Patients’ perspectives can be integrated in health technology assessments: an exploratory analysis of CADTH Common Drug Review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Plain language summary In Canada, the CADTH Common Drug Review helps ensure that scarce health care resources are used to fund the most effective drugs. Clinicians, researchers, payers, and patients all have important, but potentially different, ideas on what should be considered, to determine a drug’s value. Since 2010, CADTH has invited patient groups to contribute their perspectives to the Common Drug Review. We explored whether, and how, insights offered by patient groups are integrated into assessment reports and Recommendations by the CADTH Canadian Drug Expert Committee. After examining 30 completed drug assessments, we found that: Patient insights are used by CADTH reviewers to frame an assessment and are used by the expert committee to interpret the evidence. Drug trials do not always measure outcomes that patients consider important. Survival, symptom relief, the process of recovery, and maintaining health are all important aspects to consider when determining value during health technology assessments. Abstract Background Since 2010, Canadian patient groups have contributed to the CADTH Common Drug Review (CDR). CADTH conducts health technology assessments of new drugs to support publicly funded drug plans’ reimbursement decisions. We explored whether, and how, patient insights were integrated into assessment reports and Recommendations by the CADTH Canadian Drug Expert Committee (CDEC). Methods We descriptively analyzed 30 consecutive assessments. One researcher identified a set of issues, insights, and desired treatment outcomes provided by patient groups for each included drug assessment. We tracked the presence of each identified patient insight in the relevant assessment protocol, in clinical trials as reported in the assessment, and in the CDEC Recommendations. Additionally, patient insights were categorized by topic and grouped into a three-tier framework to explore the observed juxtaposition between immediate treatment outcomes as seen in clinical trials and the insights from patients living with a chronic condition. Results In 30 drug assessments, 119 patient insights were identified. Of these insights, 89 were included in assessment protocols; 61 in reported clinical trial data; and 67 insights were reflected upon within the CDEC Recommendations. Patient insights within the first framework tier (health status achieved) were frequently included in all aspects of CDR assessments. Within the second tier (progress of recovery), although two-thirds of patient insights were included in protocols, only one-third was reflected in reported trial data or in CDEC Recommendations. Insights within the third tier, which address the long-term consequences of illness and treatment, were even less frequently addressed in all aspects of CDR assessments. Conclusions Patients’ perspectives need not be “considered” in isolation. Patient insights are used by CADTH reviewers to frame an assessment and used by CDEC to interpret the evidence. As health technology assessments should address the indirect and unintended consequences of a technology, as well as its direct and intended effects, drug assessments should consider the progress of recovery and sustainability of health, in addition to survival and immediate health achieved.
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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 | 0.051 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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 it