Implementation of an Institution-Wide Rules-Based Automated CT Protocoling System.

Area of Science:

• Radiology
• Medical Imaging
• Health Informatics

Background:

• Radiologists face increased workload and workflow inefficiencies due to manual examination protocoling.
• Automated protocoling systems aim to streamline the process and reduce noninterpretive tasks.

Purpose of the Study:

• To evaluate the impact of an automated CT protocoling system on examination process times.
• To assess the protocol error rates associated with automated versus manual CT protocoling.

Main Methods:

• Retrospective analysis of 317,597 CT examinations over two years.
• Implementation of a rules-based automated protocoling system within the electronic health record (EHR).
• Comparison of process times, quality improvement (QI) reports, and recalls between automated and manual protocoling.

Main Results:

• Automatic protocoling increased from 27.4% to 64.5% over the study phases (p < .001).
• Automated protocoling significantly reduced times from order entry to protocol assignment and examination completion across all patient types (p < .001).
• Protocol error rates, indicated by QI reports and recalls, were infrequent for automated protocoling.

Conclusions:

• The automated protocoling system effectively reduced radiologists' workload and improved efficiency.
• The system demonstrated a high degree of accuracy, comparable to manual protocoling.
• Automated CT protocoling offers a viable solution for enhancing care efficiency by minimizing noninterpretive tasks.