Topics: behavioral science

Essay by Crawford Hollingworth and Liz Barker: “…Both of these stories are illustrations of what many mums and gym–goers may have experienced across the United Kingdom and United States as they tried to cope with the pandemic. We, along with other behavioral scientists, would label both as sludge—when users face high levels of friction obstructing their efforts to achieve something that is in their best interest, or are misled or encouraged to take action that is not in their best interest.

We can think of what the English mum goes through as unintentional sludge—friction due to factors like rushed design, poor infrastructure, and inadequate oversight. The mother is trying to access a benefit that will help her and which she has a right to claim, and which the government genuinely wants her to access. Yet multiple barriers prevented her from accessing the voucher that would help feed her children. Millions of parents found themselves in this situation as schools closed in England earlier this year. All over the country schools ended up paying for food parcels and gift vouchers out of their own budgets to help families who were going hungry.

What the New York gym-goer faces is different. It is intentional sludge—friction put in place knowingly to benefit an organization at the expense of the user. The gym doesn’t want him to cancel the membership, which would mean lost revenue. Even absent the pandemic, the policy would be considered unnecessarily difficult to cancel. The gym’s hope is that people forget, give up, or don’t bother canceling in person or over the phone, or that it takes them longer to do so. This translates into revenue for them, without any of the costs of providing a service. Stories like this have resulted in class-action lawsuits against companies that make it overly difficult or impossible to cancel gym memberships. One lawsuit alleged that one large gym company was stealing over $30 million per month from customers….(More)”.

Article by Ravi Parikh et al: “When conversations about goals and end-of-life wishes happen early, they can improve patients’ quality of life and decrease their chances of dying on a ventilator or in an intensive care unit. Yet doctors treating cancer focus so much of their attention on treating the disease that these conversations tend to get put off until it’s too late. This leads to costly and often unwanted care for the patient.Related: 

This can be fixed, but it requires addressing two key challenges. The first is that it is often difficult for doctors to know how long patients have left to live. Even among patients in hospice care, doctors get it wrong nearly 70% of the time. Hospitals and private companies have invested millions of dollars to try and identify these outcomes, often using artificial intelligence and machine learning, although most of these algorithms have not been vetted in real-world settings.

In a recent set of studies, our team used data from real-time electronic medical records to develop a machine learning algorithm that identified which cancer patients had a high risk of dying in the next six months. We then tested the algorithm on 25,000 patients who were seen at our health system’s cancer practices and found it performed better than relying only on doctors to identify high-risk patients.

But just because such a tool exists doesn’t mean doctors will use it to prompt more conversations. The second challenge — which is even harder to overcome — is using machine learning to motivate clinicians to have difficult conversations with patients about the end of life.

We wondered if implementing a timely “nudge” that doctors received before seeing their high-risk patients could help them start the conversation.

To test this idea, we used our prediction tool in a clinical trial involving nine cancer practices. Doctors in the nudge group received a weekly report on how many end-of-life conversations they had compared to their peers, along with a list of patients they were scheduled to see the following week who the algorithm deemed at high-risk of dying in the next six months. They could review the list and uncheck any patients they thought were not appropriate for end-of-life conversations. For the patients who remained checked, doctors received a text message on the day of the appointment reminding them to discuss the patient’s goals at the end of life. Doctors in the control group did not receive the email or text message intervention.

As we reported in JAMA Oncology, 15% of doctors who received the nudge text had end-of-life conversations with their patients, compared to just 4% of the control doctors….(More)”.