Relationship Between Avoidable Hospitalizations for Diabetes Mellitus and Income Level
Bibliographic record
Abstract
BACKGROUND: Acute diabetic emergencies are potentially avoidable or amenable to timely and effective outpatient therapy. OBJECTIVE: To evaluate the relationship between socioeconomic status (SES) and acute complications of diabetes mellitus in Ontario. METHODS: We used a population-based cohort of persons with diabetes mellitus (N = 605 825) derived from hospital and physician service claims between April 1, 1992, and March 31, 1999. Socioeconomic status was estimated using neighborhood-level data from the 1996 Canadian Census. Outcome events were defined as 1 or more hospitalizations or emergency department visits for hyperglycemia or hypoglycemia. RESULTS: There was a clear inverse gradient between income level and event rates. Individuals in the lowest income quintile were 44% more likely to have an event than those in the highest quintile (16.4% vs 11.4%; P<.001) and had a greater propensity toward recurrent emergency department admissions (1.9 vs 1.6 episodes per patient; P<.001). The gradient was most marked in 45- to 64-year-olds (odds ratio [OR], 1.76; 95% confidence interval [CI], 1.69-1.82) and less apparent in children (OR, 1.06; 95% CI, 0.99-1.13). The relationship between SES and events persisted after adjusting for age, sex, urban vs rural residence, comorbidity, frequency of physician visits, continuity of care, physician specialty, and geographic region (adjusted OR, 1.09 [95% CI, 1.08-1.10] per quintile level). In contrast, admission rates for non-ambulatory care-sensitive conditions (appendicitis and hip fracture) were unaffected by SES. CONCLUSION: Even when some economic barriers to accessing care are removed, patients from low-SES neighborhoods still experience an excess number of hospitalizations for conditions that should be prevented by optimal care in the ambulatory setting.
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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 | 0.000 | 0.003 |
| 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) | 0.002 | 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".