Access to multidisciplinary outpatient heart failure clinics in a Middle East country: patient and cardiologist perspectives
Bibliographic record
Abstract
Abstract Background Heart failure (HF) is a progressive condition affecting millions globally, with a significant burden. In the Gulf countries, the burden of HF is particularly severe due to a high prevalence of risk factors such as hypertension, diabetes, and obesity. Multidisciplinary heart failure clinics (HFCs) have been shown to improve survival, reduce hospitalizations, and enhance the quality of life. Despite the proven benefits of HFCs, there is limited research on the factors influencing access to these services, particularly in countries within the Gulf region. Purpose This study investigated factors influencing patient access to multidisciplinary outpatient heart failure clinics from the perspective of multiple stakeholders: patients and cardiologists in Qatar, a Gulf country. Methods This was a qualitative study. A trained researcher conducted semi-structured face-to-face interviews with patients and online interviews with cardiologists. The interviews were conducted between March and October 2023. Audio recordings of the interviews were made. Transcripts were cleaned and analyzed by two well-trained researchers independently. Codes were derived from the transcripts and grouped and organized into themes. Results A total of twenty-six individuals (14 patients and 12 cardiologists) participated in the interviews. Four major themes were identified: health system organization (subthemes: benefits, heart failure clinics triage criteria, need/capacity), heart failure clinics referral process (subthemes: electronic record system, patient communication, and education), care continuity and communication (subthemes: patient navigators, clinician preferences), and access challenges (subthemes: transportation, costs). Conclusion(s) Resources are needed to expand HFC capacity and coverage, leverage electronic medical record tools and telehealth, and educate physicians and patients on referral guidelines and processes. Addressing transportation and financial barriers, alongside improving care coordination and communication, can enhance access to HFCs, ultimately improving HF outcomes and quality of life for patients.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".