Innovation Booster Digital Health Nation

Switzerland’s upcoming transition from the legacy TARMED tariff system to TARDOC and outpatient flat rates (ambulante Pauschalen) will fundamentally reshape how outpatient medical services are documented, coded and reimbursed as of 1 January 2026. This change is more than administrative — it demands a transformation in how healthcare providers document and code patient interactions.

TARDOC and outpatient flat rates introduce new layers of billing logic: the billing outcome for a case depends not only on what was done, but also on when it was done, which insurance type was involved, and which organ system the case relates to. If the codes are incomplete or the case is not grouped correctly, it may not qualify for flat-rate reimbursement or even be ultimately rejected. The logic is strict, and errors can lead to underbilling, compliance risks or delays in reimbursement.

After care is delivered to a patient, hospital IT systems assemble billing-relevant information into a structured format. At KSBL and many other Swiss hospitals, this is done using ALIS, a standardized data interface that packages key service and diagnostic information. The ALIS format does not include full clinical documentation; instead, it captures essential metadata such as performed services, timestamps and department codes. This dataset eventually lands on the desk of the coding team, which assign billing codes retrospectively.

This is where AI can make a tangible impact. The right solutions can act as a validation layer between ALIS data export and coding – analyzing structured data to reduce manual work, increase coding accuracy, and enable hospitals to navigate the new TARDOC and outpatient flat rate environment by, for example:

Crucially, AI can do this before the case reaches final billing — catching issues while they are still easy to correct.

By building usable AI tools that support coders within the new reimbursement process, participants will contribute not only to smoother hospital operations, but to a more transparent and efficient Swiss healthcare system overall. The solutions co-created within the framework of this Challenge can become the foundation for broader adoption across the country as these new reimbursement models take hold.

Challenge participants will receive a detailed overview of KSBL’s reimbursement workflows, user journeys, and IT system requirements.

Interested in learning more about the upcoming switch to TARDOC and outpatient flat rates? Join our events and check out the links below:

Meet the projects selected for this challenge

ALIS Transformer (led by d-fine)
The ALIS Transformer tool provides hospitals with an efficient solution for ensuring accurate and comprehensive data for billing processes without disrupting existing workflows and infrastructure. By offering this advanced technological support, hospitals can maintain high coding quality in outpatient services with minimal additional resources.

KODIQ (led by MediData)
An AI powered tool for validating the completeness and quality of outpatient coding under TARDOC and ambulatory lump sum tariffs.
KODIQ detects missing or inconsistent ICD10 codes, checks grouping and trigger logic, and suggests corrections or completions. This supports hospitals to prevent coding errors before billing, reducing rejections and revenue losses.

AmbuCody (led by Swisscoding)
To support hospitals in the 2026 transition to TARDOC and flat-rate outpatient billing, KSBL and Swisscoding Technologies are developing an AI-powered solution that accurately validates and predicts the newly required ICD-10-GM diagnosis codes. The system directly addresses one of the key administrative challenges of the reform, helping ensure that outpatient coding is accurate, efficient, and fully compliant with the new regulations.

Tar.ai (led by Codepan)
An AI-powered pre-billing validation tool designed to help healthcare providers ensure coding accuracy and compliance, reducing manual work. It automatically checks ICD-10, LKAAT, and TARDOC code combinations, detects missing or invalid codes, and suggests corrections with confidence scores, flagging high-risk cases.

CareBoost (led by Prognosix)
CareBoost brings AI-powered scanning and documentation to the bedside, freeing time for what matters most: safe, effective care.

What Innovation Booster support is available?