National Trends In ED Visits, Hospital Admissions, And Mortality For Medicare Patients During The COVID-19 Pandemic
Bibliographic record
Abstract
Concerns about avoidance or delays in seeking emergency care during the COVID-19 pandemic are widespread, but national data on emergency department (ED) visits and subsequent rates of hospitalization and outcomes are lacking. Using data on all traditional Medicare beneficiaries in the US from October 1, 2018, to September 30, 2020, we examined trends in ED visits and rates of hospitalization and thirty-day mortality conditional on an ED visit for non-COVID-19 conditions during several stages of the pandemic and for areas that were considered COVID-19 hot spots versus those that were not. We found reductions in ED visits that were largest by the first week of April 2020 (52 percent relative decrease), with volume recovering somewhat by mid-June (25 percent relative decrease). These reductions were of similar magnitude in counties that were and were not designated as COVID-19 hot spots. There was an early increase in hospitalizations and in the relative risk for thirty-day mortality, starting with the first surge of the pandemic, peaking at just over a 2-percentage-point increase. These results suggest that patients were presenting with more serious illness, perhaps related to delays in seeking care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".