A theoretical decision model to help inform advance directive discussions for patients with COPD

Other Ways of Knowing

BACKGROUND

Patients with advanced-stage chronic obstructive pulmonary disease (COPD) may suffer severe respiratory exacerbations and need to decide between accepting life-sustaining treatments versus foregoing these treatments (choosing comfort care only). We designed the InformedTogether decision aid to inform this decision and describe results of a pilot study to assess usability focusing on participants' trust in the content of the decision aid, acceptability, recommendations for improvement, and emotional reactions to this emotionally laden decision.

METHODS

Study participants ( N = 26) comprising clinicians, patients, and surrogates viewed the decision aid, completed usability tasks, and participated in interviews and focus groups assessing comprehension, trust, perception of bias, and perceived acceptability of InformedTogether. Mixed methods were used to analyze results.

RESULTS

Almost all participants understood the gist (general meaning) of InformedTogether. However, many lower literacy participants had difficulty answering the more detailed questions related to comprehension, especially when interpreting icon arrays, and many were not aware that they had misunderstood the information. Qualitative analysis showed a range of emotional reactions to the information. Participants with low verbatim comprehension frequently referenced lived experiences when answering knowledge questions, which we termed "alternative knowledge."

CONCLUSIONS

We found a range of emotional reactions to the information and frequent use of alternative knowledge frameworks for deriving meaning from the data. These observations led to insights into the impact of lived experiences on the uptake of biomedical information presented in decision aids. Communicating prognostic information could potentially be improved by eliciting alternative knowledge as a starting point to build communication, in particular for low literacy patients. Decision aids designed to facilitate shared decision making should elicit this knowledge and help clinicians tailor information accordingly.

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

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.

Informing shared decisions about advance directives for patients with severe chronic obstructive pulmonary disease: a modeling approach

OBJECTIVE

To estimate the survival and quality-adjusted life-years (QALYs) of Full Code versus Do Not Intubate (DNI) advance directives in patients with severe chronic obstructive pulmonary disease and to evaluate how patient preferences and place of residence influence these outcomes.

METHODS

A Markov decision model using published data for COPD exacerbation outcomes. The advance directives that were modeled were as follows: DNI, allowing only noninvasive mechanical ventilation, or Full Code, allowing all forms of mechanical ventilation including invasive mechanical ventilation with endotracheal tube (ETT) insertion.

RESULTS

In community-dwellers, Full Code resulted in a greater likelihood of survival and higher QALYs (4-year survival: 23% Full Code, 18% DNI; QALYs: 1.34 Full Code, 1.24 DNI). When considering patient preferences regarding complications, however, if patients were willing to give up >3 months of life expectancy to avoid ETT complications, or >1 month of life expectancy to avoid long-term institutionalization, DNI resulted in higher QALYs. For patients in long-term institutions, DNI resulted in a greater likelihood of survival and higher QALYs (4-year survival: 2% DNI, 1% Full Code; QALYs: 0.29 DNI, 0.24 Full Code). In sensitivity analyses, the model was sensitive to the probabilities of ETT complication and noninvasive mechanical ventilation failure and to patient preferences about ETT complications and long-term institutionalization.

CONCLUSION

Our model demonstrates that patient preferences regarding ETT complications and long-term institutionalization, as well as baseline place of residence, affect the advance directive recommendation when considered in terms of both survival and QALYs. Decision modeling can demonstrate the potential trade-off between survival and quality of life, using patient preferences and disease-specific data, to inform the shared advance directive decision.