Multiple valued logic approach for matching patient records in multiple databases

Many problems arise when linking medical records from multiple databases. Matching these data to other data is problematic since even small errors, such as data entry errors, different text format, and missing data, can prevent the exact-match algorithms. Evidence from previous studies suggested that approximate field matching represent a solution to resolve the problem by identifying equivalent string values in different representations. The purpose of this article is to explore the effectiveness of a medical record matching method using a fuzzy logic framework. This article considers quantitative measures of the typical elements in medical records, and fuzzy logic is applied to link to the linguistic concepts. Moreover, this article discusses the medical record matching from the developed framework, which is tested on a public data set. The results from the test on a public data set indicate that the medical record matching method using fuzzy logic framework provides an effective solution for dealing with linkage problems, and illustrate that the multiple valued logic method outlined can potentially be applied to address similar problems in other databases.

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► Probabilistic matching has effects on decreasing missing matched records.
► Describe record matching method using fuzzy logic framework.
► Model was evaluated to perform very well.
► Can apply to match patient records in multiple resources.