Industry Specific Software Package - Decision Support For Medical Documentation - Llm -Based Doctors Letter Description. The Award Procedure Pursues The Goal Of Identifying A Powerful, Experienced And Technologically Innovative Provider For Decision -Making For Medical Documentation - Llm -Based Doctors Letter Description. The Selection Is To Be Made On The Basis Of Objective, Transparent And Compliance With Public Procurement Law And Ensures Sustainable, Economically Sustainable And Future -Proof System Solution, Which Meets The Specific Requirements Of The Client. By Using An Automated Clinical Decision -Making System (Project 4.01 According To The Application) Based On Artificial Intelligence (Ai), Patient -Specific Information On Possible Diseases, Complications Or Risks Should Be Generated In Real Time And These Are Presented To The Practitioner. The Practitioners Are Supported By The Automated Information And Recommendations In Their Treatment Decisions With The Aim Of Increasing The Quality Of Care. The Aim Of The Procurement Project Is To Provide An Integrable Solution To The Llm-Based Generation Of Doctors Letters Based On Structured Medical Data From Leading Systems/ Primary Systems. The Object Of Procurement Supports Medical Specialist Personnel In The Efficient, Content-Fully And Formally Correct Creation Of Doctors Letters Through The Automated Processing Of Relevant Treatment And Case Data. The Central Functional Element For The Decision-Making Support For Medical Documentation Is A Visual Overview/Homepage In The Form Of A Dashboard, Which Combines Structured Clinical, Administrative And Treatment-Related Information From Different Primary Systems. This Decision -Making Support Enables A Comprehensive View Of The Patient Process - From Recording To Discharge - And Forms The Starting Point For A Targeted, Contextual Doctors Letter Description. The Start Page Shows, Among Other Things, Anamnesis, Diagnoses, Medications, Vital Parameters, Imaging, Findings And Progress Data And Makes A Visual Recognition And Lack Of Content. In Addition, Relevant System Information, In Particular Station, Room, Length Of Stay And Processing Status, Are Shown In A Role -Specific Manner. The Solution Fits Functionally Into Existing Clinical System Landscapes And Uses Interoperable Data Sources That Are Standardized Via The Procurement Object. The Documents Generated Are Based On Clinical And Documentation-Relevant Requirements And Enable A Semantically Consistent, Gender And Context-Friendly Text Edition. In Addition, The Solution Shows Roll-Based Processing, Testing And Release Processes, Guarantees The Traceability Of All Processing Steps And Contributes To Structured Communication With Subsequent Service Providers. The Ai-Based Doctors Letter Description Strength
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