Digital health cannot deliver on its promise without patient activation
When it comes to changing patients’ health behaviour, simply providing them with information is not enough.
"There’s a big gap between knowledge and intention," said Dr Praveen Deorani, senior data scientist at the Singapore Ministry of Health in his session "Data-driven Approach for Patient Activation and Behaviour Change."
He told delegates at HIMSS22 APAC that it was vital to motivate patients so they can become active participants in their own care.
"Health-related behaviours are significantly more important predictors of health outcomes than medical care. What happens at home is more important than what happens in the clinic," explained Dr Deorani. "Even when they know about healthy lifestyle, most patients don’t change their behaviour."
For example, around 20%-50% of patients do not take their medication as prescribed, despite knowing its importance.
"In Singapore, like everywhere in the world, the burden of chronic disease is rising in ageing societies," Dr Deorani continued. "It’s estimated in Singapore that government-related healthcare expenditure will increase more than two-fold."
Digital health has been hailed as a solution to increasing healthcare capacity but without sufficient patient motivation, remote monitoring and other technologies it may not be able to deliver its potential.
Risk communication
The key to empowering patients, according to Dr Deorani, is communicating risk in a way that makes sense to them.
"You have to be able to tell patients their personalised risk factors and what the data means to their health profile," he said. "For example, if you tell someone they have a 17% risk of cardiovascular disease they don’t understand what that really means."
One way of doing this is through Singapore’s ‘heart age’ project which relates the condition of a patient’s heart to age. For example, telling a 30-year-old that they have a heart similar to a 65-year-old may make more impact than simply relaying statistics.
Another issue is that many patients have multiple risk factors or chronic diseases, which can make it difficult to understand what the most impactful intervention is for them.
The MOH is trying to address this challenge through the use of personalised models based on machine learning which predict the risk over time for multiple diseases. This data-driven model is now in the back end of a tool being trialled in Singapore which can be used to educate patients about their clinical profiles.
However, Dr Deorani added that educating patients during clinic visits is not enough on its own.
"There has to be a way of continually educating and engaging the patient," he said.
To achieve this, Singapore has rolled-out digital health programmes for patients with hypertension, heart attack, and schizophrenia using telemonitoring tools which consider their clinical risk, psychometric profile, and history. The tool also provides patients with automated personalised reminders, lifestyle coaching, and access to clinicians.
"Patients are always a resource if they participate in their health management and we can empower them to take care of their own health," concluded Dr Deorani.