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62. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V. (GMDS)

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie

17.09. - 21.09.2017, Oldenburg

Development of patient safety indicators using routine care data

Meeting Abstract

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  • Michael Schaller - UMIT – University for Health Sciences, Medical Informatics and Technology, Hall in Tirol, Österreich
  • Werner Hackl - UMIT – University for Health Sciences, Medical Informatics and Technology, Hall in Tirol, Österreich
  • Elske Ammenwerth - UMIT – University for Health Sciences, Medical Informatics and Technology, Hall in Tirol, Österreich

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie. 62. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS). Oldenburg, 17.-21.09.2017. Düsseldorf: German Medical Science GMS Publishing House; 2017. DocAbstr. 240

doi: 10.3205/17gmds101, urn:nbn:de:0183-17gmds1012

Published: August 29, 2017

© 2017 Schaller et al.
This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 License. See license information at



Background: Patient safety is an important issue and receiving increasing attention [1]. Information technology (IT) and IT-based strategies can help to improve patient safety in hospitals. Existing approaches are often targeted at detecting patient safety issues (e.g. critical incidence reporting systems - CIRS). Disadvantage of such systems is their dependence on voluntary, manual data collection associated with a low sensitivity [2]. A better approach could be to use already existing data within hospital information systems for recognizing patient safety issues and gaining knowledge about manifestations, causes and effects by a retrospective analysis of existing routine care data. The challenge of this approach is both to define appropriate patient safety indicators and to analyse whether the available data within the hospital information system is sufficient to measure these indicators.

Aim of the study: The aim of the PATIS-project which is funded by the Austrian Science-Fund (FWF) is to develop patient safety indicators and to validate them based on available clinical routine data from hospital information systems. PATIS aims at developing a PATient safety Intelligence System and framework for the secondary use of multimodal clinical data to assess and improve patient safety.

Proposed methods: For the design of the patient safety intelligence system the SPIRIT framework (Systematic Planning of Intelligent Reuse of Integrated Clinical Routine Data [3]) will be used. A central task among the first SPIRIT phases is the definition of relevant questions for any intelligence system. In the context of the PATIS-project patient safety indicators represent the relevant questions. For developing these indicators, a systematic and transparent indicator development methodology [4] will be used. This methodology proposes four phases: 1. define the context, 2. define the goals, 3. define the methods for indicator development and 4. define the data and test the developed indicators. It contains both top-down and bottom-up strategies for the indicator development. The top-down approach is based on a literature search and considers already existing patient safety classifications. The bottom-up approach is based on a thorough information needs analysis of stakeholder groups in a hospital [5], i.e. documentation analysis, interviews and observations with the users and with patients. This combination of methodologies will help to provide an overarching set of patient safety indicators in alignment with the various stakeholders’ point of view. Additionally a detailed system analysis with regard to available patient data will be conducted, to verify which patient safety indicators can be assessed via available data. The resulting indicators will be classified with regard to the quality dimensions: structure, process or outcome indicators. Finally, an expert-based consolidation of the identified indicators will be conducted, i.e. by an international mixed-method Delphi study.

Points for discussion: Next steps in the project comprise designing patient safety data models for specific areas of application (e.g. in nursing care, postoperative treatment or for intensive care units) and to investigate if it will be possible to propose a common patient safety minimum data set which can be used by hospitals to detect previous and to prevent future patient safety issues.

Die Autoren geben an, dass kein Interessenkonflikt besteht.

Die Autoren haben keine Angabe zur Beratung durch einen Ethikkommission gemacht.


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