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Web-Interface-Driven Development for Neuro3D, a Clinical Data Capture and Decision Support System for Deep Brain Stimulation

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Health Information Science (HIS 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10038))

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Abstract

Parkinson’s Disease is a common chronic neurological motor system disorder that affects more than 10 million people worldwide with no known cure. With Deep Brain Stimulation (DBS) emerging as one of the main treatments for Parkinson’s Disease, the effective capture, retrieval, and analysis of data generated from DBS are important informatics challenges. To address these challenges, this paper presents the design and implementation of Neuro3D, a web-interfaced system for DBS data capture and management in the clinical setting. Neuro3D provides: (1) data capture interfaces with multiple data entry assistances and validations to improve both the data entry efficiency and the data quality; (2) intuitive data organization that mirrors the workflow of clinical operations; and (3) a novel data exploration as a basis for clinical decision support. Neuro3D accomplishes these utilizing an agile development strategy called Web-Interface-Driven Development (WIDD) to optimize the communication between software developers and domain experts. 36 distinct data forms consisting of 1109 discrete data elements are captured and managed in Neuro3D. Pilot deployment of Neuro3D in the Movement Disorders Center of the University Hospitals Neurological Institute in Cleveland captured clinical data for 236 patients, in a comprehensive and research-ready fashion beyond the scope of current EMR. Neuro3D fills an important void in terms of tools for capturing large-scale clinical neurology data to improve care and outcome for patients with Parkinson’s disease.

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Acknowledgement

The work was supported by University of Kentucky Center for Clinical and Translational Science (Clinical and Translational Science Award UL1TR0001998).

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Correspondence to Guo-Qiang Zhang .

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Tao, S., Walter, B.L., Gu, S., Zhang, GQ. (2016). Web-Interface-Driven Development for Neuro3D, a Clinical Data Capture and Decision Support System for Deep Brain Stimulation. In: Yin, X., Geller, J., Li, Y., Zhou, R., Wang, H., Zhang, Y. (eds) Health Information Science. HIS 2016. Lecture Notes in Computer Science(), vol 10038. Springer, Cham. https://doi.org/10.1007/978-3-319-48335-1_4

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  • DOI: https://doi.org/10.1007/978-3-319-48335-1_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-48334-4

  • Online ISBN: 978-3-319-48335-1

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