Abstract 259: Identifying Predictors of Cumulative Health Care Costs in Incident Atrial Fibrillation: a Population-Based Study
Bibliographic record
Abstract
Background: The dramatic increase in the incidence of atrial fibrillation (AF) has substantial impacts on health care resource utilization. Our objective was to understand the pattern and predictors of cumulative health care costs in patients with incident AF. Methods: All patients discharged after a first presentation of AF to the emergency department (ED) in Ontario, Canada were identified from April 1st, 2005 to March 31st, 2010. Per patient cumulative health care costs were determined until death or March 31st 2012. The cost sectors included were acute and chronic hospitalizations, same-day surgeries, emergency room visits, physician fee-for-service billings, home care, long term care and drug costs for patients over the age of 65 years. All costs were adjusted to 2013 Canadian dollars. Join-point analyses identified clinically relevant phases of health care costs. Hierarchical generalized linear models with a logarithmic link and gamma distribution determined predictors of cost per phase. Results: There were a total of 61,112 ED visits for AF over the period of interest. Our cohort consisted of 17,980 patients with new onset AF who were discharged from the ED. Mean age was 65.7 and 45.8% were female. Over the mean follow-up period of 3.9 years, 17.1% of patients died. Three distinct phases of cumulative cost were identified: 2 month phase post index ED visit; 12 month phase pre-death and a stable/chronic phase. The mean cost per patient in the 1st month post-index was $1,876 (95% CI 1,822-1,931), while the mean cost per patient in the month prior to death was $8,050 (95% CI 7,666-8,434), compared to $640 (95% CI 624-655) per month for the stable/chronic phase. The main component of costs in the post-index and stable/chronic phases were physician services (67% of all costs for 1-month post-index; 44% of all costs for stable/chronic phase). In contrast, acute-hospitalizations represented the largest component of costs in the pre-death phase at 72%. The CHA2DS2VASC clinical risk score was the strongest predictor of increasing costs, with a gradient of increasing per patient cost with increasing score (Rate ratio (RR) of 6.8 and 2.06 for score of 9 versus score of 0 in pre-death phase and post-index phase respectively) Conclusion: There are distinct phases of resource utilization after the diagnosis of AF, with highest costs in the pre-death phase. Cumulative costs are driven by patient co-morbidities, as captured by the CHA2DS2VASC risk score.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".