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681 results on '"Bodendorf, Freimut"'

202. Integrierte Anwendungssysteme

Author

Mertens, Peter, primary, Bodendorf, Freimut, additional, König, Wolfgang, additional, Picot, Arnold, additional, and Schumann, Matthias, additional

Published
2000
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203. Rechner und Netze

Author

Mertens, Peter, primary, Bodendorf, Freimut, additional, König, Wolfgang, additional, Picot, Arnold, additional, and Schumann, Matthias, additional

Published
2000
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217. Daten und ihre Integration

Author

Mertens, Peter, primary, Bodendorf, Freimut, additional, König, Wolfgang, additional, Picot, Arnold, additional, and Schumann, Matthias, additional

Published
1998
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219. Integrierte Anwendungssysteme

Author

Mertens, Peter, primary, Bodendorf, Freimut, additional, König, Wolfgang, additional, Picot, Arnold, additional, and Schumann, Matthias, additional

Published
1998
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224. Context Specific Complexity Management - A recommendation model for optimal corporate complexity

Author

Schott, Peter, Horstmann, Felix, and Bodendorf, Freimut

Subjects
complexity drivers, ddc:650, scoring algorithm, law of requisite variety, recommendation model, lcsh:Business, lcsh:HF5001-6182, complexity management
Abstract

Companies face emerging external complexities that they must respond to with internal complexity to be able to perform on a superior performance level. On that account, an application-oriented methodology to support the context specific selection of appropriate complexity management methods for accomplishing the optimal level of internal complexity is lacking. A complexity management model is introduced that tackles this deficiency. Based on the identification of 37 complexity drivers that determine corporate complexity and 81 complexity management methods from literature, an assignment matrix with 2,997 relations between complexity drivers and methods is stretched. A scoring algorithm uses these relations to generate a sorted list of appropriate management methods for a specific complexity context determined by relevant complexity drivers. The approach is operationalized by a software prototype and evaluated through six interviews with experts from the field who confirmed practical relevance, appropriateness, and value-added of the provided management recommendation.

Published
2015

227. Integrierte Anwendungssysteme

Author

Mertens, Peter, primary, Bodendorf, Freimut, additional, König, Wolfgang, additional, Picot, Arnold, additional, and Schumann, Matthias, additional

Published
1996
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232. Daten und ihre Integration

Author

Mertens, Peter, primary, Bodendorf, Freimut, additional, König, Wolfgang, additional, Picot, Arnold, additional, and Schumann, Matthias, additional

Published
1996
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236. Integrierte Anwendungssysteme

Author

Mertens, Peter, primary, Bodendorf, Freimut, additional, König, Wolfgang, additional, Picot, Arnold, additional, and Schumann, Matthias, additional

Published
1995
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239. Daten und ihre Integration

Author

Mertens, Peter, primary, Bodendorf, Freimut, additional, König, Wolfgang, additional, Picot, Arnold, additional, and Schumann, Matthias, additional

Published
1995
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241. An Intelligent Clinical Decision Support System to Determine the Optimal Time of Patient Discharge in Hospitals.

Author

Eigner, Isabella and Bodendorf, Freimut

Subjects
INTELLIGENT agents, MACHINE learning, DECISION support systems, DECISION making in clinical medicine, HOSPITAL admission & discharge, PATIENT readmissions, HOSPITAL administration, PREDICTION models
Abstract

Unplanned readmissions are a popular factor to determine the quality of healthcare services that can lead to negative financial and reputational ramifications for hospitals. Identifying patients at high-risk of readmission is key to allow for early interventions and proper discharge management. This paper proposes an intelligent clinical decision support system (ICDSS) that incorporates multiple risk prediction models according to the eight surgical groups defined by the Australian Institute of Health and Welfare (AIHW). The goal of this ICDSS is to enable the identification and visualisation of individual patients at high risk of readmission combined with economic factors to support decision-making in hospital discharge. This paper presents the design, prototypical implementation, and evaluation of an ICDSS that offers relevant insights to healthcare providers based on procedure-specific readmission risk prediction models. The results of the evaluation confirm the suitability and effectiveness of the system to support the decision process in patient discharge. [ABSTRACT FROM AUTHOR]

Published
2020

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