Objective
To quantify the impact of the SARS-CoV-2 pandemic on emergency department volumes and patient presentations, and to evaluate changes in community mortality for the purpose of characterizing new patterns of emergency care utilization.
Patients and Methods
This is an observational cross-sectional study using electronic health records for emergency department visits in an integrated, multi-hospital system with academic and community practices across four states for visits between March 17 to April 21, 2019, and February 9 to April 21, 2020.
We compared numbers and proportions of common and critical chief complaints and diagnoses, triage assessments, throughput, disposition, and selected hospital lengths of stay and out-of-hospital deaths.
Results
In the period of interest, emergency department visits decreased by nearly 50%. Total number of patients diagnosed with myocardial infarctions, stroke, appendicitis and cholecystitis decreased. The percentage of visits for mental health complaints increased. There was an increase in deaths, driven by out-of-hospital mortality.
Conclusion
Fewer patients presenting with acute and time-sensitive diagnoses suggests that patients are deferring care, this may be further supported by an increase in out of hospital mortality. Understanding which patients are deferring care and why will allow us to develop outreach strategies and ensure that those in need of rapid assessment and treatment will do so, preventing downstream morbidity and mortality.
BackgroundEmergency Medicine Telehealth (TeleEM) represents an opportunity to work directly with referral centres, rural facilities and underserved areas to mitigate unnecessary testing, optimise resource utilisation and facilitate patient transfers across health systems. To optimise the impact of a TeleEM programme, a tool is needed to remotely monitor patient activity in multiple emergency department facilities, concurrently.MethodsAfter identifying data sources for activation criteria put forth by the TeleEM operations group, rules were constructed within the electronic health record to facilitate data checks and ultimately produce a yes/no response if the category’s conditions were met. Responses were organised into a table, with functionality allowing end users to drill into the different sites to see patient-specific information for patients meeting activation criteria.ConclusionsThe TeleEM dashboard allows for proactive engagement by the TeleEM physician and strengthens the team-based approach of critically ill.
Shaman, 2020) and 70% of CCBs in each county were assumed to be occupied by non-COVID-19 patients. For each county, three potential constraints on increasing capacity were estimated: the number of nurses, the number of physicians (including APPs), and the number of CCBs. One or more constraints could be active at any time. Results: Prior to optimization, 91% of counties were able to meet the demand for projected case counts. In contrast, 8.4% were limited by nursing resources, 0.09% by physicians, and 0.8% by the number of CCBs. After optimization, 16.9% of counties sent nurses to a different county(s) (median 6 nurses sent, IQR 13.75) compared with 5.5% counties receiving them (median 23, IQR 43.5). Fewer physicians were relocated (0.09% sent, median 1, IQR 1; 0.06% received, median 2.5, IQR 1.5) (Figure). Using baseline staffing ratios and availability, these redistributions led to a reduction in total unmet demand from 24,155 to 19,976. In order to fully meet demand across the US under these conditions, an additional 1,225 physicians, 41,939 nurses and 13,905 CCBs would have been needed. Conclusion: This work shows that with the redeployment of resources even within state boundaries may provide relief to areas of need without causing strain in other locations. While validation with actual redeployment during the pandemic can improve estimates, these models can provide decision support to stakeholders by suggesting optimal reallocation or the ability of existing resources to support additional capacity.
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