The Economic Burden of Acute Venous Thromboembolism During One Year Following Diagnosis: A Population-Based Cohort Study
Bibliographic record
Abstract
Abstract Abstract 1152 Background: Although venous thromboembolism (VTE) is the third most common cardiovascular condition after myocardial infarct and stroke, few data exist on the economic burden associated with this condition. Objective: We aimed to quantify the economic burden of acute VTE in direct medical costs in the general population. Methods: Using the linked administrative healthcare databases of the province of Québec, Canada, including the provincial hospitalization database (MED-ÉCHO) and the healthcare claims databases of RAMQ which is a government agency that administers the provincial universal healthcare program, we determined a source population of all RAMQ beneficiaries with a physician visit or a hospitalization associated with an ICD-9-CM or ICD-10-CA diagnosis code for deep vein thrombosis (DVT) or pulmonary embolism (PE) between January 1, 2000 and December 31, 2009 and without a DVT or PE code prior to January 1, 2000. From the source population, we identified a cohort of Québec residents with a definite VTE and a cohort with a definite or probable VTE. We used a priori determined diagnostic algorithms using RAMQ and MED-ÉCHO data to identify definite and probable VTE cases. Subjects were followed forward in time from first VTE until the earliest of either death or end of study period (December 31, 2009). We determined the total direct cost per year for VTE by applying unit costs to the patient resource use profile in the year after diagnosis of VTE. Resource costs included hospitalizations, physician visits, and prescription medications. Resources were valued by the use of individual patient-level information from RAMQ and MED-ÉCHO. All costs were standardized to the 2009–2010 fiscal year costs, and are reported in Canadian dollars (year 2010 average US exchange rate 1.04). The RAMQ Manuel de Facturation and Manuel des Services de laboratoire en établissement was used to determine fees physician acts associated with a VTE diagnosis. The RAMQ List des médicaments contains information on drugs covered by the provincial drug insurance plan and was used to determine VTE-related drug costs. Because hospital costs are not available in Québec, we used the Ontario Case Costing Initiative to obtain hospital cost data. Hospitalizations for VTE–related outcomes were identified. The mean cost per person-years of follow-up was calculated as the sum of all costs during the year after VTE diagnosis divided by the total person-time of follow-up during that year. Results: From the 245 452 Québec residents between 2000 and 2009 with at least 1 VTE diagnosis in RAMQ or MED-ÉCHO, we identified 40 776 cases with definite VTE, and 14 027 cases with probable VTE. The average direct cost per person-year for VTE is $4,449.13 in the year following a definite VTE (Table 1) and $3,418.83 in the year following a definite or probable VTE. In both cohorts, the majority of cost was incurred by hospitalization for the initial VTE, and average cost after PE was higher than cost following DVT. Conclusions: The economic burden of VTE is large, and is mainly due to the initial VTE hospitalization. Use of measures favouring the safe out-patient treatment of VTE and the development of management strategies to identify patients with acute PE who can safely be treated in the ambulatory setting have the potential to decrease cost. Disclosures: No relevant conflicts of interest to declare.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".