title: Projecting future medical care costs using four scenarios of lifestyle risk rates.
abstract: OBJECTIVE
  This study predicts medical care expenditures over 10 years for Union Pacific Railroad (UPRR) under alternative health risk factor scenarios for the UPRR workforce.
  
  
  METHODS
  This paper describes the development of an economic forecasting model to predict medical care expenditures assuming four different scenarios of population risk. The variables used to predict medical care expenditures are employee demographics and health risk profiles.
  
  
  METHODS
  UPRR is a transportation company with more than 56,000 employees in 25 states west and south of the Mississippi River.
  
  
  METHODS
  Employees of UPRR.
  
  
  METHODS
  Intermediate outcomes included health risk measures related to exercise patterns, body weight, eating habits, smoking, alcohol consumption, total cholesterol, blood glucose, blood pressure, stress, and depression. Major outcome measures included projected total annual payments by UPRR for medical care services for the decade following 1998.
  
  
  RESULTS
  The UPRR work force is projected to grow by 500 employees per year over the 10-year study period. The average age is expected to increase from 44 to 48 years. Without further health promotion intervention, 7 of the 11 risk factors assessed would likely worsen among UPRR's workforce. Medical care cost increases are projected to range from $22.2 million to $99.6 million in constant 1998 dollars over the next decade, depending on the effectiveness of risk factor modification programs. With an expected health promotion budget averaging $1.9 million annually over 10 years, health risks must decline at least 0.09% per year for the program to pay for itself.
  
  
  CONCLUSIONS
  Estimating various risk and cost scenarios can facilitate program planning and produce an economic justification for worksite health programs.
authors.affiliation: Union Pacific Railroad, Omaha, NE 68179-0101, USA.
authors.forename: J A
authors.initials: JA
authors.lastname: Leutzinger
authors.forename: R J
authors.initials: RJ
authors.lastname: Ozminkowski
authors.forename: R L
authors.initials: RL
authors.lastname: Dunn
authors.forename: R Z
authors.initials: RZ
authors.lastname: Goetzel
authors.forename: D E
authors.initials: DE
authors.lastname: Richling
authors.forename: M
authors.initials: M
authors.lastname: Stewart
authors.forename: R W
authors.initials: RW
authors.lastname: Whitmer
mesh_terms: D000328:Adult; D017046:Cost Savings; D005260:Female; D005544:Forecasting; D015438:Health Behavior; D006264:Health Benefit Plans, Employee / Q000191:economics; D005102:Health Expenditures / Q000639:trends*; D006293:Health Promotion / Q000191:economics*; D006801:Humans; D008019:Life Style; D008297:Male; D008875:Middle Aged; D018803:Models, Economic; D009786:Occupational Health Services / Q000191:economics*; D012309:Risk-Taking