Rural Residence Associated with Receipt of Recommended Postdischarge Chronic Obstructive Pulmonary Disease Care among a Cohort of U.S. Veterans
Bibliographic record
Abstract
Abstract Rationale Individuals with chronic obstructive pulmonary disease (COPD) in rural areas experience inequitable access to care. Objectives To assess whether rural residence is associated with receipt of recommended postdischarge COPD care. Methods We conducted a cohort study of all U.S. veterans discharged from a Veterans Affairs medical center after COPD hospitalization from 2010 to 2019. Rural residence was defined by rural-urban commuting area classification. Our primary outcome was the proportion of recommended care received within 90 days of hospital discharge, including smoking cessation therapy, appropriate management of supplemental oxygen, appropriate prescription of inhaled therapy, and pulmonary rehabilitation. We conducted multivariable linear regression between rural residence and the proportion of recommended care received, adjusting for age, sex, race, ethnicity, comorbidities, and primary care facility type. We tested multivariable linear probability models for each of the recommended therapies. Results Of 67,649 patients, 7,370 (10.8%) resided in rural areas and 2,000 (3.0%) in highly rural areas. Overall, the proportion of recommended COPD treatments received was low (mean, 15.0%; standard deviation, 21.0%). Compared with urban residence, patients with rural and highly rural residence received fewer recommended COPD care treatments (rural estimate [adjusted percentage difference (95% confidence interval)], −1.1 [−1.6, −0.6]; highly rural estimate, −1.2 [−2.1, −0.3]). Rural and highly rural residence were associated with lower likelihood of receiving appropriate inhaled therapy escalation (rural estimate, −4.0 [−5.1, −3.0]; highly rural estimate, −3.0 [−5.0, −1.1]) and pulmonary rehabilitation referral (rural estimate, −1.2 [−1.6, −0.9]; highly rural estimate, −2.1 [−2.7, −1.4]) but a higher likelihood of receiving smoking cessation therapy (rural estimate, 5.4 [3.3, 7.5]; highly rural estimate, 7.2 [3.3, 11.2]). There was no significant difference in appropriate oxygen management (rural estimate, −1.0 [−2.8, 0.9]; highly rural estimate, 3.1 [−0.7, 6.9]). Conclusions Patients across the rural–urban spectrum received few recommended postdischarge COPD treatments. Health systems approaches are needed to address widespread underuse of evidence-based COPD care.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".