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Formalization and Computation of Diabetes Quality Indicators with Patient Data from a Chinese Hospital

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Knowledge Representation for Health Care (ProHealth 2016, KR4HC 2016)

Abstract

Clinical quality indicators are tools to measure the quality of healthcare and can be classified into structure-related, process-related and outcome-related indicators. The objective of this study is to investigate whether Electronic Medical Record (EMR) data from a Chinese diabetes specialty hospital can be used for the automated computation of a set of 38 diabetes quality indicators, especially process-related indicators. The clinical quality indicator formalization (CLIF) method and tool and SNOMED CT were adopted to formalize diabetes indicators into executable queries. The formalized indicators were run on the patient data to test the feasibility of their automated computation. In this study, we successfully formalized and computed 32 of 38 quality indicators based on the EMR data. The results indicate that the data from our Chinese EMR can be used for the formalization and computation of most diabetes indicators, but that it can be improved to support the computation of more indicators.

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Notes

  1. 1.

    http://cliftool.org/, https://github.com/LiuHaitong/CLIF2.

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Correspondence to Kathrin Dentler .

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Liu, H., ten Teije, A., Dentler, K., Ma, J., Zhang, S. (2017). Formalization and Computation of Diabetes Quality Indicators with Patient Data from a Chinese Hospital. In: Riaño, D., Lenz, R., Reichert, M. (eds) Knowledge Representation for Health Care. ProHealth KR4HC 2016 2016. Lecture Notes in Computer Science(), vol 10096. Springer, Cham. https://doi.org/10.1007/978-3-319-55014-5_2

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  • DOI: https://doi.org/10.1007/978-3-319-55014-5_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-55013-8

  • Online ISBN: 978-3-319-55014-5

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