Measuring and valuing patient and caregiver productivity costs: a scoping review protocol
Bibliographic record
Abstract
INTRODUCTION: Economic evaluations are essential for informing healthcare resource allocation. When conducted from a societal perspective, they may include productivity costs such as paid and unpaid productivity losses for patients and their caregivers. Although several methods exist to measure and value productivity costs, there is limited methodological consensus on which methods should be used. This scoping review aims to synthesise existing methods for measuring and valuing patient and caregiver productivity costs. METHODS AND ANALYSIS: This review will follow the Arksey and O'Malley framework, enhanced by subsequent methodological guidance from Levac and the Joanna Briggs Institute. The six stages include identifying the research question; identifying relevant studies; selecting studies; charting the data; collating, summarising and reporting the results; and consultation. We will search MEDLINE, Embase and EconLit from 1996 to July 2025. Eligible sources will include peer-reviewed literature that reports methods for the measurement or valuation of productivity costs related to paid or unpaid work among patients or caregivers. Screening and data extraction will be conducted independently by two reviewers. Extracted data will include types of productivity costs, instruments used, valuation approaches, as well as recommendations on preferred measurement and valuation methods. Results will be synthesised thematically and reported using the Preferred Reporting Items for Systematic Review and Meta-Analysis for Scoping Reviews checklist. ETHICS AND DISSEMINATION: Ethics approval is not required as this review will rely exclusively on publicly available literature and does not involve human participants or the use of primary data. The findings will first be shared with Canada's Drug Agency as a report and then disseminated through peer-reviewed publication and academic presentations to inform future research and practice. REGISTRATION: This protocol has been registered with the Open Science Framework (https://doi.org/10.17605/OSF.IO/FK9D4).
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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 | 0.160 | 0.134 |
| Meta-epidemiology (narrow) | 0.006 | 0.008 |
| Meta-epidemiology (broad) | 0.012 | 0.012 |
| Bibliometrics | 0.022 | 0.019 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.008 | 0.009 |
| Research integrity | 0.012 | 0.010 |
| Insufficient payload (model declined to judge) | 0.091 | 0.029 |
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".