October 9 - 12, 2012
Building 10 & Natcher Conference Center
- General Schedule of Events
- Opening Plenary Session
- Concurrent Symposia Sessions
- Poster Sessions
- National Graduate Student Research Conference
- FARE Award Ceremony
- Special Exhibits on Resources for Intramural Research
- TSA Research Festival Exhibit Show
- Clinical Center Tours
- Research Festival Committees
- Past Research Festivals
Data quality of open source extraction software unified with data repository in computed tomography (CT) radiation dose monitoring
| Friday, November 08, 2013 — Poster Session III | |||
|---|---|---|---|
10:00 a.m. – 12:00 p.m. |
FAES Academic Center (Upper-Level Terrace) |
CC |
CLIN-6 |
Authors
- VM Derderian
- JW Siegelman
- T Cook
- S Rath
- EC Jones
- C Lee
- LR Folio
Abstract
Purpose: To assess utility and data quality of open-source computed tomography (CT) scanner output data extraction and management software merge with a clinical data repository (Biomedical Translational Research Information System, BTRIS) in a research hospital CT radiation monitoring program. Methods: Following IRB exemption, 250 consecutive CT scanner parameters (CTDIvol, DLP) extracted by RADIANCE (http://www.radiancedose.com) were exported and integrated with clinical data in the NIH BTRIS data repository; accession and medical record numbers, study description and scanner were matched with patient records (BMI, demographics, protocol/physician). One month of RADIANCE data was compared with PACS. Resource cost savings from querying merged database versus manual extraction was estimated. Results: RADIANCE capture rate was 84% (250/296); 18% (40/222) of patients had missing data. Overall 41% missed scans were cardiac, 13% sinus, 11% chest/abdomen/pelvis, and 9% chest; 63% were missed from one scanner. Incomplete capture rate was due to incompatible vendor layouts and incomplete dose page distribution for multi-region studies. The data repository matched PACS and returned results for all 250 exams sent. Estimated time saved for one month of data queries was 21 hours. Conclusions: Our sampling study identified data oversight and capture discrepancies; these open-source limitations can be mitigated through stewardship.
