The Ottawa Hospital Regional Warfarin Anticoagulation Management Service. Efficacy and a Patient Satisfaction Survey
Bibliographic record
Abstract
Background: 5% of the population over 65 is on oral anticoagulant therapy. The indications for anticoagulation therapy are wide, not limited to but including treatment of arterial and venous thrombosis, and primary stroke prophylaxis is patients with atrial fibrillation and mechanical cardiac valves. While new oral anticoagulants not requiring monitoring are being more widely prescribed, vitamin K antagonists (VKA) are still being used for many patients in whom the novel agents are contra-indicated (renal failure), not available (funding), or patient/physician preference. Most patients on VKA have their family physicians manage their oral anticoagulants. On average, the time in therapeutic range achieved by family physicians is low (50-55%). There is also a number of patients who have no family physician and are either taking VKA without monitoring, or are having their anticoagulants monitored routinely though emergency room physicians/visits. The Ottawa Hospital (TOH) anticoagulation management service is an e-health solution that offers patients world beating time in therapeutic range (TIR). TOH uses a pharmacy managed DAWN software package (computer-assisted warfarin dosing program). Maintaining patients in therapeutic range for a high percentage of time (greater than 70%) can reduce the risk or recurrent thrombosis (venous or arterial) from under-anticoagulation and the risk of bleeding complications from over-anticoagulation. Well managed VKA therapy has also been suggested to be as safe as therapy with novel oral anticoagulants in some subgroup analysis of studies investigating the novel oral anticoagulants. Objectives/Methods: The purpose of this study was to bring the benefits of the TOH experience to provide a Regional Anticoagulation Management Service across a wide region of eastern Ontario, Canada. This service includes remote blood testing (at a lab near the patient’s home), integrated LIS link to a computerized dosing system (possible through a commercial lab partnership), and communication of dosing and testing instructions via interactive voice recognition (IVRS), email, or live (pharmacist/pharmacist assistant). We administered a patient satisfaction survey to a sample of 111 patients enrolled in the service as well as reported TIR for patients enrolled in our service during the study period (2009-2011). Results: At the beginning of the study, 1400 patients were enrolled in the program. After 2 years, the number has increased to by 66% to 2325. The average TIR for patients in the program as of October 2011 was 76.3% (overall), 77.8% (IVRS), 76.8% (email), and 73.3% (live). The patient satisfaction survey demonstrated that 94% patients prefer VKA anticoagulation monitoring through TOH service compared to their previous experience. 84% patients either satisfied or very satisfied with VKA anticoagulation care through TOH service (compared to 53% satisfaction with anticoagulant care prior to enrolling in our program). Conclusions: The TOH model of anticoagulation management service results in excellent VKA monitoring (high TIR) for a large number of patients across a wide geographical area, as well as a high level of patient satisfaction. This service allows for the safe and efficient management of VKAs in patients in whom VKA therapy is indicated. 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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.015 | 0.003 |
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".