A comparison, for older people with diabetes, of health and health care utilisation in two different health systems on the island of Ireland
Bibliographic record
Abstract
BACKGROUND: There are social and economic differences between Northern Ireland (NI) and the Republic of Ireland (ROI). There are also differences in the health care systems in the two jurisdictions. The aims of this study are to compare health (prevalence of diabetes and related complications) and health care utilisation (general practitioner, outpatient or accident and emergency utilisation) among older people with diabetes in the NI and ROI. METHODS: Large scale comparable surveys of people over 50 years of age in Northern Ireland (NICOLA, wave 1) and the Republic of Ireland (TILDA, wave 1) are used to compare people with diabetes (type I and type II) in the two jurisdictions. The combined data set comprises 1536 people with diabetes. A coarsened exact matching approach is used to compare health care utilisation among people with diabetes in NI and ROI with equivalent demographic, lifestyle and illness characteristics (age, gender, education, smoking status and self-related health, number of other chronic diseases and number of diabetic complications). RESULTS: The overall prevalence of diabetes in the 50 to 84 years old age group is 3.4 percentage points higher in NI (11.1% in NI, 7.7% ROI, p-value < 0.01). The diabetic population in NI appear sicker - with more diabetic complications and more chronic illnesses. Comparing people with diabetes in the two jurisdictions with similar levels of illness we find that there are no statistically significant differences in GP, outpatient or A&E utilisation. CONCLUSION: Despite the proximity of NI and ROI there are substantial differences in the prevalence of diabetes and its related complications. Despite differences in the health services in the two jurisdictions the differences in health care utilisation for an equivalent cohort are small.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".