Costs and predictors of costs in rheumatoid arthritis: a prevalence-based study

Arthritis Rheum. 2003 Feb 15;49(1):64-70. doi: 10.1002/art.10905.

Abstract

Objective: To analyze the annual cost of rheumatoid arthritis (RA) and its predictive factors.

Methods: Data were obtained from a 12-month retrospective cohort of 201 RA patients, randomly selected from a rheumatology registry, through a structured interview and records of the Central Information System of the hospital. Results were divided into direct, indirect, and total costs in 2001 US dollars. A sensitivity analysis was performed. Multiple linear regression models for the different types of costs were carried out.

Results: The total cost was US dollars 2.2 million per year, with a cost attributable to RA of US dollars 2.07 million per year. The average cost per patient was US dollars 10419 per year (ranging from US dollars 7914 per patient per year in the best scenario to US dollars 12922 per patient per year in the worst case). Direct costs represent nearly 70% of total costs. We found an average increment in total costs of US dollars 11184 per year per unit of Health Assessment Questionnaire (HAQ) score (P < 0.0001) and an average annual increment of US dollars 621 per year of disease (P < 0.0001). After adjustment, the HAQ score, inability to perform housework tasks, and being permanently disabled for work were the only predictors of high costs.

Conclusion: Our data show a remarkable economic impact of RA over society and link the costs of the disease to its consequences in terms of functional disability, work disability, and housework disability.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Arthritis, Rheumatoid / economics*
  • Arthritis, Rheumatoid / epidemiology
  • Cost of Illness*
  • Disability Evaluation
  • Employment
  • Female
  • Health Care Costs*
  • Humans
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Predictive Value of Tests
  • Prevalence
  • Sensitivity and Specificity
  • Socioeconomic Factors
  • Spain / epidemiology