CareSelect Imaging – AI Indication Selection
Leverage CareSelect Imaging with Artificial Intelligence to improve the indication selection workflow.
Improve the CDS Consultation Workflow
Order triggers decision support session.
Leverage patient, provider, and order context for the AI prediction model.
Auto-match to an indication when possible.
When multiple indications are relevant, show short list to provider for quick indication selection.
Reduce Provider Burden with Automated Indication Selection
Predict relevant indications to streamline the provider ordering workflow
Effective decision support relies on the selection of clinical indications to tie a patient’s clinical scenario to relevant Appropriate Use Criteria (AUC). CareSelect AI leverages relevant data about the patient, provider, and order context, to predict the most likely indications a provider might select.
In some cases, the system can auto-select the relevant indication, requiring no input from the provider. AI results are based on NDSC’s national transaction registry, which comprises decision support consultation data from over 300 healthcare organizations.
CareSelect Imaging AI Goals
- Improve quality of care and patient outcomes – Better specificity of indications based on AI analysis of encounter data improves guidance and quality of care.
- Simplify user experience – AI embedded within the EHR simplifies the user experience by predicting the most relevant indications based on the patient, provider, and order context.
- Expand relevant data – The AI model learns from a transaction registry of 75 million radiology decision support sessions aggregated over seven years.
- Assist providers with PAMA compliance – Optimize indication model for greater visibility and less maintenance to ensure compliance.
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