P156 Myositis flares are associated with reduced work productivity and fewer hours worked: illustration of the future potential of digital healthcare solutions in rheumatic diseases

Abstract Background/Aims The digital healthcare revolution provides the opportunity for clinicians and researchers to collect useful data on a frequent and remote basis. Work ability is impacted by many rheumatic diseases, including the idiopathic inflammatory myopathies (IIMs), however, methods to assess the real-time impacts are limited. This study aims to explore the impact of IIM flares and symptoms upon employment using frequently collected data via a smartphone-based app. Methods The Myositis Physical Activity Device Study recruited a UK-based adult IIM cohort who completed weekly employment and flare questions via a specially designed smartphone-based app throughout a 91 day period in 2019/20. Employment-related questions were assessed every week (see Table 1 for details). Flares were reported via a weekly question. Employment variables were compared between flare and non-flare weeks using descriptive statistics. The relationship between flares and work productivity was assessed using multi-level mixed effects logistic regression modelling, adjusted for age and sex. Results Data on 13 (69% female) employed participants was analysed. A median of 5 flares were reported per patient during the three month period (IQR 3, 9). Summary employment results are displayed in Table 1. Participants reported greater impact of IIM upon employment, lower productivity and fewer hours worked during a flare week, compared to a non-flare week. There was a significant association between flares and detrimental impact upon work productivity (odds ratio [OR] 1.07, 95% confidence interval [CI] 1.03, 1.12, p < 0.01). Flares were also significantly associated with an increased number of work hours missed due to IIM (OR 1.04, 95% CI 1.01, 1.08, p = 0.02) P156 Table 1:- Summary employment parameters compared between flare and non-flare weeksEmployment parameterAnswer formatWhole study period (159 weeks)Flare weeks (60 weeks)Non-flare weeks (99 weeks)p-value*Number of weeks’ work productivity affected by IIM (%)Dichotomous - “yes”, “no”54 (34.0)33 (55.0)21 (21.2)<0.01Mean effect of IIM upon work productivity (SD)Visual analogue scale - “Myositis had no effect on work" (0);“Myositis completely prevented me from working” (100)29.8 (28.8)46.2 (33.3)19.9 (20.0)<0.01Mean number of scheduled work hours per week per participant (SD)Numerical33.2 (15.8)36.9 (19.33)31.0 (13.0)<0.01Mean number of hours worked per week per participant (SD)Numerical23.5 (15.1)18.86 (17.1)26.23 (13.2)<0.01Proportion of hours worked per week per participant / % (SD)Calculated by research team73.7 (38.7)55.9 (43.2)84.7 (31.1)<0.01Mean number of hours of weekly work missed due to IIM per participant (SD)Numerical6.6 (16.6)14.9 (23.4)1.5 (6.6)<0.01Proportion of hours of weekly work missed due to IIM per participant / % (SD)Calculated by research team12.7% (29.5)29.2 (41.1)2.6 (10.0)<0.01SD = standard deviation *Categorical variables were compared using the Chi-squared test and continuous variables compared using the student t-test. Conclusion Our study has demonstrated that IIM flares are significantly associated with detrimental impact upon employment ability. On average, patients lost 15 hours of work a week during a flare compared to less than 2 hours outside a flare. The economic and personal impact of flares highlights the need for research in this area, with the aim of allowing early identification and instigation of treatment and possible need for supported work. Smartphone based remote monitoring of flares and other pertinent variables could enhance digital consultations, which may become more common in the post COVID-19 setting. Disclosure J.C. Williams: None. A.G.S. Oldroyd: None. W.G. Dixon: None. H. Chinoy: None.