AJMC: ASCO Spotlight With Ravi B. Parikh, MD, MPP: Can Nudges Increase the Number of Serious Illness Conversations in Community Oncology?
From AJMC:
Getting oncologists to speak with patients about their care goals at the start of treatment has been a mission of the quality care movement for years. But matching this with the reality of busy clinic schedules has been a challenge, especially among community oncologists, who typically see more patients than their counterparts in academic medicine.
Yet if conversations about serious illness (SI) or end-of-life (EOL) care are to translate into hospice referrals—or fewer costly, toxic late treatments that won’t work—community practice is where they must happen, according to Ravi B. Parikh, MD, MPP, an assistant professor in the Department of Medical Ethics and Health Policy and Medicine at Perelman School of Medicine, University of Pennsylvania in Philadelphia.
Parikh spoke with Evidence-Based Oncology™ (EBO) during the 2022 American Society of Clinical Oncology (ASCO) Annual Meeting, just before he presented long-term findings from a clinical trial. The trial tested a protocol that prompted oncologists to have SI conversations with patients who were predicted to have a 6-month mortality risk, based on inputs from their electronic heath record (EHR) to an algorithm.
This type of work applies nudge theory, a Nobel Prize–winning concept rooted in behavioral economics that calls for the use of positive reinforcement to influence decision-making. Many health-related applications have involved patient behavior; Parikh’s team applies the concepts to physician behavior.
Parikh’s team at Penn Medicine deployed the protocol, and data first published in JAMA Oncology showed that after oncologists received artificial intelligence–driven prompts at the start of their shift, conversations increased 4-fold, from a rate of 3.4% to 13.5%. As Parikh explained during his ASCO presentation, the protocol was layered with a “kitchen sink” of motivational tools:
- Each week, oncologists were emailed a secure list of how their SI conversations compared with those of their peers.
- Oncologists were sent a secure list each week of high-risk patients on their upcoming schedule who, based on the algorithm, were deemed candidates for SI conversations. The doctors were asked to preselect up to 6 patients per week for conversations.
- Opt-out texts were sent ahead of high-risk patient encounters, on the morning of the clinic visit.