Allscripts Healthcare Solutions has been granted a patent for a resource management system that optimizes and distributes predictively processed data in medical software applications. The system uses profile data from different health care facilities to improve operational capabilities and capacities, addressing out-of-threshold conditions for future cycles. GlobalData’s report on Allscripts Healthcare Solutions gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on Allscripts Healthcare Solutions, was a key innovation area identified from patents. Allscripts Healthcare Solutions's grant share as of February 2024 was 79%. Grant share is based on the ratio of number of grants to total number of patents.
Resource management system for medical software applications optimization
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A recently granted patent (Publication Number: US11908570B1) discloses a resource management system designed to optimize and distribute predictively processed data within a medical software application on a computer network. The system includes a memory for storing profile data of various computer systems associated with remote healthcare facilities, a processing apparatus to group these systems based on linked characteristics, and a communications interface to transmit resource management data and receive feedback. The processing apparatus utilizes simulation and feedback data to generate updated resource management data for future operational cycles, addressing any out-of-threshold conditions. This updated data is then transmitted to relevant computer systems to replace existing data, ensuring optimized operational capability and capacity.
Furthermore, the patent details a method for implementing this resource management system, involving storing profile data, probabilistically grouping computer systems, transmitting resource management data, receiving feedback, and predictively processing data via simulation. The method aims to optimize operational capability and capacity data within medical software applications by addressing out-of-threshold conditions based on feedback. The system utilizes a resource model, such as a decision tree hierarchical structure or fuzzy logic model, to perform predictive processing. Additionally, the system re-groups computer systems based on chronological data and transmits updated resource management data to systems indicating out-of-threshold conditions, replacing existing data. This innovative approach ensures efficient resource management and distribution within medical software applications on computer networks, enhancing overall operational performance.
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