The Detection and Causality Assessment of Adverse Events Related to Natural Health Product Use in Community Pharmacies through the Implementation of Active Surveillance.
Bibliographic record
Abstract
Background: Natural health products (NHP) are widely used by the public. Since NHPs are pharmacologically active products, their ability to cause adverse reactions (AR) is present and well-documented. Currently employed passive surveillance systems are not well-equipped to detect NHP adverse events (AE) due to issues with significant underreporting, lack of patient disclosure of NHP use to health care providers and patients not attributing an AE to a NHP due to their perception of safety with these products. Other types of surveillance systems, such as active surveillance, may be more appropriate to detect NHP AEs as increased detection has been documented with these systems. Pharmacists are well-trained to screen for NHP use and AEs, including interactions between health products. Once an AE is detected, causality assessment is required to determine if there is a causal link between a health product and the AE. Currently, no causality tools are available, or take into consideration, the evaluation of AEs involving NHPs. Methods: The work for this thesis was derived from two studies. The first study involved the implementation of active surveillance into community pharmacies to screen for the proportion of patients taking prescription drugs and/or NHPs, as well as their respective AE rates. All AEs reported by patients who consented to, and were available for, a detailed telephone interview were adjudicated fully to assess for causality. The second study involved developing, piloting and refining an adjudication process and subsequent causality assessment tools to be used to assess AEs; these process and tools were modified for inclusion of NHP-specific factors. Important case reports resulting from the screening and causality assessment were used to translate knowledge to pharmacists. Results: We screened 1118 patients screened in 10 community pharmacies across Alberta and British Columbia, and obtained reports of 54 AEs. Of the 657 (58.8%; 95% CI: 55.5-61.6) patients who took prescription drugs and NHPs concurrently, 48 (7.3%; 95% CI: 5.6% to 9.6%) reported an AE. This AE rate is 6.4 times (OR; 95% CI: 2.5 – 16.2; p<0.001) greater than those who took prescription drugs alone. On a national level, combined with data from Ontario, Canada, 45.4% (95% CI: 43.8%-47.0%) of Canadians that visit community pharmacies take NHPs and prescription drugs concurrently and of those, 7.4% (95% CI: 6.3%-8.8%) report an AE. Three causality assessment scales, Naranjo, Horn and WHO-UMC, were modified to include the assessment of NHP AEs. The adjudication process and scales developed were piloted in 24 cases (patients reporting an AE with NHP use and available for a full interview) and were able to assess causality of all cases. The tools were then refined by the adjudication team until no further changes were deemed necessary. Two cases found through this process were submitted and will be published in a well-known national pharmacists’ journal to highlight the importance of the data found to practicing pharmacists. Conclusion: A substantial proportion of community pharmacy patients use both prescription drugs and NHPs concurrently; these patients are more likely to experience an AE than those taking prescription drugs only. Active surveillance provides a means of detecting such AEs and collecting high-quality data on which causality assessment can be based. The causality assessment tools developed allowed for full adjudication of AEs involving NHPs. Lastly, such data has clinical relevance for pharmacists in terms of raising awareness around NHP use and the potential risks for their patients.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".