A geospatial approach to identify patterns of antibiotic susceptibility at a neighborhood level in Wisconsin, United States.

The global threat of antimicrobial resistance (AMR) varies regionally. This study explores whether geospatial analysis and data visualization methods detect both clinically and statistically significant variations in antibiotic susceptibility rates at a neighborhood level. This observational multicenter geospatial study collected 10 years of patient-level antibiotic susceptibility data and patient addresses from three regionally distinct Wisconsin health systems (UW Health, Fort HealthCare, Marshfield Clinic Health System [MCHS]). We included the initial Escherichia coli isolate per patient per year per sample source with a patient address in Wisconsin (N = 100,176). Isolates from U.S. Census Block Groups with less than 30 isolates were excluded (n = 13,709), resulting in 86,467 E. coli isolates. The primary study outcomes were the results of Moran's I spatial autocorrelation analyses to quantify antibiotic susceptibility as spatially dispersed, randomly distributed, or clustered by a range of - 1 to + 1, and the detection of statistically significant local hot (high susceptibility) and cold spots (low susceptibility) for variations in antibiotic susceptibility by U.S. Census Block Group. UW Health isolates collected represented greater isolate geographic density (n = 36,279 E. coli, 389 = blocks, 2009-2018), compared to Fort HealthCare (n = 5110 isolates, 48 = blocks, 2012-2018) and MCHS (45,078 isolates, 480 blocks, 2009-2018). Choropleth maps enabled a spatial AMR data visualization. A positive spatially-clustered pattern was identified from the UW Health data for ciprofloxacin (Moran's I = 0.096, p = 0.005) and trimethoprim/sulfamethoxazole susceptibility (Moran's I = 0.180, p < 0.001). Fort HealthCare and MCHS distributions were likely random. At the local level, we identified hot and cold spots at all three health systems (90%, 95%, and 99% CIs). AMR spatial clustering was observed in urban areas but not rural areas. Unique identification of AMR hot spots at the Block Group level provides a foundation for future analyses and hypotheses. Clinically meaningful differences in AMR could inform clinical decision support tools and warrants further investigation for informing therapy options.

"What brought you in today?": Modeling patient-provider clinic visits to characterize rural providers' antibiotic treatment decisions.

BACKGROUND: Designing clinical decision support (CDS) tools is challenging because clinical decision-making must account for an invisible task load: incorporating non-linear objective and subjective factors to make an assessment and treatment plan. This calls for a cognitive task analysis approach. OBJECTIVES: The objectives of this study were to 1.) understand healthcare providers' decision making during a typical clinic visit, and 2.) explore how antibiotic treatment decisions are made when they arise. METHODS: Two cognitive task analysis methods were applied - Hierarchical Task Analysis (HTA) and Operations Sequence Diagramming (OSD) - to 39 h of observational data collected at family medicine, urgent care, and emergency medicine clinical sites. RESULTS: The resulting HTA models included a coding taxonomy detailing ten cognitive goals and associated sub-goals and demonstrated how the goals occur as interactions between the provider and electronic health record, the patient, and the physical clinic environment. Although the HTA detailed resources for antibiotic treatment decisions, antibiotics were a minority of drug classes ordered. The OSD shows the sequence of events and when decisions are made solely at the provider level and when shared decision making occurs with the patient. Qualitative data from the observations informed a constructed vignette case example portraying select tasks from the HTA. CONCLUSIONS: These findings emphasize that the scope of disease states presenting to a generalist clinical setting is broad and could include acute exacerbations of rare diseases within a time-pressured environment. CDS must be accessible, time efficient, and fit within the resource gathering task before treatment decisions are made.

Surveillance for multidrug resistant Escherichia coli carriage in cattle, dogs and humans reveals predominance of CMY-2, CTX-M-15 and CTX-M-9 groups of ß-lactamases.

Global spread of antimicrobial multidrug resistance (MDR) in human and veterinary medicine relies upon diagnostics, surveillance and stewardship to guide mitigation. Utilizing surveillance of fecal samples from our service area for detecting MDR Escherichia coli carriage in humans (2143), dogs (627), and cattle (130), we found isolates resistant to third/fourth generation cephems present in 3.7 %, 13.1 %, and 51.5 %, respectively. CMY-2, CTX-M-15-like and CTX-M9 group genes in descending order were predominant in all hosts and accounted for 83.3 % of non-wild-type gene targets. MDR carriage mirrored cephem non-susceptibility rates as published in annual antibiograms for humans and dogs; notably, no carbapenem-resistant carriage isolates were detected. Given the scale of MDR E. coli carriage in cattle (14X) and dogs (3.5X) compared to humans, bench-marking of the resistance gene pool by host species utilizing regional One Health surveillance may aid in assessing occupational and geographic risks for acquiring resistance and for monitoring of mitigation strategies.

Application of consolidated framework for implementation research to improve Clostridioides difficile infection management in district hospitals.

BACKGROUND: Clostridioides difficile infection (CDI) contributes the global threats of drug resistant infections, healthcare acquired infections and antimicrobial resistance. Yet CDI knowledge among healthcare providers in low-resource settings is limited and CDI testing, treatment, and infection prevention measures are often delayed. OBJECTIVES: to develop a CDI intervention informed by the local context within South African public district level hospitals, and analyze the CDI intervention and implementation process. METHODS: A CDI checklist intervention was designed and implemented at three district level hospitals in the Western Cape, South Africa that volunteered to participate. Data collection included a retrospective medical records review of patients hospitalized with C. difficile test orders during the 90 days post-implementation. Patient outcomes and checklist components (e.g. antibiotics) were collected. Qualitative interviews (n = 14) and focus groups (n = 6) were conducted with healthcare providers on-site. The Consolidated Framework for Implementation Research (CFIR) and the Framework for Reporting Adaptations and Modifications to Evidence-based Implementation Strategies (FRAME-IS) were applied to collected data and observations in order to identify drivers and barriers to implementation and understand differences in uptake. RESULTS: One of the three hospitals displayed high intervention uptake. Highly relevant CFIR constructs linked to intervention uptake included tension for change, strong peer intervention champions, champions in influential leadership positions, and the intervention's simplicity (CFIR construct: complexity). Tension for change, a recognized need to improve CDI identification and treatment, at the high uptake hospital was also supported by an academic partnership for antimicrobial stewardship. CONCLUSIONS: This research provides a straight-forward health systems strengthening intervention for CDI that is both needed and uncomplicated, in an understudied low resource setting. Intervention uptake was highest in the hospital with tension for change, influential champions, and existing academic partnerships. Implementation in settings with fewer academic connections requires further testing of collaborative implementation strategies and proactive adaptations.

A One Health Approach to Compare Self-Prescribed Antibiotic Use across Rural and Semi-urban Populations in San Lucas Tolimán, Guatemala.

Antimicrobial resistance resulting from antibiotic overuse represents an increasing public health challenge. The purpose of this study was to investigate antibiotic self-medication practices in a rural, indigenous Guatemalan population, and to compare self-prescribing patterns in rural and semi-urban populations using a One Health integrated approach, a framework acknowledging that health arises at the interface of humans, animals, and the environment. We conducted a mixed methods study using semi-structured interviews in and around San Lucas Tolimán, Guatemala. Antibiotic self-medication was common in both rural and semi-urban populations, regardless of demographic characteristics. Antibiotic usage in animals, while less common, almost always occurred without a veterinary consult. Although subjects recognized that self-medication could be harmful to health, they face significant barriers to accessing appropriate care. These patterns of use have impacts on the rise of antimicrobial resistance locally, and have the potential to contribute to the spread of such resistance globally.

Assessment of perceived workload in academic health center community pharmacies before and after implementation of a central call center.

PURPOSE: Results of a study to determine whether reducing pharmacy phone call workload through implementation of a pharmacy services call center (PSCC) led to decreased employee workload, improved efficiency, and increased pharmacist availability for patient care are reported. METHODS: A pre-post study was conducted using the NASA Task Load Index (NASA-TLX) instrument. Pharmacists, pharmacy technicians at 7 academic health center community pharmacies, and PSCC staff provided NASA-TLX data over 5 days during 3 data collection periods before and after PSCC implementation. Perceived workload was measured as an overall workload score (OWS) and mean scores for 6 NASA-TLX workload dimensions (mental demand, physical demand, temporal demand, performance, effort, and frustration). RESULTS: Relative to pre-PSCC values, mean postimplementation OWS scores significantly decreased in all 7 pharmacies (from 33.3 to 29.1 overall, p < 0.001) but especially in small pharmacies (from 31.7 to 27.6, p < 0.001). Scores for the physical demand and frustration dimensions were low in both the PSCC and in the 7 pharmacies, while scores for the performance dimension remained high (range, 6.8-8.3). In general, scores for all other measured NASA-TLX dimensions decreased after PSCC implementation, more so at smaller pharmacies. The PSCC staff mean OWS score increased over time (from 26.8 to 28.6, p < 0.0001) but remained near the overall pharmacy average of 29.1. CONCLUSION: Use of the NASA TLX allowed for a direct subjective measurement of workload as perceived by pharmacy and PSCC employees before and after PSCC implementation. Long-term effects of the PSCC on workload should be assessed.

Geographic Mapping of Escherichia coli Susceptibility To Develop a Novel Clinical Decision Support Tool.

Antimicrobial resistance (AMR) varies regionally. This study longitudinally maps Escherichia coli susceptibility leveraging Wisconsin antibiograms (n = 202) collected from 2009, 2013, and 2015 to inform the development of a novel clinical decision support tool. Spatial interpolation methods were tested with E. coli susceptibilities to create geographic AMR visualizations and to estimate susceptibility in areas without AMR data. These visualizations and an interactive mapping tool, the AMR Tracker, provide a proof of concept for empirical antibiotic treatment decisions.

Clostridium difficile infection perceptions and practices: a multicenter qualitative study in South Africa.

Background: Clostridium difficile infection (CDI) is understudied in limited resource settings. In addition, provider awareness of CDI as a prevalent threat is unknown. An assessment of current facilitators and barriers to CDI identification, management, and prevention is needed in limited resource settings to design and evaluate quality improvement strategies to effectively minimize the risk of CDI. Methods: Our study aimed to identify CDI perceptions and practices among healthcare providers in South African secondary hospitals to identify facilitators and barriers to providing quality CDI care. Qualitative interviews (11 physicians, 11 nurses, 4 pharmacists,) and two focus groups (7 nurses, 3 pharmacists) were conducted at three district level hospitals in the Cape Town Metropole. Semi-structured interviews elicited provider perceived facilitators, barriers, and opportunities to improve clinical workflow from patient presentation through CDI (1) Identification, (2) Diagnosis, (3) Treatment, and (4) Prevention. In addition, a summary provider CDI knowledge score was calculated for each interviewee for seven components of CDI and management. Results: Major barriers identified were knowledge gaps in characteristics of C. difficile identification, diagnosis, treatment, and prevention. The median overall CDI knowledge score (scale 0-7) from individual interviews was 3 [interquartile range 0.25, 4.75]. Delays in C. difficile testing workflow were identified. Participants perceived supplies for CDI management and prevention were usually available; however, hand hygiene and use of contact precautions was inconsistent. Conclusions: Our analysis provides a detailed description of the facilitators and barriers to CDI workflow and can be utilized to design quality improvement interventions among limited resource settings.

Epidemiology and outcomes of Clostridium difficile infection among hospitalised patients: results of a multicentre retrospective study in South Africa.

INTRODUCTION: Limited data exist on Clostridium difficile infection (CDI) in low-resource settings and settings with high prevalence of HIV. We aimed to determine baseline CDI patient characteristics and management and their contribution to mortality. METHODS: We reviewed adult patients hospitalised with diarrhoea and a C. difficile test result in 2015 from four public district hospitals in the Western Cape, South Africa. The primary outcome measures were risk factors for mortality. Secondary outcomes were C. difficile risk factors (positive vs negative) and CDI treatment. RESULTS: Charts of patients with diarrhoea tested for C. difficile (n=250; 112 C. difficile positive, 138 C. difficile negative) were reviewed. The study population included more women (65%). C. difficile-positive patients were older (46.5 vs 40.7 years, p<0.01). All-cause mortality was more common in the C. difficile-positive group (29% vs 8%, p<0.0001; HR 2.0, 95% CI 1.1 to 3.6). Tuberculosis (C. difficile positive 54% vs C. difficile negative 32%, p<0.001), 30-day prior antibiotic exposure (C. difficile positive 83% vs C. difficile negative 46%, p<0.001) and prior hospitalisation (C. difficile positive 55% vs C. difficile negative 22%, p<0.001) were also more common in the C. difficile-positive group. C. difficile positive test result (OR 4.7, 95% CI 2.0 to 11.2; p<0.001), male gender (OR 2.8, 95% CI 1.1 to 7.2; p=0.031) and tuberculosis (OR 2.3, 95% CI 1.0 to 5.0; p=0.038) were independently associated with mortality. Of patients starting treatment, metronidazole was the most common antimicrobial therapy initiated (70%, n=78); 32 C. difficile-positive (29%) patients were not treated. CONCLUSION: Patients testing positive for C. difficile are at high risk of mortality at public district hospitals in South Africa. Tuberculosis should be considered an additional risk factor for CDI in populations with high tuberculosis and HIV comorbidity. Interventions for CDI prevention and management are urgently needed.