Trends in all‐cause mortality and inpatient and outpatient visits for ambulatory care sensitive conditions during the first year of the COVID‐19 pandemic: A population‐based study
Bibliographic record
Abstract
BACKGROUND: The impact of the COVID-19 pandemic on the management of ambulatory care sensitive conditions (ACSCs) remains unknown. OBJECTIVES: To compare observed and expected (projected based on previous years) trends in all-cause mortality and healthcare use for ACSCs in the first year of the pandemic (March 2020 to March 2021). DESIGN, SETTING AND PARTICIPANTS: We conducted a population-based study using provincial health administrative data on general adul population (Ontario, Canada). OUTCOMES AND MEASURES: Monthly all-cause mortality, and hospitalizations, emergency department (ED) and outpatient visit rates (per 100,000 people at-risk) for seven combined ACSCs (asthma, chronic obstructive pulmonary disease, angina, congestive heart failure, hypertension, diabetes, and epilepsy) during the first year were compared with similar periods in previous years (2016-2019) by fitting monthly time series autoregressive integrated moving-average models. RESULTS: Compared to previous years, all-cause mortality rates increased at the beginning of the pandemic (observed rate in March to May 2020 of 79.98 vs. projected of 71.24 [66.35-76.50]) and then returned to expected in June 2020-except among immigrants and people with mental health conditions where they remained elevated. Hospitalization and ED visit rates for ACSCs remained lower than projected throughout the first year: observed hospitalization rate of 37.29 versus projected of 52.07 (47.84-56.68); observed ED visit rate of 92.55 versus projected of 134.72 (124.89-145.33). ACSC outpatient visit rates decreased initially (observed rate of 4299.57 vs. projected of 5060.23 [4712.64-5433.46]) and then returned to expected in June 2020.
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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 | 0.001 |
| 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".