Quantifying Health Services Use for Chronic Obstructive Pulmonary Disease
Bibliographic record
Abstract
RATIONALE: Chronic obstructive pulmonary disease (COPD), a common manageable condition, is a leading cause of death. A better understanding of its impact on health-care systems would inform strategies to reduce its burden. OBJECTIVES: To quantify health services use in a large, North American COPD population. METHODS: We conducted a cohort study using health administrative data from Ontario, a province with a population of 13 million and universal health-care insurance. All individuals with physician-diagnosed COPD in 2008 were identified and followed for 3 years. Proportions of all hospital visits, emergency department visits, ambulatory care visits, long-term care residence places, and homecare made or used by people with COPD were determined and rates of each compared between people with and without COPD. MEASUREMENTS AND MAIN RESULTS: A total of 853,438 individuals with COPD (11.8% of the population aged 35 yr and older) were responsible for 24% of hospitalizations, 24% of emergency department visits, and 21% of ambulatory care visits; filled 35% of long-term care places; and used 30% of homecare services. After adjusting for several factors, people with COPD had rates of hospital, emergency department, and ambulatory care visits that were, respectively, 63%, 85%, and 48% higher than the rest of the population. Their rates of long-term care and homecare use were 56 and 59% higher, respectively. CONCLUSIONS: Individuals with COPD use large and disproportionate amounts of health services. Strategies that target this group are needed to improve their health and minimize their need for health services.
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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".