Healthcare Apps And Behavioural Science — Maybe Its Time?
Patient engagement is a perennial problem, perhaps thats about to change.
You are inherently irrational.
Now, before you scramble to leave this page and vow to never engage with my posts again, lets test out that statement:
Why is it, that you selected option 1 in the first scenario, yet chose option 2 in the second?
This question and many other peculiarities have been pondered by some of the greatest minds within behavioural science. From the initial works of Kahneman and Tversky to Malcom Gladwell’s most recent book: Talking to Strangers. The conclusion, it turns out, is that humans are intrinsically difficult to understand. Ironically, however, our irrationality is systematic.
(If you’re still wondering, the above scenario can be explained by prospect theory — a phenomenon which states that individuals make decisions based on perceived gains instead of perceived losses.)
A broader question arises: how many of these cognitive biases exist and what impact do they have on our day to day lives?
Well, behavioural scientists describe a variety. Estimates range from 25 to 104, with finance, big tech and others applying these techniques to influence the way we interact with their services. (Social media companies and the gaming industry have truly mastered this wizardry).
Meanwhile, over in the healthcare industry, there are a plethora of issues related to patient engagement. For instance, medication adherence is at a mere 50%, and thought to result in a staggering 100,000 preventable deaths per year.
Behavioural science may be the answer, and whilst some attempts have been made, in day to day practice, examples are few and far between. But perhaps this is about to change, with over 45,000 medical apps attempting to deliver more personalised care. In particular, some movers and shakers are adopting behavioural techniques to drive engagement and retention. Sadly however, recent research suggests that the delivery leaves much to be yearned.
What then, can developers of healthcare applications do to utilise these methods?
Well, rather conveniently, three methods to optimise the use of behavioural techniques are outlined below:
Patient Understanding — determining prior knowledge
Behavioural Segmentation — targeting based on user motivations
Behaviour Based Incentives — providing personalised rewards
1. Patient Understanding
Patients often think they are significantly healthier than they are. 76% of patients with high risk conditions described their health as either excellent, very good or good. What that means in practice is that many interventions fail to alter health behaviours (often through attracting individuals already cognisant of their condition).
And for those that think everything is fine and dandy, they simply aren’t interested. As such, it is important to understand the users prior knowledge, in order to facilitate tailored interventions depending on their needs.
Summary: understand the user and determine their prior knowledge to effectively plug the gap
2. Behavioural Segmentation
Often in healthcare, we categorise patients by their condition. There’s the patient with a nosebleed in bed three and the heart failure patient in bedfifteen (no idea why they are on the same ward, but it happens). Unfortunately, this often extends into their care, with a one size fits all process to their management.
Thus, there is a need to move beyond this basic categorisation, especially when it is delivered through a digital medium. We need to understand not just a patients demographics, but an individual’s behaviour, motivation and personal circumstances. Only then can we offer appropriate behaviour based incentives…
Summary: go beyond the basics, what drives the users motivations and behaviours?
3. Behaviour Based Incentives
This brings us to the Behaviour Change Technique Taxonomy (what a mouthful). This documents all of the cognitive methods used to nudge users to a specific goal. So, by knowing an individuals prior knowledge and appreciating what makes them tick, we can use cognitive biases to personalise rewards. A select few are outlined below:
By utilising these cognitive biases, we can create behaviour based incentives such as:
providing feedback on a patients’ health
agreeing behaviour dependent health goals
offering rewards for obtaining achievements
These are by no means exhaustive, but they provide an exciting flavour of what is yet to come.
Summary: experimenting with behavioural based incentives can reap rewards, gaining loyalty and hence user retention
So, behavioural science is all rosy, right? Well maybe not. There is an argument that exploiting these biases may be manipulative, especially when used in excess. It’s important not to understate this, particularly within healthcare — a highly regulated and autonomy focused field.
As such, the following guidelines by Innovia Technology should be considered when venturing into these quarters:
Behavioural interventions built on untruths aren’t acceptable
Nudges that make it difficult for people to choose otherwise are unethical
Behavioural interventions should be scrutinised for unintended, as well as intended, consequences
Consent should not be hidden, and transparency is necessary
Creators should be comfortable to defend their approach, methods and motives in public
It’s evident that behavioural science has great potential to improve patient engagement and encourage preventative care. Yet, in healthcare, it’s still within its infancy, so best practices and effective techniques are elusive.
Moving forward, it is clear that if we are truly committed to a proactive healthcare system, then there is a need to shift the narrative from ‘one size fits all’ to an individualised behavioural based approach. Ultimately, resulting in stickier and more efficacious healthcare products and services.