Managing Complexity. From Documentation to Knowledge Integration and Informed Decision Findings from the Clinical Information Systems Perspective for 2018

应对复杂性:从文档编制到知识整合和知情决策——2018年临床信息系统视角的研究成果

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Abstract

OBJECTIVE: To summarize recent research and to propose a selection of best papers published in 2018 in the field of Clinical Information Systems (CIS). METHOD: Each year a systematic process is carried out to retrieve articles for the CIS section of the IMIA Yearbook of Medical Informatics and to select a set of pest papers for the section. The same query as in the last five years was used. The retrieved articles were categorized in a multi-pass review carried out by the two section editors. The final selection of candidate papers was then peer-reviewed by Yearbook editors and external reviewers. Based on the review results the best papers were then chosen at the selection meeting with the IMIA Yearbook editorial board. Text mining, and term co-occurrence mapping techniques were again used to get an overview of the content of the retrieved articles. RESULTS: The query was carried out in mid-January 2019, yielding a consolidated, deduplicated result set of 2,264 articles which had been published in 957 different journals. This year, we nominated twelve papers as candidates and three of them were finally selected as best papers in the CIS section. Again, the content analysis of the articles revealed the broad spectrum of topics which is covered by CIS research. CONCLUSIONS: We could observe ongoing trends from our 2017 analysis. The patient increasingly moves in the focus of the research activities and trans-institutional aggregation of data is still an important field of work. The move to use patient and other clinical data directly for the patient and to support data driven process management, the move away from clinical documentation to patient-focused knowledge generation and support of informed decision, is gaining momentum by the application of new or already known but, due to technological advances, now applicable methodological approaches.

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