Estimating direct healthcare costs attributable to laboratory‐confirmed Lyme disease in Ontario, Canada: A population‐based matched cohort study using health administrative data
Bibliographic record
Abstract
The objective of this study was to determine healthcare costs attributable to laboratory-confirmed Lyme disease (LD) from the healthcare payer perspective in Ontario, Canada. A cost-of-illness study was conducted for incident LD subjects from 1 January 2006 through 31 December 2013 ascertained from provincial laboratory and reportable disease databases, linked to health administrative data. All LD subjects included were laboratory-confirmed, according to provincial case definitions. Incident LD subjects were propensity-score matched to uninfected subjects on age, sex, comorbidities and urban/rural status. We used phase-of-care methods to calculate attributable costs for two phases of illness: initial care (≤30 days following "index date") and continuing care (>30 days after index date to the end of the follow-up period). A total of 663 incident, confirmed LD subjects were identified from 2006 through 2013. Mean age was 44.2 ± 20.1 years; 339 (51.1%) were female; and 31 (4.7%) were hospitalized ≤30 days after index date. Six hundred fifty-eight (99.2%) LD subjects were matched to uninfected subjects; mean follow-up time was 3.3 years. Mean attributable costs per case during the initial care phase and continuing care were $277 (95% CI: $197, $357) and -$5 (-$27, $17), respectively. Attributable costs per LD subject aged 5-14 years were $440 ($132, $747), greater than the costs observed for other age strata. Expected 1-year attributable costs were $832, given continuing care costs were negligible. Limitations to our study include estimating costs using a cohort of only laboratory-confirmed LD cases, introducing selection bias for diagnosed and treated patients who may have a lower risk of developing sequelae. In conclusion, the initial care phase of LD is associated with increased healthcare costs, but without significant costs attributable to LD infection after 30 days. Estimates of costs attributable to LD are important for healthcare resource prioritization and the evaluation of novel interventions.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".