Root Cause Tracing Algorithm and One-Click Repair Mechanism for Medical Server Failures

Abstract

Delays in laboratory test reports at primary healthcare facilities often stem from server failures, with the lack of on-site expertise resulting in a mean time to repair (MTTR) of up to two hours. This directly hampers diagnostic efficiency and patient experience. To address this, we propose a root cause tracing algorithm and one-click repair mechanism tailored for medical scenarios. By embedding business process semantics into a fault propagation graph, we achieve zero-threshold self-healing. Methodologically, we first utilize eBPF probes to collect system metrics and align them with BPMN medical process diagrams to construct a business-aware root cause analysis model. Through random walk inference, the model identifies the top root cause within one minute. Subsequently, we encapsulate 23 HIPAA-audited repair scripts into a “one-click repair” controller using Kubernetes CRDs, achieving an average fault recovery time of 14 minutes. In a prospective cohort experiment conducted in 12 community health centers in 2024, we injected 411 faults. The results showed that the root cause localization accuracy increased from 52% to 93%, MTTR decreased from 119 minutes to 14 minutes, and the number of human interventions per fault dropped from 1.8 to 0.05. The annual maintenance cost was reduced by 60%. The bilingual usability score reached 4.7 out of 5, with no difference between English and Spanish interfaces. This study is the first to incorporate MTTR into CLIA quality indicators, providing a replicable, compliant, and language-friendly zero-threshold maintenance paradigm for resource-constrained regions.