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SummaryObjective: To perform a review of recent research in clinical data reuse or secondary use, and envision future advances in this field. Methods: The review is based on a large literature search in MEDLINE (through PubMed), conference proceedings, and the ACM Digital Library, focusing only on research published between 2005 and early 2016. Each selected publication was reviewed by the authors, and a structured analysis and summarization of its content was developed. Results: The initial search produced 359 publications, reduced after a manual examination of abstracts and full publications. The following aspects of clinical data reuse are discussed: motivations and challenges, privacy and ethical concerns, data integration and interoperability, data models and terminologies, unstructured data reuse, structured data mining, clinical practice and research integration, and examples of clinical data reuse (quality measurement and learning healthcare systems). Conclusion: Reuse of clinical data is a fast-growing field recognized as essential to realize the potentials for high quality healthcare, improved healthcare management, reduced healthcare costs, population health management, and effective clinical research.

Despite booming of Internet use in Germany, consumers still value and use more the traditional sources of health information/communication with their doctors. Followup studies with a subsequent survey in 2007 will be pursued.

In an ED, caADEs are frequent, and a significant proportion of these events and their related costs appear to be predictable and preventable. The ED as a first-line provider for ADE cases appears to be an appropriate environment to implement strategic and operative improvements for enhanced patient safety.

The evaluation of clinical information systems is essential as they are increasingly used in clinical routine and may even influence patient outcome on the basis of reminder functions and decision support. Therefore we try to answer three questions in this paper: what to evaluate; how to evaluate; how to interpret the results. Those key questions lead to the discussion of goals, methods and results of evaluation studies in a common context. We will compare the objectivist and the subjectivist evaluation approach and illustrate the evaluation process itself in some detail, discussing different phases of software development and potential evaluation techniques in each phase. We use four different practical examples of evaluation studies that were conducted in various settings to demonstrate how defined evaluation goals may be achieved with a limited amount of resources. This also illustrates advantages, limitations and costs of the different evaluation methods and techniques that may be used when evaluating clinical information systems.

Data from the electronic medical record comprise numerous structured but uncoded ele-ments, which are not linked to standard terminologies. Reuse of such data for secondary research purposes has gained in importance recently. However, the identification of rele-vant data elements and the creation of database jobs for extraction, transformation and loading (ETL) are challenging: With current methods such as data warehousing, it is not feasible to efficiently maintain and reuse semantically complex data extraction and trans-formation routines. We present an ontology-supported approach to overcome this challenge by making use of abstraction: Instead of defining ETL procedures at the database level, we use ontologies to organize and describe the medical concepts of both the source system and the target system. Instead of using unique, specifically developed SQL statements or ETL jobs, we define declarative transformation rules within ontologies and illustrate how these constructs can then be used to automatically generate SQL code to perform the desired ETL procedures. This demonstrates how a suitable level of abstraction may not only aid the interpretation of clinical data, but can also foster the reutilization of methods for un-locking it.

Elderly patients more frequently suffer from ADR and from the clinical consequences of medication errors. Elderly patients taking PIMs are more likely to suffer from ADRs and MEs, even though most drug-related events are still attributable to non-PIM.

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