# US 2019/0172012 A1 · Healthcare supply chain management systems, methods, and computer program products > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2019/0172012 A1 - Document ID: US20190172012A1 - Status: Published application - Kind: A1 - Application number: 16/210,544 - Filed: 2018-12-05 - Published: 2019-06-06 - Earliest claimed: 2017-12-05 - Assignees: Standvast Healthcare Fulfillment, LLC - Applicants: Standvast Healthcare Fulfillment, LLC - Inventors: Cayce Roy; Tim Hwu; John Appert - Web page: https://patentgrep.com/patent/US20190172012A1 ## CPC - G06Q 10/0875: Itemisation or classification of parts, supplies or services, e.g. bill of materials - G06Q 10/06315: {Needs-based resource requirements planning or analysis} - G06Q 10/0832: Special goods or special handling procedures, e.g. handling of hazardous or fragile goods - G06Q 10/0833: Tracking - G06Q 10/0837: Return transactions - G06N 7/01: Probabilistic graphical models, e.g. probabilistic networks - G06N 20/00: Machine learning - G06Q 10/10: Office automation; Time management - G06Q 40/08: Insurance - G16B 40/00: ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS - G16B: BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY ## Abstract In one aspect, a method for a healthcare supply chain management system is provided. The method may include extracting schedule and procedure information from electronic health record systems. The method may include ordering required medical items at least based on the extracted schedule and procedure information. The method may include creating an order for a medical procedure at least based on the extracted schedule and procedure information, where the order includes a request for at least one or more medical items related to the medical procedure. The method may include managing the order for the medical procedure. The method may include employing machine learning to optimize the healthcare supply management system. ## Claims ### Claim 1 A method for a healthcare supply chain management system, the method comprising: extracting schedule and procedure information from electronic health record systems; ordering required medical items at least based on the extracted schedule and procedure information; creating an order for a particular medical procedure at least based on the extracted schedule and procedure information, wherein the order comprises a request for at least one or more medical items related to the particular medical procedure; managing the order for the particular medical procedure; and employing machine learning to optimize the healthcare supply management system. ### Claim 2 (depends on 1) The method of claim 1, wherein the schedule and procedure information comprises at least one or more of electronic medical records (EMR), electronic health records (EHR), customer billing information, finance accounting information, and enterprise resource planning (ERP) information. ### Claim 3 (depends on 1) The method of claim 1, wherein managing the order for the particular medical procedure comprises: scheduling replenishment of the one or more medical items related to the particular medical procedure at a warehouse; and scheduling delivery of the one or more medical items to a facility conducting the particular medical procedure. ### Claim 4 (depends on 3) The method of claim 3, wherein managing the order for the medical procedure further comprises: fulfilling the one or more medical items using mass customized e-commerce fulfillment capabilities. ### Claim 5 (depends on 3) The method of claim 3, wherein managing the order for the medical procedure further comprises: tracking the one or more medical items delivered to the facility, wherein tracking the one or more medical items comprises tracking the one or more medical items delivered to a point of use at the facility and tracking any non-used items of the one or more medical items delivered to the point of use. ### Claim 6 (depends on 5) The method of claim 5, wherein at least one of barcodes, RFID, voice recognition, cameras, visual recognition systems, and a block chain system is used to track the one or more medical items delivered to the facility. ### Claim 7 (depends on 3) The method of claim 3, wherein managing the order for the medical procedure further comprises: determining whether all of the delivered one or more medical items were used in the medical procedure; and as a result of determining that all of the one or more medical items were not used in the medical procedure, determining one or more medical items that were not used in the medical procedure. ### Claim 8 (depends on 7) The method of claim 7, wherein employing machine learning to optimize the healthcare supply management system comprises: optimizing a future order creation for the medical procedure based on the one or more medical items that were not used. ### Claim 9 (depends on 8) The method of claim 8, wherein optimizing the future order creation for the medical procedure is further based on at least one or more of: (i) quality of the medical procedure outcome and (ii) cost of the medical items. ### Claim 10 (depends on 7) The method of claim 7, wherein employing machine learning to optimize the healthcare supply management system comprises: automatically managing an inventory at the facility based on the one or more medical items that were not used. ### Claim 11 (depends on 10) The method of claim 10, wherein employing machine learning to optimize the healthcare supply management system comprises: automatically managing the inventory at the facility further based on at least one or more of the extracted schedule and procedure information, changing lead times, and healthcare supply chain processes. ### Claim 12 (depends on 1) The method of claim 1, wherein employing machine learning to optimize the healthcare supply management system comprises: providing a recommendation for the at least one or more medical items related to the medical procedure. ### Claim 13 (depends on 1) The method of claim 1, wherein the machine learning comprises at least one or more of unsupervised classification algorithms and predictive algorithms. ### Claim 14 A healthcare supply chain management system, the system comprising: one or more servers, wherein each of the one or more servers comprise: memory; and processing circuitry coupled to the memory, the processing circuitry configured to: extract schedule and procedure information from electronic health record systems; order required medical items at least based on the extracted schedule and procedure information; create an order for a medical procedure at least based on the extracted schedule and procedure information, wherein the order comprises a request for at least one or more medical items related to the medical procedure; manage the order for the medical procedure; and employ machine learning to optimize the healthcare supply management system. ### Claim 15 A computer program stored on a non-transitory computer readable medium, the computer program comprising instructions, which when executed by processing circuitry, causes the processing circuitry to: extract schedule and procedure information from electronic health record systems; order required medical items at least based on the extracted schedule and procedure information; create an order for a medical procedure at least based on the extracted schedule and procedure information, wherein the order comprises a request for at least one or more medical items related to the medical procedure; manage the order for the medical procedure; and employ machine learning to optimize a healthcare supply management system.