Better Quality and Continuity of Care

↑300%
 Accuracy of
​Diagnostic Codes 

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↑5-10%
Diversity of
Complication Codes

Clinical Diagnostic Reasoning Network

Every patient has a unique medical history and journey. The more complex the history, the longer it takes to process and document. DxPrime simplifies this with our exclusive Clinical Deep Reasoning Networks analysis technology in real-time based on each patient's specific conditions, enhancing the quality and efficiency of the diagnostic decision-making process.

Evidence-Based Analysis to Reduce Diagnostic Error

DxPrime proactively conducts gap analysis between diagnoses and clinical evidence during the diagnostic decision-making process, providing real-time feedback on potentially missed, incomplete, or unclear diagnostic items. By promoting accuracy in diagnostic information sourced from medical records, it reduces diagnostic errors and unnecessary back-and-forth confirmations, enhancing timely, effective, and appropriate care.

Better Hospital Performance

↑26%
CDI
​Extension

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↑5-10%
Boost
​in Performance

Comprehensive Diagnosis Decision Variables

DxPrime utilizes machine learning to analyze a variety of data, encompassing problems, medications, lab tests, treatments, and operations. Our research highlights DxPrime's 99% accuracy in identifying and analyzing data. It provides substantial support to doctors throughout the diagnostic process.

Directly Integrated into Clinical Workflows​

DxPrime is seamlessly integrated into the physician's clinical workflow. It can be readily accessed via the electronic health record system with a simple click. Physicians can now free themselves from traditional, inefficient manual search and input methods, without getting lost in complex medical information.

Early Prediction and Timely Intervention of Comorbidities

​Real-time feedback on primary and secondary diagnoses for potentially missed, incomplete, or unclear diagnostic items.

• ​CCs, MCCs, comorbidity index-relevant diagnoses
• Possible diagnoses for rare or complex cases ( Long-tail suggestions )

​Explainable AI for Comprehensive Overview of Diagnostic Decision Variables

Dynamic and on-demand display of the network relationships between suggested items and clinical evidence allows for one-click integration into medical records, optimizing diagnostic decisions and improving the quality of medical documentation.

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