Precision and population health to enable personalised interventions

When newly born Lucy began experiencing seizures, a range of standard medical tests were unable to identify the cause for months. It took a genetic test to discover that she had a rare mutation that only 300 people in the world had, opening the doors to developing a cure.

This is one example of how the Children’s Hospital of Philadelphia, one of the world’s largest pediatric hospitals turned their data bane into a data boon by tapping on Amazon Web Services (AWS)’ HealthOmics, a data sharing and analytics platform.

With the cloud platform, they were able to harmonise diverse datasets and tap on artificial intelligence (AI) to analyse rare conditions, compare them against population data, and develop personalised treatments for young children – what is known as precision health.

The healthcare sector produces almost one-third of the world’s data volume, but it can be difficult for healthcare institutions to use that data meaningfully and provide relief for patients who require personalised interventions.

At the recent GovInsider Live Healthcare Day event, Singapore public healthcare and AWS speakers made the case for healthcare sector to take a precision approach to achieve broader population goals, supporting Singapore’s data-driven population health programme, Healthier SG.

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Providing personalised support

National Cancer Centre Singapore (NCCS)’s Head of the Cancer Genetics Service and Senior Consultant in the Division of Medical Oncology, Associate Professor Joanne Ngeow, shared that patient adherence to cancer screening increases when they are presented with precision data about themselves.

“When they know they are at increased risk of cancer, patients are more willing to comply with screening... once you can let people know why it's important to them personally, they're much more likely to take action,” she said.

She was speaking on a panel titled Population health and precision health: Enabling transformation in public health.

Tan Tock Seng Hospital (TTSH)’s Senior Consultant (Public Health), Dr Clive Tan, similarly shared that in the future, healthcare professionals may use AI-powered software to provide personalised medical advice for patients, but he cautioned that models need to be trained on culturally relevant datasets to avoid situations where the medical advice is culturally inappropriate.

Enabling data-driven efforts

When it comes to data-driven policymaking, accessibility and understandability of data are very important factors as most people find data complicated.

Data harmonisation and AI are key to generating actionable insights for clinicians and patients.

Given limited resources in the healthcare setting, Changi General Hospital (CGH)’s Deputy Chief Medical Officer, Dr Charlene Liew, said that leveraging data and AI can also help to better optimise resources and allocate them to specific groups in society who need it the most.

As big data becomes more available and new technologies gradually come online, Singapore’s public sector healthcare clusters will develop more capability and capacity to “do targeted interventions on [their] catchment population” added Dr Tan.

In the Healthier SG era, the clusters have become "regional health managers", with the mandate and responsibilities to care for residents in their geographical area, Channel NewsAsia previously reported.

As both population health and precision health require the analysis of large amounts of healthcare data, cloud platforms like AWS can provide a secure, scalable infrastructure that allow healthcare leaders to perform complex research across large amounts of diverse data.

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Public health enablers of precision approach

A trusted data sharing environment and data interoperability remain key challenges for the public healthcare sector, said the speakers.

On the topic of data sharing, TTSH’s Dr Tan explained that most data sharing starts with bilateral sharing.

But as institutions move to “more mature modes of [data] sharing,” stakeholders will need an entity within the group to be responsible to set up a “high-trust environment” to better facilitate data sharing.

CGH’s Dr Liew shared that a high-trust data sharing environment is “achievable” thanks to national data exchange platforms set up by the government for researchers and clinicians.

One such platform is the Trusted Research and Real world-data Utilisation and Sharing Tech (TRUST) that aims to enable health-related research and anonymised data sharing between public institutions, as well as between public and private sectors.

The platform was developed as part of Singapore’s National Precision Medicine programme, which aims to implement precision medicine on a large scale and develop comprehensive Singaporean genomic databases by 2030.

Enabling collaboration across healthcare

NCCS’ Assoc Prof Ngeow emphasised the importance of a “feedback loop” between researchers and clinicians to get data to the frontline of healthcare delivery.

Synapxe’s HEALIX, a cloud-based analytics platform that connects existing public health data infrastructures to support data sharing and discovery, was highlighted as an enabler for more collaborations between researchers, clinicians and private sector innovators.

GovInsider recently covered the opening of Synapxe’s innovation lab, and how HEALIX helps to secure innovation efforts in the sector.

There are other use cases for AI when it comes to preventive healthcare, and public education will be crucial to bring about higher adoption rates for the use of AI in this field.

For instance, AI can help doctors explain their medical results in simple terms to patients. The technology can also be weaved into wearables to nudge the patients towards healthier behaviors.