Covid-19 triage in the emergency department 2.0: how analytics and AI transform a human-made algorithm for the prediction of clinical pathways.

The Covid-19 pandemic has pushed many hospitals to their capacity limits. Therefore, a triage of patients has been discussed controversially primarily through an ethical perspective. The term triage contains many aspects such as urgency of treatment, severity of the disease and pre-existing conditions, access to critical care, or the classification of patients regarding subsequent clinical pathways starting from the emergency department. The determination of the pathways is important not only for patient care, but also for capacity planning in hospitals. We examine the performance of a human-made triage algorithm for clinical pathways which is considered a guideline for emergency departments in Germany based on a large multicenter dataset with over 4,000 European Covid-19 patients from the LEOSS registry. We find an accuracy of 28 percent and approximately 15 percent sensitivity for the ward class. The results serve as a benchmark for our extensions including an additional category of palliative care as a new label, analytics, AI, XAI, and interactive techniques. We find significant potential of analytics and AI in Covid-19 triage regarding accuracy, sensitivity, and other performance metrics whilst our interactive human-AI algorithm shows superior performance with approximately 73 percent accuracy and up to 76 percent sensitivity. The results are independent of the data preparation process regarding the imputation of missing values or grouping of comorbidities. In addition, we find that the consideration of an additional label palliative care does not improve the results.

Factors associated with an increased risk of SARS-CoV-2 infection in healthcare workers in aerosol-generating disciplines.

BACKGROUND: Healthcare workers (HCWs) are at a high risk of SARS-CoV-2 infection due to exposure to potentially infectious material, especially during aerosol-generating procedures (AGP). We aimed to investigate risk factors for SARS-CoV-2 infection among HCWs in medical disciplines with AGP. METHODS: A nationwide questionnaire-based study in private practices and hospital settings was conducted between 12/16/2020 and 01/24/2021. Data on SARS-CoV-2 infections among HCWs and potential risk factors of infection were investigated. RESULTS: 2070 healthcare facilities with 25113 employees were included in the study. The overall infection rate among HCWs was 4.7%. Multivariate analysis showed that regions with higher incidence rates had a significantly increased risk of infection. Furthermore, hospital setting and HCWs in gastrointestinal endoscopy (GIE) had more than double the risk of infection (OR 2.63; 95% CI 2.50-2.82, p<0.01 and OR 2.35; 95% CI 2.25-2.50, p<0.01). For medical facilities who treated confirmed SARS-CoV-2 cases, there was a tendency towards higher risk of infection (OR 1.39; 95% CI 1.11-1.63, p=0.068). CONCLUSION: Both factors within and outside medical facilities appear to be associated with an increased risk of infection among HCWs. Therefore, GIE and healthcare delivery setting were related to increased infection rates. Regions with higher SARS-CoV-2 incidence rates were also significantly associated with increased risk of infection.

A Simulation-Based Cost-Effectiveness Analysis of Severe Acute Respiratory Syndrome Coronavirus 2 Infection Prevention Strategies for Visitors of Healthcare Institutions.

OBJECTIVES: The aim is to quantitatively evaluate different infection prevention strategies in the context of hospital visitor management during pandemics and to provide a decision support system for strategic and operational decisions based on this evaluation. METHODS: A simulation-based cost-effectiveness analysis is applied to the data of a university hospital in Southern Germany and published COVID-19 research. The performance of different hospital visitor management strategies is evaluated by several decision-theoretic methods with varying objective functions. RESULTS: Appropriate visitor restrictions and infection prevention measures can reduce additional infections and costs caused by visitors of healthcare institutions by >90%. The risk of transmission of severe acute respiratory syndrome coronavirus 2 by visitors of terminal care (ie, palliative care) patients can be reduced almost to 0 if appropriate infection prevention measures are implemented. Antigen tests do not seem to be beneficial from both a cost and an effectiveness perspective. CONCLUSIONS: Hospital visitor management is crucial and effectively prevents infections while maintaining cost-effectiveness. For terminal care patients, visitor restrictions can be omitted if appropriate infection prevention measures are taken. Antigen testing plays a subordinate role, except in the case of a pure focus on additional infections caused by visitors of healthcare institutions. We provide decision support to authorities and hospital visitor managers to identify appropriate visitor restriction and infection prevention strategies for specific local conditions, incidence rates, and objectives.

Cost-effectiveness analysis of SARS-CoV-2 infection prevention strategies including pre-endoscopic virus testing and use of high risk personal protective equipment.

BACKGROUND: Infection prevention strategies to protect healthcare workers in endoscopy units during the post-peak phase of the COVID-19 pandemic are currently under intense discussion. In this paper, the cost-effectiveness of routine pre-endoscopy testing and high risk personal protective equipment (PPE) is addressed. METHOD: A model based on theoretical assumptions of 10 000 asymptomatic patients presenting to a high volume center was created. Incremental cost-effectiveness ratios (ICERs) and absolute costs per endoscopy were calculated using a Monte Carlo simulation. RESULTS: ICER values for universal testing decreased with increasing prevalence rates. For higher prevalence rates (≥ 1 %), ICER values were lowest for routine pre-endoscopy testing coupled with use of high risk PPE, while cost per endoscopy was lowest for routine use of high risk PPE without universal testing. CONCLUSION: In general, routine pre-endoscopy testing combined with high risk PPE becomes more cost-effective with rising prevalence rates of COVID-19.

Performance of antigen testing for diagnosis of COVID-19: a direct comparison of a lateral flow device to nucleic acid amplification based tests.

OBJECTIVES: The gold standard for diagnosing an infection with SARS-CoV-2 is detection of viral RNA by nucleic acid amplification techniques. Test capacities, however, are limited. Therefore, numerous easy-to-use rapid antigen tests based on lateral flow technology have been developed. Manufacturer-reported performance data seem convincing, but real-world data are missing. METHODS: We retrospectively analysed all prospectively collected antigen tests results performed between 23.06.2020 and 26.11.2020, generated by non-laboratory personnel at the point-of-care from oro- or nasopharyngeal swab samples at the University Hospital Augsburg and compared them to concomitantly (within 24 h.) generated results from molecular tests. RESULTS: For a total of 3630 antigen tests, 3110 NAAT results were available. Overall, sensitivity, specificity, NPV and PPV of antigen testing were 59.4%, 99.0%, 98.7% and 64.8%, respectively. Sensitivity and PPV were lower in asymptomatic patients (47.6% and 44.4%, respectively) and only slightly higher in patients with clinical symptoms (66.7% and 85.0%, respectively). Some samples with very low Ct-values (minimum Ct 13) were not detected by antigen testing. 31 false positive results occurred. ROC curve analysis showed that reducing the COI cut-off from 1, as suggested by the manufacturer, to 0.9 is optimal, albeit with an AUC of only 0.66. CONCLUSION: In real life, performance of lateral-flow-based antigen tests are well below the manufacturer's specifications, irrespective of patient's symptoms. Their use for detection of individual patients infected with SARS-CoV2 should be discouraged. This does not preclude their usefulness in large-scale screening programs to reduce transmission events on a population-wide scale.

Evaluation of score-based tertiary triage policies during the COVID-19 pandemic: simulation study with real-world intensive care data.

OBJECTIVE: The explicit prohibition of discontinuing intensive care unit (ICU) treatment that has already begun by the newly established German Triage Act in favor of new patients with better prognoses (tertiary triage) under crisis conditions may prevent saving as many patients as possible and therefore may violate the international well-accepted premise of undertaking the "best for the most" patients. During the COVID-19 pandemic, authorities set up lockdown measures and infection-prevention strategies to avoid an overburdened health-care system. In cases of situational overload of ICU resources, when transporting options are exhausted, the question of a tertiary triage of patients arises. METHODS: We provide data-driven analyses of score- and non-score-based tertiary triage policies using simulation and real-world electronic health record data in a COVID-19 setting. Ten different triage policies, for example, based on the Simplified Acute Physiology Score (SAPS II), are compared based on the resulting mortality in the ICU and inferential statistics. RESULTS: Our study shows that score-based tertiary triage policies outperform non-score-based tertiary triage policies including compliance with the German Triage Act. Based on our simulation model, a SAPS II score-based tertiary triage policy reduces mortality in the ICU by up to 18 percentage points. The longer the queue of critical care patients waiting for ICU treatment and the larger the maximum number of patients subject to tertiary triage, the greater the effect on the reduction of mortality in the ICU. CONCLUSION: A SAPS II score-based tertiary triage policy was superior in our simulation model. Random allocation or "first come, first served" policies yield the lowest survival rates, as will adherence to the new German Triage Act. An interdisciplinary discussion including an ethical and legal perspective is important for the social interpretation of our data-driven results.

The AI ethics of digital COVID-19 diagnosis and their legal, medical, technological, and operational managerial implications.

The COVID-19 pandemic has given rise to a broad range of research from fields alongside and beyond the core concerns of infectiology, epidemiology, and immunology. One significant subset of this work centers on machine learning-based approaches to supporting medical decision-making around COVID-19 diagnosis. To date, various challenges, including IT issues, have meant that, notwithstanding this strand of research on digital diagnosis of COVID-19, the actual use of these methods in medical facilities remains incipient at best, despite their potential to relieve pressure on scarce medical resources, prevent instances of infection, and help manage the difficulties and unpredictabilities surrounding the emergence of new mutations. The reasons behind this research-application gap are manifold and may imply an interdisciplinary dimension. We argue that the discipline of AI ethics can provide a framework for interdisciplinary discussion and create a roadmap for the application of digital COVID-19 diagnosis, taking into account all disciplinary stakeholders involved. This article proposes such an ethical framework for the practical use of digital COVID-19 diagnosis, considering legal, medical, operational managerial, and technological aspects of the issue in accordance with our diverse research backgrounds and noting the potential of the approach we set out here to guide future research.

Simulation of the mortality after different ex ante (secondary) and ex post (tertiary) triage methods in people with disabilities and pre-existing diseases.

The significant increase in patients during the COVID-19 pandemic presented the healthcare system with a variety of challenges. The intensive care unit is one of the areas particularly affected in this context. Only through extensive infection control measures as well as an enormous logistical effort was it possible to treat all patients requiring intensive care in Germany even during peak phases of the pandemic, and to prevent triage even in regions with high patient pressure and simultaneously low capacities. Regarding pandemic preparedness, the German Parliament passed a law on triage that explicitly prohibits ex post (tertiary) triage. In ex post triage, patients who are already being treated are included in the triage decision and treatment capacities are allocated according to the individual likelihood of success. Legal, ethical, and social considerations for triage in pandemics can be found in the literature, but there is no quantitative assessment with respect to different patient groups in the intensive care unit. This study addressed this gap and applied a simulation-based evaluation of ex ante (primary) and ex post triage policies in consideration of survival probabilities, impairments, and pre-existing conditions. The results show that application of ex post triage based on survival probabilities leads to a reduction in mortality in the intensive care unit for all patient groups. In the scenario close to a real-world situation, considering different impaired and prediseased patient groups, a reduction in mortality of approximately 15% was already achieved by applying ex post triage on the first day. This mortality-reducing effect of ex post triage is further enhanced as the number of patients requiring intensive care increases.

[Simulation of mortality after different ex-ante and ex-post-triage methods in people with disabilities and comorbidities]. / Simulation der Letalität nach verschiedenen Ex-ante- und Ex-post-Triage-Verfahren bei Menschen mit Behinderungen und Vorerkrankungen.

The significant increase in patients during the COVID-19 pandemic presented the healthcare system with a variety of challenges. The intensive care unit is one of the areas particularly affected in this context. Only through extensive infection control measures as well as an enormous logistical effort was it possible to treat all patients requiring intensive care in Germany even during peak phases of the pandemic, and to prevent triage even in regions with high patient pressure and simultaneously low capacities. Regarding pandemic preparedness, the German Parliament passed a law on triage that explicitly prohibits ex post (tertiary) triage. In ex post triage, patients who are already being treated are included in the triage decision and treatment capacities are allocated according to the individual likelihood of success. Legal, ethical, and social considerations for triage in pandemics can be found in the literature, but there is no quantitative assessment with respect to different patient groups in the intensive care unit. This study addressed this gap and applied a simulation-based evaluation of ex ante (primary) and ex post triage policies in consideration of survival probabilities, impairments, and pre-existing conditions. The results show that application of ex post triage based on survival probabilities leads to a reduction in mortality in the intensive care unit for all patient groups. In the scenario close to a real-world situation, considering different impaired and prediseased patient groups, a reduction in mortality of approximately 15% was already achieved by applying ex post triage on the first day. This mortality-reducing effect of ex post triage is further enhanced as the number of patients requiring intensive care increases.