21 research outputs found
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The association of patient complexities with antibiotic ordering
BackgroundAntibiotic treatment decisions for medically complex patients are complicated, as the risk of undertreatment may be severe, whereas overtreatment may be associated with adverse effects and the emergence of antibiotic resistant pathogens.ObjectiveTo determine the influence of patient complexities on providers' decisions to prescribe antibiotics in 3 common hospital-based clinical vignettes.DesignA physician survey.SettingThree urban medical centers in Los Angeles County, California.ParticipantsHospital-based physicians.MeasurementsPhysicians were presented 3 clinical vignettes, with variations by patient age, comorbidity burden, functional status, and follow-up, and asked to choose the best antibiotic regimen. We described the association of additional patient complexity on the proportion of guideline-adherent antibiotic choices.ResultsIn the survey, 28% to 49% of physicians recommended antibiotics that were inconsistent with national guidelines. This percentage increased to 48% to 63% for medically complex patients, defined as those with either older age, high medical comorbidity burden, poor functional status, or limited follow-up after hospital discharge (P < 0.01).ConclusionsIn 3 vignettes depicting common clinical scenarios among hospitalized adults, inappropriate antibiotic use was prevalent and occurred more often for patients with medical complexities. Treatment guidelines should consider addressing medically complex patients in the context of infection management
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Assessing past versus present severe acute respiratory coronavirus virus 2 (SARS-CoV-2) infection: A survey of criteria for discontinuing precautions in asymptomatic patients testing positive on admission.
Infection prevention program leaders report frequent use of criteria to distinguish recently recovered coronavirus disease 2019 (COVID-19) cases from actively infectious cases when incidentally positive asymptomatic patients were identified on routine severe acute respiratory coronavirus virus 2 (SARS-CoV-2) polymerase chain reaction (PCR) testing. Guidance on appropriate interpretation of high-sensitivity molecular tests can prevent harm from unnecessary precautions that delay admission and impede medical care
Contributions of the Regional Emerging Special Pathogen Treatment Centers to the US COVID-19 Pandemic Response.
The National Emerging Special Pathogens Training and Education Center (NETEC) was established in 2015 to improve the capabilities of healthcare facilities to provide safe and effective care to patients with Ebola and other special pathogens in the United States. Through NETEC, a collaborative network of 10 Regional Emerging Special Pathogen Treatment Centers (RESPTCs) undertook readiness activities that included potential respiratory pathogens. These preparations, which took place before the COVID-19 pandemic, established a foundation of readiness that enabled RESPTCs to play a pivotal role in the US COVID-19 pandemic response. As initial COVID-19 cases were detected in the United States, RESPTCs provided essential isolation capacity, supplies, and subject matter expertise that allowed for additional time for healthcare systems to prepare. Through the Special Pathogen Research Network, RESPTCs rapidly enrolled patients into early clinical trials. During periods of high community transmission, RESPTCs provided educational, clinical, and logistical support to a wide range of healthcare and nonhealthcare settings. In this article, we describe how NETEC and the RESPTC network leveraged this foundation of special pathogen readiness to strengthen the national healthcare system\u27s response to the COVID-19 pandemic. NETEC and the RESPTC network have proven to be an effective model that can support the national response to future emerging special pathogens
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Evaluation of the National Healthcare Safety Network standardized infection ratio risk adjustment for healthcare-facility-onset Clostridioides difficile infection in intensive care, oncology, and hematopoietic cell transplant units in general acute-care hospitals.
ObjectiveTo evaluate the National Health Safety Network (NHSN) hospital-onset Clostridioides difficile infection (HO-CDI) standardized infection ratio (SIR) risk adjustment for general acute-care hospitals with large numbers of intensive care unit (ICU), oncology unit, and hematopoietic cell transplant (HCT) patients.DesignRetrospective cohort study.SettingEight tertiary-care referral general hospitals in California.MethodsWe used FY 2016 data and the published 2015 rebaseline NHSN HO-CDI SIR. We compared facility-wide inpatient HO-CDI events and SIRs, with and without ICU data, oncology and/or HCT unit data, and ICU bed adjustment.ResultsFor these hospitals, the median unmodified HO-CDI SIR was 1.24 (interquartile range [IQR], 1.15-1.34); 7 hospitals qualified for the highest ICU bed adjustment; 1 hospital received the second highest ICU bed adjustment; and all had oncology-HCT units with no additional adjustment per the NHSN. Removal of ICU data and the ICU bed adjustment decreased HO-CDI events (median, -25%; IQR, -20% to -29%) but increased the SIR at all hospitals (median, 104%; IQR, 90%-105%). Removal of oncology-HCT unit data decreased HO-CDI events (median, -15%; IQR, -14% to -21%) and decreased the SIR at all hospitals (median, -8%; IQR, -4% to -11%).ConclusionsFor tertiary-care referral hospitals with specialized ICUs and a large number of ICU beds, the ICU bed adjustor functions as a global adjustment in the SIR calculation, accounting for the increased complexity of patients in ICUs and non-ICUs at these facilities. However, the SIR decrease with removal of oncology and HCT unit data, even with the ICU bed adjustment, suggests that an additional adjustment should be considered for oncology and HCT units within general hospitals, perhaps similar to what is done for ICU beds in the current SIR
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Evaluation of the National Healthcare Safety Network standardized infection ratio risk adjustment for healthcare-facility-onset Clostridioides difficile infection in intensive care, oncology, and hematopoietic cell transplant units in general acute-care hospitals.
ObjectiveTo evaluate the National Health Safety Network (NHSN) hospital-onset Clostridioides difficile infection (HO-CDI) standardized infection ratio (SIR) risk adjustment for general acute-care hospitals with large numbers of intensive care unit (ICU), oncology unit, and hematopoietic cell transplant (HCT) patients.DesignRetrospective cohort study.SettingEight tertiary-care referral general hospitals in California.MethodsWe used FY 2016 data and the published 2015 rebaseline NHSN HO-CDI SIR. We compared facility-wide inpatient HO-CDI events and SIRs, with and without ICU data, oncology and/or HCT unit data, and ICU bed adjustment.ResultsFor these hospitals, the median unmodified HO-CDI SIR was 1.24 (interquartile range [IQR], 1.15-1.34); 7 hospitals qualified for the highest ICU bed adjustment; 1 hospital received the second highest ICU bed adjustment; and all had oncology-HCT units with no additional adjustment per the NHSN. Removal of ICU data and the ICU bed adjustment decreased HO-CDI events (median, -25%; IQR, -20% to -29%) but increased the SIR at all hospitals (median, 104%; IQR, 90%-105%). Removal of oncology-HCT unit data decreased HO-CDI events (median, -15%; IQR, -14% to -21%) and decreased the SIR at all hospitals (median, -8%; IQR, -4% to -11%).ConclusionsFor tertiary-care referral hospitals with specialized ICUs and a large number of ICU beds, the ICU bed adjustor functions as a global adjustment in the SIR calculation, accounting for the increased complexity of patients in ICUs and non-ICUs at these facilities. However, the SIR decrease with removal of oncology and HCT unit data, even with the ICU bed adjustment, suggests that an additional adjustment should be considered for oncology and HCT units within general hospitals, perhaps similar to what is done for ICU beds in the current SIR
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Pre-existing traits associated with Covid-19 illness severity
ImportanceCertain individuals, when infected by SARS-CoV-2, tend to develop the more severe forms of Covid-19 illness for reasons that remain unclear.ObjectiveTo determine the demographic and clinical characteristics associated with increased severity of Covid-19 infection.DesignRetrospective observational study. We curated data from the electronic health record, and used multivariable logistic regression to examine the association of pre-existing traits with a Covid-19 illness severity defined by level of required care: need for hospital admission, need for intensive care, and need for intubation.SettingA large, multihospital healthcare system in Southern California.ParticipantsAll patients with confirmed Covid-19 infection (N = 442).ResultsOf all patients studied, 48% required hospitalization, 17% required intensive care, and 12% required intubation. In multivariable-adjusted analyses, patients requiring a higher levels of care were more likely to be older (OR 1.5 per 10 years, P<0.001), male (OR 2.0, P = 0.001), African American (OR 2.1, P = 0.011), obese (OR 2.0, P = 0.021), with diabetes mellitus (OR 1.8, P = 0.037), and with a higher comorbidity index (OR 1.8 per SD, P<0.001). Several clinical associations were more pronounced in younger compared to older patients (Pinteraction<0.05). Of all hospitalized patients, males required higher levels of care (OR 2.5, P = 0.003) irrespective of age, race, or morbidity profile.Conclusions and relevanceIn our healthcare system, greater Covid-19 illness severity is seen in patients who are older, male, African American, obese, with diabetes, and with greater overall comorbidity burden. Certain comorbidities paradoxically augment risk to a greater extent in younger patients. In hospitalized patients, male sex is the main determinant of needing more intensive care. Further investigation is needed to understand the mechanisms underlying these findings