title: Choosing models for health care cost analyses: issues of nonlinearity and endogeneity.
abstract: OBJECTIVE
  To compare methods of analyzing endogenous treatment effect models for nonlinear outcomes and illustrate the impact of model specification on estimates of treatment effects such as health care costs.
  
  
  METHODS
  Secondary data on cost and utilization for inpatients hospitalized in five Veterans Affairs acute care facilities in 2005-2006.
  
  
  METHODS
  We compare results from analyses with full information maximum simulated likelihood (FIMSL); control function (CF) approaches employing different types and functional forms for the residuals, including the special case of two-stage residual inclusion; and two-stage least squares (2SLS). As an example, we examine the effect of an inpatient palliative care (PC) consultation on direct costs of care per day.
  
  
  METHODS
  We analyzed data for 3,389 inpatients with one or more life-limiting diseases.
  
  
  RESULTS
  The distribution of average treatment effects on the treated and local average treatment effects of a PC consultation depended on model specification. CF and FIMSL estimates were more similar to each other than to 2SLS estimates. CF estimates were sensitive to choice and functional form of residual.
  
  
  CONCLUSIONS
  When modeling cost or other nonlinear data with endogeneity, one should be aware of the impact of model specification and treatment effect choice on results.
authors.affiliation: GRECC/REAP, James J. Peters VA Medical Center, Bronx, NY 10468, USA. melissa.garrido@mssm.edu
authors.forename: Melissa M
authors.initials: MM
authors.lastname: Garrido
authors.forename: Partha
authors.initials: P
authors.lastname: Deb
authors.forename: James F
authors.initials: JF
authors.lastname: Burgess
authors.forename: Joan D
authors.initials: JD
authors.lastname: Penrod
mesh_terms: D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D005102:Health Expenditures / Q000706:statistics & numerical data*; D006761:Hospitals / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D008875:Middle Aged; D018803:Models, Economic; D010166:Palliative Care / Q000706:statistics & numerical data*; D012959:Socioeconomic Factors; D014481:United States; D014493:United States Department of Veterans Affairs / Q000706:statistics & numerical data*