The NHWS was used to examine patient-reported health outcomes, work impairment, and HCRU among employed respondents with RRMS and those without MS in the US. The current study showed that employed individuals with RRMS exhibited greater work impairment, HCRU, and lower HRQoL compared to those without MS. In a previous study, the level of work impairment due to MS was similar to the findings in this study [20]. However, to the best of our knowledge, this is the first study to evaluate outcomes (HRQOL, HCRU) at different levels of work impairment (i.e., based on a tertile distribution: 0%, 1–30%, 31–68%, 69–100%) in individuals with RRMS who are in the workforce.

An earlier study of patients with MS identified from 1998 to 2009 demonstrated the negative impact of MS on HRQoL and reported that on average an MS patient lost 10.04 quality-adjusted life years due to their disease [40]. The present study also highlighted the impact of RRMS on HRQoL. In fact, the minimal important differences (MIDs) of 0.07 points on the EQ-5D index and 3 points on the SF-36 PCS were exceeded in the current study, indicating the magnitude of these influential effects [31, 41].

We found that only 36.1% of the surveyed respondents with RRMS were employed at the time of the study with an average age of 45.2 years. A progressive disease course and increasing age have previously been shown to be associated with unemployment in MS. [12] Large-scale evaluations of the real-world association between RRMS and employment and productivity in the workplace are lacking. Though previous studies have demonstrated the association of MS with considerable rates of unemployment [42, 43], studies have found that absenteeism and presenteeism were both common among individuals with MS. [17] The affected pattern of total work productivity impairment was consistent with absenteeism and presenteeism, with significantly higher levels of impairment among those with RRMS compared with matched controls in the current study. These findings replicate earlier findings about the affected pattern of overall work impairment being consistent with absenteeism and presenteeism [17, 20]. A study by Kigozi et al. found that the influence of disease on presenteeism in employed individuals is high and should considered in economic studies [22]. The impact of RRMS on work productivity appears to be similar to that of patients suffering from other chronic diseases using the NHWS. Absenteeism and presenteeism was reported to be 4.3 and 32.4% in irritable bowel syndrome [44], 5.0 and 20.0% in asthma [45], and 18.3 and 40.5% in Crohn’s disease [46], respectively.

Fatigue, cognitive dysfunction, depression, and impaired mobility have previously been reported to be associated with QoL and thereby unemployment in patients with MS. [47] Our study in respondents with RRMS reiterates that MS symptom severity parallels greater work impairment. These individuals also experience significant decreases in HRQoL indicators including pain, depression, fatigue, and other cognitive impairments. A few longitudinal studies of patients with MS regressing from employed to unemployed status have shown that decreases in cognition and motor functioning are the critical factors [48, 49]. The results of the current study are validated by the real-world data used and add to our understanding regarding the management of RRMS on long-term productivity loss.

Reduced PCS, MCS, and EQ5D scores indicated that for employed respondents with RRMS, both physical and emotional problems (e.g., anxiety and depression) are associated with reduced work productivity. In this study, greater work impairment among respondents with RRMS was associated with significantly more HCP visits, PCP visits, ER visits, and hospitalizations during the previous 6 months compared to the visits and hospitalizations required from those with less work impairment. Appropriate treatment with an efficacious agent should improve MS symptoms, reduce absenteeism/presenteeism, and therefore increase work productivity for individuals with RRMS.

Healthcare costs in MS are driven by the use of disease modifying treatments (DMTs), which are prescribed based on the initial severity of MS and on its subsequent progression [50]. Moccia et al. [50] found that patients who received more expensive DMTs, specifically indicated for a more aggressive disease progression, presented better long-term outcomes (such as lower risk of reaching milestones of short- and long-term disease progression) compared with patients with relatively milder symptoms who received lower-cost DMTs. This issue should be considered not only by physicians when assessing patients with MS to design the most suitable course of treatment, but also by policy makers when establishing eligibility criteria for DMTs [50, 51]. These more expensive DMTs could have beneficial effects on the MS patients’ ability to work, which could be evaluated in further studies.

There are limitations in the current study and they are as follows. The cross-sectional study design allows the detection of association between the variables at a single point in time, but limits causal inferences. Study data were obtained through online self-report, increasing the chances of confounding self-reporting bias. For example, cognitive impairments were perceived by the respondents and not quantified by objective measures of cognition. It was not possible to confirm the patient-reported responses. To overcome this shortcoming, future research could supplement self-reporting with more objective sources of data (e.g., medical records) to validate participants’ responses. Recall bias may have been introduced, due to the self-reported response format. The fact that the study involved only patients with RRMS might be a limitation considering that patients with progressive MS have higher disability and larger impact on daily activities/work, compared with RRMS [52]. However, considering that patients with RRMS are the “active” subgroup of MS, this is possibly the subpopulation of greatest interest and with largest room for improvement in the clinical practice. The survey may possibly under-represent the RRMS population, due to age-related limitations (e.g., extremely severe cases of RRMS elderly patients are less likely to complete the survey) and limited access to the internet (e.g., very low-income individuals and elderly RRMS patients may not have computer access). A drawback with the matched sample is that the groups may differ on unmeasured variables that may have an impact on outcomes. The respondents’ population may not have been normally distributed which is evidenced by high standard deviation values. Job type or occupational characteristics were not considered in the analysis. The level of unemployment in both the RRMS and controls groups was higher than expected. The most current estimates from 2018 show the 55 years and over age group to have about 3% unemployment [53]. Work productivity may be influenced by the type of work. Physically and cognitively demanding jobs are associated with different rates of work impairment.