health Surveill", year="2023", month="Mar", day="8", volume="9", pages="e45121", keywords="digital tools", keywords="mass gathering", keywords="Kumbh Mela", keywords="antibiotics", keywords="antimicrobial", keywords="stewardship", keywords="surveillance", keywords="public health", keywords="informatics", keywords="India", doi="10.2196/45121", url="https://publichealth.jmir.org/2023/1/e45121", url="http://www.ncbi.nlm.nih.gov/pubmed/36805363" } @Article{info:doi/10.2196/41834, author="Mackey, Ken Tim and Jarmusch, K. Alan and Xu, Qing and Sun, Kunyang and Lu, Aileen and Aguirre, Shaden and Lim, Jessica and Bhakta, Simran and Dorrestein, C. Pieter", title="Multifactor Quality and Safety Analysis of Antimicrobial Drugs Sold by Online Pharmacies That Do Not Require a Prescription: Multiphase Observational, Content Analysis, and Product Evaluation Study", journal="JMIR Public Health Surveill", year="2022", month="Dec", day="23", volume="8", number="12", pages="e41834", keywords="online pharmacy", keywords="antimicrobial resistance", keywords="drug safety", keywords="cyberpharmacies", keywords="public health", keywords="health website", keywords="online health", keywords="web surveillance", keywords="patient safety", abstract="Background: Antimicrobial resistance is a significant global public health threat. However, the impact of sourcing potentially substandard and falsified antibiotics via the internet remains understudied, particularly in the context of access to and quality of common antibiotics. In response, this study conducted a multifactor quality and safety analysis of antibiotics sold and purchased via online pharmacies that did not require a prescription. Objective: The aim of this paper is to identify and characterize ``no prescription'' online pharmacies selling 5 common antibiotics and to assess the quality characteristics of samples through controlled test buys. Methods: We first used structured search queries associated with the international nonproprietary names of amoxicillin, azithromycin, amoxicillin and clavulanic acid, cephalexin, and ciprofloxacin to detect and characterize online pharmacies offering the sale of antibiotics without a prescription. Next, we conducted controlled test buys of antibiotics and conducted a visual inspection of packaging and contents for risk evaluation. Antibiotics were then analyzed using untargeted mass spectrometry (MS). MS data were used to determine if the claimed active pharmaceutical ingredient was present, and molecular networking was used to analyze MS data to detect drug analogs as well as possible adulterants and contaminants. Results: A total of 109 unique websites were identified that actively advertised direct-to-consumer sale of antibiotics without a prescription. From these websites, we successfully placed 27 orders, received 11 packages, and collected 1373 antibiotic product samples. Visual inspection resulted in all product packaging consisting of pill packs or blister packs and some concerning indicators of potential poor quality, falsification, and improper dispensing. Though all samples had the presence of stated active pharmaceutical ingredient, molecular networking revealed a number of drug analogs of unknown identity, as well as known impurities and contaminants. Conclusions: Our study used a multifactor approach, including web surveillance, test purchasing, and analytical chemistry, to assess risk factors associated with purchasing antibiotics online. Results provide evidence of possible safety risks, including substandard packaging and shipment, falsification of product information and markings, detection of undeclared chemicals, high variability of quality across samples, and payment for orders being defrauded. Beyond immediate patient safety risks, these falsified and substandard products could exacerbate the ongoing public health threat of antimicrobial resistance by circulating substandard product to patients. ", doi="10.2196/41834", url="https://publichealth.jmir.org/2022/12/e41834", url="http://www.ncbi.nlm.nih.gov/pubmed/36563038" } @Article{info:doi/10.2196/37663, author="Mohamad, Asrah Zuraifah and Bakon, Karen Sophia and Jamilan, Jamilan Mohd Azerulazree and Daud, Norhafizan and Ciric, Lena and Ahmad, Norazah and Muhamad, Asiah Nor", title="Prevalence of Antibiotic-Resistant Bacteria and Antibiotic-Resistant Genes and the Quantification of Antibiotics in Drinking Water Treatment Plants of Malaysia: Protocol for a Cross-sectional Study", journal="JMIR Res Protoc", year="2022", month="Nov", day="21", volume="11", number="11", pages="e37663", keywords="drinking water", keywords="river", keywords="safe", keywords="antibiotic", keywords="resistant", keywords="antimicrobial", keywords="sanitation", keywords="Malaysia", keywords="Asia", keywords="bacteria", abstract="Background: Antimicrobial resistance is a known global public health threat. In addition, it brings serious economic consequences to agriculture. Antibiotic resistance in humans, animals, and environment is interconnected, as proposed in the tricycle surveillance by the World Health Organization. In Malaysia, research and surveillance of antimicrobial resistance are mainly performed in clinical samples, agricultural settings, and surface waters, but no surveillance of the drinking water systems has been performed yet. Hence, this policy-driven study is a combined effort of microbiologists and engineers to provide baseline data on the magnitude of antimicrobial resistance in the drinking water systems of Malaysia. Objective: The aim of this study was to study the baseline level of antibiotic-resistant bacteria in the drinking water distribution systems of Malaysia by collecting samples from the pretreatment and posttreatment outlets of water treatment plants in a selected state of Malaysia. We aimed to determine the prevalence of antibiotic-resistant bacteria, the occurrence of antibiotic-resistant genes, and the level of antibiotics present in the drinking water systems. Methods: This is a laboratory-based, cross-sectional study in a selected state of Malaysia. Water samples from 6 drinking water treatment plants were collected. Samples were collected at 3 sampling points, that is, the intake sampling station, service reservoir outlet station, and the distribution system sampling station. These were tested against 7 types of antibiotics in triplicates. Samples were screened for antibiotic-resistant bacteria and antibiotic-resistant genes and quantified for the level of antibiotics present in the drinking water treatment plants. Results: We will show the descriptive statistics of the number of bacterial colonies harvested from water samples grown on Reasoner's 2A agar with or without antibiotics, the occurrence of antibiotic-resistant genes, and the level of antibiotics detected in the water samples. The sampling frame was scheduled to start from November 2021 and continue until December 2022. Data analysis is expected to be completed by early 2023, and the results are expected to be published in mid-2023. Conclusions: This study provides baseline information on the status of the antimicrobial-resistant bacteria, the presence of resistance genes as contaminants, and the level of antibiotics present in the drinking water systems of Malaysia, with the aim of demonstrating to policymakers the need to consider antimicrobial resistance as a parameter in drinking water surveillance. International Registered Report Identifier (IRRID): DERR1-10.2196/37663 ", doi="10.2196/37663", url="https://www.researchprotocols.org/2022/11/e37663", url="http://www.ncbi.nlm.nih.gov/pubmed/36409546" } @Article{info:doi/10.2196/35774, author="Papan, Cihan and Reifenrath, Katharina and Last, Katharina and Attarbaschi, Andishe and Graf, Norbert and Groll, H. Andreas and Huebner, Johannes and Laws, Hans-J{\"u}rgen and Lehrnbecher, Thomas and Liese, Johannes and Martin, Luise and Tenenbaum, Tobias and Weichert, Stefan and Vieth, Simon and von Both, Ulrich and Hufnagel, Markus and Simon, Arne", title="Antimicrobial Use in Pediatric Oncology and Hematology: Protocol for a Multicenter Point-Prevalence Study With Qualitative Expert Panel Assessment", journal="JMIR Res Protoc", year="2022", month="Jun", day="20", volume="11", number="6", pages="e35774", keywords="point-prevalence study", keywords="antimicrobial stewardship", keywords="pediatric oncology", keywords="pediatric hematology", keywords="expert panel", keywords="antimicrobial resistance", keywords="oncology", keywords="cancer", keywords="pediatrics", abstract="Background: Because infections are a major driver of morbidity and mortality in children with hematologic or oncologic diseases, antimicrobials are frequently prescribed in pediatric oncology practice. However, excess or inappropriate use of antimicrobials is directly linked to the emergence of antimicrobial resistance. Although point-prevalence studies have examined the extent of antimicrobial use, a comprehensive qualitative evaluation of individual antimicrobial prescriptions remains lacking. Objective: The aim of this study is to identify appropriate versus inappropriate antimicrobial use among pediatric cancer patients in a point-prevalence study, followed by an expert panel adjudication process and a subsequent report of these findings to participating centers. This study also aims to improve the quality of patient care by informing centers about discrepancies between internal standards of care and national guidelines. Methods: Our point-prevalence study is performed at pediatric cancer centers in Germany and Austria. All patients under 18 years old who are hospitalized at the time of the study are included. As a supplement to the point-prevalence study, an expert panel is qualitatively assessing each of the antimicrobial prescriptions at the participating centers to review local guidelines and compare them with national guidelines. Results: As of December 2021, the point-prevalence survey has been conducted at 30 sites and expert panel adjudication for qualitative assessment of each antimicrobial use is ongoing. Results of the study are expected in 2022. Conclusions: This is the first point-prevalence study conducted among pediatric cancer centers with an integrated, multistep, qualitative approach that assesses each antimicrobial prescription. The results of this study will inform possible interventions for internal guidelines and antimicrobial stewardship programs implemented at pediatric cancer centers. In addition, local guidelines will be compared with national guidelines. Furthermore, this study will contribute to the overall integration of antimicrobial stewardship principles and initiatives in pediatric oncology and hematology, thereby improving safety and quality of care for children and adolescents with cancer and blood disorders. International Registered Report Identifier (IRRID): DERR1-10.2196/35774 ", doi="10.2196/35774", url="https://www.researchprotocols.org/2022/6/e35774", url="http://www.ncbi.nlm.nih.gov/pubmed/35723906" } @Article{info:doi/10.2196/35969, author="Garcia, Cristian and Rehman, Nadia and Lawson, O. Daeria and Djiadeu, Pascal and Mbuagbaw, Lawrence", title="Developing Reporting Guidelines for Studies of HIV Drug Resistance Prevalence: Protocol for a Mixed Methods Study", journal="JMIR Res Protoc", year="2022", month="May", day="13", volume="11", number="5", pages="e35969", keywords="HIV", keywords="drug resistance", keywords="reporting guideline", keywords="prevalence", keywords="surveillance", keywords="antiretroviral therapy", keywords="report", keywords="global health", keywords="problem", abstract="Background: HIV drug resistance is a global health problem that limits the effectiveness of antiretroviral therapy. Adequate surveillance of HIV drug resistance is challenged by heterogenous and inadequate data reporting, which compromises the accuracy, interpretation, and usability of prevalence estimates. Previous research has found that the quality of reporting in studies of HIV drug resistance prevalence is low, and thus better guidance is needed to ensure complete and uniform reporting. Objective: This paper contributes to the process of developing reporting guidelines for prevalence studies of HIV drug resistance by reporting the methodology used in creating a reporting item checklist and generating key insights on items that are important to report. Methods: We will conduct a sequential explanatory mixed methods study among authors and users of studies of HIV drug resistance. The two-phase design will include a cross-sectional electronic survey (quantitative phase) followed by a focus group discussion (qualitative phase). Survey participants will rate the essentiality of various reporting items. This data will be analyzed using content validity ratios to determine the items that will be retained for focus group discussions. Participants in these discussions will revise the items and any additionally suggested items and settle on a complete reporting item checklist. We will also conduct a thematic analysis of the group discussions to identify emergent themes regarding the agreement process. Results: As of November 2021, data collection for both phases of the study is complete. In July 2021, 51 participants had provided informed consent and completed the electronic survey. In October 2021, focus group discussions were held. Nine participants in total participated in two virtual focus group discussions. As of May 2022, data are being analyzed. Conclusions: This study supports the development of a reporting checklist for studies of HIV drug resistance by achieving agreement among experts on what items should be reported in these studies. The results of this work will be refined and elaborated on by a writing committee of HIV drug resistance experts and external reviewers to develop finalized reporting guidelines. International Registered Report Identifier (IRRID): DERR1-10.2196/35969 ", doi="10.2196/35969", url="https://www.researchprotocols.org/2022/5/e35969", url="http://www.ncbi.nlm.nih.gov/pubmed/35559984" } @Article{info:doi/10.2196/26122, author="Turner, Mitchell Monique and Choung, Hyesun and Bui, Mai Quoc-Ha Hannah and Beck, Paige and Ashraf, Hera", title="Reversing the Antibiotic Resistance ``Yelp Effect'' Through the Use of Emotionally Framed Responses to Negative Reviews of Providers: Questionnaire Study", journal="JMIR Form Res", year="2022", month="Mar", day="22", volume="6", number="3", pages="e26122", keywords="online patient review", keywords="antimicrobial resistance", keywords="emotion", keywords="health communication", abstract="Background: The overuse of antibiotics has rapidly made antimicrobial resistance a global public health challenge. There is an emerging trend where providers who perceive that their patients expect antibiotics are more likely to prescribe antibiotics unprompted or upon request. Particularly, health care providers have expressed concern that dissatisfied patients will provide disparaging online reviews, therefore threatening the reputation of the practice. To better deal with the negative reviews and inform patients, some health care staff directly respond to patients' online feedback. Engaging with patients' online reviews gives providers an opportunity to prevent reputational damage and improve patients' understanding of the antibiotic resistance problem. Objective: We aim to test the effectiveness of different response strategies to the negative patient online reviews on the readers' perceptions of the health care provider and their perceptions related to antibiotics resistance. Methods: Two experiments were conducted to examine the impact of message tactics (apologizing, inducing fear or guilt) that can be employed by health care providers when responding to patients' negative online feedback related to not receiving an antibiotic. Results: Overall, our results demonstrated positive impacts of responding to patients' online reviews. In study 1, we found apologetic messaging and use of emotional appeals in the response were effective in making readers feel more favorable toward the message. Readers also expressed a greater credibility perception toward the provider and willingness to visit the clinic when emotional appeals were used. Findings from study 2 largely supported the effectiveness of a fear-based response in improving the readers' credibility perceptions and willingness to visit the clinic. The fear-inducing information was particularly effective among parent readers. Conclusions: This paper demonstrated that a strategic response to online patient complaints could prevent reputational damage and minimize the potential negative impacts of the review. The results also glean insight into the step toward developing a novel intervention---crafting a persuasive response to patients' negative feedback that can help improve the understanding of antibiotic resistance problems. ", doi="10.2196/26122", url="https://formative.jmir.org/2022/3/e26122", url="http://www.ncbi.nlm.nih.gov/pubmed/35315787" } @Article{info:doi/10.2196/26891, author="Ongadi, Beatrice and Lihana, Raphael and Kiiru, John and Ngayo, Musa and Obiero, George", title="An Android-Based Mobile App (ARVPredictor) for the Detection of HIV Drug-Resistance Mutations and Treatment at the Point of Care: Development Study", journal="JMIR Form Res", year="2022", month="Feb", day="2", volume="6", number="2", pages="e26891", keywords="database", keywords="mobile Android app", keywords="HIV/AIDS", keywords="mutation", keywords="pol gene", keywords="protease", keywords="reverse transcriptase", keywords="integrase", keywords="ARVPredictor", keywords="mobile app", keywords="mHealth", keywords="HIV", keywords="Android", keywords="digital health", abstract="Background: HIV/AIDS remains one of the major global human health challenges, especially in resource-limited environments. By 2017, over 77.3 million people were infected with the disease, and approximately 35.4 million individuals had already died from AIDS-related illnesses. Approximately 21.7 million people were accessing ART with significant clinical outcomes. However, numerous challenges are experienced in the delivery and accurate interpretation of data on patients with HIV data by various health care providers at different care levels. Mobile health (mHealth) technology is progressively making inroads into the health sector as well as medical research. Different mobile devices have become common in health care settings, leading to rapid growth in the development of downloadable software specifically designed to fulfill particular health-related purposes. Objective: We developed a mobile-based app called ARVPredictor and demonstrated that it can accurately define HIV-1 drug-resistance mutations in the HIV pol gene for use at the point of care. Methods: ARVPredictor was designed using Android Studio with Java as the programming language and is compatible with both Android and iOS. The app system is hosted on Nginx Server, and network calls are built on PHP's Laravel framework handled by the Retrofit Library. The DigitalOcean offers a high-performance and stable cloud computing platform for ARVPredictor. This mobile app is enlisted in the Google Play Store as an ``ARVPredictor'' and the source code is available under MIT permissive license at a GitHub repository. To test for agreement between the ARVPredictor and Stanford HIV Database in detecting HIV subtype and NNRT and NRTI mutations, a total of 100 known HIV sequences were evaluated. Results: The mobile-based app (ARVPredictor) takes in a set of sequences or known mutations (protease, reverse transcriptase and integrase). It then returns inferred levels of resistance to selected nucleoside, nonnucleoside protease, and integrase inhibitors for accurate HIV/AIDS management at the point of care. The ARVPredictor identified similar HIV subtypes in 98/100 sequences compared with the Stanford HIV Database ($\kappa$=0.98, indicating near perfect agreement). There were 89/100 major NNRTI and NRTI mutations identified by ARVPredictor, similar to the Stanford HIV Database ($\kappa$=0.89, indicating near perfect agreement). Eight mutations classified as major by the Stanford HIV Database were classified as others by ARVPredictor. Conclusions: The ARVPredictor largely agrees with the Stanford HIV Database in identifying both major and minor proteases, reverse transcriptase, and integrase mutations. The app can be conveniently used robustly at the point of care by HIV/AIDS care providers to improve the management of HIV infection. ", doi="10.2196/26891", url="https://formative.jmir.org/2022/2/e26891", url="http://www.ncbi.nlm.nih.gov/pubmed/35107425" } @Article{info:doi/10.2196/28307, author="Hu, Alvin", title="Conjugation of Silver Nanoparticles With De Novo--Engineered Cationic Antimicrobial Peptides: Exploratory Proposal", journal="JMIR Res Protoc", year="2021", month="Dec", day="8", volume="10", number="12", pages="e28307", keywords="antimicrobial peptides", keywords="silver nanoparticles", keywords="ESKAPE pathogens", keywords="research proposal", abstract="Background: Cationic antimicrobial peptides have broad antimicrobial activity and provide a novel way of targeting multidrug-resistant bacteria in the era of increasing antimicrobial resistance. Current developments show positive prospects for antimicrobial peptides and silver nanoparticles (AgNPs) individually. Objective: The primary objective is to propose another method for enhancing antimicrobial activity by conjugating AgNPs with cationic antimicrobial peptides, with a subsequent preliminary assessment of the minimum inhibitory concentration of multidrug-resistant bacteria. The secondary objective is to evaluate the safety of the conjugated compound and assess its viability for in vivo use. Methods: The proposal involves 3 stages. First, WLBU2C, a modified version of the antimicrobial peptide WLBU2 with an added cysteine group, needs to be synthesized using a standard Fmoc procedure. It can then be stably conjugated with AgNPs ideally through photochemical means. Second, the WLBU2C-AgNP conjugate should be tested for antimicrobial activity according to the Clinical \& Laboratory Standards Institute manual on standard minimum inhibitory concentration testing. Third, the cytotoxicity of the conjugate should be tested using cell lysis assays if the above stages are completed. Results: I-TASSER (iterative threading assembly refinement) simulation revealed that the modified peptide WLBU2C has a secondary structure similar to that of the original WLBU2 peptide. No other results have been obtained at this time. Conclusions: The addition of AgNPs to already developed de novo--engineered antimicrobial peptides provides an opportunity for the development of potent antimicrobials. Future prospects include emergency last-line therapy and treatment for current difficult-to-eradicate bacterial colonization, such as in cystic fibrosis, implantable medical devices, cancer, and immunotherapy. As I do not anticipate funding at this time, I hope this proposal provides inspiration to other researchers. International Registered Report Identifier (IRRID): PRR1-10.2196/28307 ", doi="10.2196/28307", url="https://www.researchprotocols.org/2021/12/e28307", url="http://www.ncbi.nlm.nih.gov/pubmed/34780345" } @Article{info:doi/10.2196/23571, author="M{\"u}ller, Lars and Srinivasan, Aditya and Abeles, R. Shira and Rajagopal, Amutha and Torriani, J. Francesca and Aronoff-Spencer, Eliah", title="A Risk-Based Clinical Decision Support System for Patient-Specific Antimicrobial Therapy (iBiogram): Design and Retrospective Analysis", journal="J Med Internet Res", year="2021", month="Dec", day="3", volume="23", number="12", pages="e23571", keywords="antimicrobial resistance", keywords="clinical decision support", keywords="antibiotic stewardship", keywords="data visualization", abstract="Background: There is a pressing need for digital tools that can leverage big data to help clinicians select effective antibiotic treatments in the absence of timely susceptibility data. Clinical presentation and local epidemiology can inform therapy selection to balance the risk of antimicrobial resistance and patient risk. However, data and clinical expertise must be appropriately integrated into clinical workflows. Objective: The aim of this study is to leverage available data in electronic health records, to develop a data-driven, user-centered, clinical decision support system to navigate patient safety and population health. Methods: We analyzed 5 years of susceptibility testing (1,078,510 isolates) and patient data (30,761 patients) across a large academic medical center. After curating the data according to the Clinical and Laboratory Standards Institute guidelines, we analyzed and visualized the impact of risk factors on clinical outcomes. On the basis of this data-driven understanding, we developed a probabilistic algorithm that maps these data to individual cases and implemented iBiogram, a prototype digital empiric antimicrobial clinical decision support system, which we evaluated against actual prescribing outcomes. Results: We determined patient-specific factors across syndromes and contexts and identified relevant local patterns of antimicrobial resistance by clinical syndrome. Mortality and length of stay differed significantly depending on these factors and could be used to generate heuristic targets for an acceptable risk of underprescription. Combined with the developed remaining risk algorithm, these factors can be used to inform clinicians' reasoning. A retrospective comparison of the iBiogram-suggested therapies versus the actual prescription by physicians showed similar performance for low-risk diseases such as urinary tract infections, whereas iBiogram recognized risk and recommended more appropriate coverage in high mortality conditions such as sepsis. Conclusions: The application of such data-driven, patient-centered tools may guide empirical prescription for clinicians to balance morbidity and mortality with antimicrobial stewardship. ", doi="10.2196/23571", url="https://www.jmir.org/2021/12/e23571", url="http://www.ncbi.nlm.nih.gov/pubmed/34870601" } @Article{info:doi/10.2196/33365, author="Alam, Mahbub-Ul and Ferdous, Sharika and Ercumen, Ayse and Lin, Audrie and Kamal, Abul and Luies, Khan Sharmin and Sharior, Fazle and Khan, Rizwana and Rahman, Ziaur Md and Parvez, Masud Sarker and Amin, Nuhu and Tadesse, Tilahun Birkneh and Moushomi, Akter Niharu and Hasan, Rezaul and Taneja, Neelam and Islam, Aminul Mohammad and Rahman, Mahbubur", title="Effective Treatment Strategies for the Removal of Antibiotic-Resistant Bacteria, Antibiotic-Resistance Genes, and Antibiotic Residues in the Effluent From Wastewater Treatment Plants Receiving Municipal, Hospital, and Domestic Wastewater: Protocol for a Systematic Review", journal="JMIR Res Protoc", year="2021", month="Nov", day="26", volume="10", number="11", pages="e33365", keywords="antimicrobial resistance", keywords="antimicrobial-resistant bacteria", keywords="antibiotic-resistant bacteria", keywords="antimicrobial-resistance genes", keywords="antibiotic-resistance genes", keywords="antibiotics", keywords="antibiotic residues", keywords="wastewater treatment plant", keywords="effluent", keywords="systematic review", abstract="Background: The widespread and unrestricted use of antibiotics has led to the emergence and spread of antibiotic-resistant bacteria (ARB), antibiotic-resistance genes (ARGs), and antibiotic residues in the environment. Conventional wastewater treatment plants (WWTPs) are not designed for effective and adequate removal of ARB, ARGs, and antibiotic residues, and therefore, they play an important role in the dissemination of antimicrobial resistance (AMR) in the natural environment. Objective: We will conduct a systematic review to determine the most effective treatment strategies for the removal of ARB, ARGs, and antibiotic residues from the treated effluent disposed into the environment from WWTPs that receive municipal, hospital, and domestic discharge. Methods: We will search the MEDLINE, EMBASE, Web of Science, World Health Organization Global Index Medicus, and ProQuest Environmental Science Collection databases for full-text peer-reviewed journal articles published between January 2001 and December 2020. We will select only articles published in the English language. We will include studies that measured (1) the presence, concentration, and removal rate of ARB/ARGs going from WWTP influent to effluent, (2) the presence, concentration, and types of antibiotics in the effluent, and (3) the possible selection of ARB in the effluent after undergoing treatment processes in WWTPs. At least two independent reviewers will extract data and perform risk of bias assessment. An acceptable or narrative synthesis method will be followed to synthesize the data and present descriptive characteristics of the included studies in a tabular form. The study has been approved by the Ethics Review Board at the International Centre for Diarrhoeal Disease Research, Bangladesh (protocol number: PR-20113). Results: This protocol outlines our proposed methodology for conducting a systematic review. Our results will provide an update to the existing literature by searching additional databases. Conclusions: Findings from our systematic review will inform the planning of proper treatment methods that can effectively reduce the levels of ARB, ARGs, and residual antibiotics in effluent, thus lowering the risk of the environmental spread of AMR and its further transmission to humans and animals. International Registered Report Identifier (IRRID): PRR1-10.2196/33365 ", doi="10.2196/33365", url="https://www.researchprotocols.org/2021/11/e33365", url="http://www.ncbi.nlm.nih.gov/pubmed/34842550" } @Article{info:doi/10.2196/29954, author="Nabadda, Susan and Kakooza, Francis and Kiggundu, Reuben and Walwema, Richard and Bazira, Joel and Mayito, Jonathan and Mugerwa, Ibrahimm and Sekamatte, Musa and Kambugu, Andrew and Lamorde, Mohammed and Kajumbula, Henry and Mwebasa, Henry", title="Implementation of the World Health Organization Global Antimicrobial Resistance Surveillance System in Uganda, 2015-2020: Mixed-Methods Study Using National Surveillance Data", journal="JMIR Public Health Surveill", year="2021", month="Oct", day="21", volume="7", number="10", pages="e29954", keywords="antimicrobial resistance", keywords="surveillance", keywords="microbiology", keywords="laboratory", keywords="Uganda", keywords="implementation", keywords="WHO", keywords="collection", keywords="analysis", keywords="data", keywords="antimicrobial", keywords="progress", keywords="bacteria", keywords="feasibility", keywords="resistance", keywords="antibiotic", abstract="Background: Antimicrobial resistance (AMR) is an emerging public health crisis in Uganda. The World Health Organization (WHO) Global Action Plan recommends that countries should develop and implement National Action Plans for AMR. We describe the establishment of the national AMR program in Uganda and present the early microbial sensitivity results from the program. Objective: The aim of this study is to describe a national surveillance program that was developed to perform the systematic and continuous collection, analysis, and interpretation of AMR data. Methods: A systematic qualitative description of the process and progress made in the establishment of the national AMR program is provided, detailing the progress made from 2015 to 2020. This is followed by a report of the findings of the isolates that were collected from AMR surveillance sites. Identification and antimicrobial susceptibility testing (AST) of the bacterial isolates were performed using standard methods at both the surveillance sites and the reference laboratory. Results: Remarkable progress has been achieved in the establishment of the national AMR program, which is guided by the WHO Global Laboratory AMR Surveillance System (GLASS) in Uganda. A functional national coordinating center for AMR has been established with a supporting designated reference laboratory. WHONET software for AMR data management has been installed in the surveillance sites and laboratory staff trained on data quality assurance. Uganda has progressively submitted data to the WHO GLASS reporting system. Of the 19,216 isolates from WHO GLASS priority specimens collected from October 2015 to June 2020, 22.95\% (n=4411) had community-acquired infections, 9.46\% (n=1818) had hospital-acquired infections, and 68.57\% (n=12,987) had infections of unknown origin. The highest proportion of the specimens was blood (12,398/19,216, 64.52\%), followed by urine (5278/19,216, 27.47\%) and stool (1266/19,216, 6.59\%), whereas the lowest proportion was urogenital swabs (274/19,216, 1.4\%). The mean age was 19.1 (SD 19.8 years), whereas the median age was 13 years (IQR 28). Approximately 49.13\% (9440/19,216) of the participants were female and 50.51\% (9706/19,216) were male. Participants with community-acquired infections were older (mean age 28, SD 18.6 years; median age 26, IQR 20.5 years) than those with hospital-acquired infections (mean age 17.3, SD 20.9 years; median age 8, IQR 26 years). All gram-negative (Escherichia coli, Klebsiella pneumoniae, and Neisseria gonorrhoeae) and gram-positive (Staphylococcus aureus and Enterococcus sp) bacteria with AST showed resistance to each of the tested antibiotics. Conclusions: Uganda is the first African country to implement a structured national AMR surveillance program in alignment with the WHO GLASS. The reported AST data indicate very high resistance to the recommended and prescribed antibiotics for treatment of infections. More effort is required regarding quality assurance of laboratory testing methodologies to ensure optimal adherence to WHO GLASS--recommended pathogen-antimicrobial combinations. The current AMR data will inform the development of treatment algorithms and clinical guidelines. ", doi="10.2196/29954", url="https://publichealth.jmir.org/2021/10/e29954", url="http://www.ncbi.nlm.nih.gov/pubmed/34673531" } @Article{info:doi/10.2196/24378, author="Lambraki, Anna Irene and Majowicz, Elizabeth Shannon and Parmley, Jane Elizabeth and Wernli, Didier and L{\'e}ger, Ana{\"i}s and Graells, Tiscar and Cousins, Melanie and Harbarth, Stephan and Carson, Carolee and Henriksson, Patrik and Troell, Max and J{\o}rgensen, S{\o}gaard Peter", title="Building Social-Ecological System Resilience to Tackle Antimicrobial Resistance Across the One Health Spectrum: Protocol for a Mixed Methods Study", journal="JMIR Res Protoc", year="2021", month="Jun", day="10", volume="10", number="6", pages="e24378", keywords="antimicrobial resistance", keywords="One Health", keywords="resilience", keywords="transdisciplinary", keywords="participatory", keywords="interventions", keywords="systems dynamics", keywords="social-ecological system", abstract="Background: Antimicrobial resistance (AMR) is an escalating global crisis with serious health, social, and economic consequences. Building social-ecological system resilience to reduce AMR and mitigate its impacts is critical. Objective: The aim of this study is to compare and assess interventions that address AMR across the One Health spectrum and determine what actions will help to build social and ecological capacity and readiness to sustainably tackle AMR. Methods: We will apply social-ecological resilience theory to AMR in an explicit One Health context using mixed methods and identify interventions that address AMR and its key pressure antimicrobial use (AMU) identified in the scientific literature and in the gray literature using a web-based survey. Intervention impacts and the factors that challenge or contribute to the success of interventions will be determined, triangulated against expert opinions in participatory workshops and complemented using quantitative time series analyses. We will then identify indicators using regression modeling, which can predict national and regional AMU or AMR dynamics across animal and human health. Together, these analyses will help to quantify the causal loop diagrams (CLDs) of AMR in the European and Southeast Asian food system contexts that are developed by diverse stakeholders in participatory workshops. Then, using these CLDs, the long-term impacts of selected interventions on AMR will be explored under alternate future scenarios via simulation modeling and participatory workshops. A publicly available learning platform housing information about interventions on AMR from a One Health perspective will be developed to help decision makers identify promising interventions for application in their jurisdictions. Results: To date, 669 interventions have been identified in the scientific literature, 891 participants received a survey invitation, and 4 expert feedback and 4 model-building workshops have been conducted. Time series analysis, regression modeling of national and regional indicators of AMR dynamics, and scenario modeling activities are anticipated to be completed by spring 2022. Ethical approval has been obtained from the University of Waterloo's Office of Research Ethics (ethics numbers 40519 and 41781). Conclusions: This paper provides an example of how to study complex problems such as AMR, which require the integration of knowledge across sectors and disciplines to find sustainable solutions. We anticipate that our study will contribute to a better understanding of what actions to take and in what contexts to ensure long-term success in mitigating AMR and its impact and provide useful tools (eg, CLDs, simulation models, and public databases of compiled interventions) to guide management and policy decisions. International Registered Report Identifier (IRRID): DERR1-10.2196/24378 ", doi="10.2196/24378", url="https://www.researchprotocols.org/2021/6/e24378", url="http://www.ncbi.nlm.nih.gov/pubmed/34110296" } @Article{info:doi/10.2196/27276, author="Vighio, Anum and Syed, Asif Muhammad and Hussain, Ishfaque and Zia, Masroor Syed and Fatima, Munaza and Masood, Naveed and Chaudry, Ambreen and Hussain, Zakir and Iqbal Baig, Zeeshan Mirza and Baig, Amir Mirza and Ikram, Aamer and S Khader, Yousef", title="Risk Factors of Extensively Drug Resistant Typhoid Fever Among Children in Karachi: Case-Control Study", journal="JMIR Public Health Surveill", year="2021", month="May", day="11", volume="7", number="5", pages="e27276", keywords="case-control study", keywords="drug resistance", keywords="extensively drug resistant typhoid fever", keywords="risk factors", keywords="typhoid fever", abstract="Background: Extensively drug resistant typhoid fever (XDR-TF) has been responsible for an ongoing outbreak in Pakistan, which began in November 2016. Objective: This study aimed to determine the risk factors associated with?XDR-TF. Methods: This age- and sex-matched case-control study was conducted during May-October 2018 in Karachi. All patients with XDR-TF were identified from the laboratory-based surveillance system data. Cases included patients aged <15 years living in Karachi with culture-positive Salmonella enterica serovar Typhi with resistance to chloramphenicol, ampicillin, trimethoprim/sulfamethoxazole, fluoroquinolones, and third-generation cephalosporins. Age- and sex-matched controls included children free from the symptoms of TF, aged under 15 years, and residing in Karachi. All controls were recruited from among those who attended outpatient clinics. Results: A total of 75 cases and 75 controls were included in this study. On univariate analysis, the odds of having XDR-TF were 13-fold higher among participants who used piped municipal water than among those who did not (odds ratio [OR] 12.6, 95\% CI 4.1-38.6). The use of bore water was significantly associated with XDR-TF (OR 5.1, 95\% CI 1.4-19.0). Cases were more likely to report eating French fries with sauce (OR 13.5, 95\% CI 3.9-47.0) and poppadum (OR 3.4, 95\% CI 1.7-6.7) from street vendors than controls. Boiling water at home was negatively associated with XDR-TF (OR 0.3, 95\% CI 0.2-0.7). On multivariate analysis, 2 factors were independently associated with XDR-TF. Using piped municipal water (OR 10.3, 95\% CI 3.4-30.4) and eating French fries with sauce from street vendors (OR 8.8, 95\% CI 2.1-36.2) were significantly associated with an increased odds of XDR-TF. Conclusions: Community water supply and street food eating habits were implicated in the spread of the superbug S typhi outbreak, which continues to grow in Karachi. Therefore, it is recommended to improve the community water supply to meet recommended standards and to develop a policy to improve the safety of street food. In addition, health authorities are required to conduct mass vaccination for TF among high-risk groups. ", doi="10.2196/27276", url="https://publichealth.jmir.org/2021/5/e27276", url="http://www.ncbi.nlm.nih.gov/pubmed/33973861" } @Article{info:doi/10.2196/20525, author="Hua, Xueliang and Li, Chen and Pogue, M. Jason and Sharma, S. Varun and Karaiskos, Ilias and Kaye, S. Keith and Tsuji, T. Brian and Bergen, J. Phillip and Zhu, Yan and Song, Jiangning and Li, Jian", title="ColistinDose, a Mobile App for Determining Intravenous Dosage Regimens of Colistimethate in Critically Ill Adult Patients: Clinician-Centered Design and Development Study", journal="JMIR Mhealth Uhealth", year="2020", month="Dec", day="16", volume="8", number="12", pages="e20525", keywords="ColistinDose", keywords="colistimethate", keywords="colistin methanesulfonate", keywords="colistin", keywords="polymyxins", keywords="mobile app", keywords="renal function", keywords="renal replacement therapy", keywords="intermittent hemodialysis", keywords="sustained low-efficiency dialysis", keywords="continuous renal replacement therapy", abstract="Background: Determining a suitable dose of intravenous colistimethate is challenging because of complicated pharmacokinetics, confusing terminology, and the potential for renal toxicity. Only recently have reliable pharmacokinetic/pharmacodynamic data and dosing recommendations for intravenous colistimethate become available. Objective: The aim of this work was to develop a clinician-friendly, easy-to-use mobile app incorporating up-to-date dosing recommendations for intravenous colistimethate in critically ill adult patients. Methods: Swift programming language and common libraries were used for the development of an app, ColistinDose, on the iPhone operating system (iOS; Apple Inc). The compatibility among different iOS versions and mobile devices was validated. Dosing calculations were based on equations developed in our recent population pharmacokinetic study. Recommended doses generated by the app were validated by comparison against doses calculated manually using the appropriate equations. Results: ColistinDose provides 3 major functionalities, namely (1) calculation of a loading dose, (2) calculation of a daily dose based on the renal function of the patient (including differing types of renal replacement therapies), and (3) retrieval of historical calculation results. It is freely available at the Apple App Store for iOS (version 9 and above). Calculated doses accurately reflected doses recommended in patients with varying degrees of renal function based on the published equations. ColistinDose performs calculations on a local mobile device (iPhone or iPad) without the need for an internet connection. Conclusions: With its user-friendly interface, ColistinDose provides an accurate and easy-to-use tool for clinicians to calculate dosage regimens of intravenous colistimethate in critically ill patients with varying degrees of renal function. It has significant potential to avoid the prescribing errors and patient safety issues that currently confound the clinical use of colistimethate, thereby optimizing patient treatment. ", doi="10.2196/20525", url="http://mhealth.jmir.org/2020/12/e20525/", url="http://www.ncbi.nlm.nih.gov/pubmed/33325835" } @Article{info:doi/10.2196/23482, author="Han, Min Seung and Greenfield, Geva and Majeed, Azeem and Hayhoe, Benedict", title="Impact of Remote Consultations on Antibiotic Prescribing in Primary Health Care: Systematic Review", journal="J Med Internet Res", year="2020", month="Nov", day="9", volume="22", number="11", pages="e23482", keywords="remote consultations", keywords="antibiotic", keywords="primary health care", keywords="systematic review", keywords="consultation", keywords="telehealth", keywords="COVID-19", keywords="safety", keywords="prescription", abstract="Background: There has been growing international interest in performing remote consultations in primary care, particularly amidst the current COVID-19 pandemic. Despite this, the evidence surrounding the safety of remote consultations is inconclusive. The appropriateness of antibiotic prescribing in remote consultations is an important aspect of patient safety that needs to be addressed. Objective: This study aimed to summarize evidence on the impact of remote consultation in primary care with regard to antibiotic prescribing. Methods: Searches were conducted in MEDLINE, Embase, HMIC, PsycINFO, and CINAHL for literature published since the databases' inception to February 2020. Peer-reviewed studies conducted in primary health care settings were included. All remote consultation types were considered, and studies were required to report any quantitative measure of antibiotic prescribing to be included in this systematic review. Studies were excluded if there were no comparison groups (face-to-face consultations). Results: In total, 12 studies were identified. Of these, 4 studies reported higher antibiotic-prescribing rates, 5 studies reported lower antibiotic-prescribing rates, and 3 studies reported similar antibiotic-prescribing rates in remote consultations compared with face-to-face consultations. Guideline-concordant prescribing was not significantly different between remote and face-to-face consultations for patients with sinusitis, but conflicting results were found for patients with acute respiratory infections. Mixed evidence was found for follow-up visit rates after remote and face-to-face consultations. Conclusions: There is insufficient evidence to confidently conclude that remote consulting has a significant impact on antibiotic prescribing in primary care. However, studies indicating higher prescribing rates in remote consultations than in face-to-face consultations are a concern. Further, well-conducted studies are needed to inform safe and appropriate implementation of remote consulting to ensure that there is no unintended impact on antimicrobial resistance. ", doi="10.2196/23482", url="http://www.jmir.org/2020/11/e23482/", url="http://www.ncbi.nlm.nih.gov/pubmed/33031045" } @Article{info:doi/10.2196/23241, author=" and Das, Kumar Manoja and Mahapatra, Ashoka and Pathi, Basanti and Panigrahy, Rajashree and Pattnaik, Swetalona and Mishra, Shekhar Sudhansu and Mahapatro, Samarendra and Swain, Priyabrat and Das, Jayakrushna and Dixit, Shikha and Sahoo, Narayan Satya and Pillai, N. Rakesh", title="Harmonized One Health Trans-Species and Community Surveillance for Tackling Antibacterial Resistance in India: Protocol for a Mixed Methods Study", journal="JMIR Res Protoc", year="2020", month="Oct", day="30", volume="9", number="10", pages="e23241", keywords="bacterial infection", keywords="antibiotics resistance", keywords="sentinel surveillance", keywords="drug prescriptions", keywords="One Health", keywords="India", abstract="Background: India has the largest burden of drug?resistant organisms compared with other countries around the world, including multiresistant and extremely drug?resistant tuberculosis and resistant Gram?negative and Gram?positive bacteria. Antibiotic resistant bacteria are found in all living hosts and in the environment and move between hosts and ecosystems. An intricate interplay of infections, exposure to antibiotics, and disinfectants at individual and community levels among humans, animals, birds, and fishes triggers evolution and spread of resistance. The One Health framework proposes addressing antibiotic resistance as a complex multidisciplinary problem. However, the evidence base in the Indian context is limited. Objective: This multisectoral, trans-species surveillance project aims to document the infection and resistance patterns of 7 resistant-priority bacteria and the risk factors for resistance following the One Health framework and geospatial epidemiology. Methods: This hospital- and community-based surveillance adopts a cross-sectional design with mixed methodology (quantitative, qualitative, and spatial) data collection. This study is being conducted at 6 microbiology laboratories and communities in Khurda district, Odisha, India. The laboratory surveillance collects data on bacteria isolates from different hosts and their resistance patterns. The hosts for infection surveillance include humans, animals (livestock, food chain, and pet animals), birds (poultry), and freshwater fishes (not crustaceans). For eligible patients, animals, birds and fishes, detailed data from their households or farms on health care seeking (for animals, birds and fishes, the illness, and care seeking of the caretakers), antibiotic use, disinfection practices, and neighborhood exposure to infection risks will be collected. Antibiotic prescription and use patterns at hospitals and clinics, and therapeutic and nontherapeutic antibiotic and disinfectant use in farms will also be collected. Interviews with key informants from animal breeding, agriculture, and food processing will explore the perceptions, attitudes, and practices related to antibiotic use. The data analysis will follow quantitative (descriptive and analytical), qualitative, and geospatial epidemiology principles. Results: The study was funded in May 2019 and approved by Institute Ethics Committees in March 2019. The data collection started in September 2019 and shall continue till March 2021. As of June 2020, data for 56 humans, 30 animals and birds, and fishes from 10 ponds have been collected. Data analysis is yet to be done. Conclusions: This study will inform about the bacterial infection and resistance epidemiology among different hosts, the risk factors for infection, and resistance transmission. In addition, it will identify the potential triggers and levers for further exploration and action. International Registered Report Identifier (IRRID): DERR1-10.2196/23241 ", doi="10.2196/23241", url="http://www.researchprotocols.org/2020/10/e23241/", url="http://www.ncbi.nlm.nih.gov/pubmed/33124993" } @Article{info:doi/10.2196/18648, author="L{\"o}ffler, Christin and Kr{\"u}ger, Antje and Daubmann, Anne and Iwen, Julia and Biedermann, Marc and Schulz, Maike and Wegscheider, Karl and Altiner, Attila and Feldmeier, Gregor and Wollny, Anja", title="Optimizing Antibiotic Prescribing for Acute Respiratory Tract Infection in German Primary Care: Study Protocol for Evaluation of the RESIST Program", journal="JMIR Res Protoc", year="2020", month="Sep", day="30", volume="9", number="9", pages="e18648", keywords="antibacterial agents", keywords="respiratory tract infection", keywords="upper respiratory tract infection", keywords="lower respiratory tract infection", keywords="primary care", keywords="primary health care", keywords="physician-patient relation", keywords="shared decision making", keywords="antibiotic resistance", abstract="Background: The emergence and increased spread of microbial resistance is a major challenge to all health care systems worldwide. In primary care, acute respiratory tract infection (ARTI) is the health condition most strongly related to antibiotic overuse. Objective: The RESIST program aims at optimizing antibiotic prescribing for ARTI in German primary care. By completing a problem-orientated online training course, physicians are motivated and empowered to utilize patient-centered doctor-patient communication strategies, including shared decision making, in the treatment of patients with ARTI. Methods: RESIST will be evaluated in the form of a nonrandomized controlled trial. Approximately 3000 physicians of 8 (out of 16) German federal states can participate in the program. Patient and physician data are retrieved from routine health care data. Physicians not participating in the program serve as controls, either among the 8 participating regional Associations of Statutory Health Insurance Physicians (control group 1) or among the remaining associations not participating in RESIST (control group 2). Antibiotic prescription rates before the intervention (T0: 2016, 1st and 2nd quarters of 2017) and after the intervention (T1: 3rd quarter of 2017 until 1st quarter of 2019) will be compared. The primary outcome measure is the overall antibiotic prescription rate for all patients insured with German statutory health insurance before and after provision of the online course. The secondary outcome is the antibiotic prescription rate for coded ARTI before and after the intervention. Results: RESIST is publicly funded by the Innovations funds of the Federal Joint Committee in Germany and was approved in December 2016. Recruitment of physicians is now completed, and a total of 2460 physicians participated in the intervention. Data analysis started in February 2020. Conclusions: With approximately 3000 physicians participating in the program, RESIST is among the largest real-world interventions aiming at reducing inadequate antibiotic prescribing for ARTI in primary care. Long-term follow up of up to 21 months will allow for investigating the sustainability of the intervention. Trial Registration: ISRCTN Registry ISRCTN13934505; http://www.isrctn.com/ISRCTN13934505 International Registered Report Identifier (IRRID): RR1-10.2196/18648 ", doi="10.2196/18648", url="http://www.researchprotocols.org/2020/9/e18648/", url="http://www.ncbi.nlm.nih.gov/pubmed/32996888" } @Article{info:doi/10.2196/17940, author="Peiffer-Smadja, Nathan and Poda, Armel and Ouedraogo, Abdoul-Salam and Guiard-Schmid, Jean-Baptiste and Delory, Tristan and Le Bel, Josselin and Bouvet, Elisabeth and Lariven, Sylvie and Jeanmougin, Pauline and Ahmad, Raheelah and Lescure, Fran{\c{c}}ois-Xavier", title="Paving the Way for the Implementation of a Decision Support System for Antibiotic Prescribing in Primary Care in West Africa: Preimplementation and Co-Design Workshop With Physicians", journal="J Med Internet Res", year="2020", month="Jul", day="20", volume="22", number="7", pages="e17940", keywords="decision support systems, clinical", keywords="antibiotic resistance, microbial", keywords="drug resistance, microbial", keywords="antibiotic stewardship", keywords="implementation science", keywords="Africa, Western", keywords="diffusion of innovation", keywords="medical informatics applications", abstract="Background: Suboptimal use of antibiotics is a driver of antimicrobial resistance (AMR). Clinical decision support systems (CDSS) can assist prescribers with rapid access to up-to-date information. In low- and middle-income countries (LMIC), the introduction of CDSS for antibiotic prescribing could have a measurable impact. However, interventions to implement them are challenging because of cultural and structural constraints, and their adoption and sustainability in routine clinical care are often limited. Preimplementation research is needed to ensure relevant adaptation and fit within the context of primary care in West Africa. Objective: This study examined the requirements for a CDSS adapted to the context of primary care in West Africa, to analyze the barriers and facilitators of its implementation and adaptation, and to ensure co-designed solutions for its adaptation and sustainable use. Methods: We organized a workshop in Burkina Faso in June 2019 with 47 health care professionals representing 9 West African countries and 6 medical specialties. The workshop began with a presentation of Antibioclic, a publicly funded CDSS for antibiotic prescribing in primary care that provides personalized antibiotic recommendations for 37 infectious diseases. Antibioclic is freely available on the web and as a smartphone app (iOS, Android). The presentation was followed by a roundtable discussion and completion of a questionnaire with open-ended questions by participants. Qualitative data were analyzed using thematic analysis. Results: Most of the participants had access to a smartphone during their clinical consultations (35/47, 74\%), but only 49\% (23/47) had access to a computer and none used CDSS for antibiotic prescribing. The participants considered that CDSS could have a number of benefits including updating the knowledge of practitioners on antibiotic prescribing, improving clinical care and reducing AMR, encouraging the establishment of national guidelines, and developing surveillance capabilities in primary care. The most frequently mentioned contextual barrier to implementing a CDSS was the potential risk of increasing self-medication in West Africa, where antibiotics can be bought without a prescription. The need for the CDSS to be tailored to the local epidemiology of infectious diseases and AMR was highlighted along with the availability of diagnostic tests and antibiotics using national guidelines where available. Participants endorsed co-design involving all stakeholders, including nurses, midwives, and pharmacists, as central to any introduction of CDSS. A phased approach was suggested by initiating and evaluating CDSS at a pilot site, followed by dissemination using professional networks and social media. The lack of widespread internet access and computers could be circumvented by a mobile app with an offline mode. Conclusions: Our study provides valuable information for the development and implementation of a CDSS for antibiotic prescribing among primary care prescribers in LMICs and may, in turn, contribute to improving antibiotic use, clinical outcomes and decreasing AMR. ", doi="10.2196/17940", url="https://www.jmir.org/2020/7/e17940", url="http://www.ncbi.nlm.nih.gov/pubmed/32442155" } @Article{info:doi/10.2196/17009, author="Workneh, Meklit and Hamill, M. Matthew and Kakooza, Francis and Mande, Emmanuel and Wagner, Jessica and Mbabazi, Olive and Mugasha, Rodney and Kajumbula, Henry and Walwema, Richard and Zenilman, Jonathan and Musinguzi, Patrick and Kyambadde, Peter and Lamorde, Mohammed and Manabe, C. Yukari", title="Antimicrobial Resistance of Neisseria Gonorrhoeae in a Newly Implemented Surveillance Program in Uganda: Surveillance Report", journal="JMIR Public Health Surveill", year="2020", month="Jun", day="10", volume="6", number="2", pages="e17009", keywords="gonorrhea", keywords="antimicrobial resistance", keywords="surveillance", keywords="Uganda", keywords="STD", keywords="STI", keywords="sexually transmitted", keywords="Neisseria Gonorrhoeae", keywords="antibiotic resistance, EGASP", abstract="Background: Neisseria gonorrhoeae (commonly known as gonorrhea) has developed resistance to all first-line therapy in Southeast Asia. East Africa has historically had absent or rudimentary gonorrhea surveillance programs and, while the existence of antimicrobial-resistant gonorrhea is recognized, the extent of its resistance is largely unknown. In 2016, the World Health Organization's Enhanced Gonococcal Antimicrobial Surveillance Program (EGASP) was initiated in Uganda to monitor resistance trends. Objective: This study characterizes gonorrhea and antibiotic resistance in a large surveillance program of men with urethral discharge syndrome from Kampala, Uganda. Methods: Men attending sentinel clinics with urethritis provided demographic information, behavior data, and a urethral swab in line with the World Health Organization's EGASP protocols for culture, identification, and antibiotic-sensitivity testing using 2 methods---disk diffusion (Kirby-Bauer test) and Etest (BioM{\'e}rieux Inc). A subset of samples underwent detailed antimicrobial resistance testing. Results: Of 639 samples collected from September 2016 to February 2018, 400 (62.6\%) were culture-positive though 414 (64.8\%) had microscopic evidence of gonorrhea. The mean age of the men from whom the samples were collected was 26.9 (SD 9.6) years and 7.2\% (46/639) reported having HIV. There was high-level resistance to ciprofloxacin, tetracycline, and penicillin (greater than 90\%) by Kirby-Bauer disk diffusion and 2.1\% (4/188) had reduced azithromycin sensitivity by Etest. Of the early isolates that underwent detailed characterization, 60.3\% (70/116) were culture-positive, 94\% (66/69) isolates were either ciprofloxacin-resistant or ciprofloxacin-intermediate by Etest, 96\% (65/68) were azithromycin-sensitive, and 96\% (66/69) were gentamicin-sensitive. Resistance profiles were comparable between methods except for ceftriaxone (disk diffusion: 68/69, 99\%; Etest: 67/69, 97\%) and for gentamicin (disk diffusion: 2/8, 25\%; Etest: 66/69, 96\%) sensitivity. Conclusions: This is the first report from a systematic gonorrhea surveillance program in Uganda. Findings demonstrated resistance or increased minimum inhibitory concentration to all key antigonococcal antibiotics. There was evidence of poor antibiotic stewardship, near-universal resistance to several antibiotics, and emerging resistance to others. Individuals in the population sampled were at exceptionally high risk of STI and HIV infection requiring intervention. Ongoing surveillance efforts to develop interventions to curtail antimicrobial-resistant gonorrhea are needed. ", doi="10.2196/17009", url="http://publichealth.jmir.org/2020/2/e17009/", url="http://www.ncbi.nlm.nih.gov/pubmed/32519969" } @Article{info:doi/10.2196/17710, author="Arnold, Helene Sif and Jensen, Nygaard Jette and Kousgaard, Brostr{\o}m Marius and Siersma, Volkert and Bjerrum, Lars and Holm, Anne", title="Reducing Antibiotic Prescriptions for Urinary Tract Infection in Nursing Homes Using a Complex Tailored Intervention Targeting Nursing Home Staff: Protocol for a Cluster Randomized Controlled Trial", journal="JMIR Res Protoc", year="2020", month="May", day="8", volume="9", number="5", pages="e17710", keywords="urinary tract infection", keywords="nursing home", keywords="antibiotics", keywords="antibiotic resistance", keywords="drug prescription", keywords="communication", keywords="communication barriers", keywords="interprofessional relationship", keywords="elderly", abstract="Background: Urinary tract infection (UTI) is the most common reason for antibiotic prescription in nursing homes. Overprescription causes antibiotic-related harms in those who are treated and others residing within the nursing home. The diagnostic process in nursing homes is complicated with both challenging issues related to the elderly population and the nursing home setting. A physician rarely visits a nursing home for suspected UTI. Consequently, the knowledge of UTI and communication skills of staff influence the diagnosis. Objective: The objective of this study is to describe a cluster randomized controlled trial with a tailored complex intervention for improving the knowledge of UTI and communication skills of nursing home staff in order to decrease the number of antibiotic prescriptions for UTI in nursing home residents, without changing hospitalization and mortality. Methods: The study describes an open-label cluster randomized controlled trial with two parallel groups and a 1:1 allocation ratio. Twenty-two eligible nursing homes are sampled from the Capital Region of Denmark, corresponding to 1274 nursing home residents. The intervention group receives a dialogue tool, and all nursing home staff attend a workshop on UTI. The main outcomes of the study are the antibiotic prescription rate for UTI, all-cause hospitalization, all-cause mortality, and suspected UTI during the trial period. Results: The trial ended in April 2019. Data have been collected and are being analyzed. We expect the results of the trial to be published in a peer-reviewed journal in the fall of 2020. Conclusions: The greatest strengths of this study are the randomized design, tailored development of the intervention, and access to medical records. The potential limitations are the hierarchy in the prescription process, Hawthorne effect, and biased access to data on signs and symptoms through a UTI diary. The results of this trial could offer a strategy to overcome some of the challenges of increased antibiotic resistance and could have implications in terms of how to handle cases of suspected UTI. Trial Registration: ClinicalTrials.gov NCT03715062; https://clinicaltrials.gov/ct2/show/NCT03715062 International Registered Report Identifier (IRRID): DERR1-10.2196/17710 ", doi="10.2196/17710", url="https://www.researchprotocols.org/2020/5/e17710", url="http://www.ncbi.nlm.nih.gov/pubmed/32383679" } @Article{info:doi/10.2196/14504, author="Allison, Rosalie and Hayes, Catherine and Young, Vicki and McNulty, M. Cliodna A.", title="Evaluation of an Educational Health Website on Infections and Antibiotics in England: Mixed Methods, User-Centered Approach", journal="JMIR Form Res", year="2020", month="Apr", day="6", volume="4", number="4", pages="e14504", keywords="user experience", keywords="usability", keywords="quality", keywords="online", keywords="science", keywords="health", abstract="Background: e-Bug, an educational health website for teachers and students, aims to help control antibiotic resistance by educating young people about microbes, hygiene, and antibiotic resistance, reducing the incidence of infection and, therefore, the need for antibiotics. The teachers' section of the e-Bug website has not been evaluated since it was launched in 2009, and worldwide page views have been steadily decreasing since 2013. Objective: This study aimed to apply GoodWeb, a comprehensive framework utilizing methodologies and attributes that are relevant to the digital era, to evaluate and suggest improvements to the e-Bug website. Methods: Electronic questionnaires and face-to-face completion of task scenarios were used to assess content, ease of use, interactivity, technical adequacy, appearance, effectiveness, efficiency, and learnability of the teachers' section of the e-Bug website. Results: A total of 106 teachers evaluated the e-Bug website; 97.1\% (103/106) of them reported that they would use e-Bug, and 98.1\% (104/106) of them reported that they would recommend it to others. Participants thought that there was a niche for e-Bug because of the way the resources fit into the national curriculum. Suggestions for improvements included changing the menu indication by highlighting the current page or deactivating links, improving home page indication, and providing a preview of resources when hovering the mouse over hyperlinks. Additional features requested by users included a search function and access to training opportunities. Conclusions: This paper reports that the GoodWeb framework was successfully applied to evaluate the e-Bug website, and therefore, it could be used to guide future website evaluations in other fields. Results from this study will be used to appraise the current quality and inform any future changes, modifications, and additions to e-Bug. ", doi="10.2196/14504", url="https://formative.jmir.org/2020/4/e14504", url="http://www.ncbi.nlm.nih.gov/pubmed/32203932" } @Article{info:doi/10.2196/14574, author="Asaduzzaman, Muhammad and Hossain, Iqbal Muhammed and Saha, Rani Sumita and Islam, Rayhanul Md and Ahmed, Niyaz and Islam, Aminul Mohammad", title="Quantification of Airborne Resistant Organisms With Temporal and Spatial Diversity in Bangladesh: Protocol for a Cross-Sectional Study", journal="JMIR Res Protoc", year="2019", month="Dec", day="19", volume="8", number="12", pages="e14574", keywords="antimicrobial resistance", keywords="airborne resistomes", keywords="air quality", keywords="global health", keywords="planetary health", keywords="environmental risk assessment", abstract="Background: Antimicrobial resistance is a widespread, alarming issue in global health and a significant contributor to human death and illness, especially in low and middle-income countries like Bangladesh. Despite extensive work conducted in environmental settings, there is a scarcity of knowledge about the presence of resistant organisms in the air. Objective: The objective of this protocol is to quantify and characterize the airborne resistomes in Bangladesh, which will be a guide to identify high-risk environments for multidrug-resistant pathogens with their spatiotemporal diversity. Methods: This is a cross-sectional study with an environmental, systematic, and grid sampling strategy focused on collecting air samples from different outdoor environments during the dry and wet seasons. The four environmental compartments are the frequent human exposure sites in both urban and rural settings: urban residential areas (n=20), live bird markets (n=20), rural households (n=20), and poultry farms (n=20). We obtained air samples from 80 locations in two seasons by using an active microbial air sampler. From each location, five air samples were collected in different media to yield the total bacterial count of 3rd generation cephalosporin (3GC) resistant Enterobacteriaceae, carbapenem-resistant Enterobacteriaceae, vancomycin-resistant Enterococci and methicillin-resistant Staphylococcus aureus. Results: The study started in January 2018, and the collection of air samples was completed in November 2018. We have received 800 air samples from 80 study locations in both dry and wet seasons. Currently, the laboratory analysis is ongoing, and we expect to receive the preliminary results by October 2019. We will publish the complete result as soon as we clean and analyze the data and draft the manuscript. Conclusions: The existence of resistant bacteria in the air like those producing extended-spectrum beta-lactamases, carbapenem-resistant Enterobacteriaceae, vancomycin-resistant Enterococci, and methicillin-resistant Staphylococcus aureus will justify our hypothesis that the outdoor environment (air) in Bangladesh acts as a reservoir for bacteria that carry genes conferring resistance to antibiotics. To our knowledge, this is the first study to explore the presence of superbugs in the air in commonly exposed areas in Bangladesh. International Registered Report Identifier (IRRID): DERR1-10.2196/14574 ", doi="10.2196/14574", url="http://www.researchprotocols.org/2019/12/e14574/", url="http://www.ncbi.nlm.nih.gov/pubmed/31855188" } @Article{info:doi/10.2196/14984, author="Kyaw, Myint Bhone and Tudor Car, Lorainne and van Galen, Sandra Louise and van Agtmael, A. Michiel and Costelloe, E. C{\'e}ire and Ajuebor, Onyema and Campbell, James and Car, Josip", title="Health Professions Digital Education on Antibiotic Management: Systematic Review and Meta-Analysis by the Digital Health Education Collaboration", journal="J Med Internet Res", year="2019", month="Sep", day="12", volume="21", number="9", pages="e14984", keywords="digital education", keywords="antibiotic management", keywords="systematic review", keywords="meta-analysis", keywords="randomized controlled trial", abstract="Background: Inappropriate antibiotic prescription is one of the key contributors to antibiotic resistance, which is managed with a range of interventions including education. Objective: We aimed to summarize evidence on the effectiveness of digital education of antibiotic management compared to traditional education for improving health care professionals' knowledge, skills, attitudes, and clinical practice. Methods: Seven electronic databases and two trial registries were searched for randomized controlled trials (RCTs) and cluster RCTs published between January 1, 1990, and September 20, 2018. There were no language restrictions. We also searched the International Clinical Trials Registry Platform Search Portal and metaRegister of Controlled Trials to identify unpublished trials and checked the reference lists of included studies and relevant systematic reviews for study eligibility. We followed Cochrane methods to select studies, extract data, and appraise and synthesize eligible studies. We used random-effect models for the pooled analysis and assessed statistical heterogeneity by visual inspection of a forest plot and calculation of the I2 statistic. Results: Six cluster RCTs and two RCTs with 655 primary care practices, 1392 primary care physicians, and 485,632 patients were included. The interventions included personal digital assistants; short text messages; online digital education including emails and websites; and online blended education, which used a combination of online digital education and traditional education materials. The control groups received traditional education. Six studies assessed postintervention change in clinical practice. The majority of the studies (4/6) reported greater reduction in antibiotic prescription or dispensing rate with digital education than with traditional education. Two studies showed significant differences in postintervention knowledge scores in favor of mobile education over traditional education (standardized mean difference=1.09, 95\% CI 0.90-1.28; I2=0\%; large effect size; 491 participants [2 studies]). The findings for health care professionals' attitudes and patient-related outcomes were mixed or inconclusive. Three studies found digital education to be more cost-effective than traditional education. None of the included studies reported on skills, satisfaction, or potential adverse effects. Conclusions: Findings from studies deploying mobile or online modalities of digital education on antibiotic management were complementary and found to be more cost-effective than traditional education in improving clinical practice and postintervention knowledge, particularly in postregistration settings. There is a lack of evidence on the effectiveness of other digital education modalities such as virtual reality or serious games. Future studies should also include health care professionals working in settings other than primary care and low- and middle-income countries. Clinical Trial: PROSPERO CRD42018109742; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=109742 ", doi="10.2196/14984", url="http://www.jmir.org/2019/9/e14984/", url="http://www.ncbi.nlm.nih.gov/pubmed/31516125" } @Article{info:doi/10.2196/13365, author="Castro-S{\'a}nchez, Enrique and Sood, Anuj and Rawson, Miles Timothy and Firth, Jamie and Holmes, Helen Alison", title="Forecasting Implementation, Adoption, and Evaluation Challenges for an Electronic Game--Based Antimicrobial Stewardship Intervention: Co-Design Workshop With Multidisciplinary Stakeholders", journal="J Med Internet Res", year="2019", month="Jun", day="04", volume="21", number="6", pages="e13365", keywords="serious games", keywords="antimicrobial stewardship", keywords="medical education", abstract="Background: Serious games have been proposed to address the lack of engagement and sustainability traditionally affecting interventions aiming to improve optimal antibiotic use among hospital prescribers. Objective: The goal of the research was to forecast gaps in implementation, adoption and evaluation of game-based interventions, and co-design solutions with antimicrobial clinicians and digital and behavioral researchers. Methods: A co-development workshop with clinicians and academics in serious games, antimicrobials, and behavioral sciences was organized to open the International Summit on Serious Health Games in London, United Kingdom, in March 2018. The workshop was announced on social media and online platforms. Attendees were asked to work in small groups provided with a laptop/tablet and the latest version of the game On call: Antibiotics. A workshop leader guided open group discussions around implementation, adoption, and evaluation threats and potential solutions. Workshop summary notes were collated by an observer. Results: There were 29 participants attending the workshop. Anticipated challenges to resolve reflected implementation threats such as an inadequate organizational arrangement to scale and sustain the use of the game, requiring sufficient technical and educational support and a streamlined feedback mechanism that made best use of data arriving from the game. Adoption threats included collective perceptions that a game would be a ludic rather than professional tool and demanding efforts to integrate all available educational solutions so none are seen as inferior. Evaluation threats included the need to combine game metrics with organizational indicators such as antibiotic use, which may be difficult to enable. Conclusions: As with other technology-based interventions, deploying game-based solutions requires careful planning on how to engage and support clinicians in their use and how best to integrate the game and game outputs onto existing workflows. The ludic characteristics of the game may foster perceptions of unprofessionalism among gamers, which would need buffering from the organization. ", doi="10.2196/13365", url="https://www.jmir.org/2019/6/e13365/", url="http://www.ncbi.nlm.nih.gov/pubmed/31165712" } @Article{info:doi/10.2196/12272, author="Skelton, Felicia and Martin, Ann Lindsey and Evans, T. Charlesnika and Kramer, Jennifer and Grigoryan, Larissa and Richardson, Peter and Kunik, E. Mark and Poon, Oiyee Ivy and Holmes, Ann S. and Trautner, W. Barbara", title="Determining Best Practices for Management of Bacteriuria in Spinal Cord Injury: Protocol for a Mixed-Methods Study", journal="JMIR Res Protoc", year="2019", month="Feb", day="14", volume="8", number="2", pages="e12272", keywords="spinal cord injury", keywords="urinary tract infection", keywords="patient-focused care", keywords="qualitative evaluation", keywords="antimicrobial stewardship", abstract="Background: Bacteriuria, either asymptomatic (ASB) or symptomatic, urinary tract infection (UTI), is common in persons with spinal cord injury (SCI). Current Veterans Health Administration (VHA) guidelines recommend a screening urinalysis and urine culture for every veteran with SCI during annual evaluation, even when asymptomatic, which is contrary to other national guidelines. Our preliminary data suggest that a positive urine culture (even without signs or symptoms of infection) drives antibiotic use. Objective: Through a series of innovative studies utilizing mixed methods, administrative databases, and focus groups, we will gain further knowledge about the attitudes driving current urine testing practices during the annual exam, as well as quantitative data on the clinical outcomes of these practices. Methods: Aim 1 will identify patient, provider, and facility factors driving bacteriuria testing and subsequent antibiotic use after the SCI annual evaluation through qualitative interviews and quantitative surveys. Aim 2 will use national VHA databases to identify the predictors of urine testing and subsequent antibiotic use during the annual examination and compare the clinical outcomes of those who received antibiotics with those who did not. Aim 3 will use the information gathered from the previous 2 aims to develop the Test Smart, Treat Smart intervention, a combination of patient and provider education and resources that will help stakeholders have informed conversations about urine testing and antibiotic use; feasibility will be tested at a single site. Results: This protocol received institutional review board and VHA Research and Development approval in July 2017, and Veterans Affairs Health Services Research and Development funding started on November 2017. As of submission of this manuscript, 10/15 (67\%) of the target goal of provider interviews were complete, and 77/100 (77\%) of the goal of surveys. With regard to patients, 5/15 (33\%) of the target goal of interviews were complete, and 20/100 (20\%) of the target goal of surveys had been completed. Preliminary analyses are ongoing; the study team plans to present these results in April 2019. Database analyses for aim 2 will begin in January 2019. Conclusions: The negative consequences of antibiotic overuse and antibiotic resistance are well-documented and have national and even global implications. This study will develop an intervention aimed to educate stakeholders on evidence-based management of ASB and UTI and guide antibiotic stewardship in this high-risk population. The next step will be to refine the intervention and test its feasibility and effectiveness at multiple sites as well as reform policy for management of this common but burdensome condition. International Registered Report Identifier (IRRID): DERR1-10.2196/12272 ", doi="10.2196/12272", url="https://www.researchprotocols.org/2019/2/e12272/", url="http://www.ncbi.nlm.nih.gov/pubmed/30762584" }