DIFFERENCES IN HOSPITALIZATIONS, ER ADMISSIONS, AND OUTPATIENT VISITS FOR MEXICAN-AMERICANS AGE 75 AND OLDER
Bibliographic record
Abstract
Abstract Few studies have investigated the healthcare utilization of Mexican-American Medicare beneficiaries. We used data from 1,196 Hispanic-EPESE participants aged >75 years that has been linked with Medicare claims to describe the healthcare utilization of older Mexican-Americans and determine common reasons for hospitalizations. Participants were followed for two-years (eight-quarters). We estimated the probability of >1 hospitalization, emergency room (ER) admissions, and outpatient visits per quarter. The percentage of participants who had >1 hospitalizations, ER admissions, and outpatient visits for each quarter ranged from 10.6%-13.2%, 14.6%-19.5%, and 77.2%-80.5%, respectively. Twenty-three percent of hospitalizations were for circulatory conditions and 17% were for respiratory conditions. Older age (OR=1.26) and Spanish language (OR=1.51) were associated with hospitalizations. Women had higher odds than men to have an outpatient visit (OR=1.61). Greater education was associated with ER admissions (OR=0.72). Continued research is needed to identify social determinants and health characteristics associated with healthcare utilization among older Mexican-Americans.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".