Using modeling to inform patient-centered care choices at the end of life

J Comp Eff Res. 2013 Sep;2(5):497-508. doi: 10.2217/cer.13.53.

Abstract

Aim: Advance directives are often under-informed due to a lack of disease-specific prognostic information. Without well-informed advance directives patients may receive default care that is incongruent with their preferences. We aimed to further inform advance care planning in patients with severe chronic obstructive pulmonary disease by estimating outcomes with alternative advance directives.

Methods: We designed a Markov microsimulation model estimating outcomes for patients choosing between the Full Code advance directive (permitting invasive mechanical ventilation), and the Do Not Intubate directive (only permitting noninvasive ventilation).

Results: Our model estimates Full Code patients have marginally increased one-year survival after admission for severe respiratory failure, but are more likely to be residing in a nursing home and have frequent rehospitalizations for respiratory failure.

Conclusion: Patients with severe chronic obstructive pulmonary disease may consider these potential tradeoffs between survival, rehospitalizations and institutionalization when making informed advance care plans and end-of-life decisions. We highlight outcomes research needs for variables most influential to the model's outcomes, including the risk of complications of invasive mechanical ventilation and failing noninvasive mechanical ventilation.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Advance Directives*
  • Choice Behavior*
  • Decision Making
  • Humans
  • Markov Chains
  • Models, Statistical
  • Patient-Centered Care*
  • Pulmonary Disease, Chronic Obstructive / therapy*
  • Respiration, Artificial
  • Terminal Care*