Potential barriers to physician follow-up within 7 days of discharge from a chronic obstructive pulmonary disease hospital admission
Bibliographic record
Abstract
RATIONALE: Given that physician follow-up after hospital may reduce readmissions for patients with chronic obstructive pulmonary disease (COPD), understanding factors associated with follow-up could help to improve discharge transitions.OBJECTIVES To determine rate and factors associated with physician follow-up within 7 days of discharge from a COPD-related hospitalization.METHODS Population-based retrospective cohort study of patients with COPD discharged from an Ontario hospital between April 1, 2010 and March 31, 2016 using health administrative data. All patients > =35 years old were included. The primary outcome was follow-up with family doctor, respirologist or internal medicine specialist within 7 days of discharge. Multivariable logistic regression analysis was used to determine demographic, socioeconomic, provider and health care access variables associated with follow-up.MEASUREMENTS AND MAIN RESULTS: Overall, 24,438 (29.8%) out of 81,960 patients had physician follow-up within 7 days of discharge. Women (OR 0.89, 95% CI 0.86-0.91), rural dwellers (OR 0.86, 95% CI 0.82-0.90), patients without a family doctor (OR 0.38, 95% CI 0.34-0.44) and those from low-income regions, or those who had hospital length-of-stay >7 days (OR 0.81, 95% CI 0.78-0.85) were less likely to receive follow-up within 7 days. Patients were more likely to receive follow-up if they required intensive care (OR 1.07, 95% CI 1.02-1.12) or had seen a physician frequently in the past.CONCLUSIONS Fewer than 1 in 3 patients received early follow-up. Barriers to follow-up may exist for women, rural-dwellers, patients without a family doctor, those residing in low-income regions, or who experienced prolonged hospital stays.
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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 | 0.002 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".