Article Text
Abstract
Objective To understand how treatment-related financial burden affects patients with gynecologic cancer and to identify targets for interventions to reduce financial toxicity.
Methods Patients with gynecologic cancer were invited to participate in a qualitative focus group study. Each participant completed an online, secure survey that included questions regarding diagnosis, treatment, employment status, and income. The Comprehensive Score for Financial Toxicity (COST) tool was used to measure economic burden (COST score 0–44), with lower scores indicating worse toxicity. Each participant then took part in a virtual semistructured focus group with a social worker and a study staff member. Three investigators independently analyzed the transcripts for common themes and reconciled disagreements through consensus.
Results Over 60% of participants had private insurance, and 54% had moderate to high financial toxicity (COST scores <26). The five most commonly discussed themes included extent of insurance coverage, out-of-pocket health expenses, employment status changes, health system inefficiencies, and opportunity costs. Minor themes included issues surrounding delayed care, provider conversations, parking, and transportation. Participants with moderate to high toxicity reported strain associated with employment status changes, opportunity costs, and health system inefficiencies more often than those with mild toxicity.
Conclusions Our findings suggest that patient-centered interventions to optimize insurance coverage and enhance care coordination may reduce financial toxicity. Both targets are potentially immediately actionable and could have downstream effects on health outcomes. Meanwhile, advocacy efforts to improve work leave policies and reduce out-of-pocket health expenditure are system-level interventions that also should be considered to curtail financial toxicity.
- Gynecology
Data availability statement
Data are available upon reasonable request. Available through REDcap. All de-identified.
Statistics from Altmetric.com
Data availability statement
Data are available upon reasonable request. Available through REDcap. All de-identified.
Footnotes
Contributors KN: data curation, formal analysis, investigation, writing original draft; RB: data curation, methodology, project administration, writing: review and editing; SG: data curation, formal analysis, writing: review and editing; CS: data curation, writing: review and editing; MRH: visualization, validation, writing: review and editing; LD: visualization, validation, writing: review and editing; KME: guarantor, conceptualization, project administration, methodology, visualization, validation, writing: review and editing.
Funding This work was conducted with support from Harvard Catalyst | The Harvard Clinical and Translational Science Center (National Center for Advancing Translational Sciences, National Institutes Health Award UL1 TR002541) and financial contributions from Harvard University and its affiliated academic healthcare centers.
Competing interests None declared.
Provenance and peer review Not commissioned; externally peer reviewed.