What U.S. healthcare can learn from Southeast Asia about building a digital foundation
By David Lareau, President and CEO, Medicomp Systems
LinkedIn:Â David Lareau
LinkedIn:Â Medicomp Systems
Health systems in the U.S. are no strangers to the slow pace of new IT implementations. For example, an electronic health record (EHR) implementation can drag on for years before the official go-live date and still not be fully implemented.
Compare that experience to Southeast Asia and other global markets where hospitals are implementing enterprise-wide clinical systems in under a year, even achieving advanced Electronic Medical Record Adoption Model (EMRAM) certifications in the process. EMRAM, developed by HIMSS, is an eight-stage framework that measures how advanced a hospital’s electronic records are, with Stages 6 and 7 signaling not just digital maturity but the use of analytics, decision support, and structured data to improve outcomes.
The difference comes down to priorities. Hospitals in Southeast Asia focus on structured data, team-based care, and clear benchmarks rather than designing documentation primarily around billing. By starting with fundamentals that empower clinicians, these health systems accelerate adoption and improve outcomes. U.S. leaders can apply the same principles in their own organizations to shorten timelines, strengthen data foundations, and prepare for responsible use of emerging technologies like artificial intelligence.
Why Global Systems Move Faster
One reason Southeast Asian hospitals move faster is cultural alignment. From the outset of a project, leadership mobilizes hundreds of staff across disciplines, ensuring physicians, nurses, and administrators are united around a shared goal. This collective approach to change management reduces delays and speeds adoption.
Another reason is financial pressure. In Southeast Asia, hospitals often compete in the medical tourism market, where international patients look for providers with global recognition. EMRAM certification has become a critical credential and a direct path to growth and prestige. That clarity of purpose creates urgency that shortens timelines.
Structured Data as a Cornerstone
A hallmark of faster implementation abroad is the early prioritization of structured clinical data. Instead of designing documentation around revenue cycle management, most hospitals in Southeast Asia standardize data capture across domains—such as symptoms, history, exam findings, and care plans—so the information is immediately useful for both clinicians and analytics.
The National Heart Institute of Malaysia (IJN) illustrates this approach. In 2024, it became the first hospital in Malaysia to achieve EMRAM Stage 6 certification, less than a year after beginning its digital transformation. During the process, adoption of electronic documentation jumped from 40% to 95% in just 90 days, while inpatient paper chart use fell from 100% to 6%. This progress was possible because leaders emphasized workflow redesign, embedded evidence-based guidelines into documentation, and trained teams across specialties to use structured templates from day one.
By contrast, U.S. systems often treat structured data as secondary. Documentation is primarily designed to satisfy payer requirements, leaving little room to design workflows that support clinical decision-making. The result is that clinicians frequently view documentation as a burden rather than a tool.
Setting the Right Priorities
EMRAM certification explains not only why Southeast Asian hospitals move faster but also why their implementations often deliver more clinical value. Similar to Joint Commission International accreditation, EMRAM is seen as a mark of excellence. Hospitals pursuing Stage 6 or 7 must demonstrate not just digital adoption but also outcomes improvement and analytics maturity.
In practice, this forces organizations to build a solid foundation before moving on to more advanced technologies. Instead of chasing trends, they focus first on reliable, structured documentation, data exchange, and decision support. Only then do they layer on predictive analytics, mobile tools, or AI. The sequencing matters: without clean, structured data, no amount of AI will deliver meaningful results.
Clinician Empowerment
Another unique cultural difference is that many health systems in Southeast Asian countries prioritize clinician empowerment and team-based care to accelerate adoption. By embedding protocols, risk assessments, and multidisciplinary documentation tools directly into workflows, hospitals reduce the time physicians and nurses spend on repetitive administrative tasks. Shared documentation views and role-based dashboards allow care teams to collaborate seamlessly.
This approach creates a unified source of truth for the care team, improving efficiency and strengthening patient safety. By contrast, U.S. digital transformation projects often overlook the importance of aligning IT goals with frontline clinical needs, leading to slower adoption and lower satisfaction.
The AI Race
While EHR projects may move slowly in the U.S., health systems are rushing to layer conversational AI interfaces and large language models on top of EHRs, often before resolving fundamental documentation challenges. In Southeast Asia, hospitals are more deliberate. They remain focused on building the structured data foundation that will allow AI tools to succeed.
This sequencing may ultimately enable them to leapfrog the U.S. in AI effectiveness. Once their data is reliable and structured, they will be able to deploy AI in ways that directly improve care coordination, decision support, and patient outcomes—without the frustration of trying to retrofit advanced tools onto weak foundations.
A Cultural Shift
Digital transformation is not about installing technology; it is about aligning incentives, processes, and people to create a foundation for sustainable innovation. U.S. systems can learn from global counterparts’ digital transformations, such as emphasizing structured data, multidisciplinary care, and certification-driven standards. By doing so, they will not only accelerate implementation, but also ensure that emerging technologies like AI deliver on their promise.
It is a model worth studying and one U.S. healthcare leaders should consider if they want to unlock the full potential of digital health.