Functional Requirements for Medical Data Integration in Knowledge Management Environments: A Systematic Literature Analysis (Preprint)

BACKGROUND In patient care, data are historically generated and stored in heterogeneous databases that are domain specific and are often non-interoperable or isolated. As the amount of health data increases, the number of isolated data silos is also expected to grow, limiting the accessibility of collected data. Medical Informatics is developing ways to move from siloed data to a more harmonized arrangement in information architectures. This paradigm shift will allow future research to integrate medical data at many levels and from various sources. Currently comprehensive requirements engineering is working on data integration projects both in a patient care- and research-oriented context and they are significantly contributing to the success of such data integration projects. In addition to various stakeholder-based methods, document-based requirements elicitation is a valid method to improve the scope and quality of requirements. OBJECTIVE Our main objective is to provide a general set of functional requirements for medical data integration into knowledge management environments. We aim to identify where integration projects intersect to derive consistent and representative functional requirements from literature. Based on these findings, we identify which functional requirements for data integration exist in the literature and thus provide a generic blueprint of requirements. METHODS This work begins by conducting a literature-based requirement elicitation based on a holistic requirement engineering approach. We thus first perform a web based systematic literature review to identify published articles that deal with requirements for medical data integration. We identify and analyze the available literature by applying the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines and screen the results for functional requirements using the requirements engineering method of document analysis and derive requirements into a uniform requirement syntax. Finally, we classify the elicited requirements into a category scheme that represents the data life cycle. RESULTS Our systematic literature search yielded 821 articles of which we include 61 articles in the requirements elicitation process. There we identify a total of 217 requirements, which are covered by a total of 314 references. We assign the requirements to the different data life cycle categories as follows: 56 to the Data Acquisition, 77 to Data Processing, 26 to Data Storage, 20 to Data Analysis, 14 to Metadata Management, 5 to Data Lineage, 7 to Data Traceability, and 12 to the category Data Security. CONCLUSIONS The aim of this work is to present a cross-section of functional data integration related requirements defined in literature by other researchers. The aim is achieved with 217 distinct requirements from a total of 61 publications. We conclude that scientific publications are in principle a reliable source of information for functional requirements with respect to medical data integration. Finally, we provide a generic blueprint to support other scientists in the requirements elicitation phase.