Lara D. Veeken · 2010 · 56 citations · 18 references
PharmacyClinical SciencesPharmacoeconomicsCost-effectiveness AnalysisResource Utilization AnalysisRheumatologyDirect Medical CostsHealth Care CostsHealth Care Expenditure AnalysisHealthcare Cost AnalysisResource Utilization MeasurementSystemic SclerosisCost Driver MeasurementDirect CostsDisease Activity MeasurementDisease Cost Of IllnessDisease Severity EstimationEconomic Burden Of DiseaseIndirect Cost AnalysisIndirect Cost Calculation
OBJECTIVE: The aim of our study was to assess the costs of SSc and to analyse cost drivers. METHODS: A cross-sectional survey of consecutive patients with SSc was performed in a rheumatology centre in Hungary. Clinical characteristics, the European Scleroderma Study Group activity index, disease severity scale (DSS), scleroderma HAQ (S-HAQ) and health care utilization were recorded. Cost calculation was performed and correlation with clinical variables was analysed. Results were compared with RA and PsA. RESULTS: Eighty patients were involved: 72 (90%) women, mean age (s.d.) 57.4 (9.6) years and disease duration of 6.2 (6.6) years and 25% of the cases had dcSSc. Mean total cost was 9619 (s.d. 6444) euros/patient/year with rate of indirect cost being 56%. Disability-related productivity loss (55.2%) and hospitalization (28.3%) were the highest among the cost items. Patients with dcSSc had significantly higher direct costs (P = 0.005) compared with the lcSSc subset. Disease activity showed significant correlation with total costs, DSS and S-HAQ with direct costs. SSc-related costs were higher than in matched RA and PsA cases. CONCLUSIONS: The cost-of-illness of SSc is high with a dominance of productivity loss related costs. Moreover, the disease activity is an important cost driver.
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Scleroderma (systemic sclerosis): classification, subsets and pathogenesis
E. Carwile LeRoy, Casilda G. Black, Raúl Fleischmajer et al. · 2001 · 4K citations
Medicine, Pathobiology, Pathology +10
A disease severity scale for systemic sclerosis: development and testing.
Thomas A. Medsger, Alan J. Silman, Virginia Steen et al. · PubMed · 1999 · 445 citations
Education, Biostatistics, Clinical Classification Systems +15