Macro and meso level influences on distributed integrated COPD care delivery: a social network perspective
Bibliographic record
Abstract
Background Care guidelines for people with chronic obstructive pulmonary disease (COPD) recommend an integrated approach for holistic, flexible, and tailored interventions. Continuity of care is also emphasised. However, many patients with COPD experience fragmented care. Discontinuities in healthcare and related social services are likely to result in disjointed rather than integrated care which can negatively affect patient health outcomes. The purpose of this qualitative study was to improve our understanding of, and how, contextual features pertaining to structures and processes of COPD integrated care influence delivery of care within patients’ healthcare networks. Methods We conducted individual interviews with 28 participants (9 patients, 16 healthcare professionals, and 3 spousal caregivers). Participants were recruited through the lung clinic at a city hospital in western Canada. We employed a social network paradigm to analyse and interpret the data. Results The analysis revealed an overarching theme of fragmented COPD care with two sub-themes: (1) Funding shortfalls and availability of resources, and (2) Dis(mis)connected communication pathways. The overarching theme depicts variations, delays, and discontinuities in patient care. The sub-themes describe how macro level influences and meso level shortfalls were perceived to influence the availability of respiratory care resources that contributed to fragmented COPD care. Conclusions Employing a social network lens drew particular attention to family physicians’ pivotal role in delivering community-based COPD care. While an integrated approach to care is recommended by care guidelines, institutional and organizational structures and processes, such as financial and communication structures, may inhibit delivery of integrated care. Thus, macro and meso level structures and processes have the potential to shape patient care by constraining family physicians’ purposive and communication actions necessary for facilitating an integrated distributed approach to care. We propose a context of care which fosters a context for family physicians’ delivery of patient-centered care. Integrated care delivery may improve patients’ wellbeing and alleviate financial constraints on the healthcare system.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.012 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".