Private Hospital Group
Six hospitals. Four regions. Six separate HIS instances. One unified definitional layer. No system replaced.
Six private hospitals across Vienna, Graz, Salzburg, and Tyrol — under shared management, each operating its own hospital information system. No unified view of network-wide utilization, specialist availability, or patient pathway throughput. Stathon deployed at Forge Tier with nightly batch integration across all six Dedalus ORBIS instances. Within the first 60 days at the Vienna sites: central capacity planning decision cycle compressed from days to minutes, manual cross-site reconciliation reduced by 40–55%, and cross-site patient routing informed by network-level utilization data for the first time.
The network.
Six private hospitals across four Austrian regions — three in Vienna, one in Graz, one in Salzburg, one in Tyrol — under shared corporate governance. The network operates inpatient and outpatient care, surgical interventions, diagnostics, an oncology center, and an international patient service.
The contracted specialist network comprises approximately 600 physicians working on a case-by-case engagement basis — most practicing across multiple sites. Each hospital ran its own Dedalus ORBIS instance, the dominant HIS in the DACH-region private healthcare sector with approximately 700,000 daily users across Germany, Austria, and Switzerland.
Management received site-level data through monthly reports, manual extracts, and ad hoc reconciliation calls — typically with a 5–10 day lag. ELGA integration ensured statutory compliance, but ELGA is designed for patient-provider documentation — not network-level operational intelligence.
Six separate ORBIS installations. Configuration, version, and ELGA integration depth varied across sites.
Six definitions of capacity.
The operational fragmentation across six hospitals did not stem from system heterogeneity — the deeper problem was that the network had never structurally defined what a “pathway event” means at the network level. The concept itself meant different things in Vienna and Graz.
A Vienna outpatient examination appeared with different coding, a different status model, and a different timestamp convention than one in Graz. Aggregating site-level data was not merely a technical task — the aggregation was structurally meaningless, because the definitions were not consistent.
The problem was not that data was unavailable. The problem was that no one had defined what a patient pathway event means across six different hospital contexts — and until that was done, every aggregation was an illusion.
Stathon engagement assessment
Management could not determine, on a weekly basis, which hospital had available surgical capacity over the next two weeks — while Vienna sites were overloaded and regional hospitals were partially underutilized. This question could not be answered with the existing systems, because the concept of “surgical capacity” carried six different definitions.
The concept of a patient pathway event carried different coding, status models, and timestamp conventions across sites. A Vienna outpatient examination appeared with different attributes than one in Graz. Aggregation across sites was structurally meaningless.
Six hospitals operated four different logics for the concept of "surgical day." Two Vienna sites aligned; the other four diverged. No one could answer the question: which hospital has available surgical capacity next week?
Cross-site patient matching was not defined at the network level. A patient seen at Confraternität and Döbling existed as two unrelated records. Care continuity was maintained by phone calls, not by data.
Quality management data required 4–6 working hours per site per week to aggregate manually. Results typically reached decision-makers only after the operational reality had already shifted.
Previous partner assessments
Previous IT consulting partners had assessed the problem as a systems integration challenge and recommended HIS consolidation or a central data warehouse. The group's leadership rejected this: replacing the HIS across six hospitals was not realistic in either time or budget. The question was whether unified operational visibility could be established above the existing systems — without replacing them.
Three phases.
Forge-tier deployment. Four modules — Arché, Core, Athena, Aegis — deployed in phased sequence. All six hospital information systems remained in place, unchanged.
Definition & Integration Spine
Weeks 1–6The first work was not integration — it was definition. During the definitional work, it emerged that the six hospitals operated four different logics for the concept of “surgical day.” Harmonizing the entity graph required three rounds of alignment sessions. This caused a two-week delay — but without consensus the integration layer would have been meaningless.
Stathon deployment record
First Live Capabilities
Months 2–4A single interface showing available bed capacity, surgical blocks, and outpatient slots across all six hospitals for the current and following week. Above 90% accuracy at the Vienna hospitals; regional sites initially at 70–75% due to later batch extract configuration.
Tracking elapsed time from admission to intervention and discharge, per site and at the network level. First network-wide view of patient pathway duration in the group’s history.
Five of eight central management team members switched to the new view within two weeks. Three Vienna site directors adopted within the first month. Regional directors remain in parallel run — validating network data against their own site-level extracts.
Orthopedic surgical utilization: Döbling at 92%, Confraternität at 61%. Two patients rerouted from a 10–12 day waiting list to available blocks — shortening the patient pathway by 8 days. This routing could not have occurred previously.
Two calibration cycles were required to bring the regional hospitals’ data quality to an acceptable level, adding six additional weeks to the rollout. Data gaps at regional sites — where batch extract configuration started later — initially reduced accuracy.
Athena — Intelligence & Foresight
Current · OngoingThe Athena layer — rule-based escalation logic layered beneath a probabilistic scoring engine — is launching in advisory mode at the largest Vienna hospital. Capacity forecasting on 7- and 14-day horizons, based on historical patient movement patterns, seasonal trends, and contracted specialist availability calendars. The model does not make automated decisions — it provides signals. Every Athena query is logged in the Aegis audit event taxonomy.
GDPR alongside the ELGA Act (Gesundheitstelematikgesetz 2012) and the Austrian Data Protection Act (DSG). All three regulatory layers addressed in the governance architecture.
RBAC policy enforces site-level access boundaries: the Vienna director cannot access individual-level data from Graz — only network-level aggregated views.
Every data access is logged and retrievable. Patient-level access is presentable under regulatory review. Deletion requests enforce network-wide, not only at the originating site.
What changed.
Measured impact from the first 60 days at the three Vienna hospitals in production. Regional sites remain in parallel run.
This is not acceleration — it is a structural change in the temporal relationship between the operational decision and reality: what was previously retrospective is now near real-time. The decision logic itself has changed, not merely the speed at which legacy decisions are made.
The ~130–175 hours per month freed from manual data collection did not disappear. The capacity was redirected: the management team now uses time previously spent on manual reconciliation for proactive capacity planning and patient pathway optimization.
What this case revealed.
The problem was definitional, not technical
What previous partners would have attempted to solve through HIS replacement or a central data warehouse, Stathon resolved above the existing systems — by doing the definitional work that no one had previously undertaken. The client did not receive software. They received structural capacity. The six ORBIS instances, the site-level administrative systems, the ELGA integration — all remained in place. They now operate beneath a definitional, continuity, inference, and sovereignty layer they did not previously have.
Trust builds through validation
The regional directors — Graz, Salzburg, Tyrol — remain in parallel run: they can see the network data, but continue to rely primarily on their own site-level extracts for decision-making. This is a natural adoption pattern. Trust in the new layer builds through validation against the site’s own data. The Vienna directors adopted within the first month because they could verify the network view against their known operational reality.
Infrastructure position, not integration position
The Stathon infrastructure is not a tool and not a platform. It is the operational logic layer that organizes six hospitals’ separate systems into a single coherent operational reality. The Forge position does not mean replacing what the organization built. It means making it structurally coherent for the first time. Six hospitals, six HIS instances, six operational logics — now a single defined reality.
The integration is not visible from the surface. Its absence would be.
Stathon deployment conclusion
Forward roadmap.
Athena predictive capacity forecasting
7- and 14-day horizon capacity forecasting, launching in advisory mode at the largest Vienna hospital. Model signals based on historical patient movement patterns, seasonal trends, and specialist availability calendars.
Regional hospital production rollout
Completion of parallel run at Graz, Salzburg, and Tyrol sites. Full network-level production across all six hospitals. Regional directors transition from site-level extracts to unified operational view.
International patient coordination
Structured status tracking from initial inquiry through discharge across the full patient journey. Requires Aegis layer extension to address GDPR implications of patient-level cross-border data handling.
Specialist workload optimization
Network-level visibility into multi-site scheduling of the ~600 contracted physicians. Workload balancing and availability intelligence across the full specialist network.
Deployment record.
Stathon · Definitional Infrastructure Company. Client identity anonymized at the institution's request. Operational metrics and system references reflect the actual deployment environment.