Research Activities, January 2013: Patient Safety and Quality: Decision modeling can demonstrate potential trade-offs between survival and quality of life in advance directives

Research Activities, January 2013: Patient Safety and Quality: Decision modeling can demonstrate potential trade-offs between survival and quality of life in advance directives

Decision modeling can demonstrate potential trade-offs between survival and quality of life in advance directives

When patients are critically ill and no longer able to make decisions, advance directives help maintain patient autonomy by allowing them to specify ahead of time the type of care desired. To determine if they could identify patient preferences for quality of life that might make a Do Not Intubate (DNI) versus a Full Code advance directive result in more favorable outcomes, a research team built a decision analytic model (mathematical simulation) comparing Full Code versus DNI in patients with severe chronic obstructive pulmonary disease (COPD), as an example of a highly prevalent chronic disease. The modeled DNI advance directive only allowed noninvasive mechanical ventilation versus the Full Code advance directive that allowed all forms of mechanical ventilation, including invasive mechanical ventilation via an endotracheal tube (ETT).
The simulation revealed that for community dwellers with COPD, Full Code resulted in a greater likelihood of survival and higher estimated quality-adjusted life years (QALYs). When considering patient preferences regarding complications, however, if patients were willing to give up more than 3 months of life expectancy to avoid ETT complications, or were willing to give up more than 1 month of life expectancy to avoid long-term institutionalization, DNI resulted in higher estimated QALYs.
The researchers conclude that advance directive decisionmaking must be informed by the likelihood of outcomes beyond survival alone, such as potential tradeoffs between survival and complications, as well as patients' preferences for these outcomes. Decision analytic modeling can assist with such complex decisionmaking by synthesizing evidence-based data with patient-specific factors to estimate more individualized likelihoods of outcomes and potential tradeoffs. This study was supported in part by the Agency for Healthcare Research and Quality (HS19473).
See "Informing shared decisions about advance directives for patients with severe chronic obstructive pulmonary disease: A modeling approach" by Negin Hajizadeh, MD, Kristina Crothers, MD, and R. Scott Braithwaite, MD, in Value in Health 15, pp. 357-366, 2012.

— MWS