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. 2012;2012:799-808.
Epub 2012 Nov 3.

OPIC: Ontology-driven Patient Information Capturing System for Epilepsy

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Free PMC article

OPIC: Ontology-driven Patient Information Capturing System for Epilepsy

Satya S Sahoo et al. AMIA Annu Symp Proc. .
Free PMC article

Abstract

The widespread use of paper or document-based forms for capturing patient information in various clinical settings, for example in epilepsy centers, is a critical barrier for large-scale, multi-center research studies that require interoperable, consistent, and error-free data collection. This challenge can be addressed by a web-accessible and flexible patient data capture system that is supported by a common terminological system to facilitate data re-usability, sharing, and integration. We present OPIC, an Ontology-driven Patient Information Capture (OPIC) system that uses a domain-specific epilepsy and seizure ontology (EpSO) to (1) support structured entry of multi-modal epilepsy data, (2) proactively ensure quality of data through use of ontology terms in drop-down menus, and (3) identify and index clinically relevant ontology terms in free-text fields to improve accuracy of subsequent analytical queries (e.g. cohort identification). EpSO, modeled using the Web Ontology Language (OWL), conforms to the recommendations of the International League Against Epilepsy (ILAE) classification and terminological commission. OPIC has been developed using agile software engineering methodology for rapid development cycles in close collaboration with domain expert and end users. We report the result from the initial deployment of OPIC at the University Hospitals Case Medical Center (UH CMC) epilepsy monitoring unit (EMU) as part of the NIH-funded project on Sudden Unexpected Death in Epilepsy (SUDEP). Preliminary user evaluation shows that OPIC has achieved its design objectives to be an intuitive patient information capturing system that also reduces the potential for data entry errors and variability in use of epilepsy terms.

Figures

Figure 1:
Figure 1:
Information flow in an EMU
Figure 2:
Figure 2:
Schematic overview of OPIC illustrating the different components and the associated process flow
Figure 3:
Figure 3:
EpSO class hierarchy
Figure 4:
Figure 4:
“Range check” data validation for the dosage information
Figure 5:
Figure 5:
Conceptual view of “paroxysmal episode” skip pattern (left) and the corresponding sections (right)
Figure 6:
Figure 6:
EpSO terms identified and indexed in free text fields
Figure 7:
Figure 7:
Table for input of medication information
Figure 8:
Figure 8:
User responses to evaluation queries comparing OPIC (left) with the original document-based system (right)
Figure 9:
Figure 9:
The average value of user responses comparing the original document-based system with OPIC

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