Patient Cost Share for Emergency Physician Servcies During the COVID-19 Pandemic
Bibliographic record
Abstract
BACKGROUND: As a result of the Coronavirus disease 2019 (COVID-19) pandemic, health plans were required to implement, or voluntarily implemented, patient cost-share waivers for COVID-19-related emergency care. The impact of the cost waivers on patients for emergency physician services has not been previously reported. OBJECTIVE: To measure the impact of COVID-19 cost-sharing waivers on patients for emergency physician services. METHODS: A multicenter retrospective review of emergency physician commercial claims was conducted to determine the impact of the patient cost share waivers on COVID-19-related emergency physician services. Seventy-seven emergency departments (EDs) representing about a quarter of all EDs in California were included in the study. Emergency physician claims during a 9-month prepandemic period in 2019 were compared with claims during a 9-month pandemic period in 2020 to determine if there were any changes in the patient cost share between the two study periods and between COVID vs. non-COVID-related care. RESULTS: The average patient cost share was $19 for COVID-19-related emergency physician professional care and $52 for visits unrelated to COVID-19. Compared with non-COVID-19 care visits, the patient cost share was 63% less for COVID-19-related care. There was a small increase (< $2) in the patient cost share for non-COVID-19 emergency professional care during the pandemic compared with the prepandemic period. CONCLUSION: Payment policies implemented by California health plans were effective at reducing the patient cost share for patients that required COVID-19-related emergency physician care.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".