Capacity-Driven State Machines in Health-IT: A Proactive Architecture for Automated Point-of-Service Workflows

Conventional healthcare management systems rely heavily on rule-based validation and restrictive feedback mechanisms ("defensive UI logic"), leading to operational bottlenecks and high administrative overhead at the Point of Service (PoS). This paper proposes a proactive, event-driven workflow engine based on state machines governed by dynamic capacity vectors (the "Fierley Principle"). Instead of blocking user interaction through real-time validation constraints, the architecture decouples task ingestion from asynchronous execution by leveraging pre-calculated system capacity ("capacity engine"). We demonstrate the implementation of this paradigm through an operational self-service kiosk system (CareVado) integrated into medical practice environments. Empirical data from baseline workflow analyses shows a 72% reduction in operational friction, reclaiming 3.48 hours/day of net operational capacity per 50 daily service contacts without compromising operational safety or regulatory compliance. Key Contributions:- Formalization of the Fierley Principle (Capacity-Driven State Transitions / "Battery & Switch" model)- Systemic contrast between restrictive validation ("Scissors & Warnings") and capacity-decoupled execution- Case study and empirical analysis of the CareVado Point-of-Service kiosk appliance