title: Predicting elderly outpatients' life-sustaining treatment preferences over time: the majority rules.
abstract: BACKGROUND
  This study describes longitudinal changes in the composition and accuracy of modal life-sustaining treatment preferences as predictors of patients' treatment preferences.
  
  
  METHODS
  Healthy outpatients age 65 and older and their surrogate decision makers recorded preferences for 4 treatments in 9 hypothetical illness scenarios 3 times over a period of 2 years. A statistical prediction model, based on patients' modal preferences, was created using initial responses and updated 2 years later.
  
  
  RESULTS
  When reestimating the model at 2 years, 4 of 27 items in the model created using baseline responses no longer reached the threshold for inclusion, but 5 new items did meet criteria. All modal preference changes reflected a trend toward refusing treatment. Both the original and updated models were more accurate in predicting patients' preferences than were surrogates making concurrent predictions. Adding covariates (e.g., gender, age, presence of plans for future medical care) did not alter the model's predictive superiority over surrogates.
  
  
  CONCLUSIONS
  Models using modal preferences are useful to patients, surrogates, and physicians when trying to accurately discern end-of-life treatment choices, but the models must be updated periodically.
authors.affiliation: Center for Developmental Science, University of North Carolina at Chapel Hill, USA. rhouts@rti.org
authors.forename: Renate M
authors.initials: RM
authors.lastname: Houts
authors.forename: William D
authors.initials: WD
authors.lastname: Smucker
authors.forename: Jill A
authors.initials: JA
authors.lastname: Jacobson
authors.forename: Peter H
authors.initials: PH
authors.lastname: Ditto
authors.forename: Joseph H
authors.initials: JH
authors.lastname: Danks
mesh_terms: D000206:Actuarial Analysis; D016223:Advance Directives / Q000523:psychology*; D000367:Age Factors; D000368:Aged; D001499:Bayes Theorem; D003657:Decision Making; D005260:Female; D006801:Humans; D007872:Legal Guardians / Q000706:statistics & numerical data; D008020:Life Support Care / Q000523:psychology / Q000706:statistics & numerical data*; D008137:Longitudinal Studies; D008297:Male; D009820:Ohio; D010045:Outpatients / Q000523:psychology*; D017060:Patient Satisfaction / Q000706:statistics & numerical data*; D011594:Psychometrics; D012959:Socioeconomic Factors; D011795:Surveys and Questionnaires; D026712:Value of Life