Resource utilization, work productivity and costs in patients with hidradenitis suppurativa: a cost-of-illness study.
Krisztián GáspárL Hunor GergelyBalázs JeneiNorbert M WikonkálÁgnes KinyóAndrea SzegediÉva RemenyikNorbert KissXiang JinMiklós SárdyZsuzsanna BeretzkyMárta PéntekLászló GulácsiAndrás BánvölgyiValentin BrodszkyFanni RenczPublished in: Expert review of pharmacoeconomics & outcomes research (2021)
Background: Hidradenitis suppurativa (HS) is a, chronic skin disease affecting up to 1% of the population in Europe. This study aims to assess the cost-of-illness of HS from a societal perspective in Hungary and to analyze the predictors of costs.Methods: A multicentre, cross-sectional cost-of-illness study was performed among 200 adult HS patients. We evaluated direct medical (physician consultations, inpatient admissions, medical, and surgeries), direct non-medical (transportation and caregiving), and indirect costs (productivity loss).Results: The mean annual cost-of-illness of HS was €6,791 per patient. The main cost components were productivity loss (53.3%), biological treatment (21.5%), and informal care (9.2%). Patients missed, on average, 26 and 63 days from work annually due to absenteeism and presenteeism, respectively. Male sex, more severe disease, gluteal involvement, and coexisting inflammatory bowel disease were associated with higher direct medical costs, while lower education level and worse quality-of-life outcomes predicted higher indirect costs.Conclusion: This is the first study to assess both direct and indirect costs in HS patients. HS imposes a substantial burden on patients and society, predominantly arising from productivity loss and biological therapy. Resource utilization data and cost-of-illness estimates provide valuable inputs into cost-effectiveness analyses of health interventions in HS.
Keyphrases
- end stage renal disease
- healthcare
- newly diagnosed
- ejection fraction
- chronic kidney disease
- cross sectional
- peritoneal dialysis
- climate change
- emergency department
- machine learning
- mental health
- adipose tissue
- palliative care
- patient reported outcomes
- type diabetes
- physical activity
- artificial intelligence
- hidradenitis suppurativa
- bone marrow
- patient reported
- african american
- skeletal muscle
- smoking cessation
- big data
- childhood cancer
- general practice