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Interoperability Assessment in Health Systems Based on Process Mining and MCDA Methods

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Recent Advances in Information Systems and Technologies (WorldCIST 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 569))

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Abstract

Healthcare processes are complex and require a high-level of interdisciplinary cooperation among the different specialists and sectors involved in their delivery. Information flows among organizational entities, sectors, areas and employees represent possible risks of low process interoperability as well as of non-compliance between business rules and actual process deliveries. In addition to this complexity, the Brazilian healthcare area has well-known problems in its public and private health care systems. These problems are of structural, organizational and financial natures, reflecting the low value attributed to quality and to the actual services provided evidenced in recent surveys of Instituto Data Folha and the Brazilian Ministry of Health (Ministério da Saúde). The extraction of process data logs, and the use of process mining, enables extraction of qualitative and quantitative indicators for hospital processes. On top of these, multi-criteria decision analysis (MCDA) tools can be used for analysis and decision making in support to process diagnosis. This paper aims to propose the joint use of process data mining and multi-criteria decision analysis (MCDA) methods in analysing and identifying organizational performance levels in a particular hospital process. In order to accomplish this, a case study was carried out through the use of treatment data logs of venous chemotherapy patients at the Erasto Gaertner Hospital, located in Curitiba – PR, Brazil, a local reference in cancer treatments.

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Correspondence to Gustavo Riz .

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Riz, G., Santos, E.A.P., de Freitas Rocha Loures, E. (2017). Interoperability Assessment in Health Systems Based on Process Mining and MCDA Methods. In: Rocha, Á., Correia, A., Adeli, H., Reis, L., Costanzo, S. (eds) Recent Advances in Information Systems and Technologies. WorldCIST 2017. Advances in Intelligent Systems and Computing, vol 569. Springer, Cham. https://doi.org/10.1007/978-3-319-56535-4_44

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