Consumer experiences of Chronic Obstructive Pulmonary Disease in regional Australia: A mixed methods study and logic model to identify consumer-experience mechanisms to avoid hospital and enhance outcomes
Bibliographic record
Abstract
The objective of this study to explore consumer experiences of their care for Chronic Obstructive Pulmonary Disease (COPD) in a regional Australian hospital and to ascertain consumer identified contexts and mechanisms that can enhance consumer-experience outcomes. A sequential, explanatory mixed methods design was employed including a retrospective audit of COPD admissions and re-admissions and semi-structured interviews with a sample of consumers (n=12). Themes were synthesised using a realist framework and the Expanded Chronic Care Model to develop a logic model. Audit data identified above national average hospital admission rates and length of stay for treatment of COPD. Interview data revealed three key themes namely contexts of care, mechanisms for providing care, and outcomes of care. A logic model was constructed to highlight the necessary contexts and consumer-identified mechanisms that can be enacted to achieve consumer-valued outcomes. The model outlined factors at individual, provider and system levels in a regional and rural setting including interaction and relationships with health care providers; consumer capability; workforce; care pathway; capacity to offer services and support; and continuity of care. This research identifies that positive and continuous relationships are one of the most important consumer-identified mechanisms for influencing COPD consumer experience of their care and capacity to self-manage to stay out of hospital. This research challenges regional and rural health services to harness relationships and connectedness to improve consumer experiences and the impact of care for COPD consumers. The logic model provides a template to assist health services to rise to this challenge. Experience Framework This article is associated with the Patient, Family & Community Engagement lens of The Beryl Institute Experience Framework. (http://bit.ly/ExperienceFramework) Access other PXJ articles related to this lens. Access other resources related to this lens.
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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 | 0.010 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".