Open Health Knowledge Management Platform: A Comprehensive Evaluation of a Data-centric Approach for Patient Care and Research

Abstract

Abstract Background In the evolving landscape of healthcare, the fragmented IT environment poses challenges to data utilization. This paper introduces the Open Health Knowledge Management Platform, designed to overcome data fragmentation, heterogeneity, and interoperability challenges. The platform aims to bridge the gap between research and patient care, showcased through real-world scenarios, emphasizing seamless data integration and collaborative research. The University Hospital Schleswig-Holstein's (UKSH) diverse IT landscape is a specific focus, and the platform proposes a solution to the separation between patient care and research, aligning with the Medical Informatics Initiative’s goal of efficient, unified data access. Methods The study evaluates the "open health knowledge management platform" designed to target data silos and interoperability issues. Utilizing the Framework for Evaluation in Design Science Research (FEDS), three hypotheses guide scenario-based evaluations: data integration, data quality, and scalability. The platform's technical evaluation, centered on interoperability, single-point-of-truth, and real-world scenarios, follows the FEDS framework and ISO/IEC 25000 standard. Three scenarios cardiology, neurology, and radiology are selected for a naturalistic, qualitative evaluation, showcasing the platform's effectiveness. The FEDS components Problem, Solution, Evaluation, and Communication guide a comprehensive understanding and dissemination of the platform's impact. The system architecture emphasizes interoperability, a single point of truth, and use case agnosticism. Results The Open Health Knowledge Management Platform has undergone successful evaluation at UKSH. Demonstrating adaptability across diverse data formats like HL7 V2 messages, CSV exports, and BIDS-formatted EEG data, the platform showed its efficacy in certain real-world scenarios of cardiology, neurology and radiology. Our evaluation confirms the platform’s capacity to bridge gaps between patient care and research data utilization, facilitating collaboration and advancing clinical decision-making. Conclusion Our evaluation of the open health knowledge management platform at UKSH reveals its capabilities in tackling data fragmentation, enhancing interoperability, and enabling seamless knowledge transfer between patient care and research. The platform's architecture and standardized terminologies significantly improved data quality and facilitated robust querying. Challenges notwithstanding, the platform demonstrated reliability in handling diverse data types, integration effectiveness, and scalability, validating our hypotheses. Ongoing development and potential quantitative measures will further enhance its applicability and performance in dynamic health care landscapes.