Health Care Utilization and Cost of Herpes Zoster Infection in Patients with Rheumatoid Arthritis, A Retrospective Cohort Study
Bibliographic record
Abstract
Objectives Patients with rheumatoid arthritis (RA) have approximately a twofold increased risk of developing herpes zoster (HZ) compared to the general population. This elevated risk is attributed to the disease itself and related. We aimed to measure health care utilization (HCU) and related costs of HZ infections among RA patients from the health care payer perspective. Methods Patients with RA were identified from the Ontario Rheumatoid Arthritis Database (ORAD), housed at ICES. Costs were measured from a single universal payer (Ontario Health Insurance Plan). We included all adult patients diagnosed with HZ between 2008 and 2020. A cohort was identified and included all Ontario RA patients that were not diagnosed with HZ during the same period of time. The 2 cohorts were matched based on sex, date of birth (± 3 years) and index date (± 60 days of HZ infection). The primary outcome was total HCU cost (in Canadian Dollars) per year, up to 10 years of follow-up (adjusted for 2022 inflation). We also looked at the total number of clinical events (CEs) including the number of hospital admissions, emergency department visits, physician visits and other HCU. The 2 cohorts were compared using unadjusted gamma distribution models to assess HCU costs, and unadjusted generalized estimating equations (GEEs) with negative binomial distribution to assess total CEs. Results We identified 15,573 RA patients diagnosed with HZ. The same number of RA patients without a HZ diagnosis were matched to this cohort. The RA with HZ cohort had significantly higher total HCU costs across all 10 years of follow-up (except year 2) compared to the RA without HZ cohort (Figure 1, p<0.05). The mean total cost ranged from 13,507 CAD at year 1 to 17,120 CAD at year 10 for the RA with HZ cohort compared to 12,651 to 14,534 CAD in the RA without HZ cohort. Physician billing and inpatient hospital costs were the largest cost drivers for both cohorts. Compared to RA patients with HZ, RA patients without HZ experienced a significantly lower mean number of total CEs (p<0.05). This difference was the highest 1 year following a HZ infection. Physician visits were the main driver for total CEs. Conclusion We found that HCU costs and total CEs were higher in RA patients with HZ compared to RA patients without HZ. Thus, rheumatologists should consider treatment strategies that minimize the risk of HZ and ensure patients’ vaccinations are up to date.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".