Spontaneous adverse drug reaction reporting by patients in Canada: a multi-method study—study protocol
Bibliographic record
Abstract
BACKGROUND: Monitoring adverse drug reactions (ADRs) through pharmacovigilance are vital to patient safety. Spontaneous ADR reporting is one method of pharmacovigilance, and in Canada all reporter types admitted to report an ADR to the Canadian Vigilance Program at Health Canada. Reports are submitted to Health Canada by post, telephone, or via the internet. The Canada Vigilance Program electronically records submitted information to detect medication safety alerts. Although previous studies have shown differences between patients and healthcare professionals (HCPs) on the types of drugs and reactions reported, relatively little is known about the importance of patient reports to pharmacovigilance activities. This article proposed a multi-method approach to evaluate the importance of patient ADR reporting on pharmacovigilance activities, by systematically review the available literature, comparing patient-versus HCPs-generated ADR reports that were submitted to the Canada Vigilance Program, and exploring patient views and experiences regarding the Canadian ADR reporting system. METHODS: Guided by a risk-perception theoretical lens, the proposed multi-methods research study will involve three phases. Phase I is a systematic review of all studies that analyse the factors influence ADR reporting by patients to the pharmacovigilance schemes. Phase II is a descriptive statistical analysis of all ADR reports received by the Canada Vigilance Program database between 1 January 2000 and 31 December 2014 from patients and HCPs to compare ADRs reported by patients with those reported by HCP reports in terms of ADR seriousness, ADR classification by system organ class, and the medication involved based on the anatomical therapeutic class system. In phase III, an interpretative descriptive approach will be used to explore patient's views and experiences on ADR reporting and usability of the Canadian Vigilance ADR report. Participants will be purposefully selected to ensure diverse backgrounds and experiences. Interviews will be digitally-recorded, transcribed verbatim, and inductively analysed to identify themes. Patients will be interviewed until theoretical saturation is achieved. DISCUSSION: Findings from this research will highlight the role of the patients in directly reporting ADRs, and provide information that may guide streamline and optimizing patient ADR reporting. Policy makers, public health officials, and regulatory agencies will require this critical information in order to improve medication safety in Canada and worldwide.
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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 | 0.058 | 0.051 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 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".