Benchmarking emergency department prediction models with machine learning and public electronic health records.

The demand for emergency department (ED) services is increasing across the globe, particularly during the current COVID-19 pandemic. Clinical triage and risk assessment have become increasingly challenging due to the shortage of medical resources and the strain on hospital infrastructure caused by the pandemic. As a result of the widespread use of electronic health records (EHRs), we now have access to a vast amount of clinical data, which allows us to develop prediction models and decision support systems to address these challenges. To date, there is no widely accepted clinical prediction benchmark related to the ED based on large-scale public EHRs. An open-source benchmark data platform would streamline research workflows by eliminating cumbersome data preprocessing, and facilitate comparisons among different studies and methodologies. Based on the Medical Information Mart for Intensive Care IV Emergency Department (MIMIC-IV-ED) database, we created a benchmark dataset and proposed three clinical prediction benchmarks. This study provides future researchers with insights, suggestions, and protocols for managing data and developing predictive tools for emergency care.

Medical Students to the Rescue: Fighting COVID-19 with an Outpatient Pulse Oximetry Monitoring Protocol

The emergency department (ED) is a key point of entry for most of these patients.1 In the setting of an ongoing pandemic, emergency medicine clinicians are forced to make disposition decisions with incomplete information and significant uncertainty regarding the disease course both on an individual and community level.2 From clinical experiences in China, Italy, and New York, it is clear that patients with minor symptoms could subsequently develop severe hypoxia with rapid progression to respiratory failure days to weeks later.3 Furthermore, while certain population-based risk factors for serious illness were known (advanced age, obesity and hypertension), there are no definitive guidelines to identify which of the patients are at highest risk of disease progression, and therefore, warranting early hospital admission. The CO-POP leveraged the availability of medical students withdrawn from clinical rotations to provide emergency medicine physicians an opportunity to discharge patients with COVID-19 with the outpatient pulse oximetry monitoring protocol and close structured follow-up. [...]we have identified the medical student body as one of the few resources that has become more available as pandemic volumes increase.

Developing a pulse oximetry home monitoring protocol for patients suspected with COVID-19 after emergency department discharge.

OBJECTIVES: Patients with COVID-19 can present to the emergency department (ED) without immediate indication for admission, but with concern for decompensation. Clinical experience has demonstrated that critical illness may present later in the disease course and hypoxia is often the first indication of disease progression. The objectives of this study are to (a) assess feasibility and describe a protocol for ED-based outpatient pulse-oximetry monitoring with structured follow-up and (b) determine rates of ED return, hospitalisation and hypoxia among participants. METHODS: Prospective observational study of patients presenting to a single academic ED in Boston with suspected COVID-19. Eligible patients were adults being discharged from the ED with presumed COVID-19. Exclusion criteria included resting oxygen saturation <92%, ambulatory oxygen saturation <90%, heart rate >110 beats per minute or inability to use the device. Study personnel made scripted phone calls on postdischarge days 1, 3 and 7 to review the pulse-oximetry readings and to evaluate for decompensation. Return visit and admission information were collected via medical record and 28-day follow-up calls. RESULTS: 81 patients were enrolled of which 10 (12%) developed hypoxia after their initial discharge from the ED. Overall, 23 (28%) of the 81 patients returned to the ED at least once and 10 of those who returned (43%) were admitted. We successfully contacted 76/81 (94%) of subjects via phone at least once for follow-up assessment. DISCUSSION: Patients are eager and willing to participate in home monitoring systems and are comfortable with using technology, which will allow providers and health systems to extend our hospitals capabilities for tracking patient populations in times of crisis. CONCLUSIONS: It is feasible to implement an outpatient pulse-oximetry monitoring protocol to monitor patients discharged from the ED with confirmed or suspected COVID-19.