Can a Decision Model Lead to Higher Patient Satisfaction Among Terminally Ill Patients?

A prospective cohort study of patients with terminal illness showed that when faced with the decision of either continuing potentially curative or life-prolonging treatment or of initiating end-of-life hospice care, patients may experience better satisfaction with their care and treatment choices if they use a regret-based decision model to clarify their preferences.

“The decision process in [these] situations is heavily affected by emotions, chief among them is regret,” the researchers, led by Benjamin Djulbegovic, MD, PhD, from the Departments of Hematology and Health Outcomes & Behavior at the H. Lee Moffitt Cancer Center & Research Institute in Tampa, Florida, said, explaining the choice to focus on regret in their decision model. “Modern cognitive science increasingly accepts a dual-processing approach to human cognition that takes into account both emotion-based and analytical-based cognitive processing. Because regret is a human emotion that involves counterfactual deliberations, we propose that it can activate both cognitive domains by serving as a link between [emotion- and analytical-based] processes.”

Dr. Djulbegovic and authors assessed 178 adult patients with a terminal disease seen at the Tampa General Hospital and the Moffitt Cancer Center between March 2013 and December 2015 to determine if a decision model based on regret would help patients clarify their end-of-life preferences and facilitate decisions about hospice.

The study had four parts:

  1. The patient’s probability of survival at six months was calculated, then communicated to patients in three forms (as a percentage, in a pictorial model, and as life expectancy in days).
  2. Patient preferences for continuing treatment versus accepting hospice care were elicited.
  3. Researchers determined the threshold at which each patient was likely to be indifferent to either choice. This threshold was then contrasted against the previously estimated survival probability to suggest a patient-specific management plan, which was later compared with the patient’s actual choice.
  4. Each patient was asked a series of qualitative questions to evaluate the usefulness of the regret-based decision model in the hospice referral process.

The majority of patients reported that the information provided by the model in step 2 was helpful (96%; n=171/178) and stated that it would influence their care decision (90%; n=160/178).

The model was also “descriptively and predictively valid,” the researchers wrote. Most patients (85%; n=151/178) agreed with the model’s recommendations (provided in step 3) to either accept hospice care or continue with current treatment (p<0.000001), and the regret-based model predicted the actual choices for 72 percent of patients (n=128/178; p<0.00001).

Patients’ initial inclination to choose hospice referral and the decision model’s recommendation of hospice (rather than continuing treatment) were the two factors with the strongest predictive probability (~98%) of patients choosing end-of-life hospice care. Other factors (including age, gender, race, education status, and pain level) had no effect on patients’ actual treatment choices.

“We found that people suffering from a terminal disease who are initially inclined to choose hospice and do not regret such a choice will select hospice care with a high level of certainty,” Dr. Djulbegovic said.


Reference

Djulbegovic B, Tsalatsanis A, Mhaskar R, et al. Improving hospice referral: application of regret-based decision modeling at end-of-life care. Abstract #535. Presented at the 2016 ASH Annual Meeting, December 4, 2016; San Diego, California.

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