title: A theoretical decision model to help inform advance directive discussions for patients with COPD.
abstract: BACKGROUND
  Advance directives (AD) may promote preference-concordant care yet are absent in many patients with Chronic Obstructive Pulmonary Disease (COPD). In order to begin to inform AD discussions between clinicians and COPD patients, we constructed a decision tree to estimate the impact of alternative AD decisions on both quality and quantity of life (quality adjusted life years, QALYs).
  
  
  METHODS
  Two aspects of the AD were considered, Do Not Intubate (DNI; i.e., no invasive mechanical ventilation) and Full Code (i.e., may use invasive mechanical ventilation). Model parameters were based on published estimates. Our model follows hypothetical patients with COPD to evaluate the effect of underlying COPD severity and of hypothetical patient-specific preferences (about long-term institutionalization and complications from invasive mechanical ventilation) on the recommended AD.
  
  
  RESULTS
  Our theoretical model recommends endorsing the Full Code advance directive for patients who do not have strong preferences against having a potential complication from intubation (ETT complications) or being discharged to a long-term ECF. However, our model recommends endorsing the DNI advance directive for patients who do have strong preferences against having potential complications of intubation and are were willing to tradeoff substantial amounts of time alive to avoid ETT complications or permanent institutionalization. Our theoretical model also recommends endorsing the DNI advance directive for patients who have a higher probability of having complications from invasive ventilation (ETT).
  
  
  CONCLUSIONS
  Our model suggests that AD decisions are sensitive to patient preferences about long-term institutionalization and potential complications of therapy, particularly in patients with severe COPD. Future work will elicit actual patient preferences about complications of invasive mechanical ventilation, and incorporate our model into a clinical decision support to be used for actual COPD patients facing AD decisions.
authors.affiliation: Yale Center for Medical Informatics, Yale University School of Medicine, New Haven, USA. Negin.Hajizadeh@yale.edu
authors.forename: Negin
authors.initials: N
authors.lastname: Hajizadeh
authors.forename: Kristina
authors.initials: K
authors.lastname: Crothers
authors.forename: R Scott
authors.initials: RS
authors.lastname: Braithwaite
mesh_terms: D016223:Advance Directives; D003661:Decision Support Techniques; D003663:Decision Trees; D006801:Humans; D007442:Intubation, Intratracheal; D008017:Life Expectancy; D029424:Pulmonary Disease, Chronic Obstructive; D019057:Quality-Adjusted Life Years; D012720:Severity of Illness Index