Urinary tract infection stewardship: A urinary antibiogram and electronic medical record alert nudging narrower-spectrum antibiotics for urinary tract infections.
Ontology highlight
ABSTRACT:
SUBMITTER: Laguio-Vila M
PROVIDER: S-EPMC9495411 | biostudies-literature | 2021
REPOSITORIES: biostudies-literature
Publications
Urinary tract infection stewardship: A urinary antibiogram and electronic medical record alert nudging narrower-spectrum antibiotics for urinary tract infections.
Laguio-Vila Maryrose M Staicu Mary L ML Brundige Mary Lourdes ML Alcantara Jose J Yang Hongmei H Lautenbach Ebbing E Dumyati Ghinwa G
Antimicrobial stewardship & healthcare epidemiology : ASHE 20210629 1
An antimicrobial stewardship intervention consisting of a urinary antibiogram and an electronic health record best-practice advisory promoted narrower-spectrum antibiotics for uncomplicated urinary tract infections in hospitalized patients. Over 20 months, the intervention significantly reduced ceftriaxone orders by 48% (<i>P</i> < .001) and increased cefazolin use 19 times from baseline (<i>P</i> < .001). ...[more]
Similar Datasets
Project description:Asymptomatic bacteriuria and urinary tract infection in renal transplant are important antimicrobial stewardship targets but are difficult to identify within electronic medical records. We validated an "electronic phenotype" of antibacterials prescribed for these indications. This may be more useful than billing data in assessing antibiotic indication in this outpatient setting.
| S-EPMC10964979 | biostudies-literature
Project description:ObjectivePatients with acute gout are frequently treated in the emergency department (ED) and represent a typically underresourced and understudied population. A key limitation for gout research in the ED is the timely ability to identify acute gout patients. Our goal was to refine a multicriteria, electronic medical record alert for gout flares and to determine its diagnostic characteristics in the ED.MethodsThe gout flare alert used electronic medical record data from ED nursing notes and was triggered by the term 'gout' preceding past medical history in the chief complaint, the term 'gout' and a musculoskeletal problem in the chief complaint, or the term 'gout' in the problem list and a musculoskeletal chief complaint. We validated its diagnostic properties to assess presence/absence of gout through manual medical record review using adjudicated expert consensus as the gold standard.ResultsIn January 2020, we analyzed 202 patient records from 2 university-based EDs; from these records, 57 patients were identified by our gout flare alert, and 145 were identified by other means as potentially having an acute gout flare. The gout flare alert's positive predictive value was 47% (95% confidence interval [95% CI] 34-60%), negative predictive value was 94% (95% CI 90-98%), sensitivity was 75% (95% CI 61-89%), and specificity was 82% (95% CI 76-88%). The diagnostic properties were similar at both institutions.ConclusionOur multicomponent gout flare alert had reasonable sensitivity and specificity, albeit a modest positive predictive value. An electronic gout flare alert may help enable the conduct of gout research in the ED setting.
| S-EPMC10500930 | biostudies-literature
Project description:BackgroundMeasuring the appropriateness of antibiotic use is crucial for antibiotic stewardship (ABS) programmes to identify targets for interventions.ObjectivesTo assess the technical feasibility of converting electronic medical record (EMR) data into ABS indicators.MethodsIn this observational feasibility study covering a period of 2 years, the EMRs of patients hospitalized at a large non-university hospital network and receiving at least one dose of a systemic antibiotic were included. ABS indicators measuring steps in the process of antibiotic prescription proposed by the literature were collected and rephrased or defined more specifically to be calculable if needed. Algorithms were programmed in R to convert EMR data into ABS indicators. The indicators were visualized in an interactive dashboard and the plausibility of each output value was assessed.ResultsIn total, data from 25 337 hospitalizations from 20 723 individual patients were analysed and visualized in an interactive dashboard. Algorithms could be programmed to compute 89% (25/28) of all pre-selected indicators assessing treatment decisions automatically out of EMR data, with good data quality for 46% (13/28) of these indicators. According to the data quality observed, the most important issues were (i) missing or meaningless information on indication (e.g. 'mild infection') and (ii) data processing issues such as insufficiently categorized metadata.ConclusionsThe calculation of indicators assessing treatment decisions from EMRs was feasible. However, better data structure and processing within EMR systems are crucial for improving the validity of the results.
| S-EPMC10477111 | biostudies-literature
Project description:IntroductionCurrent guidelines advise the prompt diagnosis and treatment of urinary tract infection (UTI) in children to improve both short and longer term outcomes. However, the risk of long-term complications following childhood UTI is unclear.UTI is relatively common but difficult to diagnose in children as symptoms are non-specific. Diagnosis requires a urine sample, but sampling is difficult and infrequent, and it is not clear if sampling should be given greater priority in primary care. The LUCI study will assess the short, medium and longer term outcomes of childhood UTI associated with routine and systematic sampling practices.Methods and analysisTwo data sets will be established. The first will consist of routinely collected data (hospital, general practice (GP), microbiology) from children born and resident in Wales, linked via the Secure Anonymised Information Linkage (SAIL) Databank (an 'e-cohort'). Urine sampling in this data set reflects normal practice 'routine sampling'. Outcomes (including renal scarring, hypertension, end-stage renal failure, hospital admissions, GP consultations, antibiotic prescriptions) for children with at least one UTI confirmed with microbiological culture (mcUTI) or no mcUTI before the age of 5 will be compared.The second will combine data from two prospective observational studies ('DUTY' and 'EURICA') employing systematic urine sampling for children presenting to primary care with acute, undifferentiated illness, linked to routine data via SAIL (Wales) and NHS Digital (England). Outcomes (as above, plus features of mcUTI) for children with an mcUTI in this data set, identified through systematic urine sampling, will be compared with those with an mcUTI identified through routine urine sampling (data set 1).Ethics and disseminationThe study protocol has been approved by NHS Wales Research Ethics Committee and the Health Research Authority's Confidentiality Advisory Group. Methods of innovative study design and findings will be disseminated through peer-review journals and conferences. Results will be of interest to clinical and policy stakeholders in the UK.
| S-EPMC6527987 | biostudies-literature
Project description:BackgroundSepsis remains the top cause of morbidity and mortality of hospitalised patients despite concerted efforts. Clinical decision support for sepsis has shown mixed results reflecting heterogeneous populations, methodologies and interventions.ObjectivesTo determine whether the addition of a real-time electronic health record (EHR)-based clinical decision support alert improves adherence to treatment guidelines and clinical outcomes in hospitalised patients with suspected severe sepsis.DesignPatient-level randomisation, single blinded.SettingMedical and surgical inpatient units of an academic, tertiary care medical centre.Patients1123 adults over the age of 18 admitted to inpatient wards (intensive care units (ICU) excluded) at an academic teaching hospital between November 2014 and March 2015.InterventionsPatients were randomised to either usual care or the addition of an EHR-generated alert in response to a set of modified severe sepsis criteria that included vital signs, laboratory values and physician orders.Measurements and main resultsThere was no significant difference between the intervention and control groups in primary outcome of the percentage of patients with new antibiotic orders at 3 hours after the alert (35% vs 37%, p=0.53). There was no difference in secondary outcomes of in-hospital mortality at 30 days, length of stay greater than 72 hours, rate of transfer to ICU within 48 hours of alert, or proportion of patients receiving at least 30 mL/kg of intravenous fluids.ConclusionsAn EHR-based severe sepsis alert did not result in a statistically significant improvement in several sepsis treatment performance measures.
| S-EPMC6860967 | biostudies-literature
Project description:ObjectiveWe aimed to determine whether automated identification of antibiotic targeting suspected urinary tract infection (UTI) shortened the time to antimicrobial stewardship (AS) intervention.DesignRetrospective before-and-after study.SettingTertiary and quaternary care academic medical center.PatientsEmergency department (ED) or admitted adult patients meeting best practice alert (BPA) criteria during pre- and post-BPA periods.MethodsWe developed a BPA to alert AS pharmacists of potential ASB triggered by the following criteria: ED or admitted status, antibiotic order with genitourinary indication, and a preceding urinalysis with ≤ 10 WBC/hpf. We evaluated the median time from antibiotic order to AS intervention and overall percent of UTI-related interventions among patients in pre-BPA (01/2020-12/2020) and post-BPA (04/15/2021-04/30/2022) periods.Results774 antibiotic orders met inclusion criteria: 355 in the pre- and 419 in the post-BPA group. 43 (35 UTI-related) pre-BPA and 117 (94 UTI-related) post-BPA interventions were documented. The median time to intervention was 28 hours (IQR 18-65) in the pre-BPA group compared to 16 hours (IQR 2-34) in the post-BPA group (P < 0.01). Despite absent pyuria, there were six cases with gram-negative bacteremia presumably from a urinary source.ConclusionsAutomated identification of antibiotics targeting UTI without pyuria on urinalysis reduced the time to stewardship intervention and increased the rate of UTI-specific interventions. Clinical decision support aided in the efficiency of AS review and syndrome-targeted impact, but cases still required AS clinical review.
| S-EPMC11450662 | biostudies-literature
Project description:Antibiotic resistance is a major cause of treatment failure and leads to increased use of broad-spectrum agents, which begets further resistance. This vicious cycle is epitomized by uncomplicated urinary tract infection (UTI), which affects one in two women during their life and is associated with increasing antibiotic resistance and high rates of prescription for broad-spectrum second-line agents. To address this, we developed machine learning models to predict antibiotic susceptibility using electronic health record data and built a decision algorithm for recommending the narrowest possible antibiotic to which a specimen is susceptible. When applied to a test cohort of 3629 patients presenting between 2014 and 2016, the algorithm achieved a 67% reduction in the use of second-line antibiotics relative to clinicians. At the same time, it reduced inappropriate antibiotic therapy, defined as the choice of a treatment to which a specimen is resistant, by 18% relative to clinicians. For specimens where clinicians chose a second-line drug but the algorithm chose a first-line drug, 92% (1066 of 1157) of decisions ended up being susceptible to the first-line drug. When clinicians chose an inappropriate first-line drug, the algorithm chose an appropriate first-line drug 47% (183 of 392) of the time. Our machine learning decision algorithm provides antibiotic stewardship for a common infectious syndrome by maximizing reductions in broad-spectrum antibiotic use while maintaining optimal treatment outcomes. Further work is necessary to improve generalizability by training models in more diverse populations.
| S-EPMC9527766 | biostudies-literature
Project description:BackgroundOver the past decade, overdoses involving opioids and benzodiazepines have risen at alarming rates, making reductions in coprescribing of these medications a priority, particularly among patients who may be susceptible to adverse events due to high-risk conditions.ObjectivesThis quality improvement project evaluated the effectiveness of a medication alert designed to reduce opioid and benzodiazepine coprescribing among Veterans with known high-risk conditions (substance use, sleep apnea, suicide-risk, age 65 and above) at 1 Veterans Affairs (VA) health care system.MethodsPrescribers were exposed to the point-of-prescribing alert for 12 months. For each high-risk cohort we used interrupted time series design to examine population trends in coprescribing 12 months after alert launch adjusting for coprescribing 12 months before launch, demographics and clinical covariates. Trends at the alert site were compared with those of a similar VA health care system without the alert. Secondary analyses examined population trends in opioid and benzodiazepine prescribing separately.ResultsOver 12 months, the alert activated for 1332 patients. Proportions of patients with concurrent prescriptions decreased significantly postalert launch among substance use [adjusted odds ratio (AOR)=0.97; 95% confidence interval (CI)=0.96-0.99; 12-month decrease=25.0%], sleep apnea (AOR=0.97, 95% CI=0.95-0.98, 12-month decrease=38.5%), and suicide-risk (AOR=0.94, 95% CI=0.91-0.98, 12-month decrease=61.5%) cohorts at the alert site. Decreases in coprescribing were significantly different from the comparison site among suicide-risk (AOR=0.92, 95% CI=0.86-0.97) and sleep apnea (AOR=0.98, 95% CI=0.96-1.00) cohorts. Significant decreases in benzodiazepine prescribing trends were observed at the alert site only.ConclusionsMedication alerts hold promise as a means of reducing opioid and benzodiazepine coprescribing among certain high-risk groups.
| S-EPMC10191171 | biostudies-literature
Project description:The treatment of urinary tract infections (UTIs) has been complicated by the emergence of multidrug-resistant, β-lactamase-expressing pathogens. As a result of the limited treatment options, patients often require hospitalization and intravenous therapy. In essence, a strong unmet need for oral antibiotics, active against extended-spectrum β-lactamase (ESBL) uropathogens has emerged. Oral carbapenems (tebipenem and sulopenem) and oral cephalosporin/β-lactamase inhibitor combinations are in various stages of clinical development for the treatment of uncomplicated and complicated UTI. Tebipenem, if approved, will be the first oral treatment for complicated UTI while sulopenem will be for uncomplicated UTI. The β-lactamase inhibitors ETX0282, VNRX7145, ARX1796, and QPX7728 are combined with cefpodoxime proxetil or ceftibuten that achieve favorable exposures in urine compared to other uropathogen-active oral cephalosporins. The combination ceftibuten-QPX7728 has potential broad-spectrum coverage against carbapenemase producers including metallo β-lactamase producers. Other novel combinations, namely cefpodoxime/ETX0282, ceftibuten/VNRX-7145, and ceftibuten/ARX1796, have also demonstrated excellent activity against Klebsiella pneumoniae carbapanemase (KPC) and OXA-48-like producers. All these agents, upon their arrival for commercial use, would strengthen the outpatient therapy.
| S-EPMC8572892 | biostudies-literature
Project description:BackgroundTo establish antibiotic preregimes and administration routes for studies on urinary microbiota.Methods and materialsAntibiotics for enteritis (Abx-enteritis) and UTIs (Abx-UTI) were administered via gavage and/or urinary catheterisation (UC) for 1 and/or 2 weeks. The effects of these Abx on the urinary microbiota of rats were examined via 16S rRNA sequencing and urine culture, including anaerobic and aerobic culture. Additionally, the safety of the Abx was examined.ResultsAbx-enteritis/Abx-UTI (0.5 g/L and 1 g/L) administered via gavage did not alter the microbial community and bacterial diversity in the urine of rats (FDR > 0.05); however, Abx-UTI (1 g/L) administered via UC for 1 and 2 weeks altered the urinary microbial community (FDR < 0.05). Rats administered Abx-UTI (1 g/L) via UC for 1 week demonstrated a distinct urinary microbiota in culture. Abx-enteritis/Abx-UTI administered via gavage disrupted the microbial community and reduced bacterial diversity in the faeces of rats (FDR < 0.05), and Abx-UTI administered via UC for 2 weeks (FDR < 0.05) altered the fecal microbiota. Abx-UTI (1 g/L) administered via UC did not alter safety considerations. In addition, we noticed that UC did not induce infections and injuries to the bladder and kidney tissues.ConclusionsAdministration of Abx-UTI via UC for 1 week can be considered a pre-treatment option while investigating the urinary microbiota.
| S-EPMC10338079 | biostudies-literature