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Taiwan health insurance authority cuts drug review time 99%+

BCT helped a Taiwan health authority turn precedent-heavy drug review into AI-assisted decision support.

Taiwan health insurance authority cuts drug review time 99%+

Client

Challenge

For a national health insurance authority in Taiwan, every new drug application carries consequences well beyond one file. The authority decides which new pharmaceutical products enter a single-payer reimbursement system covering virtually the entire population. Each decision therefore has public-health, budgetary and policy implications, and must remain defensible against decades of precedent.

The review process made that standard difficult to sustain at scale. Reviewers had to determine whether comparable products already existed in the reimbursement system, then reconcile each application against historical records and prior government rulings. They performed that evidence gathering manually, document by document.

A single review commonly took more than three months. At the same time, applications continued to arrive, while review capacity could not grow at the same rate. Consistency also depended heavily on what an individual reviewer could recall from past cases. The risk was not simply delay. A slow evidence-gathering cycle could create an approval backlog for new therapies and leave scarce expert capacity tied up in retrieval rather than judgment.

Solution

The authority introduced an AI-based decision-support system designed around the part of the review that consumed the most time: finding and comparing evidence.

BCT designed and delivered the system using retrieval-augmented generation (RAG) and an AI agent. A reviewer uploads a new drug application. The system searches the authority’s own historical database for relevant prior records and related government rulings, then compares the application against that historical corpus.

The output is structured around the evidence a reviewer needs to assess the case. It identifies comparable products and applicable precedents and presents a preliminary analysis. The end-to-end data flow is automated, replacing the document-by-document retrieval process with a repeatable evidence-gathering workflow.

The architecture also respected the regulatory decision itself. The system does not make the final reimbursement determination. It supplies decision support, while the reviewer retains full authority over the final decision. That distinction matters in a public-sector setting where traceability and accountable human judgment are part of the process, not an afterthought.

The most important design choice was to ground the analysis in the authority’s own precedent base rather than generic external knowledge. That lets reviewers work from the records and rulings that actually govern their decisions. A local delivery team also worked within the customer’s language, regulatory context and document conventions.

Impact

The change was measured in the time it took to reach a preliminary analytical result. The data-analysis stage fell from more than three months to approximately 15 minutes, reducing elapsed time to a preliminary result by more than 99%.

Manual document-comparison effort was effectively eliminated. Skilled reviewers could therefore spend more of their capacity on judgment and policy assessment instead of locating and comparing records.

The process also became more consistent. Each review is assessed against the full historical record available to the system, rather than only the precedents an individual reviewer happens to remember.

For the authority, the outcome is not an automated policy decision. It is a materially faster and more systematic evidence base for the people who make that decision. The technology accelerates the search and comparison work while leaving statutory authority where it belongs: with the reviewer.

Office location

148, Rajiv Gandhi Salai(OMR), Okkiyam Thoraipakkam, Chennai - 600 097

Phone number

+91 44 43449000,
+91 44 61739000

Email address

talktous@bahwancybertek.com

Bahwan CyberTek is a global technology transformation partner, driving innovation and equipping companies for the future.

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