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1.  Developing an Automated Database for Monitoring Ultrasound- and Computed Tomography-Guided Procedure Complications and Diagnostic Yield 
Journal of Digital Imaging  2013;27(2):270-279.
Monitoring complications and diagnostic yield for image-guided procedures is an important component of maintaining high quality patient care promoted by professional societies in radiology and accreditation organizations such as the American College of Radiology (ACR) and Joint Commission. These outcome metrics can be used as part of a comprehensive quality assurance/quality improvement program to reduce variation in clinical practice, provide opportunities to engage in practice quality improvement, and contribute to developing national benchmarks and standards. The purpose of this article is to describe the development and successful implementation of an automated web-based software application to monitor procedural outcomes for US- and CT-guided procedures in an academic radiology department. The open source tools PHP: Hypertext Preprocessor (PHP) and MySQL were used to extract relevant procedural information from the Radiology Information System (RIS), auto-populate the procedure log database, and develop a user interface that generates real-time reports of complication rates and diagnostic yield by site and by operator. Utilizing structured radiology report templates resulted in significantly improved accuracy of information auto-populated from radiology reports, as well as greater compliance with manual data entry. An automated web-based procedure log database is an effective tool to reliably track complication rates and diagnostic yield for US- and CT-guided procedures performed in a radiology department.
PMCID: PMC3948931  PMID: 24146357
Procedures; Complications; Diagnostic yield; Tracking; Automated
2.  Orion: A Web-Based Application Designed to Monitor Resident and Fellow Performance On-Call 
Journal of Digital Imaging  2011;24(5):897-907.
Radiology residency and fellowship training provides a unique opportunity to evaluate trainee performance and determine the impact of various educational interventions. We have developed a simple software application (Orion) using open-source tools to facilitate the identification and monitoring of resident and fellow discrepancies in on-call preliminary reports. Over a 6-month period, 19,200 on-call studies were interpreted by 20 radiology residents, and 13,953 on-call studies were interpreted by 25 board-certified radiology fellows representing eight subspecialties. Using standard review macros during faculty interpretation, each of these reports was classified as “agreement”, “minor discrepancy”, and “major discrepancy” based on the potential to impact patient management or outcome. Major discrepancy rates were used to establish benchmarks for resident and fellow performance by year of training, modality, and subspecialty, and to identify residents and fellows demonstrating a significantly higher major discrepancy rate compared with their classmates. Trends in discrepancies were used to identify subspecialty-specific areas of increased major discrepancy rates in an effort to tailor the didactic and case-based curriculum. A series of missed-case conferences were developed based on trends in discrepancies, and the impact of these conferences is currently being evaluated. Orion is a powerful information technology tool that can be used by residency program directors, fellowship programs directors, residents, and fellows to improve radiology education and training.
PMCID: PMC3180545  PMID: 21249419
Software design; Quality improvement; Residency; Medical informatics applications; Natural language processing; Performance measurement; Discrepancies; Performance; Web-based; Residents
3.  Use of a Dedicated Server to Perform Coronal and Sagittal Reformations in Trauma Examinations 
Journal of Digital Imaging  2010;24(3):494-499.
The purpose of this study was to evaluate the impact of implementing an automated process for generating coronal and sagittal reformatted images on radiologist workflow. When performing trauma-related CT examinations of the cervical, thoracic, and lumbar spine at our institution, technologists manually generate coronal and sagittal reconstructions at the scanner console and send these images to a picture archiving and communication system (PACS) for interpretation by radiologists and clinical viewing. Although certain PACS, thin-client three-dimensional systems, and CT scanners are capable of automatically generating reconstructed or reformatted images, the systems at our institution do not support this functionality. We have recently integrated a dedicated server that is capable of automatically generating multiplanar reformatted (MPR) images from source thin-section axial images and sending these images to PACS without requiring technologist input. This dedicated server was used to generate coronal and sagittal MPRs for trauma-related spine studies in parallel with technologist-generated coronal and sagittal reconstructions. When comparing the two methods, using the dedicated server to automatically generate reformations resulted in substantial time savings for the radiologist compared to technologist-generated reconstructions. Additionally, a survey of interpreting radiologists indicated that a significant majority preferred to view the automatically generated MPRs on PACS compared to the thin-client system, considered the image quality to be good or excellent, and believed that viewing MPRs increased diagnostic accuracy and confidence. It is expected that this automated process will significantly improve radiologist workflow with respect to image interpretation time and report turnaround time.
PMCID: PMC3092042  PMID: 20393869
Transforming the Radiological Interpretation Process (TRIP™); workflow; productivity; automation

Results 1-3 (3)