title: Annual incremental health benefit costs and absenteeism among employees with and without rheumatoid arthritis.
abstract: OBJECTIVE
  To assess the impact of rheumatoid arthritis (RA) on absence time, absence payments, and other health benefit costs from the perspective of US employers.
  
  
  METHODS
  Retrospective regression-controlled analysis of a database containing US employees' administrative health care and payroll data for those who were enrolled for at least 1 year in an employer-sponsored health insurance plan.
  
  
  RESULTS
  Employees with RA (N = 2705) had $4687 greater average annual medical and prescription drug costs (P < 0.0001) and $525 greater (P < 0.05) indirect costs (because of sick leave, short- and long-term disability, and workers' compensation absences) than controls (N = 338,035). Compared with controls, the employees with RA used an additional 3.58 annual absence days, including 1.2 more sick leave and 1.91 more short-term disability days (both P < 0.0001).
  
  
  CONCLUSIONS
  Employees with RA have greater costs across all benefits than employees without RA.
authors.affiliation: Data Analytics, HCMS Group, Cheyenne, WY, USA.
authors.forename: Nathan L
authors.initials: NL
authors.lastname: Kleinman
authors.forename: Mary A
authors.initials: MA
authors.lastname: Cifaldi
authors.forename: James E
authors.initials: JE
authors.lastname: Smeeding
authors.forename: James W
authors.initials: JW
authors.lastname: Shaw
authors.forename: Richard A
authors.initials: RA
authors.lastname: Brook
mesh_terms: D000041:Absenteeism; D000328:Adult; D001172:Arthritis, Rheumatoid / Q000191:economics*; D015331:Cohort Studies; D017281:Cost of Illness; D016208:Databases, Factual; D005260:Female; D006264:Health Benefit Plans, Employee / Q000191:economics* / Q000706:statistics & numerical data; D006801:Humans; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D012189:Retrospective Studies; D018582:Sick Leave / Q000191:economics / Q000706:statistics & numerical data; D014481:United States; D014942:Workers' Compensation / Q000191:economics / Q000706:statistics & numerical data