To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure firstname.lastname@example.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
Background: Carbapenem-resistant Acinetobacter baumannii (CRAB) has emerged as a major cause of bloodstream infection among hospitalized patients in low- and middle-income countries (LMICs). CRAB infections can be difficult to treat and are devastating in neonates (~30% mortality). CRAB outbreaks are hypothesized to arise from reservoirs in the hospital environment, but outbreak investigations in LMICs seldom incorporate whole-genome sequencing (WGS). Methods: WGS (Illumina NextSeq) was performed at the National Institute for Communicable Diseases (South Africa) on 43 preserved A. baumannii isolates from a 530-bed referral hospital in Gaborone, Botswana, from March 2021–August 2022. This included 23 blood-culture isolates from 21 unique patients (aged 2 days–69 years) and 20 environmental isolates collected at the 36-bed neonatal unit in April–June 2021. Infections were considered healthcare-associated if the culture was obtained >72 hours after hospital arrival (or sooner in inborn infants). Blood cultures were incubated using an automated system (BACT/ALERT, BioMérieux) and were identified using manual methods. Environmental isolates were identified using selective or differential chromogenic media (CHROMagarTM). Taxonomic assignment, multilocus sequence typing (MLST), antimicrobial resistance gene identification, and phylogenetic analyses were performed using publicly accessible analysis pipelines. Single-nucleotide polymorphism (SNP) matrices were used to assess clonal lineage. Results: All 23 blood isolates and 5 (25%) of 20 environmental isolates were confirmed as A. baumannii; thus, 28 A. baumannii isolates were included in the phylogenetic analysis. MLST revealed that 22 (79%) of 28 isolates were sequence type 1 (ST1), including all 19 healthcare-associated blood isolates and 3 (60%) of 5 environmental isolates. Genes encoding for carbapenemases (blaNDM-1, blaOXA-23) and biocide resistance (qacE) were present in all 22 ST1 isolates; colistin resistance genes were not identified. Phylogenetic analysis of the ST1 clade demonstrated spatial clustering by hospital unit. Related isolates spanned wide ranges in time (>1 year), suggesting ongoing transmission from environmental sources (Fig. 1). An exclusively neonatal clade (0–2 SNPs) containing all 8 neonatal blood isolates was closely associated with 3 environmental isolates from the neonatal unit: a sink drain, bed rail, and a healthcare worker’s hand. Conclusions: WGS analysis of clinical and environmental A. baumannii revealed the presence of unit-specific CRAB clones, with evidence of ongoing transmission likely driven by persistent environmental reservoirs. This research highlights the potential of WGS to detect hospital outbreaks and reaffirms the importance of environmental sampling to identify and remediate reservoirs (eg, sinks) and vehicles (eg, hands and equipment) within the healthcare environment.
Background: The epidemiology of extended-spectrum cephalosporin-resistant Enterobacterales (ESCrE) in hospitalized patients in low- and middle-income countries (LMICs) is poorly described. Although risk factors for ESCrE clinical infection have been studied, little is known of the epidemiology of ESCrE colonization. Identifying risk factors for ESCrE colonization, which can predispose to infection, is therefore critical to inform antibiotic resistance reduction strategies. Methods: This study was conducted in 3 hospitals located in 3 districts in Botswana. In each hospital, we conducted ongoing surveillance in sequential units hospitalwide. All participants had rectal swabs collected which were inoculated onto chromogenic media followed by confirmatory testing using MALDI-TOF MS and VITEK-2. Data were collected via interview and review of the inpatient medical record on demographics, comorbidities, antibiotic use, healthcare exposures, invasive procedures, travel, animal contact, and food consumption. Participants with ESCrE colonization (cases) were compared to noncolonized participants (controls) using bivariable and multivariable analyses to identify risk factors for ESCrE colonization. Results: Enrollment occurred from January 15, 2020, to September 4, 2020, and 469 participants were enrolled. The median age was 42 years (IQR, 31–58) and 320 (68.2%) were female. The median time from hospital admission to date of sampling was 5 days (IQR, 3–12). There were 179 cases and 290 controls (ie, 38.2% of participants were ESCrE colonized). Independent risk factors for ESCrE colonization were a greater number of days on antibiotic, recent healthcare exposure, and tending swine prior to hospitalization. (Table). Conclusions: ESCrE colonization among hospitalized patients was common and was associated with several exposures. Our results suggest prior healthcare exposure may be important in driving ESCrE. The strong link to recent antibiotic use highlights the potential role of antibiotic stewardship interventions for prevention. The association with tending swine suggests that animal husbandry practices may play a role in community exposures, resulting in colonization detected at the time of hospital admission. These findings will help to inform future studies assessing strategies to curb further emergence of hospital ESCrE in LMICs.
Background: Community-acquired pneumonia (CAP) is a common indication for antibiotic use in hospitalized children and is a key target for pediatric antimicrobial stewardship programs (ASPs). Building upon prior work, we developed and refined an electronic algorithm to identify children hospitalized with CAP and to evaluate the appropriateness of initial antibiotic choice and duration. Methods: We performed a cross-sectional study including children 6 months to 17 years hospitalized for CAP between January 1, 2019, and October 31, 2022, at a tertiary-care children’s hospital. CAP was defined electronically as an International Classification of Disease, Tenth Revision (ICD-10) code for pneumonia, a chest radiograph or chest computed tomography scan (CT) performed within 48 hours of admission, and systemic antibiotics administered within the first 48 hours of hospitalization and continued for at least 2 days. We applied the following exclusion criteria: patients transferred from another healthcare setting, those who died within 48 hours of hospitalization, children with complex chronic conditions, and those with intensive care unit stays >48 hours. Criteria for appropriate antibiotic choice and duration were defined based on established guidelines. Two physicians performed independent medical record reviews of 80 randomly selected patients (10% sample) to evaluate the performance of the electronic algorithm in (1) identifying patients treated for clinician-diagnosed CAP and (2) classifying antibiotic choice and duration as appropriate. A third physician resolved discrepancies. The electronic algorithm was compared to this medical record review, which served as the reference standard. Results: Of 80 children identified by the electronic algorithm, 79 (99%) were diagnosed with CAP based on medical record review. Antibiotic use was classified as the appropriate choice in 75 (94%) of 80 cases, and appropriate duration in 16 (20%) of 80 cases. The sensitivity of the electronic algorithm for identifying appropriate initial antibiotic choice was 94%; specificity could not be calculated because no events of inappropriate antibiotic choice were identified based on chart review. The sensitivity and specificity for determining appropriate duration were 88% and 97%, respectively (Table 1).
Conclusions: The electronic algorithm accurately identified children hospitalized with CAP and demonstrated acceptable performance for identifying appropriate antibiotic choice and duration. Use of this electronic algorithm may improve the efficiency of stewardship activities and could facilitate alignment with updated accreditation standards. Future studies validating this algorithm at other centers are needed.
We assessed susceptibility patterns to newer antimicrobial agents among clinical carbapenem-resistant Klebsiella pneumoniae (CRKP) isolates from patients in long-term acute-care hospitals (LTACHs) from 2014 to 2015. Meropenem-vaborbactam and imipenem-relebactam nonsusceptibility were observed among 9.9% and 9.1% of isolates, respectively. Nonsusceptibility to ceftazidime-avibactam (1.1%) and plazomicin (0.8%) were uncommon.
The spatial and temporal extent of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) environmental contamination has not been precisely defined. We sought to elucidate contamination of different surface types and how contamination changes over time.
We sampled surfaces longitudinally within COVID-19 patient rooms, performed quantitative RT-PCR for the detection of SARS-CoV-2 RNA, and modeled distance, time, and severity of illness on the probability of detecting SARS-CoV-2 using a mixed-effects binomial model.
The probability of detecting SARS-CoV-2 RNA in a patient room did not vary with distance. However, we found that surface type predicted probability of detection, with floors and high-touch surfaces having the highest probability of detection: floors (odds ratio [OR], 67.8; 95% credible interval [CrI], 36.3–131) and high-touch elevated surfaces (OR, 7.39; 95% CrI, 4.31–13.1). Increased surface contamination was observed in room where patients required high-flow oxygen, positive airway pressure, or mechanical ventilation (OR, 1.6; 95% CrI, 1.03–2.53). The probability of elevated surface contamination decayed with prolonged hospitalization, but the probability of floor detection increased with the duration of the local pandemic wave.
Distance from a patient’s bed did not predict SARS-CoV-2 RNA deposition in patient rooms, but surface type, severity of illness, and time from local pandemic wave predicted surface deposition.
We prospectively surveyed SARS-CoV-2 RNA contamination in staff common areas within an acute-care hospital. An increasing prevalence of surface contamination was detected over time. Adjusting for patient census or community incidence of coronavirus disease 2019 (COVID-19), the proportion of contaminated surfaces did not predict healthcare worker COVID-19 infection on study units.
Multidrug-resistant organisms (MDROs) colonizing the healthcare environment have been shown to contribute to risk for healthcare-associated infections (HAIs), with adverse effects on patient morbidity and mortality. We sought to determine how bacterial contamination and persistent MDRO colonization of the healthcare environment are related to the position of patients and wastewater sites.
We performed a prospective cohort study, enrolling 51 hospital rooms at the time of admitting a patient with an eligible MDRO in the prior 30 days. We performed systematic sampling and MDRO culture of rooms, as well as 16S rRNA sequencing to define the environmental microbiome in a subset of samples.
The probability of detecting resistant gram-negative organisms, including Enterobacterales, Acinetobacter spp, and Pseudomonas spp, increased with distance from the patient. In contrast, Clostridioides difficile and methicillin-resistant Staphylococcus aureus were more likely to be detected close to the patient. Resistant Pseudomonas spp and S. aureus were enriched in these hot spots despite broad deposition of 16S rRNA gene sequences assigned to the same genera, suggesting modifiable factors that permit the persistence of these MDROs.
MDRO hot spots can be defined by distance from the patient and from wastewater reservoirs. Evaluating how MDROs are enriched relative to bacterial DNA deposition helps to identify healthcare micro-environments and suggests how targeted environmental cleaning or design approaches could prevent MDRO persistence and reduce infection risk.
Background: Evidence-based hospital antimicrobial stewardship interventions, such as postprescription review with feedback, prior authorization, and handshake stewardship, involve communication between stewards and frontline prescribers. Hierarchy, asymmetric responsibility, prescribing etiquette, and autonomy can obstruct high-quality communication in stewardship. Little is known about the strategies that stewards use to overcome these barriers. The objective of this study was to identify how stewards navigate communication challenges when interacting with prescribers. Methods: We conducted semistructured interviews with antimicrobial stewards recruited from hospitals across the United States. Interviews were audio recorded, transcribed, and analyzed using a flexible coding approach and the framework method. Social identity theory and role theory were used to interpret framework matrices. Results: Interviews were conducted with 58 antimicrobial stewards (25 physicians and 33 pharmacists) from 10 hospitals (4 academic medical centers, 4 community hospitals, and 2 children’s hospitals). Respondents who felt empowered in their interactions with prescribers explicitly adopted a social identity that conceptualized stewards and prescribers as being on the “same team” with shared goals (in-group orientation). Drawing on the meaning conferred via this social role identity, respondents engaged in communication strategies to build and maintain common bonds with prescribers. These strategies included moderating language to minimize defensive recommendations when delivering stewardship recommendations, aligning the goals of stewardship with the goals of the clinical team, communicating with prescribers about things other than stewardship, compromising for the sake of future interactions, and engaging in strategic face-to-face interaction. Respondents who felt less empowered in their interactions thought of themselves as outsiders to the clinical team and experienced a heightened sense of “us versus them” mentality with the perception that stewards primarily serve a gate-keeping function (ie, outgroup orientation). These respondents expressed deference to hierarchy, a reluctance to engage in face-to-face interaction, a feeling of cynicism about the impact of stewardship, and a sense of low professional accomplishment within the role. Respondents who exhibited an in-group orientation were more likely than those who did not to describe the positive impact of stewardship mentors or colleagues on their social role identity. Conclusions: The way antimicrobial stewards perceive their role and identity within the social context of their healthcare organization influences how they approach communication with prescribers. Social role identity in stewardship is shaped by the influence of mentors and colleagues, indicating the importance of supportive relationships for the development of steward skill and confidence.
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% (P < .001) and increased cefazolin use 19 times from baseline (P < .001).
To determine metrics and provider characteristics associated with inappropriate antibiotic prescribing for respiratory tract diagnoses (RTDs).
Retrospective cohort study.
Primary care practices in a university health system.
Patients seen by an attending physician or advanced practice provider (APP) at their primary care office visit with International Classification of Disease, Tenth Revision, Clinical Modification (ICD-10-CM)–coded RTDs.
Medical records were reviewed for 1,200 randomly selected office visits in which an antibiotic was prescribed to determine appropriateness. Based on this gold standard, metrics and provider characteristics associated with inappropriate antibiotic prescribing were determined.
Overall, 69% of antibiotics were inappropriate. Metrics utilizing prespecified RTDs most strongly associated with inappropriate prescribing were (1) proportion prescribing for RTDs for which antibiotics are almost never required (eg, bronchitis) and (2) proportion prescribing for any RTD. Provider characteristics associated with inappropriate antibiotic prescribing were APP versus physician (72% vs 58%; P = .02), family medicine versus internal medicine (76% vs 63%; P = .01), board certification 1997 or later versus board certification before 1997 (75% vs 63%; P = .02), nonteaching versus teaching practice (73% vs 51%; P < .01), and nonurban vs urban practice (77% vs 57%; P < .01).
Metrics utilizing proportion prescribing for RTDs for which antibiotics are almost never required and proportion prescribing for any RTD were most strongly associated with inappropriate prescribing. APPs and clinicians with family medicine training, with board certification 1997 or later, and who worked in nonteaching or nonurban practices had higher proportions of inappropriate prescribing. These findings could inform design of interventions to improve prescribing and could represent an efficient way to track inappropriate prescribing.
To develop a pediatric research agenda focused on pediatric healthcare-associated infections and antimicrobial stewardship topics that will yield the highest impact on child health.
The study included 26 geographically diverse adult and pediatric infectious diseases clinicians with expertise in healthcare-associated infection prevention and/or antimicrobial stewardship (topic identification and ranking of priorities), as well as members of the Division of Healthcare Quality and Promotion at the Centers for Disease Control and Prevention (topic identification).
Using a modified Delphi approach, expert recommendations were generated through an iterative process for identifying pediatric research priorities in healthcare associated infection prevention and antimicrobial stewardship. The multistep, 7-month process included a literature review, interactive teleconferences, web-based surveys, and 2 in-person meetings.
A final list of 12 high-priority research topics were generated in the 2 domains. High-priority healthcare-associated infection topics included judicious testing for Clostridioides difficile infection, chlorhexidine (CHG) bathing, measuring and preventing hospital-onset bloodstream infection rates, surgical site infection prevention, surveillance and prevention of multidrug resistant gram-negative rod infections. Antimicrobial stewardship topics included β-lactam allergy de-labeling, judicious use of perioperative antibiotics, intravenous to oral conversion of antimicrobial therapy, developing a patient-level “harm index” for antibiotic exposure, and benchmarking and or peer comparison of antibiotic use for common inpatient conditions.
We identified 6 healthcare-associated infection topics and 6 antimicrobial stewardship topics as potentially high-impact targets for pediatric research.
Background:Clostridioides difficile infection (CDI) is a major contributor to morbidity and mortality in patients with hematologic malignancy. Due to both immunosuppression and frequent antibiotic exposures, up to one-third of inpatients receiving chemotherapy or stem-cell transplant develop CDI. Transmission of C. difficile in healthcare facilities occurs due to environmental surface contamination and hand carriage by healthcare workers from colonized and infected patients. We investigated the effectiveness of enhanced room cleaning in collaboration with environmental services (EVS) staff to prevent CDI transmission and infection.
Methods: From April 1, 2018, to September 30, 2018, a multimodal enhanced cleaning intervention was implemented on 2 oncology units at the Hospital of the University of Pennsylvania. This intervention included real-time feedback to EVS staff following ATP bioluminescence monitoring. Additionally, all rooms on the intervention units underwent UV disinfection after terminal cleaning. We performed a system-level cohort study, comparing rates of CDI on the 2 study units to historic and 2 concurrent control units. Historic and concurrent control units received UV disinfection only for rooms with prior occupants with MRSA or CDI. All units during the intervention period received education on the importance of environmental cleaning for infection prevention. Mixed-effects Poisson regression was used to adjust for system-level confounders. Results: A median of 1.34 CDI cases per 1,000 patient days (IQR, 1.20–3.62) occurred during the 12-month baseline period. There was a trend toward a reduced rate of CDI across all units during the intervention period (median, 1.19; IQR, 0.00–2.47; P = .13) compared with all units during the historical period. Using mixed-effects Poisson regression, accounting for the random effects of study units, the intervention was associated with an incidence rate ratio for C. difficile of 0.72 compared to control units (95% CI, 0.53–0.97; P = .03). Average room turnaround time (TAT) increased across all units during the study period, from 78 minutes (IQR 74–81) to 92 minutes (IQR, 85–96; P < .001). Within the intervention period, TAT was higher on intervention units (median, 94 minutes; IQR, 92–98) compared to concurrent control units (median, 85; IQR, 80–92; P = .005). Conclusions: Enhanced environmental cleaning, including UV disinfection of all patient rooms and ATP bioluminescent monitoring with real-time feedback, was associated with a reduction in the incidence of CDI.
Background: Clinically diagnosed ventilator-associated pneumonia (VAP) is common in the long-term acute-care hospital (LTACH) setting and may contribute to adverse ventilator-associated events (VAEs). Pseudomonas aeruginosa is a common causative organism of VAP. We evaluated the impact of respiratory P. aeruginosa colonization and bacterial community dominance, both diagnosed and undiagnosed, on subsequent P. aeruginosa VAP and VAE events during long-term acute care. Methods: We enrolled 83 patients on LTACH admission for ventilator weaning, performed longitudinal sampling of endotracheal aspirates followed by 16S rRNA gene sequencing (Illumina HiSeq), and bacterial community profiling (QIIME2). Statistical analysis was performed with R and Stan; mixed-effects models were fit to relate the abundance of respiratory Psa on admission to clinically diagnosed VAP and VAE events. Results: Of the 83 patients included, 12 were diagnosed with P. aeruginosa pneumonia during the 14 days prior to LTACH admission (known P. aeruginosa), and 22 additional patients received anti–P. aeruginosa antibiotics within 48 hours of admission (suspected P. aeruginosa); 49 patients had no known or suspected P. aeruginosa (unknown P. aeruginosa). Among the known P. aeruginosa group, all 12 patients had P. aeruginosa detectable by 16S sequencing, with elevated admission P. aeruginosa proportional abundance (median, 0.97; IQR, 0.33–1). Among the suspected P. aeruginosa group, all 22 patients had P. aeruginosa detectable by 16S sequencing, with a wide range of admission P. aeruginosa proportional abundance (median, 0.0088; IQR, 0.00012–0.31). Of the 49 patients in the unknown group, 47 also had detectable respiratory Psa, and many had high P. aeruginosa proportional abundance at admission (median, 0.014; IQR, 0.00025–0.52). Incident P. aeruginosa VAP was observed within 30 days in 4 of the known P. aeruginosa patients (33.3%), 5 of the suspected P. aeruginosa patients (22.7%), and 8 of the unknown P. aeruginosa patients (16.3%). VAE was observed within 30 days in 1 of the known P. aeruginosa patients (8.3%), 2 of the suspected P. aeruginosa patients (9.1%), and 1 of the unknown P. aeruginosa patients (2%). Admission P. aeruginosa abundance was positively associated with VAP and VAE risk in all groups, but the association only achieved statistical significance in the unknown group (type S error <0.002 for 30-day VAP and <0.011 for 30-day VAE). Conclusions: We identified a high prevalence of unrecognized respiratory P. aeruginosa colonization among patients admitted to LTACH for weaning from mechanical ventilation. The admission P. aeruginosa proportional abundance was strongly associated with increased risk of incident P. aeruginosa VAP among these patients.
Background: Antibiotic overuse contributes to antibiotic resistance and unnecessary adverse drug effects. Antibiotic stewardship interventions have primarily focused on acute-care settings. Most antibiotic use, however, occurs in outpatients with acute respiratory tract infections such as pharyngitis. The electronic health record (EHR) might provide an effective and efficient tool for outpatient antibiotic stewardship. We aimed to develop and validate an electronic algorithm to identify inappropriate antibiotic use for pediatric outpatients with pharyngitis. Methods: This study was conducted within the Children’s Hospital of Philadelphia (CHOP) Care Network, including 31 pediatric primary care practices and 3 urgent care centers with a shared EHR serving >250,000 children. We used International Classification of Diseases, Tenth Revision (ICD-10) codes to identify encounters for pharyngitis at any CHOP practice from March 15, 2017, to March 14, 2018, excluding those with concurrent infections (eg, otitis media, sinusitis), immunocompromising conditions, or other comorbidities that might influence the need for antibiotics. We randomly selected 450 features for detailed chart abstraction assessing patient demographics as well as practice and prescriber characteristics. Appropriateness of antibiotic use based on chart review served as the gold standard for evaluating the electronic algorithm. Criteria for appropriate use included streptococcal testing, use of penicillin or amoxicillin (absent β-lactam allergy), and a 10-day duration of therapy. Results: In 450 patients, the median age was 8.4 years (IQR, 5.5–9.0) and 54% were women. On chart review, 149 patients (33%) received an antibiotic, of whom 126 had a positive rapid strep result. Thus, based on chart review, 23 subjects (5%) diagnosed with pharyngitis received antibiotics inappropriately. Amoxicillin or penicillin was prescribed for 100 of the 126 children (79%) with a positive rapid strep test. Of the 126 children with a positive test, 114 (90%) received the correct antibiotic: amoxicillin, penicillin, or an appropriate alternative antibiotic due to b-lactam allergy. Duration of treatment was correct for all 126 children. Using the electronic algorithm, the proportion of inappropriate prescribing was 28 of 450 (6%). The test characteristics of the electronic algorithm (compared to gold standard chart review) for identification of inappropriate antibiotic prescribing were sensitivity (99%, 422 of 427); specificity (100%, 23 of 23); positive predictive value (82%, 23 of 28); and negative predictive value (100%, 422 of 422). Conclusions: For children with pharyngitis, an electronic algorithm for identification of inappropriate antibiotic prescribing is highly accurate. Future work should validate this approach in other settings and develop and evaluate the impact of an audit and feedback intervention based on this tool.
Background: Automatic discontinuation of antimicrobial orders after a prespecified duration of therapy has been adopted as a strategy for reducing excess days of therapy (DOT) as part of antimicrobial stewardship efforts. Automatic stop orders have been shown to decrease antimicrobial DOT. However, inadvertent treatment interruptions may occur as a result, potentially contributing to adverse patient outcomes. To evaluate the effects of this practice, we examined the impact of the removal of an electronic 7-day ASO program on hospitalized patients. Methods: We performed a quasi-experimental study on inpatients in 3 acute-care academic hospitals. In the preintervention period (automatic stop orders present; January 1, 2016, to February 28, 2017), we had an electronic dashboard to identify and intervene on unintentionally missed doses. In the postintervention period (April 1, 2017, to March 31, 2018), the automatic stop orders were removed. We compared the primary outcome, DOT per 1,000 patient days (PD) per month, for patients in the automatic stop orders present and absent periods. The Wilcoxon rank-sum test was used to compare median monthly DOT/1,000 PD. Interrupted time series analysis (Prais-Winsten model) was used to compared trends in antibiotic DOT/1,000 PD and the immediate impact of the automatic stop order removal. Manual chart review on a subset of 300 patients, equally divided between the 2 periods, was performed to assess for unintentionally missed doses. Results: In the automatic stop order period, a monthly median of 644.5 antibiotic DOT/1,000 PD were administered, compared to 686.2 DOT/1,000 PD in the period without automatic stop orders (P < .001) (Fig. 1). Using interrupted time series analysis, there was a nonsignificant increase by 46.7 DOT/1,000 PD (95% CI, 40.8 to 134.3) in the month immediately following removal of automatic stop orders (P = .28) (Fig. 2). Even though the slope representing monthly change in DOT/1,000 PD increased in the period without automatic stop orders compared to the period with automatic stop orders, it was not statistically significant (P = .41). Manual chart abstraction revealed that in the period with automatic stop orders, 9 of 150 patients had 17 unintentionally missed days of therapy, whereas none (of 150 patients) in the period without automatic stop orders did. Conclusions: Following removal of the automatic stop orders, there was an overall increase in antibiotic use, although the change in monthly trend of antibiotic use was not significantly different. Even with a dashboard to identify missed doses, there was still a risk of unintentionally missed doses in the period with automatic stop orders. Therefore, this risk should be weighed against the modest difference in antibiotic utilization garnered from automatic stop orders.
Background: Antibiotic resistance has increased at alarming rates, driven predominantly by antibiotic overuse. Although most antibiotic use occurs in outpatients, antimicrobial stewardship programs have primarily focused on inpatient settings. A major challenge for outpatient stewardship is the lack of accurate and accessible electronic data to target interventions. We sought to develop and validate an electronic algorithm to identify inappropriate antibiotic use for outpatients with acute bronchitis. Methods: This study was conducted within the University of Pennsylvania Health System (UPHS). We used ICD-10 diagnostic codes to identify encounters for acute bronchitis at any outpatient UPHS practice between March 15, 2017, and March 14, 2018. Exclusion criteria included underlying immunocompromising condition, other comorbidity influencing the need for antibiotics (eg, emphysema), or ICD-10 code at the same visit for a concurrent infection (eg, sinusitis). We randomly selected 300 (150 from academic practices and 150 from nonacademic practices) eligible subjects for detailed chart abstraction that assessed patient demographics and practice and prescriber characteristics. Appropriateness of antibiotic use based on chart review served as the gold standard for assessment of the electronic algorithm. Because antibiotic use is not indicated for this study population, appropriateness was assessed based upon whether an antibiotic was prescribed or not. Results: Of 300 subjects, median age was 61 years (interquartile range, 50–68), 62% were women, 74% were seen in internal medicine (vs family medicine) practices, and 75% were seen by a physician (vs an advanced practice provider). On chart review, 167 (56%) subjects received an antibiotic. Of these subjects, 1 had documented concern for pertussis and 4 had excluding conditions for which there were no ICD-10 codes. One received an antibiotic prescription for a planned dental procedure. Thus, based on chart review, 161 (54%) subjects received antibiotics inappropriately. Using the electronic algorithm based on diagnostic codes, underlying and concurrent conditions, and prescribing data, the number of subjects with inappropriate prescribing was 170 (56%) because 3 subjects had antibiotic prescribing not noted based on chart review. The test characteristics of the electronic algorithm (compared to gold standard chart review) for identification of inappropriate antibiotic prescribing were the following: sensitivity, 100% (161 of 161); specificity, 94% (130 of 139); positive predictive value, 95% (161 of 170); and negative predictive value, 100% (130 of 130). Conclusions: For outpatients with acute bronchitis, an electronic algorithm for identification of inappropriate antibiotic prescribing is highly accurate. This algorithm could be used to efficiently assess prescribing among practices and individual clinicians. The impact of interventions based on this algorithm should be tested in future studies.
Background: There is great enthusiasm for the potential of decision support tools embedded in the electronic medical record to improve antimicrobial use in hospitals. Yet they are often limited in their ability to change prescriber behavior. Analyzing these tools using an interactive sociotechnical approach (ISTA) can identify barriers and facilitators to the implementation of electronic decision support (EDS) in antimicrobial stewardship. Objective: To examine prescriber and antimicrobial steward perceptions of EDS using an ISTA approach in the preimplementation phase of an antimicrobial stewardship intervention. Methods: We conducted semistructured interviews with prescribers and stewards from 4 hospitals in 2 health systems in the context of a multicomponent intervention to improve the use of fluoroquinolones and extended-spectrum cephalosporins. Sites planned to implement various EDS elements including order sets, antimicrobial time outs, and audit with feedback stewardship notes in the medical record. Interviews elicited respondent perceptions about the planned intervention. Two analysts systematically coded transcripts using an ISTA framework in NVivo12 software. Results: Interviews with 64 respondents were conducted: 38 physicians, 7 nurses, 6 advanced practice providers, and 13 pharmacists. We identified 4 key sociotechnical interaction types likely to influence stewardship EDS implementation. First, EDS changes the communication patterns and practices of antimicrobial stewards in a way that improves efficiency but decreases vital social interaction with prescribers to facilitate behavior change. Second, there is a gap between what stewards envision for EDS and that which is possible to build in a timely manner by hospital information technology specialists. As a result, there is often a months- to years-long delay from proposal to implementation, which negatively affects intervention acceptance. Third, prescribers expressed great enthusiasm for stewardship EDS that would simplify their workload, allow them to complete important work tasks, and save time. They strongly objected to stewardship EDS that was disruptive without a compelling purpose or did not integrate smoothly with pre-existing technology infrastructure. Fourth, physician prescribers attributed social and emotional meaning to stewardship EDS, suggesting that these tools can undermine professional authority, autonomy, and confidence. Conclusions: Implementing stewardship EDS in a way that improves the use of antimicrobials while minimizing unintended negative consequences requires attention to the interplay between new EDS and an organization’s existing workflow, culture, social interactions and technologies. Implementing EDS in stewardship will require attention to these domains to realize the full potential of these tools and to avoid negative unintended consequences.
Background: Healthcare exposure results in significant microbiome disruption, particularly in the setting of critical illness, which may contribute to risk for healthcare-associated infections (HAIs). Patients admitted to long-term acute-care hospitals (LTACHs) have extensive prior healthcare exposure and critical illness; significant microbiome disruption has been previously documented among LTACH patients. We compared the predictive value of 3 respiratory tract microbiome disruption indices—bacterial community diversity, dominance, and absolute abundance—as they relate to risk for ventilator-associated pneumonia (VAP) and adverse ventilator-associated events (VAE), which commonly complicate LTACH care. Methods: We enrolled 83 subjects on admission to an academic LTACH for ventilator weaning and performed longitudinal sampling of endotracheal aspirates, followed by 16S rRNA gene sequencing (Illumina HiSeq), bacterial community profiling (QIIME2) for diversity, and 16S rRNA quantitative PCR (qPCR) for total bacterial abundance. Statistical analyses were performed with R and Stan software. Mixed-effects models were fit to relate the admission MDIs to subsequent clinically diagnosed VAP and VAE. Results: Of the 83 patients, 19 had been diagnosed with pneumonia during the 14 days prior to LTACH admission (ie, “recent past VAP”); 23 additional patients were receiving antibiotics consistent with empiric VAP therapy within 48 hours of admission (ie, “empiric VAP therapy”); and 41 patients had no evidence of VAP at admission (ie, “no suspected VAP”). We detected no statistically significant differences in admission Shannon diversity, maximum amplicon sequence variant (ASV)–level proportional abundance, or 16S qPCR across the variables of interest. In isolation, all 3 admission microbiome disruption indices showed poor predictive performance, though Shannon diversity performed better than maximum ASV abundance. Predictive models that combined (1) bacterial diversity or abundance with (2) recent prior VAP diagnosis and (3) concurrent antibiotic exposure best predicted 14-day VAP (type S error < 0.05) and 30-day VAP (type S error < 0.003). In this cohort, VAE risk was paradoxically associated with higher admission Shannon diversity and lower admission maximum ASV abundance. Conclusions: In isolation, respiratory tract microbiome disruption indices obtained at LTACH admission showed poor predictive performance for subsequent VAP and VAE. But diversity and abundance models incorporating recent VAP history and admission antibiotic exposure performed well predicting 14-day and 30-day VAP.
Evaluate the clinical impact of the implementation of VERIGENE gram-positive blood culture testing (BC-GP) coupled with antimicrobial stewardship result notification for children with positive blood cultures.
Quaternary children’s hospital.
Hospitalized children aged 0–21 years with positive blood culture events 1 year before and 1 year after implementation of BC-GP testing.
The primary outcome was time to optimal antibiotic therapy for positive blood cultures, defined as receiving definitive therapy without unnecessary antibiotics (pathogens) or no antibiotics (contaminants). Secondary outcomes were time to effective therapy, time to definitive therapy, and time to stopping vancomycin, length of stay, and 30-day mortality. Time-to-therapy outcomes before and after the intervention were compared using Cox regression models and interrupted time series analyses, adjusting for patient characteristics and trends over time. Gram-negative events were included as a nonequivalent dependent variable.
We included 264 preintervention events (191 gram-positive, 73 gram-negative) and 257 postintervention events (168 gram-positive, 89 gram-negative). The median age was 2.9 years (interquartile range, 0.3–10.1), and 418 pediatric patients (80.2%) had ≥1 complex chronic condition. For gram-positive isolates, implementation of BC-GP testing was associated with an immediate reduction in time to optimal therapy and time to stopping vancomycin for both analyses. BC-GP testing was associated with decreased time to definitive therapy in interrupted time series analysis but not Cox modeling. No such changes were observed for gram-negative isolates. No changes in time to effective therapy, length of stay, or mortality were associated with BC-GP.
The implementation of BC-GP testing coupled with antimicrobial stewardship result notification was associated with decreased time to optimal therapy and time to stopping vancomycin for hospitalized children with gram-positive blood culture isolates.
Fluoroquinolones (FQs) and extended-spectrum cephalosporins (ESCs) are associated with higher risk of Clostridioides difficile infection (CDI). Decreasing the unnecessary use of FQs and ESCs is a goal of antimicrobial stewardship. Understanding how prescribers perceive the risks and benefits of FQs and ESCs is needed.
We conducted interviews with clinicians from 4 hospitals. Interviews elicited respondent perceptions about the risk of ESCs, FQs, and CDI. Interviews were audio recorded, transcribed, and analyzed using a flexible coding approach.
Interviews were conducted with 64 respondents (38 physicians, 7 nurses, 6 advance practice providers, and 13 pharmacists). ESCs and FQs were perceived to have many benefits, including infrequent dosing, breadth of coverage, and greater patient adherence after hospital discharge. Prescribers stated that it was easy to make decisions about these drugs, so they were especially appealing to use in the context of time pressures. They described having difficulty discontinuing these drugs when prescribed by others due to inertia and fear. Prescribers were skeptical about targeting specific drugs as a stewardship approach and felt that the risk of a negative outcome from under treatment of a suspected bacterial infection was a higher priority than the prevention of CDI.
Prescribers in this study perceived many advantages to using ESCs and FQs, especially under conditions of time pressure and uncertainty. In making decisions about these drugs, prescribers balance risk and benefit, and they believed that the risk of CDI was acceptable in compared with the risk of undertreatment.