“It's a fight to get anything you need” — Accessing care in the community from the perspectives of people with multimorbidity
Bibliographic record
Abstract
BACKGROUND: There is a growing interest in redesigning health-care systems to better manage the increasing numbers of people with multimorbidity. Knowing how patients experience health-care delivery and what they need from the health-care system are critical pieces of evidence that can be used to guide health system reforms. OBJECTIVE: The purpose of this study was to understand the challenges patients with multimorbidity face in accessing care in the community, and the implications for patients and their families. METHODS: A secondary analysis of qualitative data was conducted on semi-structured interviews with 116 patients who were receiving care in an urban rehabilitation facility in 2011. Exploratory interpretive analysis was used to identify themes about access to care. RESULTS: Challenges occurred at two levels: at the health system level and at the individual (patient) level. Issues at the health system level fell into two broad categories: availability of services (failing to qualify, coping with wait times, struggling with scarcity and negotiating the location of care) and service delivery (unreliable care, unmet needs, incongruent care and inflexible care). Challenges at the patient level fell into the themes of logistics of accessing care and financial strain. Patients interacted and responded to these challenges by: managing the system, making personal sacrifices, substituting with informal care, and resigning to system constraints. CONCLUSION: Identifying the barriers patients encounter and the lengths they go to in order to access care highlights areas where policy initiatives can focus to develop appropriate and supportive services that are more person and family-centred.
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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.018 | 0.012 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.004 | 0.010 |
| 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".