Barriers to care in patients with diabetes and poor glycemic control—A cross-sectional survey
Bibliographic record
Abstract
AIMS: To determine and quantify the prevalence of patient, provider and system level barriers to achieving diabetes care goals; and to examine whether barriers were different for people with poor glycemic control (HbA1c ≥ 10%; 86 mmol/mol) compared to fair glycemic control (7 to <8%; 53-64 mmol/mol). METHODS: We administered a survey by telephone to community-dwelling patients with diabetes, to examine patient-reported barriers and facilitators to care. We compared responses in individuals with HbA1c ≥ 10% (86 mmol/mol) against those with HbA1c between 7-8% (53-64 mmol/mol). We examined associations between HbA1c group and barriers to care, adjusting for sociodemographic factors and diabetes duration. RESULTS: The survey included 805 people with HbA1c ≥ 10% (86 mmol/mol), and 405 people with HbA1c 7-8% (53-64 mmol/mol). Participants with HbA1c ≥ 10% (86 mmol/mol) reported good access to care, however 20% of participants with HbA1c ≥ 10% (86 mmol/mol) felt that their care was not well-coordinated and 9.6% reported having an unmet health care need. In adjusted analysis, patients with HbA1c ≥10% (86 mmol/mol) were more likely to report lack of confidence and inadequate social support, compared to patients with HbA1c 7-8% (53-64 mmol/mol). They were also significantly more likely not to have drug insurance nor to have received recommended treatments because of cost. CONCLUSIONS: These results reinforce the importance of an individualized, yet multi-faceted approach. Specific attention to financial barriers seems warranted. These findings can inform the development of programs and initiatives to overcome barriers to care, and improve diabetes care and outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".