Predicting Direct-Specimen SARS-CoV-2 Assay Performance Using Residual Patient Samples.

BACKGROUND: Diagnostic sensitivities of point-of-care SARS-CoV-2 assays depend on specimen type and population-specific viral loads. Evaluation of these assays require "direct" specimens from paired-swab studies rather than more accessible residual specimens in viral transport media (VTM). METHODS: Residual VTM and limit-of-detection studies were conducted on Abbott ID NOW™ COVID-19, Quidel Sofia 2™ SARS Antigen FIA, and DiaSorin Simplexa™ COVID-19 Direct assays, with cycle threshold (CT) adjustments to approximate direct-specimen testing based on gene-target doubling each PCR cycle. Logistic regression was used to model assay performance by specimen CT. These models were applied to CT distributions of symptomatic and asymptomatic populations presenting to emergency services to predict the percentage of specimens that would be detected by each assay. A 96-sample paired-swab study was conducted to confirm model results. RESULTS: When using direct nasopharyngeal samples and fit with either VTM or limit-of-detection data, percent positivities for ID NOW (symptomatic 94.9%/97.4%; asymptomatic 88.4.0%/89.6%) and Simplexa (symptomatic 97.8%/97.2%; asymptomatic 91.1%/90.8%) were predicted to be similar. Likewise, percent positivities for ID NOW with direct nasal specimens (symptomatic 77.8%; asymptomatic 64.5%) and, fit with VTM data, Sofia 2 with direct nasopharyngeal specimens (symptomatic 76.6%, asymptomatic 60.3%) were similar. The paired-swab study comparing direct nasopharyngeal specimens on ID NOW and nasopharyngeal VTM specimens on Simplexa showed 99% concordance. CONCLUSIONS: Assay performance can be modeled as dependent on viral load, fit using laboratory bench study results, and adjusted to account for direct-specimen testing. When using nasopharyngeal specimens, direct testing on Abbott ID NOW and VTM testing on DiaSorin Simplexa have similar performance.

Best Practices for Education and Training of Resuscitation Teams for In-Hospital Cardiac Arrest.

BACKGROUND: Survival outcomes following in-hospital cardiac arrest vary significantly across hospitals. Research suggests clinician education and training may play a role. We sought to identify best practices related to the education and training of resuscitation teams. METHODS: We conducted a descriptive qualitative analysis of semistructured interview data obtained from in-depth site visits conducted from 2016 to 2017 at 9 diverse hospitals within the American Heart Association "Get With The Guidelines" registry, selected based on in-hospital cardiac arrest survival performance (5 top-, 1 middle-, 3 low-performing). We assessed coded data related to education and training including systems learning, informal feedback and debrief, and formal learning through advanced cardiopulmonary life support and mock codes. Thematic analysis was used to identify best practices. RESULTS: In total, 129 interviews were conducted with a variety of hospital staff including nurses, chaplains, security guards, respiratory therapists, physicians, pharmacists, and administrators, yielding 78 hours and 29 minutes of interview time. Four themes related to training and education were identified: engagement, clear communication, consistency, and responsive leadership. Top-performing hospitals encouraged employee engagement with creative marketing of new programs and prioritizing hands-on learning over passive didactics. Clear communication was accomplished with debriefing, structured institutional review, and continual, frequent education for departments. Consistency was a cornerstone to culture change and was achieved with uniform policies for simulation practice as well as reinforced, routine practice (weekly, monthly, quarterly). Finally, top-performing hospitals had responsive leadership teams across multiple disciplines (nursing, respiratory therapy, pharmacy and medicine), who listened and adapted programs to fit the needs of their staff. CONCLUSIONS: Among top-performing hospitals excelling in in-hospital cardiac arrest survival, we identified core elements for education and training of resuscitation teams. Developing tools to expand these areas for hospitals may improve in-hospital cardiac arrest outcomes.

Emergency department provider in triage: assessing site-specific rationale, operational feasibility, and financial impact.

Emergency department (ED) crowding is recognized as a critical threat to patient safety, while sub-optimal ED patient flow also contributes to reduced patient satisfaction and efficiency of care. Provider in triage (PIT) programs-which typically involve, at a minimum, a physician or advanced practice provider conducting an initial screening exam and potentially initiating treatment and diagnostic testing at the time of triage-are frequently endorsed as a mechanism to reduce ED length of stay (LOS) and therefore mitigate crowding, improve patient satisfaction, and improve ED operational and financial performance. However, the peer-reviewed evidence regarding the impact of PIT programs on measures including ED LOS, wait times, and costs (as variously defined) is mixed. Mechanistically, PIT programs exert their effects by initiating diagnostic work-ups earlier and, sometimes, by equipping triage providers to directly disposition patients. However, depending on local contextual factors-including the co-existence of other front-end interventions and delays in ED throughput not addressed by PIT-we demonstrate how these features may or may not ultimately translate into reduced ED LOS in different settings. Consequently, site-specific analysis of the root causes of excessive ED LOS, along with mechanistic assessment of potential countermeasures, is essential for appropriate deployment and successful design of PIT programs at individual EDs. Additional motivations for implementing PIT programs may include their potential to enhance patient safety, patient satisfaction, and team dynamics. In this conceptual article, we address a gap in the literature by demonstrating the mechanisms underlying PIT program results and providing a framework for ED decision-makers to assess the local rationale for, operational feasibility of, and financial impact of PIT programs.

Predicting Intensive Care Transfers and Other Unforeseen Events: Analytic Model Validation Study and Comparison to Existing Methods.

BACKGROUND: COVID-19 has led to an unprecedented strain on health care facilities across the United States. Accurately identifying patients at an increased risk of deterioration may help hospitals manage their resources while improving the quality of patient care. Here, we present the results of an analytical model, Predicting Intensive Care Transfers and Other Unforeseen Events (PICTURE), to identify patients at high risk for imminent intensive care unit transfer, respiratory failure, or death, with the intention to improve the prediction of deterioration due to COVID-19. OBJECTIVE: This study aims to validate the PICTURE model's ability to predict unexpected deterioration in general ward and COVID-19 patients, and to compare its performance with the Epic Deterioration Index (EDI), an existing model that has recently been assessed for use in patients with COVID-19. METHODS: The PICTURE model was trained and validated on a cohort of hospitalized non-COVID-19 patients using electronic health record data from 2014 to 2018. It was then applied to two holdout test sets: non-COVID-19 patients from 2019 and patients testing positive for COVID-19 in 2020. PICTURE results were aligned to EDI and NEWS scores for head-to-head comparison via area under the receiver operating characteristic curve (AUROC) and area under the precision-recall curve. We compared the models' ability to predict an adverse event (defined as intensive care unit transfer, mechanical ventilation use, or death). Shapley values were used to provide explanations for PICTURE predictions. RESULTS: In non-COVID-19 general ward patients, PICTURE achieved an AUROC of 0.819 (95% CI 0.805-0.834) per observation, compared to the EDI's AUROC of 0.763 (95% CI 0.746-0.781; n=21,740; P<.001). In patients testing positive for COVID-19, PICTURE again outperformed the EDI with an AUROC of 0.849 (95% CI 0.820-0.878) compared to the EDI's AUROC of 0.803 (95% CI 0.772-0.838; n=607; P<.001). The most important variables influencing PICTURE predictions in the COVID-19 cohort were a rapid respiratory rate, a high level of oxygen support, low oxygen saturation, and impaired mental status (Glasgow Coma Scale). CONCLUSIONS: The PICTURE model is more accurate in predicting adverse patient outcomes for both general ward patients and COVID-19 positive patients in our cohorts compared to the EDI. The ability to consistently anticipate these events may be especially valuable when considering potential incipient waves of COVID-19 infections. The generalizability of the model will require testing in other health care systems for validation.

Assessment of Testing and Treatment of Asymptomatic Bacteriuria Initiated in the Emergency Department.

BACKGROUND: Reducing antibiotic use in patients with asymptomatic bacteriuria (ASB) has been inpatient focused. However, testing and treatment is often started in the emergency department (ED). Thus, for hospitalized patients with ASB, we sought to identify patterns of testing and treatment initiated by emergency medicine (EM) clinicians and the association of treatment with outcomes. METHODS: We conducted a 43-hospital, cohort study of adults admitted through the ED with ASB (February 2018-February 2020). Using generalized estimating equation models, we assessed for (1) factors associated with antibiotic treatment by EM clinicians and, after inverse probability of treatment weighting, (2) the effect of treatment on outcomes. RESULTS: Of 2461 patients with ASB, 74.4% (N = 1830) received antibiotics. The EM clinicians ordered urine cultures in 80.0% (N = 1970) of patients and initiated treatment in 68.5% (1253 of 1830). Predictors of EM clinician treatment of ASB versus no treatment included dementia, spinal cord injury, incontinence, urinary catheter, altered mental status, leukocytosis, and abnormal urinalysis. Once initiated by EM clinicians, 79% (993 of 1253) of patients remained on antibiotics for at least 3 days. Antibiotic treatment was associated with a longer length of hospitalization (mean 5.1 vs 4.2 days; relative risk = 1.16; 95% confidence interval, 1.08-1.23) and Clostridioides difficile infection (CDI) (0.9% [N = 11] vs 0% [N = 0]; P = .02). CONCLUSIONS: Among hospitalized patients ultimately diagnosed with ASB, EM clinicians commonly initiated testing and treatment; most antibiotics were continued by inpatient clinicians. Antibiotic treatment was not associated with improved outcomes, whereas it was associated with prolonged hospitalization and CDI. For best impact, stewardship interventions must expand to the ED.

Demonstrating the consequences of learning missingness patterns in early warning systems for preventative health care: A novel simulation and solution.

When using tree-based methods to develop predictive analytics and early warning systems for preventive healthcare, it is important to use an appropriate imputation method to prevent learning the missingness pattern. To demonstrate this, we developed a novel simulation that generated synthetic electronic health record data using a variational autoencoder with a custom loss function, which took into account the high missing rate of electronic health data. We showed that when tree-based methods learn missingness patterns (correlated with adverse events) in electronic health record data, this leads to decreased performance if the system is used in a new setting that has different missingness patterns. Performance is worst in this scenario when the missing rate between those with and without an adverse event is the greatest. We found that randomized and Bayesian regression imputation methods mitigate the issue of learning the missingness pattern for tree-based methods. We used this information to build a novel early warning system for predicting patient deterioration in general wards and telemetry units: PICTURE (Predicting Intensive Care Transfers and other UnfoReseen Events). To develop, tune, and test PICTURE, we used labs and vital signs from electronic health records of adult patients over four years (n = 133,089 encounters). We analyzed primary outcomes of unplanned intensive care unit transfer, emergency vasoactive medication administration, cardiac arrest, and death. We compared PICTURE with existing early warning systems and logistic regression at multiple levels of granularity. When analyzing PICTURE on the testing set using all observations within a hospital encounter (event rate = 3.4%), PICTURE had an area under the receiver operating characteristic curve (AUROC) of 0.83 and an adjusted (event rate = 4%) area under the precision-recall curve (AUPR) of 0.27, while the next best tested method-regularized logistic regression-had an AUROC of 0.80 and an adjusted AUPR of 0.22. To ensure system interpretability, we applied a state-of-the-art prediction explainer that provided a ranked list of features contributing most to the prediction. Though it is currently difficult to compare machine learning-based early warning systems, a rudimentary comparison with published scores demonstrated that PICTURE is on par with state-of-the-art machine learning systems. To facilitate more robust comparisons and development of early warning systems in the future, we have released our variational autoencoder's code and weights so researchers can (a) test their models on data similar to our institution and (b) make their own synthetic datasets.

Comparing inpatient versus emergency department clinician perceptions of personal protective equipment for different isolation precautions.

Adherence to isolation precaution practices, including use of personal protective equipment (PPE), remains a challenge in most hospitals. We surveyed inpatient and emergency department clinicians about their experiences and opinions of various isolation policies, specifically those related to wearing PPE. Our findings show several differences between inpatient and emergency department clinicians involving perceptions related to safety, and the difficulty associated with using PPE for certain types of organisms.

Nursing roles for in-hospital cardiac arrest response: higher versus lower performing hospitals.

BACKGROUND: Good outcomes for in-hospital cardiac arrest (IHCA) depend on a skilled resuscitation team, prompt initiation of high-quality cardiopulmonary resuscitation and defibrillation, and organisational structures to support IHCA response. We examined the role of nurses in resuscitation, contrasting higher versus lower performing hospitals in IHCA survival. METHODS: We conducted a descriptive qualitative study at nine hospitals in the American Heart Association's Get With The Guidelines-Resuscitation registry, purposefully sampling hospitals that varied in geography, academic status, and risk-standardised IHCA survival. We conducted 158 semistructured interviews with nurses, physicians, respiratory therapists, pharmacists, quality improvement staff, and administrators. Qualitative thematic text analysis followed by type-building text analysis identified distinct nursing roles in IHCA care and support for roles. RESULTS: Nurses played three major roles in IHCA response: bedside first responder, resuscitation team member, and clinical or administrative leader. We found distinctions between higher and lower performing hospitals in support for nurses. Higher performing hospitals emphasised training and competency of nurses at all levels; provided organisational flexibility and responsiveness with nursing roles; and empowered nurses to operate at a higher scope of clinical practice (eg, bedside defibrillation). Higher performing hospitals promoted nurses as leaders-administrators supporting nurses in resuscitation care at the institution, resuscitation team leaders during resuscitation and clinical champions for resuscitation care. Lower performing hospitals had more restrictive nurse roles with less emphasis on systematically identifying improvement needs. CONCLUSION: Hospitals that excelled in IHCA survival emphasised mentoring and empowering front-line nurses and ensured clinical competency and adequate nursing training for IHCA care. Though not proof of causation, nurses appear to be critical to effective IHCA response, and how to support their role to optimise outcomes warrants further investigation.

Assessment of Rapid Response Teams at Top-Performing Hospitals for In-Hospital Cardiac Arrest.

IMPORTANCE: Rapid response teams (RRTs) are foundational to hospital response to deteriorating conditions of patients. However, little is known about differences in RRT organization and function across top-performing and non-top-performing hospitals for in-hospital cardiac arrest (IHCA) care. OBJECTIVE: To evaluate differences in design and implementation of RRTs at top-performing and non-top-performing sites for survival of IHCA, which is known to be associated with hospital performance on IHCA incidence. DESIGN, SETTING, AND PARTICIPANTS: A qualitative analysis was performed of data from semistructured interviews of 158 hospital staff members (nurses, physicians, administrators, and staff) during site visits to 9 hospitals participating in the Get With The Guidelines-Resuscitation program and consistently ranked in the top, middle, and bottom quartiles for IHCA survival during 2012-2014. Site visits were conducted from April 19, 2016, to July 27, 2017. Data analysis was completed in January 2019. MAIN OUTCOMES AND MEASURES: Semistructured in-depth interviews were performed and thematic analysis was conducted on strategies for IHCA prevention, including RRT roles and responsibilities. RESULTS: Of the 158 participants, 72 were nurses (45.6%), 27 physicians (17.1%), 27 clinical staff (17.1%), and 32 administrators (20.3%). Between 12 and 30 people at each hospital participated in interviews. Differences in RRTs at top-performing and non-top-performing sites were found in the following 4 domains: team design and composition, RRT engagement in surveillance of at-risk patients, empowerment of bedside nurses to activate the RRT, and collaboration with bedside nurses during and after a rapid response. At top-performing hospitals, RRTs were typically staffed with dedicated team members without competing clinical responsibilities, who provided expertise to bedside nurses in managing patients who were at risk for deterioration, and collaborated with nurses during and after a rapid response. Bedside nurses were empowered to activate RRTs based on their judgment and experience without fear of reprisal from physicians or hospital staff. In contrast, RRT members at non-top-performing hospitals had competing clinical responsibilities and were generally less engaged with bedside nurses. Nurses at non-top-performing hospitals reported concerns about potential consequences from activating the RRT. CONCLUSIONS AND RELEVANCE: This qualitative study's findings suggest that top-performing hospitals feature RRTs with dedicated staff without competing clinical responsibilities, that work collaboratively with bedside nurses, and that can be activated without fear of reprisal. These findings provide unique insights into RRTs at hospitals with better IHCA outcomes.

How Do Resuscitation Teams at Top-Performing Hospitals for In-Hospital Cardiac Arrest Succeed? A Qualitative Study.

BACKGROUND: In-hospital cardiac arrest (IHCA) is common, and outcomes vary substantially across US hospitals, but reasons for these differences are largely unknown. We set out to better understand how top-performing hospitals organize their resuscitation teams to achieve high survival rates for IHCA. METHODS: We calculated risk-standardized IHCA survival to discharge rates across American Heart Association Get With The Guidelines-Resuscitation registry hospitals between 2012 and 2014. We identified geographically and academically diverse hospitals in the top, middle, and bottom quartiles of survival for IHCA and performed a qualitative study that included site visits with in-depth interviews of clinical and administrative staff at 9 hospitals. With the use of thematic analysis, data were analyzed to identify salient themes of perceived performance by informants. RESULTS: Across 9 hospitals, we interviewed 158 individuals from multiple disciplines including physicians (17.1%), nurses (45.6%), other clinical staff (17.1%), and administration (20.3%). We identified 4 broad themes related to resuscitation teams: (1) team design, (2) team composition and roles, (3) communication and leadership during IHCA, and (4) training and education. Resuscitation teams at top-performing hospitals demonstrated the following features: dedicated or designated resuscitation teams; participation of diverse disciplines as team members during IHCA; clear roles and responsibilities of team members; better communication and leadership during IHCA; and in-depth mock codes. CONCLUSIONS: Resuscitation teams at hospitals with high IHCA survival differ from non-top-performing hospitals. Our findings suggest core elements of successful resuscitation teams that are associated with better outcomes and form the basis for future work to improve IHCA.

False activation of the cardiac catheterization laboratory for primary PCI.

OBJECTIVES: We sought to evaluate trends in door-to-balloon (D2B) times and false activation rates for the cardiac catheterization laboratory (CCL) in patients presenting to the emergency department (ED) with acute ST-elevation myocardial infarction (STEMI). In patients with STEMI, national efforts have focused on reducing D2B times for primary percutaneous coronary intervention (P-PCI). This emphasis on time-to-treatment may increase the rate of false CCL activations and unnecessary healthcare utilization. STUDY DESIGN: Retrospective quality improvement chart review. METHODS: We examined all emergent CCL activations for P-PCI between 2007 and 2011 at the University of Michigan Hospital. False activation was defined as emergent CCL activation when the patient did not require CCL care or emergent cardiology evaluation in the ED. Pre-hospital or ED false activation rates and mean D2B time were retrospectively determined by chart review. RESULTS: The CCL was activated 717 times for suspected STEMI. The number of CCL activations increased from 96 in 2007 to 190 in 2011. False CCL activations accounted for 28% of all prehospital and 29% of all ED activations. The false activation rate increased from 15% of all cases in 2007 to 40% of all cases in 2011. The median D2B time decreased from 67 minutes in 2007 to 55 minutes in 2011. CONCLUSIONS: Over a 5-year period with a strong emphasis on reducing D2B times, there has been an increased CCL false activation rate for P-PCI.

Duration of resuscitation efforts and survival after in-hospital cardiac arrest: an observational study.

BACKGROUND: During in-hospital cardiac arrests, how long resuscitation attempts should be continued before termination of efforts is unknown. We investigated whether duration of resuscitation attempts varies between hospitals and whether patients at hospitals that attempt resuscitation for longer have higher survival rates than do those at hospitals with shorter durations of resuscitation efforts. METHODS: Between 2000 and 2008, we identified 64,339 patients with cardiac arrests at 435 US hospitals within the Get With The Guidelines­Resuscitation registry. For each hospital, we calculated the median duration of resuscitation before termination of efforts in non-survivors as a measure of the hospital's overall tendency for longer attempts. We used multilevel regression models to assess the association between the length of resuscitation attempts and risk-adjusted survival. Our primary endpoints were immediate survival with return of spontaneous circulation during cardiac arrest and survival to hospital discharge. FINDINGS: 31,198 of 64,339 (48·5%) patients achieved return of spontaneous circulation and 9912 (15·4%) survived to discharge. For patients achieving return of spontaneous circulation, the median duration of resuscitation was 12 min (IQR 6-21) compared with 20 min (14-30) for non-survivors. Compared with patients at hospitals in the quartile with the shortest median resuscitation attempts in non-survivors (16 min [IQR 15-17]), those at hospitals in the quartile with the longest attempts (25 min [25-28]) had a higher likelihood of return of spontaneous circulation (adjusted risk ratio 1·12, 95% CI 1·06-1·18; p<0·0001) and survival to discharge (1·12, 1·02-1·23; 0·021). INTERPRETATION: Duration of resuscitation attempts varies between hospitals. Although we cannot define an optimum duration for resuscitation attempts on the basis of these observational data, our findings suggest that efforts to systematically increase the duration of resuscitation could improve survival in this high-risk population. FUNDING: American Heart Association, Robert Wood Johnson Foundation Clinical Scholars Program, and the National Institutes of Health.

Part 8: adult advanced cardiovascular life support: 2010 American Heart Association Guidelines for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care.

The goal of therapy for bradycardia or tachycardia is to rapidly identify and treat patients who are hemodynamically unstable or symptomatic due to the arrhythmia. Drugs or, when appropriate, pacing may be used to control unstable or symptomatic bradycardia. Cardioversion or drugs or both may be used to control unstable or symptomatic tachycardia. ACLS providers should closely monitor stable patients pending expert consultation and should be prepared to aggressively treat those with evidence of decompensation.

Part 9: post-cardiac arrest care: 2010 American Heart Association Guidelines for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care.

The goal of immediate post-cardiac arrest care is to optimize systemic perfusion, restore metabolic homeostasis, and support organ system function to increase the likelihood of intact neurological survival. The post-cardiac arrest period is often marked by hemodynamic instability as well as metabolic abnormalities. Support and treatment of acute myocardial dysfunction and acute myocardial ischemia can increase the probability of survival. Interventions to reduce secondary brain injury, such as therapeutic hypothermia, can improve survival and neurological recovery. Every organ system is at risk during this period, and patients are at risk of developing multiorgan dysfunction. The comprehensive treatment of diverse problems after cardiac arrest involves multidisciplinary aspects of critical care, cardiology, and neurology. For this reason, it is important to admit patients to appropriate critical-care units with a prospective plan of care to anticipate, monitor, and treat each of these diverse problems. It is also important to appreciate the relative strengths and weaknesses of different tools for estimating the prognosis of patients after cardiac arrest.