Measuring and valuing patient and caregiver productivity costs: a scoping review protocol

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.

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 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.

This protocol has been registered with the Open Science Framework (https://doi.org/10.17605/OSF.IO/FK9D4).