KAI System – AI-based Semi-Automatic Reimbursement of Medical Services Fees

Overview

The KAI system (Künstliche Intelligenz in der Kostenerstattung) is an artificial intelligence platform deployed by Austria's social insurance system to semi-automatically process reimbursement claims for medical services provided by elective (non-contracted) doctors and therapists. The system was developed by IT-Services der Sozialversicherungen GmbH (IT-SV), the shared IT service provider for Austria's social insurance carriers, with an initial project budget of EUR 2,808,120 and a project duration of 15 months. The primary operational user is the Österreichische Gesundheitskasse (ÖGK), Austria's largest statutory health insurance fund, which processes the majority of cost reimbursement requests nationwide.

In Austria's statutory health insurance system, insured persons who receive treatment from elective doctors or therapists (Wahlärzte/Wahlbehandler) — providers who do not have a direct contract with the health insurance fund — must initially pay for these services out of pocket. They can subsequently submit invoices to their responsible social insurance carrier and receive a partial reimbursement of costs (Kostenerstattung). As of 2017, approximately 5.4 million reimbursement applications were submitted annually across Austria, with volumes increasing at a rate of approximately 8 percent per year. This rising volume, combined with the high manual processing burden, created significant operational challenges: backlogs in processing, high complexity in individual cases, substantial personnel requirements, and the risk of inconsistent decision-making where identical applications could receive different outcomes depending on the individual caseworker.

The KAI system was designed to address these challenges by automating the end-to-end reimbursement workflow from invoice receipt through to approval or rejection, without requiring manual intervention for straightforward cases. The AI pipeline encompasses four core processing steps that were previously performed manually: (1) capture and recognition of submitted documents, including scanned medical invoices, forms, and correspondence from elective practitioners; (2) creation of the processing case in the administrative system; (3) recognition and encoding of medical service positions, including automated ICD-10 diagnosis encoding; and (4) plausibility checks to verify the consistency and correctness of extracted data, including invoice amounts and payment details such as IBAN numbers. The system employs machine learning for document recognition, optical character recognition (OCR) for data extraction, and supervised learning algorithms for diagnosis encoding and plausibility verification. The models are continuously trained and refined based on caseworker feedback and correction data.

The procurement process for the KAI system followed a two-stage competitive procedure. In a preliminary project, IT-SV conducted a negotiated tendering process that identified six bidders considered to be leaders in artificial intelligence. Framework agreements were concluded with all six companies. In the subsequent main project, a renewed call for competition was issued to these six pre-qualified vendors, of which five submitted bids. The best bidder was selected for implementation. The project consortium included IT-SV as project lead, the Hauptverband der österreichischen Sozialversicherungsträger (now the Dachverband der Sozialversicherungsträger), and several regional health insurance funds including the Kärntner Gebietskrankenkasse (KGKK), the Oberösterreichische Gebietskrankenkasse (OÖGKK), the Sozialversicherungsanstalt der gewerblichen Wirtschaft (SVA), the Wiener Gebietskrankenkasse (WGKK), and the Versicherungsanstalt für Eisenbahnen und Bergbau (VAEB). The project was initiated in 2019.

By October 2022, according to ÖGK's annual report (Jahresbericht 2022), two-thirds (66 percent) of reimbursement requests were being processed semi-automatically through the KAI system. The system was intended to enable the social insurance carriers to handle the continuously rising application volumes without requiring proportional increases in staffing. Additional expected benefits included standardised decision-making across cases, improved fairness for insured persons through consistent treatment of identical applications, shorter waiting times for reimbursement, and the ability for individual caseworkers to be relieved of monotonous tasks while receiving support for more complex cases. IT-SV has indicated that the ongoing quantified benefits — primarily time savings in processing reimbursement applications — substantially exceed the ongoing operational costs, including expenditure on further development and continued model training, allowing the initial investment to be amortised through efficiency gains.

However, the system's real-world performance has attracted scrutiny. A 2024 investigation by AlgorithmWatch reported that doubts exist as to whether the KAI system has actually accelerated reimbursement processing. One documented patient case showed that average reimbursement times increased from 27 days in 2021 (based on 15 submitted invoices) to 54 days in 2023 (based on 17 submitted invoices). An ÖGK representative attributed delays to the system's machine learning nature, stating that it was still in a learning phase. IT-SV declined to comment publicly on the system's performance, citing ongoing procurement policies. AlgorithmWatch also noted that Austria's freedom of information law, which was passed in January 2024, would not apply to entities such as IT-SV until 2025, limiting public transparency regarding the system's operational performance and decision logic.

The KAI system operates with a human-in-the-loop oversight model. Controls are built into the processing pipeline at defined value thresholds, for flagged critical cases, and through sampling-based quality checks. Initially, human oversight interventions were frequent and were designed to be gradually reduced as system accuracy improved over time. Caseworkers retain the ability to review and override the system's outputs at multiple points in the workflow. The decision criticality is assessed as moderate: while the system directly affects the speed, accuracy, and consistency of financial reimbursement decisions for insured persons, the amounts involved are partial reimbursements for individual medical services rather than core benefit eligibility determinations, and human review is retained for critical and high-value cases.

The system processes sensitive personal data, including medical invoices containing patient health information, ICD-10 diagnosis codes, and financial data such as IBAN numbers and reimbursement amounts. This data is classified as special category data under the EU General Data Protection Regulation (GDPR) and Austrian data protection law. The system operates under Austria's data protection framework, which implements the GDPR. IT-SV has noted that the KAI platform is also designed for extensibility, with further AI-supported use cases within the social insurance system planned to build upon the existing AI components developed for cost reimbursement. In 2023, IT-SV initiated a new procurement for AI services across six lots via framework agreements, with an execution period from February 2024 to February 2028, reflecting the broader institutional commitment to scaling AI within Austria's social insurance infrastructure. IT-SV's total planned investment in artificial intelligence amounts to EUR 52.5 million.

Classification

Programme Details

Kostenerstattung (cost reimbursement) process within Austria's statutory health insurance system, administered by the Österreichische Gesundheitskasse (ÖGK). Insured persons who receive treatment from elective (non-contracted) doctors and therapists pay out of pocket and subsequently submit invoices for partial reimbursement. The KAI system automates the processing of these reimbursement applications, encompassing document recognition, data extraction, ICD-10 diagnosis encoding, and plausibility checking.

Implementation Details

Risk & Oversight

Deployment & Outcomes

Sources

1. SRC-002-AUT-001 AlgorithmWatch (2024). Austria's Social Security Invests Over €50m in AI – Just for Bookkeeping? Berlin: AlgorithmWatch. Available at: https://algorithmwatch.org/en/austrias-social-security-invests-massively-in-ai/ (Accessed: 24 March 2026).
   https://algorithmwatch.org/en/austrias-social-security-invests-massively-in-ai/
2. SRC-004-AUT-001 International Social Security Association (ISSA) (2025). AI applications in social security: Building evidence and insights from the TechByte. Geneva: ISSA. Available at: https://www.issa.int/node/281122 (Accessed: 30 March 2026).
   https://www.issa.int/node/281122
3. SRC-001-AUT-001 IÖB – Innovationsfördernde Öffentliche Beschaffung (n.d.). Artificial Intelligence (AI) in der Kostenerstattung der SV. Vienna: IÖB. Available at: https://www.ioeb.at/erfolgreiche-projekte-detail/artificial-intelligence-ai-in-der-kostenerstattung-der-sv (Accessed: 24 March 2026).
   https://www.ioeb.at/erfolgreiche-projekte-detail/artificial-intelligence-ai-in-der-kostenerstattung-der-sv
4. SRC-003-AUT-001 Österreichische Gesundheitskasse (2023). Jahresbericht 2022. Vienna: ÖGK. Available at: https://www.gesundheitskasse.at/cdscontent/load?contentid=10008.779654&version=1689762923 (Accessed: 28 November 2025).
   https://www.gesundheitskasse.at/cdscontent/load?contentid=10008.779654&version=1689762923