Objectives: To analyze work productivity loss and costs, including absenteeism (time missed from work), presenteeism (reduced productivity while working), and unpaid work loss, among a sample of employed people with multiple sclerosis (pwMS) in Canada, as well as its association with clinical, sociodemographic, and work-related factors. Methods: We used cross-sectional data collected as part of the Canadian Prospective Cohort Study to Understand Progression in MS (CanProCo) and information from the Valuation of Lost Productivity questionnaire. Results: Among 512 pwMS who were employed, 97% showed no or mild disability and 55% experienced productivity loss due to MS in the prior 3 months. Total productivity time loss over a 3-month period averaged 60 hours (SD = 107; 23 from presenteeism, 19 from absenteeism, and 18 from unpaid work), leading to a mean cost of lost productivity of CAD$2480 (SD = 4282) per patient, with an hourly paid productivity loss greater than the wage loss. Fatigue retained significant associations with all productivity loss outcomes. Conclusion: Unpaid work loss and productivity losses exceeding those of the employee alone (due to teamwork and associated factors) are key additional contributors of the high economic burden of MS. Workplace accommodations and treatments targeted at fatigue could lessen the economic impact of MS.

Driven by technological and scientific advances, the landscape of genetic medicine is rapidly changing, which complicates strategic planning and decision-making in this area. To address this uncertainty, we sought to understand genetic professionals' opinions about the future of clinical genetic and genomic services in Canada. We used the Delphi method to survey Canadian genetic professionals about their perspectives on whether scenarios about changes in service delivery and the use of genomic testing would be broadly implemented in their jurisdiction by 2030. We conducted two survey rounds; the response rates were 32% (27/ 84) and 67% (18/27), respectively. The most likely scenario was the universal use of noninvasive prenatal screening. The least likely scenarios involved population-based genome-wide sequencing for unaffected individuals. Overall, the scenarios perceived as most likely were those that have existing evidence about their benefit and potential medical necessity, whereas scenarios were seen as unlikely if they involved emerging technologies. Participants expected that the need for genetic healthcare services would increase by 2030 owing to changes in clinical guidelines and increased use of genome-wide sequencing. This study highlights the uncertainty in the future of genetic and genomic service provision and contributes evidence that could be used to inform strategic planning in clinical genetics.

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