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Biomedical Informatics Investigator.

Peter L Elkin1, Sarah Mullin1, Sylvester Sakilay1

  • 1Department of Biomedical Informatics, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, SUNY, New York, USA.

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Summary
This summary is machine-generated.

The BMI Investigator software enables querying diverse health data, including clinical notes and lab results, for research. Usability testing confirmed its value for subject matter experts in clinical trial recruitment.

Keywords:
Automated retrospective researchClinical Research InformaticsOntologyRecruitment to clinical trialsclinical genomic trial recruitment

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Area of Science:

  • Biomedical Informatics
  • Health Data Management
  • Clinical Research Informatics

Background:

  • Efficient querying of diverse health data is crucial for clinical research and trial recruitment.
  • Integrating structured and unstructured data presents significant informatics challenges.
  • Existing systems often lack comprehensive data integration and usability for subject matter experts.

Purpose of the Study:

  • To introduce the BMI Investigator, a novel computer-human interface for querying integrated health data.
  • To describe the system's architecture for handling structured and unstructured clinical information.
  • To evaluate the usability of the BMI Investigator with subject matter experts.

Main Methods:

  • Developed a .Net-based interface for querying demographics, administrative codes, medications (RxNorm), lab results (LOINC), and clinical notes (SNOMED CT).
  • Utilized graph databases, triple stores, NoSQL (Berkeley DB for SNOMED CT), and SQL (OMOP/OHDSI format for structured data).
  • Incorporated functionality for cohort selection and automated retrospective research, with plans for genomic and image data integration.

Main Results:

  • The BMI Investigator successfully integrates and queries structured and unstructured clinical data using standardized coding systems.
  • Ontology terms from SNOMED CT are coded as assertions and stored in compositional expressions.
  • A usability experiment identified flaws, leading to software improvements, with users deeming it usable.

Conclusions:

  • The BMI Investigator provides a usable platform for subject matter experts to query complex health datasets.
  • The system supports data-driven recruitment for clinical trials and automated retrospective research.
  • Future development will enhance the query engine with genomic and image feature data integration.