Health service utilization in IBD: comparison of self-report and administrative data
Bibliographic record
Abstract
BACKGROUND: The reliability of self-report regarding health care utilization in inflammatory bowel disease (IBD) is unknown. If proven reliable, it could help justify self-report as a means of determining health care utilization and associated costs. METHODS: The Manitoba IBD Cohort Study is a population-based longitudinal study of participants diagnosed within 7 years of enrollment. Health care utilization was assessed through standardized interview. Participants (n = 352) reported the total number of nights hospitalized, frequency of physician contacts in the prior 12 months and whether the medical contacts were for IBD-related reasons or not. Reports of recent antibiotic use were also recorded. Actual utilization was drawn from the administrative database of Manitoba Health, the single comprehensive provincial health insurer. RESULTS: According to the administrative data, 15% of respondents had an overnight hospitalization, while 10% had an IBD-related hospitalization. Self-report concordance was highly sensitive (92%; 82%) and specific (96%; 97%, respectively). 97% of participants had contact with a physician in the previous year, and 69% had IBD-related visits. Physician visits were significantly under-reported and there was a trend to over-report the number of nights in hospital. CONCLUSIONS: Self-report data can be helpful in evaluating health service utilization, provided that the researcher is aware of the systematic sources of bias. Outpatient visits are well identified by self-report. The discordance for the type of outpatient visit may be either a weakness of self-report or a flaw in diagnosis coding of the administrative data. If administrative data are not available, self-report information may be a cost-effective alternative, particularly for hospitalizations.
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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 | 0.003 | 0.000 |
| 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 | 0.001 | 0.001 |
| 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".