A Web-Based Data-Querying Tool Based on Ontology-Driven Methodology and Flowchart-Based Model

Abstract

BackgroundBecause of the increased adoption rate of electronic medical record (EMR) systems, more health care records have been increasingly accumulating in clinical data repositories. Therefore, querying the data stored in these repositories is crucial for retrieving the knowledge from such large volumes of clinical data.ObjectiveThe aim of this study is to develop a Web-based approach for enriching the capabilities of the data-querying system along the three following considerations: (1) the interface design used for query formulation, (2) the representation of query results, and (3) the models used for formulating query criteria.MethodsThe Guideline Interchange Format version 3.5 (GLIF3.5), an ontology-driven clinical guideline representation language, was used for formulating the query tasks based on the GLIF3.5 flowchart in the Protégé environment. The flowchart-based data-querying model (FBDQM) query execution engine was developed and implemented for executing queries and presenting the results through a visual and graphical interface. To examine a broad variety of patient data, the clinical data generator was implemented to automatically generate the clinical data in the repository, and the generated data, thereby, were employed to evaluate the system. The accuracy and time performance of the system for three medical query tasks relevant to liver cancer were evaluated based on the clinical data generator in the experiments with varying numbers of patients.ResultsIn this study, a prototype system was developed to test the feasibility of applying a methodology for building a query execution engine using FBDQMs by formulating query tasks using the existing GLIF. The FBDQM-based query execution engine was used to successfully retrieve the clinical data based on the query tasks formatted using the GLIF3.5 in the experiments with varying numbers of patients. The accuracy of the three queries (ie, “degree of liver damage,” “degree of liver damage when applying a mutually exclusive setting,” and “treatments for liver cancer”) was 100% for all four experiments (10 patients, 100 patients, 1000 patients, and 10,000 patients). Among the three measured query phases, (1) structured query language operations, (2) criteria verification, and (3) other, the first two had the longest execution time.ConclusionsThe ontology-driven FBDQM-based approach enriched the capabilities of the data-querying system. The adoption of the GLIF3.5 increased the potential for interoperability, shareability, and reusability of the query tasks.

MicroShare: Privacy-Preserved Medical Resource Sharing through MicroService Architecture

“…In contrast to some of the existing techniques 10 , 11 , 12 , 13 , our approach relies on advanced software engineering principles and technologies for analyzing clinical datasets. For example, caGrid 1.0 11 (now caGrid 2.0), released in 2006, is an approach that discusses a complex technical infrastructure for biomedical research through an interconnected network.…”

“…A slightly similar work to this paper has been developed at Massachusetts General Hospital (QPID Inc. 5 ), offering solutions at a commercial level, but no prototype is available to experiment with. A Web-based approach for enriching the capabilities of the data-querying system is also developed [12] that considers three important aspects including the interface design used for query formulation, the representation of query results, and the models employed for formulating query criteria. The notion of differential privacy [19] aims to provide means to maximize the accuracy of queries from statistical databases while minimizing the chances of identifying its records.…”

Using Ontologies to Access Complex Data: Applications on Bio-Imaging

“…By using a web-based interface, DQG "allows researchers to design, execute, and save queries in a simple and intuitive manner, without having to write complex SQL queries". Ping et al [15] also developed a web-based dataquerying tool using ontology-driven methodology and flowchart-based model. The former was used to formulate the query task through a Protégé plugin, the later executes queries and presents the result through a visual and graphical interface.…”

A Tool for Analyzing Clinical Datasets as Blackbox

“…In contrast to some of the existing techniques [12] [2] [10] [13] [15], our approach relies on advanced software engineering principles and technologies for analyzing clinical datasets. For example, caGrid 1.0 [12] (now caGrid 2.0), released in 2006, is an approach that discusses a complex technical infrastructure for biomedical research through an interconnected network.…”

“…A slightly similar work to this paper has been developed at Massachusetts General Hospital (QPID Inc., 7 ), offering solutions at a commercial level, but no prototype is available to experiment with. A Web-based approach for enriching the capabilities of the data-querying system is also developed [13] that considers three important aspects including the interface design used for query formulation, the representation of query results, and the models employed for formulating query criteria. The notion of differential privacy [4] aims to provide means to maximize the accuracy of queries from statistical databases while minimizing the chances of identifying its records.…”