Emergency department use among Asian adults living in the United States: Results from the National Health Interview Survey (2006 – 2013)
Bibliographic record
Abstract
This paper presents secondary analyses of the National Health Interview Survey data focused on emergency department (ED) utilization among Asian adults residing in the United States. National Health Interview Survey data provided from survey years 2006-2013 was pooled and disaggregated by single-race Asian ethnic subgroups (Filipino, Chinese, Asian Indian, other Asian). We explored trends in reports of an ED visit over the survey years for the purpose of determining whether reports of an ED visit increased or decreased over survey years. We also explored background/biologic, environment, access to care, and behavior factors and their associations with having an ED visit. The majority of respondents were foreign-born (75.9%) and had lived in the United States for ten or more years (54.3%). Estimates for reports of any ED visits ranged from 8.3% for the Chinese to 15.3% for the Filipino subgroups. Filipinos were more likely to have an ED visit compared to the Chinese and other Asians (except Asian Indians). For the eight years of survey data, estimates indicate a trend of fewer reports of any ED visit among the Asian Indian and Filipino subgroups. Among Filipinos, having diabetes and a smoking history were associated with an ED visit. The odds of an ED visit were higher among Asians in the youngest age category, among other Asians born in the United States, and among those who saw/talked to a mental health professional within the previous year. As there is a paucity of information available about ED use among Asians or Asian subgroups, this report adds to the literature on patterns of health care utilization among Asian subgroups living in the United States with a specific focus on ED utilization.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".