An enhancement on Clinical Data Analytics Language (CliniDAL) by integration of free text concept search

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Abstract

Much of the important patient information can only be found in patient narratives or in free text fields of structural schema of the Clinical Information System (CIS). So, the integration of free text search facilities will improve question answering on CISs. This paper describes a method for integrating free text search facility to the proposed Data Analytics Language (CliniDAL) to improve its capabilities at answering more common clinical questions. The proposed language constructs in CliniDAL’s grammar enables its parser to recognize the part of the Restricted Natural Language Query (RNLQ) of the CliniDAL interface, which needs a free text resolution mechanism. Then the Natural Language Processing (NLP) approach of the CliniSearch tool finds the correct matches with the query. The search result is integrated into the translated CliniDAL query which can be executed to return a more comprehensive answer to the initial text query. 160 queries are tested in the current work to investigate the improvements on answering more common questions from a CIS, which result in a simple taxonomy of four query categories of: unanswerable queries, queries that require more evidence to be answered, queries requiring user interpretation and queries with suitable answers. Compatibility of query results between the structural schema and patient progress notes is examined which showed the usability of the approach in answering queries, confirming the results from different sources and finding any inconsistency in the stored data in the CIS. The proposed solution provides a simple mechanism for extracting knowledge from CISs.

Keywords

Knowledge discovery and reuse Question answering Free text search Clinical information systems 

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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Computer Engineering, Faculty of EngineeringThe University of ZanjanZanjanIran
  2. 2.Health Language AnalyticsSydneyAustralia

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