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Table 8 The impact of implemented ontologies for the assessment of data quality

From: Ontological specification of quality of chronic disease data in EHRs to support decision analytics: a realist review

Ontology functions References Defined purpose Assessed of fitness for purpose using DQ Context
Assessment ( 7 papers ) (Jacquelinet et al. 2003) To develop semantic data interoperability -Apply an ontological tool to develop semantic data interoperability through domain terminologies using quantitative analysis of the existing coding information system and a qualitative analysis checking completeness, consistency, ambiguity and implicitness of terms Failure, dialysis and transplant datasets from National information system in France
    - Represent DQ factors such as completeness of data, appropriated terms, structured thesaurus, and terminology standard  
    -Authors state usefulness of ontology based approach to support the processing of texts, and extending a terminological basis for medical experts  
  (Maragoudakis et al. 2008) To develop decision support system -Use 25 patients records from various networking appliances such as mobile phones and wireless medical sensors to establish a ubiquitous environment for medical treatment of pulmonary diseases Mobile sensor data from 25 patients in Artificial Neural Network (ANN) in GREECE
    -Use ontology approach based on hierarchical Bayesian networks which can encode a domain and make prediction  
    -Focus on data timeliness  
    -Authors states the importance of ontology based model as an ubiquitous platform to improve patient monitoring and health services in real time treatment decision  
  (Wang et al. 2007) To classify diabetic patients Use measuring precision and recall of results to show accuracy of clinical data achieved from an ontology-based fuzzy inference agent, including a fuzzy inference engine, and a fuzzy rule base, for diabetes classification Retrieve 392 cases from the Pima Indians diabetes database in US
    -Authors state that ontology approach can classify effectively classify a person as a diabetic patient for medical staff  
  (Valencia-Garcia et al. 2008) To develop retrieval and extract clinical information -Represent multiple semantic relationships among concepts with UMLS ancestors through MESH descriptors in the ontology to enrich the ontology extracted from the text Use breast cancer domain in the system with a Spanish corpus of 8649 words in Spain
    -Use an experiment (4 PhD students were asked to use the system with a Spanish corpus) to analyse a software tool by measuring precision and recall of the result (accuracy of data)  
    -Solve semantic clinical data issues and develop accuracy of retrieval information through ontologies  
  (Mabotuwana and Warren, 2009) To identify hypertensive patients in the context of quality use of medicines -Use the querying capabilities of one GP database in the context of quality use of medications in the management of hypertension over time CVD in practice management system in NZ
    -Use 8 criteria and 4 scenarios to identify hypertensive patients  
    -Focus on semantic interoperability and also data completeness and timeliness, consistency  
    -Authors show the importance of ontology based approach to enhance temporal querying requirements and identify patient data, semantically  
  (Young et al. 2009) To develop semantic data collection and integration -Use the modelling of terms to conform to and extend the existing ontologies development framework Data on Autism in the National Database for Autism Research in US
    -Theoretical discussion on completeness of data, data availability and accessibility  
    -Authors state that ontology help to extract, query, integrate and federate data for clinical researcher  
  (Preece et al. 2008) To manage information quality (IQ) in a real-life example of gene expression research - Implication of viewing high IQ as 'fitness for purpose’ for providers and consumers, in which users state their quality requirements in terms of domain concepts (such as accuracy, currency and completeness) Gene expression data which involve the use of microarrays in UK
    - Guide the development and use of metrics to measure the complexity and cohesion of ontologies  
    -Authors state that ontology helps to allow a practical division of the work between providers and consumers, in order to minimize the costs to all concerned