Abstract
<p>Evidence-based medicine can be effective only if constantly tested against errors in medical practice. Clinical record database summarization supported by a machine allows allow to detect anomalies and therefore help detect the errors in early phases of care. Summarization system is a part of Clinical Decision Support Systems however it cannot be used directly by the stakeholder as long as s/he is not able to query the clinical record database. Natural Query Languages allow opening access to data for clinical practitioners, that usually do not have knowledge about articial query languages. Results: We have developed general purpose reporting system called Ask Data Anything (ADA) that we applied to a particular CDSS implementation. As a result, we obtained summarization system that opens the access for these of clinical researchers that were excluded from the meaningful summary of clinical records stored in a given clinical database. The most significant part of the component - NQL parser - is a hybrid of Controlled Natural Language (CNL) and pattern matching with a prior error repair phase. Equipped with reasoning capabilities due to the intensive use of semantic technologies, our hybrid approach allows one to use very simple, keyword-based (even erroneous) queries as well as complex CNL ones with the support of a predictive editor. By using ADA sophisticated summarizations of clinical data are produced as a result of NQL query execution. In this paper, we will present the main ideas underlying ADA component in the context of CDSS.</p>
Highlights
We define here Clinical Decision Support System (CDSS)Anything (ADA) that we applied to a particular CDSS after Sim et al.[1] as: “a software that is designed to be a direct implementation
The most significant part of the component - Natural Query Language (NQL) parser - is a hybrid of Controlled Natural Language (CNL) and pattern matching with a prior error repair phase
Equipped with reasoning capabilities due to the intensive use of semantic technologies, our hybrid approach allows one to use very simple, keyword-based queries as well an individual patient are matched to a computerized clinical knowledge base and patient-specific assessments or recommendations are presented to the clinician or the patient for a decision”
Summary
Anything (ADA) that we applied to a particular CDSS after Sim et al.[1] as: “a software that is designed to be a direct implementation. If clinical knowledge base of the CDSS “(...) is derived from and continually reflects the most up-todate evidence from the research literature and practice-based sources.”. In other words: it is desired by the stakeholder to have the ability to examine the data in a queryresult loop, where the query is tailored within an interactive process that does not require any large prior learning and preparation. This way of querying data is supported by Natural Query Language (NQL). Strict formalization of the domain knowledge produces consistent data that can be reused for clinical studies
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