This article was co-authored with Dr. Kelvin Loh, Group Chief Healthcare Officer, AIA.
Asia has made progress in recent years in shifting towards value-based approaches to healthcare. These include bundled pricing, negotiated fees, and other ways of risk-sharing between payors and providers. These changes are necessary to put healthcare systems on a stable long-term footing. But they are just a start if healthcare systems are to evolve to meet the long-term challenge of caring for ageing populations amid rising medical inflation.
Deeper and more systemic change is needed and is possible with better management and analysis of the enormous volumes of data that Asia’s healthcare systems generate. At present, how this data is captured, coded, and used remains sub-optimal and varies widely across hospitals, markets, and payors. Too often it is fragmented, inconsistent, or incomplete. Insurance claims in Asia frequently arrive as high-level summaries, offering little visibility into what treatment was delivered, which makes assessing the cost and appropriateness of care difficult for insurers and other payors.
Change is underway. AIA has partnered with Amplify Health to implement a consistent approach for capturing, structuring, standardising, and enriching data to provide a region-wide view of healthcare costs and patterns of treatment. This approach is enabling a shift from fragmented information towards a more integrated understanding of customers’ interactions with healthcare systems: care received, costs incurred, and outcomes experienced.
Ultimately, this increased visibility has the potential to improve both health outcomes and health system efficiency. For AIA, it will help us fund more affordable, accessible, and effective care to customers. At a system level, it will allow us to work with our healthcare provider partners on a transparent basis to negotiate risk-sharing arrangements based on real-world data—outcomes, quality, effectiveness of care—with the potential to shift care in our markets further in the direction of more sustainable, value-based models.
The impact will be region-wide. AIA has rolled out this data approach across our largest markets with private healthcare systems—Hong Kong, Malaysia, Singapore, Thailand—as well as Indonesia and the Philippines. Through its work with stakeholders across the healthcare value chain—including other major insurers like Star Health in India, Muang Thai Life in Thailand, and Singlife in Singapore—Amplify Health is helping to build a modern health information system for Asia that enables payors, providers, and policymakers to understand variation in care, identify drivers of value, and take aligned action.
From fragmented data to actionable insights
The approach AIA and Amplify Health have developed transforms largely unstandardised data into usable insights. It brings information from claims, underwriting, providers, and wellness programmes into a unified model. It can be used to improve product design and chronic disease management for our customers while giving healthcare providers transparent views on how their own patient populations compare to similar hospitals in terms of complexity, costs, and other outcomes.
At its core is the concept of critical data elements: the specific pieces of information needed to generate meaningful insights. These include everything from basic claims data such as amount paid and date of admission to diagnosis, provider information, insurance product and drug details. Bill amounts allow us to compare costs. Provider information includes location to allow for geographic analyses. Altogether, we have identified hundreds of critical data elements for over a dozen categories of information.
We capture this data from medical documents, invoices, and discharge summaries and then anonymise and translate it into standardised formats, including clinical codes. We then perform the necessary data quality checks to ensure consistency and comparability. The result is that healthcare data that was once opaque becomes structured, comparable, and actionable.
Making healthcare more visible and more efficient
One of the most immediate applications is claims management. Today, claims processing often has manual interventions, is time-consuming, and prone to inconsistency. By contrast, a standardised data foundation allows for increasing automation.
With more detailed, line-level data from providers where available—capturing individual treatments, procedures, and medications—claims can be processed faster and more accurately. This shortens turnaround times for customers. It might take only seconds or minutes to approve a claim today instead of hours or days previously.
Line-level data can also be used to identify unwarranted variations in medical care—different costs for the same equipment or drug, under-delivery of care, or ineffective or inappropriate care. Instead of seeing only summarised claim amounts, AIA can understand what care was delivered, how it was delivered, and whether it aligns to local market clinical pathways. With improved visibility, AIA can better appreciate medical care in context, and identify claims for services that are potentially wasteful or fraudulent. This creates a foundation for more consistent claims adjudication and better cost management.
But the goal goes beyond cost control.
Fostering alignment through transparency
An important outcome of our approach to using data is greater alignment of interests between payors and providers. With more detailed and standardised data, it becomes possible to identify variations in treatment patterns, resource utilisation, and outcomes across providers. This allows intra-hospital, inter-hospital, and inter-country comparisons and supports more constructive, data-driven dialogue around best practices and appropriate care.
We share our data with hospitals providing a benchmark for them to see how they compare to local hospital peers. We can then use these discussions to negotiate more value-based payment models.
The outcome of these negotiations is a more sophisticated provider network. By understanding which providers consistently deliver high-quality, cost-effective care for the complexity of cases they handle, AIA can give more informed choices to customers. On an aggregate level, this could improve overall system efficiency.
The analysis that we use to develop our networks takes into consideration factors such as location, intervention, and comorbidities which require more intensive treatment. This approach means we are not simply focusing on lower cost providers, but fine-tuning the understanding of costs in the correct clinical context and ensuring that comparisons are normalised to a like-for-like basis.
Detailed line-level data is the key. To that end, AIA is working with healthcare providers across the region to establish a basis for greater sharing of line-level data, a practice that benefits the entire healthcare system. It makes waste easier to identify, variation easier to interpret, and claim decisions easier to explain. In that regard, it should be in everyone’s interest.
Establishing a common data foundation across Asia
Healthcare systems in Asia are diverse, and our approach is designed with this in mind. It defines a common and evolving “target state” for data and analytics, while allowing for phased adoption and local adaptation.
This balance is critical. While healthcare delivery remains local, a shared data foundation helps raise the overall standard across markets. It can fill gaps where information and capabilities may be limited and lead to more consistent experiences for customers.
Ultimately, this effort is about building the systems and infrastructure for a more robust and sustainable healthcare system. By making healthcare insights more accessible and more accurate, we enable better decisions for customers navigating their care, for providers delivering treatment, and for policymakers shaping healthcare systems.
In doing so, we are laying the groundwork for healthcare across Asia that is more integrated, sustainable, and affordable.
