Implementation of a prospective neurosurgical complication registry in routine clinical practice

Reliable and complete documentation is a prerequisite for quality improvement in neurosurgical care. To strengthen internal process monitoring and reduce variability in documentation practices, our department implemented a structured, web-based neurosurgical complication documentation and quality assurance registry combining automated data imports from the hospital information system with minimal standardized manual inputs. The year 2024 represented the first full operational cycle of the system.

This quality-improvement study evaluated exclusively process-related parameters of the complication documentation registry and did not include analysis of clinical content or outcome variables. Although the registry contains prospectively documented clinical and treatment-related data, the present evaluation was limited to system integration, documentation completeness, frequency of missing mandatory documentation, and performance of reporting mechanisms. Analyses were based solely on de-identified system-level metadata reflecting documentation status. Documentation completeness and workflow adherence were analyzed descriptively over time.

The registry was successfully integrated into routine clinical workflow across all neurosurgical units and across all hospital wards responsible for the management or discharge of neurosurgical patients. Documentation completeness improved steadily throughout the year, increasing from 77% in the first quarter to 88% in the fourth quarter when assessed after a predefined follow-up interval. Automated reporting identified incomplete documentation entries primarily during the early implementation phase, with alert frequencies decreasing by approximately 48% over the course of the year. Documentation completeness continued to improve beyond the formal observation period, and all inpatient stays from the 2024 cohort were fully documented during follow-up. Progressive improvements across units indicated growing feasibility, acceptance, and compliance within the clinical teams.

The structured multi-step design, combining automated data integration, binary discharge screening, and dedicated detailed documentation by designated clinicians, appeared effective in improving documentation completeness and workflow adherence. This process-oriented evaluation provides a useful structural basis for future quality improvement initiatives and ethically approved clinical research based on high-fidelity routinely collected data.