Nudging our white coats

The first question looks for anomalies on the patient’s electrocardiogram. If anomalies are found, patients are sent straight to the CCU. If not, a second question asks if the patient’s primary complaint is chest pain and a final question checks if five other factors are present.

They compared their simple decision-tree with an existing, more complex decision-tool; the Heart Disease Predictive Instrument (HDPI) where doctors need to check for the presence, absence and combination of seven symptoms and match findings to a chart containing around 50 probabilities and then calculate a logistic regression using a calculator to determine if a patient should be admitted…. Sounds complicated doesn’t it?! No surprise then that many doctors didn’t like using it. But how accurate was it compared to Green and Mehr’s decision-tree?

The simple decision-tree was more accurate. 95% of diagnoses were correct compared to only 70-80% using the more complex HDPI tool. Moreover, doctors also preferred using it; it’s easy to remember and simple to apply, and, significantly, it was better suited to the time-stretched, cognitively demanding context in which they worked.

Improving patient care by changing the default treatment

Another trial drawing on behavioural science has also succeeded in improving cardiac patient care.

The Nudge Unit at Penn Medicine Center, University of Pennsylvania, increased rates of referral for cardiac rehabilitation (known to reduce mortality by as much as 30% in high-risk patients) from 15% to over 80% simply by making referral the default for all patients.

Qualitative research in the form of interviews with cardiologists revealed that the existing referral process was manual, so they had to take action to initiate the referrals, opting patients in.  Redesigning the process as an opt-out system led to far better treatment and quality of care for patients whilst retaining freedom for clinicians to opt out of the default if they did not think rehabilitation was necessary.

Reducing costs by making generics the default prescription

Healthcare institutions are continually striving to balance quality of patient care with cost efficiency. One clear area of cost saving comes from the prescription of generic drugs - chemically identical to the branded or proprietary versions, just as effective and yet usually a fraction of the price. Given that doctors write hundreds of prescriptions each week from a wide range of treatment drugs, these costs can quickly add up.

In the NHS, generic prescribing has been rising since 1976 and stood at 84% in 2015. The Kings Fund estimates this has saved the NHS around £7.1 billion in total. However, they calculate there is still room for improvement, with potential for rates to rise to 90%, especially as there is variation between general practices. In the US, generics prescription rates stand at 89% on average but again, could be higher. In a society where the payment often falls on the patient, generics use plays an even more important role since patients are nearly three times more likely to abandon a branded medication because of the high cost.

To encourage more generics prescription, Mitesh Patel, Director of The Nudge Unit at Penn Medicine Center recently trialled a tiny tweak to the prescription order system on the University of Pennsylvania Electronic Health Record system. When doctors there select the drug they want to prescribe they click on a drop down menu. Previously, branded drugs were listed at the top of that menu and generics at the bottom. Patel flipped the order so that generic drugs were listed first. It had an astounding effect. Before the trial, the generics prescribing rate at Penn Medicine was around 75.0%. Immediately after the change in the drop down order, the generic prescribing rate increased rapidly to 98.4% and remained there for the ten-month test period.

Why might this tiny change have had such a big impact?

Sometimes the order in which items are listed can have subconscious effects on our decision-making.

For instance, it may be that doctors presumed the medical community’s preferred choice of drug was the one listed first. Or perhaps, short of time and energy, they scrolled down to the first drug they saw that matched what they were looking for and looked no further.

Patel comments “...it required only a minor modification to the order entry system. It took very little effort, but will probably save millions of dollars over the next few years for patients, insurers and the health system.” Whilst he admits that one of the biggest barriers to these kinds of interventions is that many clinicians are resistant to change and the concept of being ‘nudged’, he counters that “we often don't realize that we are already being nudged by the design and choice architecture of whatever electronic health record system we are using. It influences our choices every day, but often this is overlooked."

Conclusion

The examples provide a snapshot of just a few of the simple, low-cost, yet astoundingly effective initiatives leveraging behavioural science to improve patient care by improving clinician decision-making.  Moreover, we may soon see more units like the Penn Nudge Unit, currently one of its kind, working to integrate behavioural science into medical processes and IT systems. Whilst AI-assisted healthcare is taking the limelight, BE-assisted healthcare may be equally deserving of some attention!

How BE is transforming our lives 24/7 series - article 6