Background The profound changes wrought by COVID-19 on routine hospital operations may have influenced performance on hospital measures, including healthcare-associated infections (HAIs). We aimed to evaluate the association between COVID-19 surges and HAI and cluster rates. Methods In 148 HCA Healthcare-affiliated hospitals, 3/1/2020-9/30/2020, and a subset of hospitals with microbiology and cluster data through 12/31/2020, we evaluated the association between COVID-19 surges and HAIs, hospital-onset pathogens, and cluster rates using negative binomial mixed models. To account for local variation in COVID-19 pandemic surge timing, we included the number of discharges with a laboratory-confirmed COVID-19 diagnosis per staffed bed per month. Results Central line-associated blood stream infections (CLABSI), catheter-associated urinary tract infections (CAUTI), and methicillin-resistant Staphylococcus aureus (MRSA) bacteremia increased as COVID-19 burden increased. There were 60% (95% CI, 23-108%) more CLABSI, 43% (95% CI, 8-90%) more CAUTI, and 44% (95% CI, 10-88%) more cases of MRSA bacteremia than expected over 7 months based on predicted HAIs had there not been COVID-19 cases. Clostridioides difficile infection was not significantly associated with COVID-19 burden. Microbiology data from 81 of the hospitals corroborated the findings. Notably, rates of hospital-onset bloodstream infections and multidrug resistant organisms, including MRSA, vancomycin-resistant enterococcus and Gram-negative organisms were each significantly associated with COVID-19 surges. Finally, clusters of hospital-onset pathogens increased as the COVID-19 burden increased. Conclusion COVID-19 surges adversely impact HAI rates and clusters of infections within hospitals, emphasizing the need for balancing COVID-related demands with routine hospital infection prevention.
Background The profound changes wrought by COVID-19 on routine hospital operations may have influenced performance on hospital measures, including healthcare-associated infections (HAIs). Objective Evaluate the association between COVID-19 surges and HAI or cluster rates Methods Design: Prospective cohort study Setting 148 HCA Healthcare-affiliated hospitals, 3/1/2020-9/30/2020, and a subset of hospitals with microbiology and cluster data through 12/31/2020 Patients All inpatients Measurements We evaluated the association between COVID-19 surges and HAIs, hospital-onset pathogens, and cluster rates using negative binomial mixed models. To account for local variation in COVID-19 pandemic surge timing, we included the number of discharges with a laboratory-confirmed COVID-19 diagnosis per staffed bed per month at each hospital. Results Central line-associated blood stream infections (CLABSI), catheter-associated urinary tract infections (CAUTI), and methicillin-resistant Staphylococcus aureus (MRSA) bacteremia increased as COVID-19 burden increased (P ≤ 0.001 for all), with 60% (95% CI, 23 to 108%) more CLABSI, 43% (95% CI, 8 to 90%) more CAUTI, and 44% (95% CI, 10 to 88%) more cases of MRSA bacteremia than expected over 7 months based on predicted HAIs had there not been COVID-19 cases. Clostridioides difficile infection (CDI) was not significantly associated with COVID-19 burden. Microbiology data from 81 of the hospitals corroborated the findings. Notably, rates of hospital-onset bloodstream infections and multidrug resistant organisms, including MRSA, vancomycin-resistant enterococcus and Gram-negative organisms were each significantly associated with COVID-19 surges (P < 0.05 for all). Finally, clusters of hospital-onset pathogens increased as the COVID-19 burden increased (P = 0.02). Limitations Variations in surveillance and reporting may affect HAI data. Table 1. Effect of an increase in number of COVID-19 discharges on HAIs and hospital-onset pathogens Figure 1. Predicted mean HAI rates as COVID-19 discharges increase Predicted mean HAI rate by increasing monthly COVID-19 discharges. Panel a. CLABSI, Panel b, CAUTI Panel c. MRSA Bacteremia, Panel d. CDI. Data are stratified by small, medium and large hospitals. Figure 2. Monthly comparison of COVID discharges to clusters COVID-19 discharges and the number of clusters of hospital-onset pathogens are correlated throughout the pandemic. Conclusion COVID-19 surges adversely impact HAI rates and clusters of infections within hospitals, emphasizing the need for balancing COVID-related demands with routine hospital infection prevention. Disclosures Kenneth Sands, MD, MPH, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Susan S. Huang, MD, MPH, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Stryker (Sage) (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Xttrium (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products) Ken Kleinman, PhD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic products)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic products) Edward Septimus, MD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic products)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic products) Eunice J. Blanchard, MSN RN, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Russell Poland, PhD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Micaela H. Coady, MS, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Deborah S. Yokoe, MD, MPH, Nothing to disclose Julia Moody, MS, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Richard Platt, MD, MSc, Medline (Research Grant or Support, Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Jonathan B. Perlin, MD, PhD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)
The operation note is the single most important document in surgical practice. Ninety one operation notes were assessed on their adherence to guidelines, as well as their legibility and ability to inform postoperative care; as judged by five different healthcare professionals. Results showed a deficiency in essential information and poor legibility overall. Re-audit of 103 operation notes after intervention showed an improvement in nearly all criteria measured. The results indicate that education about current guidelines and an increase in word processing of operation notes improves quality of documentation, and therefore of postoperative care.
Objective: To assess the utility of an automated, statistically-based outbreak detection system to identify clusters of hospital-acquired microorganisms. Design: Multicenter retrospective cohort study. Setting: The study included 43 hospitals using a common infection prevention surveillance system. Methods: A space–time permutation scan statistic was applied to hospital microbiology, admission, discharge, and transfer data to identify clustering of microorganisms within hospital locations and services. Infection preventionists were asked to rate the importance of each cluster. A convenience sample of 10 hospitals also provided information about clusters previously identified through their usual surveillance methods. Results: We identified 230 clusters in 43 hospitals involving Gram-positive and -negative bacteria and fungi. Half of the clusters progressed after initial detection, suggesting that early detection could trigger interventions to curtail further spread. Infection preventionists reported that they would have wanted to be alerted about 81% of these clusters. Factors associated with clusters judged to be moderately or highly concerning included high statistical significance, large size, and clusters involving Clostridioides difficile or multidrug-resistant organisms. Based on comparison data provided by the convenience sample of hospitals, only 9 (18%) of 51 clusters detected by usual surveillance met statistical significance, and of the 70 clusters not previously detected, 58 (83%) involved organisms not routinely targeted by the hospitals’ surveillance programs. All infection prevention programs felt that an automated outbreak detection tool would improve their ability to detect outbreaks and streamline their work. Conclusions: Automated, statistically-based outbreak detection can increase the consistency, scope, and comprehensiveness of detecting hospital-associated transmission.
This study was conducted with the primary aim to distinguish patients with a true stroke versus a stroke mimic based on clinical features and imaging. We conducted a retrospective case–control study on 116 adult patients who received alteplase (tPA) to treat acute stroke at our hospital. We further analyzed 79 patients with a normal computed tomography angiography (CTA). Based on their magnetic resonance imaging (MRI) of the brain, they were divided into cases (stroke mimics) and controls (true strokes). Data were collected retrospectively by reviewing individual medical charts on the electronic medical record (EMR), including age, gender, history of stroke, seizure, hypertension, diabetes, atrial fibrillation, hyperlipidemia, presenting NIH Stroke Scale/Score, hemorrhagic conversion, history of migraine, history of depression, sidedness of symptoms and aphasia. Data were categorized to separate those who were later diagnosed to be stroke mimics by being-postictal, encephalopathic, in acute migraine, suffered post-stroke recrudescence (PSR) due to metabolic insult, or had conversion disorder when symptoms could not be attributed to any medical condition or mental illness. Of the 79 study subjects, 48 (60%) were stroke mimics. The mean age of the cohort was 68.67 years, and 46.8% of the study subjects were females. Based on the multivariate logistic regression analysis, factors associated with being a stroke mimic were older age, history of migraine, and a history of prior stroke. In conclusion, increased attention to history and clinical examination as the first step can aid in the proper diagnosis of strokes versus stroke mimics. Identifying stroke mimics early could help expedite hospital workup and prevent inadvertent investigations, reducing hospital occupancy during the ongoing COVID-19 pandemic. We could potentially avoid the administration of tPA to such patients, reducing both the cost and adverse effects of it. Every stroke can cause neurological deficits, but every deficit need not be a stroke.
57 Background: In July 2014, following judicial review, the Liverpool Care Pathway for Dying Patients was withdrawn from the UK. An individualised approach to care for dying patients was advised, laid out in “One chance to get it right”. To support this, a symptom observation chart was developed at BSUH, a UK teaching hospital with cancer centre. At the point where a patient is diagnosed as dying, this innovative tool replaces vital signs assessment tools and facilitates regular and rigorous assessment of symptoms. Additionally, it aims to improve communication between healthcare professionals (HCPs), by showing trends in symptoms over time, and to trigger urgent physician review if optimal comfort is not achieved. It has scoring and escalation prompts, similar to early warning score charts, using a red-amber-green system. Methods: 8 months after introduction, a self-completed questionnaire was distributed to HCPs. Questions related to demographic data, opinion on the chart using a 4-point Likert scale and a qualitative component. Results: 135 adequately completed questionnaires (of 150) were returned by ward nurses (61%), physicians (30%), nursing assistants (7%) and palliative care specialist nurses (3%). The majority "agreed" or “strongly agreed” that the chart was user-friendly (97%); not time consuming (98%); facilitated communication between staff of the multidisciplinary team (87%); prompted earlier intervention from physicians (83%); was useful to indicate poorly controlled symptoms (96%); had improved the symptom assessment of dying patients (91%); and had contributed to improvements in the overall care of dying patients (87%). Additionally, 86% of nurses felt the chart helped them know when to request an urgent physician review to optimise comfort. Only 51% felt they had received enough training in using the chart. These findings were also reflected in free text responses. Conclusions: The vast majority of HCPs found the chart easy to use and felt it improved overall care of dying patients. Therefore, the chart may be a valuable addition to Comfort Care Order Sets. Prospective research is warranted to further assess the chart. The chart will be visually presented. It may be adapted and reproduced with permission.
Background Up to 40% of hospitalized patients receive unnecessary or inappropriately broad antibiotics despite a low risk of multidrug-resistant organism (MDRO) infection. Empiric standard spectrum antibiotic use would reduce extended-spectrum (ES) antibiotic exposure and future resistance. We evaluated whether computerized prescriber order entry prompts providing patient-specific MDRO risk estimates could reduce ES antibiotic use compared to routine stewardship practices in patients hospitalized with pneumonia. Methods This 59 hospital cluster-randomized trial compared: 1) INSPIRE prompts providing patient-specific MDRO pneumonia risk estimates at order entry and recommended standard spectrum antibiotics for risk < 10% versus 2) routine stewardship practices. Prompt used an absolute MDRO risk algorithm based on a 140 hospital data set. Trial population included adults treated with antibiotics for pneumonia in ED or non-ICU wards in first 3 days of admission (empiric days); prompt was triggered if ES antibiotics were ordered. Prescribers received feedback on prompt response. Trial periods: 18-month Baseline (Apr 2017–Sept 2018); 6-month Phase-in (Oct 2018–Mar 2019); 15-month Intervention (Apr 2019 – June 2020). Primary outcome was ES antibiotic days of therapy (ES-DOT) per empiric day; secondary outcomes were a) vancomycin and b) anti-pseudomonal DOT per empiric day. Unadjusted, as-randomized analyses used generalized linear mixed effects models to assess differences in ES-DOT rates between the intervention vs baseline period across arms (difference in differences), while clustering by patient and hospital. Results We randomized 59 hospitals in 12 states, with 59,897 and 51,486 non-ICU pneumonia admissions in baseline and intervention periods, respectively. Intervention group had a 33% reduction in ES-DOT compared to routine care. Vancomycin and anti-pseudomonal DOT were similarly reduced in the intervention group by 27% and 33%, respectively (Table). Conclusion INSPIRE order entry prompts providing real-time, patient-specific MDRO risk estimates with recommendation to use standard spectrum antibiotics in low risk patients significantly reduced empiric ES prescribing in adults admitted with pneumonia. Disclosures Shruti K. Gohil, MD, MPH, Medline (Other Financial or Material Support, Co-Investigator in studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Molnycke (Other Financial or Material Support, Co-Investigator in studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Stryker (Sage) (Other Financial or Material Support, Co-Investigator in studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products) Edward Septimus, MD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic products)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic products) Ken Kleinman, PhD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic products)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic products) Lauren Heim, MPH, Medline (Other Financial or Material Support, Conducted clinical trials and studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Stryker (Sage) (Other Financial or Material Support, Conducted clinical trials and studies in which participating hospitals and nursing homes received contributed antiseptic product)Xttrium (Other Financial or Material Support, Conducted clinical trials and studies in which participating hospitals and nursing homes received contributed antiseptic product) Syma Rashid, MD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Stryker (Sage) (Other Financial or Material Support, Conducted clinical trials and studies in which participating hospitals and nursing homes received contributed antiseptic product)Xttrium (Other Financial or Material Support, Conducted clinical trials and studies in which participating hospitals and nursing homes received contributed antiseptic product) Taliser R. Avery, MS, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Kenneth Sands, MD, MPH, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Julia Moody, MS, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Micaela H. Coady, MS, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Kimberly N. Smith, MBA, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Brandon Carver, BA, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Caren Spencer-Smith, MS, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Russell Poland, PhD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Jason Hickok, MBA, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Arjun Srinivasan, MD, Nothing to disclose John A. Jernigan, MD, MS, Nothing to disclose Jonathan B. Perlin, MD, PhD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Richard Platt, MD, MSc, Medline (Research Grant or Support, Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Susan S. Huang, MD, MPH, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Stryker (Sage) (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Xttrium (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)
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