Artificial Intelligence: Improving Efficiency in Radiology
Artificial Intelligence (AI) continues to take the radiology world by storm. While the fear of AI replacing radiologists exists, many imaging leaders are focusing less on how to avoid it and more on how to leverage AI successfully into their radiology department. With operational efficiency being a key component to your department’s success, integrating AI will help hospitals and imaging centers streamline processes allowing you to stay competitive in today’s changing healthcare market.
So, how can imaging leaders reap the early benefits of AI? For starters, using AI for repetitive, non-complex tasks will help improve quality and efficiency within the department. Advisory Board, uncovered 4 ways to leverage AI in radiology:
Intelligent Speech Recognition
As the radiologist dictates, speech recognition software suggests changes that can reduce transcription errors. Natural language processing algorithms can also check completed dictations for inconsistencies, such as referring to the same nodule as being located in the left and right lung.
Potential Benefit: Significantly fewer dictation errors and improved efficiency as radiologists spend less time checking/correcting dictations.
Worklist Management and Exam Escalation
AI software orders the worklist based on urgency and subspecialty and continuously adjusts triage rules for new cases. For more advanced exam escalation, a built-in algorithm reviews an image for critical findings and can prioritize exams with suspected critical findings.
Potential Benefit: Improved efficiency as radiologists do not spend time finding and selecting their next exam. Provides higher quality care as critical exams are prioritized to achieve shorter turnaround times.
Quantitative Measurement Solutions
As an exam is read, radiologists use simple commands to pull in quantitative measurements captured automatically by the AI software. Advanced solutions may offer accompanying decision support, allowing for standardized recommendations.
Potential Benefit: Improved efficiency and turnaround times as well as provision of more standardized recommendations when combined with decision support based on guidelines.
Clinical Information Briefings
Before images are read, AI algorithms pull information from the EMR via the Fast Health Care Interoperability application and then combine patient background, reason for exam, and any other clinical information into a single, easy-to-read summary for radiologists.
Potential Benefit: Improved efficiency as radiologists have all the necessary information on their patient located in one concise summary.
The world of radiology has warmed up to the idea of artificial intelligence and the potential for medical and productivity benefits runs deep. With efficiency being top of mind for many imaging leaders, systems that can read and interpret multiple images quickly will reduce inefficiencies and optimize workflow allowing for a broader, deeper impact on patient care.