Abstract
To measure the quality of care in order to identify whether and how it can be improved is of increasing importance, and several organisations define quality indicators as tools for such measurement. The values of these quality indicators should ideally be calculated automatically based on data that is being collected during the care process. The central idea behind this paper is that quality indicators can be regarded as semantic queries that retrieve patients who fulfil certain constraints, and that indicators that are formalised as semantic queries can be calculated automatically by being run against patient data. We report our experiences in manually formalising exemplary quality indicators from natural language into SPARQL queries, and prove the concept by running the resulting queries against self-generated synthetic patient data. Both the queries and the patient data make use of SNOMED CT to represent relevant concepts. Our experimental results are promising: we ran eight queries against a dataset of 300,000 synthetically generated patients, and retrieved consistent results within acceptable time.
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Dentler, K., ten Teije, A., Cornet, R., de Keizer, N. (2012). Towards the Automated Calculation of Clinical Quality Indicators. In: Riaño, D., ten Teije, A., Miksch, S. (eds) Knowledge Representation for Health-Care. KR4HC 2011. Lecture Notes in Computer Science(), vol 6924. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27697-2_4
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DOI: https://doi.org/10.1007/978-3-642-27697-2_4
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