Association between perceived unmet health care needs and risk of adverse health outcomes among patients with chronic medical conditions.
Bibliographic record
Abstract
BACKGROUND: Adults with chronic medical conditions are more likely to report unmet health care needs. Whether unmet health care needs are associated with an increased risk of adverse health outcomes is unclear. METHODS: Adults with at least one self-reported chronic condition (arthritis, chronic obstructive pulmonary disease, diabetes mellitus, heart disease, hypertension, mood disorder, stroke) from the 2001 and 2003 cycles of the Canadian Community Health Survey were linked to national hospitalization data. Participants were followed from the date of their survey until March 31, 2005, for the primary outcomes of all-cause and cause-specific admission to hospital. Secondary outcomes included length of stay, 30-day and 1-year all-cause readmission to hospital, and in-hospital death. Negative binomial regression models were used to estimate the association between unmet health care needs, admission to hospital, and length of stay, with adjustment for socio-demographic variables, health behaviours, and health status. Logistic regression was used to estimate the association between unmet needs, readmission, and in-hospital death. Further analyses were conducted by type of unmet need. RESULTS: Of the 51 932 adults with self-reported chronic disease, 15.5% reported an unmet health care need. Participants with unmet health care needs had a risk of all-cause admission to hospital similar to that of patients with no unmet needs (adjusted rate ratio [RR] 1.04, 95% confidence interval [CI] 0.94-1.15). When stratified by type of need, participants who reported issues of limited resource availability had a slightly higher risk of hospital admission (RR 1.18, 95% CI 1.09-1.28). There was no association between unmet needs and length of stay, readmission, or in-hospital death. INTERPRETATION: Overall, unmet health care needs were not associated with an increased risk of admission to hospital among those with chronic conditions. However, certain types of unmet needs may be associated with higher or lower risk. Whether unmet needs are associated with other measures of resource use remains to be determined.
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 | 0.002 | 0.009 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".