Clinical Scorecard: The Quest for Widespread Adoption of Structured Reporting in Radiology
At a Glance
Category
Detail
Condition
Structured reporting in radiology
Key Mechanisms
Use of standardized templates and large language models (LLMs) to convert free-text reports into structured, mineable data formats
Target Population
Radiologists and healthcare systems globally
Care Setting
Radiology departments and clinical imaging services
Key Highlights
Structured reporting promises to transform radiology practice and unlock new data-driven healthcare possibilities.
Widespread adoption remains limited due to workflow disruption, lack of incentives, and organizational challenges.
Emerging AI technologies like LLMs may facilitate transition by structuring unstructured reports and integrating templates.
Guideline-Based Recommendations
Diagnosis
No direct diagnostic guidelines; focus is on reporting standardization to improve data quality and usability.
Management
Harmonize structured reporting templates across institutions and countries to establish best practices.
Provide incentives and necessary resources to encourage adoption during the transition phase.
Monitoring & Follow-up
Monitor impact on reporting speed, error rates, and workflow efficiency during adoption of structured reporting.
Risks
Potential disruption to traditional speech-based workflows causing temporary decreases in speed and increased errors.
Economic burden and vendor lock-in risks associated with commercial AI-based solutions.
Risk of data leakage and technical challenges with open-source LLM deployments.
Potential widening of global disparities and biases in clinical practice due to uneven access to structured reporting technologies.
Patient & Prescribing Data
Not applicable; focus on radiology reporting processes rather than direct patient treatment.
Structured reporting data can enable improved clinical decision support and optimized patient follow-up, e.g., automated scheduling for incidental findings.
Clinical Best Practices
Engage national and international radiological societies to collaborate on template harmonization.
Educate policymakers on the value of structured reporting to secure incentives and resources.
Leverage AI technologies cautiously, balancing innovation with risks of vendor lock-in and data security.
Implement structured reporting incrementally with monitoring to minimize workflow disruption.
Promote open-source solutions with adequate technical support to reduce economic barriers.
