Relocation module and methods for surgical equipment

Abstract

Module for housing electronic and electromechanical medical equipment including a portable digital camera and processing circuitry with machine vision and machine learning software for automatically documenting healthcare events and healthcare equipment operations in the electronic health record.

What is claimed is: 
     
         1 . An automated data consolidation system, the automated data consolidation system comprising:
 at least one digital camera configured to produce digital data; and   processing circuitry in wired or wireless electrical communication with the at least one digital camera to automatically receive the digital data, wherein the processing circuitry and software is configured to interpret the digital data by:
 performing at least one of machine learning (ML) analysis and artificial intelligence (AI) analysis to identify visual elements of an image of the digital data by comparing the digital data of a subject image to known images stored in an image library to determine dose events or response events in the digital data; 
 add time stamps or other indicators of time to specific visual elements following identification of the dose events or response events; and 
 automatically save the digital data including the visual elements of the image or the image itself to an electronic record or database. 
   
     
     
         2 . The automated data consolidation system of  claim 1 , wherein the processing circuitry and software is configured to structure and organize the digital data from the at least one digital camera to generate a database for subsequent big data analytics. 
     
     
         3 . The automated data consolidation system of  claim 1 , wherein the processing circuitry and software is configured to transform the digital data via steps of extract, transform, and load (ETL) to clean and prepare the digital data for input to an external device or database. 
     
     
         4 . The automated data consolidation system of  claim 1 , wherein the processing circuitry and software is configured to filter and clean the digital data for submission to a big data database, an electronic health record (EHR), or other data user. 
     
     
         5 . The automated data consolidation system of  claim 1 , wherein the processing circuitry and software is configured to apply consistent data standards, consistent data formatting, consistent data fields, consistent data labeling and timestamping, to produce data for AI analysis and research or ML analysis and research. 
     
     
         6 . The automated data consolidation system of  claim 1 , wherein the processing circuitry and software is configured to use the digital data, after being automatically saved and timestamped, for one or more of: AI and ML enabled clinical decision support (CDS) functions, AI and ML enabled remote monitoring and supervision functions, AI and ML enabled generative medical note writing and editing, AI and ML enabled big data analytics, AI and ML enabled controlled drug chain of custody monitoring, AI and ML enabled administrative and inventory functions, AI and ML enabled apps, AI and ML enabled quality assurance, and AI and ML enabled medical research. 
     
     
         7 . The automated data consolidation system of  claim 1 , wherein the at least one digital camera is a sensor. 
     
     
         8 . An automated data consolidation system, the automated data consolidation system comprising:
 at least one digital camera configured to produce digital data, the at least one digital camera positionable in a known orientation relative to pertinent visual elements of a scene and to create a standardized scene; and   processing circuitry in wired or wireless electrical communication with the at least one digital camera to automatically receive the digital data, the processing circuitry and software configured to:
 detect dose events or response events by matching a subject image of the digital data to known images of similar standardized scenes stored in an image library using at least one of machine learning (ML) and artificial intelligence (AI) analysis of the digital data to identify specific visual elements of an image of the digital data of the standardized scene; 
 add time stamps or other indicators of time to the specific visual elements so that the digital data can be temporally correlated during subsequent big data or clinical decision support analysis; and 
 automatically save information provided by the specific visual elements of the image or the image itself to an electronic record or database. 
   
     
     
         9 . The automated data consolidation system of  claim 8 , wherein the processing circuitry and software is configured to label standardized scenes stored in an image library to identify the specific visual elements of the subject image of the digital data to identify a specific person, item, or device within the scene or portion of the specific person, or item or device within the scene that is of interest and thereby limiting a number of known images of similar standardized scenes that must be compared in order to find the matching image. 
     
     
         10 . The automated data consolidation system of  claim 8 , wherein the scene is standardized at least in part by positioning the at least one digital camera in a known orientation including a front view of the pertinent visual elements of the scene and thus eliminating side views and top views and oblique views that could be confusing to the machine learning (ML) and artificial intelligence (AI) analysis. 
     
     
         11 . The automated data consolidation system of  claim 8 , wherein the scene is standardized at least in part by positioning the at least one digital camera in a known orientation to the pertinent visual elements of a scene including a medical item, a meter, a piece of medical equipment, or a patient. 
     
     
         12 . The automated data consolidation system of  claim 8 , wherein the scene is standardized at least in part by positioning the at least one digital camera in a known orientation to the pertinent visual elements of a scene such as a whole patient or a face of a patient. 
     
     
         13 . The automated data consolidation system of  claim 8 , wherein the scene is standardized at least in part by positioning the at least one digital camera in a known orientation to the pertinent visual elements of a scene including as a medical procedure, a medical therapy, a medical examination, or a surgery. 
     
     
         14 . The automated data consolidation system of  claim 8 , wherein the scene is standardized at least in part by positioning the at least one digital camera in a known orientation to the pertinent visual elements of a scene including verifying pills of a patient or observing the patient taking the pills. 
     
     
         15 . The automated data consolidation system of  claim 8 , wherein the processing circuitry and software is configured to apply consistent data standards, consistent data formatting, consistent data fields, consistent data labeling, and timestamping, to produce data for AI and ML analysis and research. 
     
     
         16 . The automated data consolidation system of  claim 8 , wherein processing circuitry and software is configured to use the digital data, after being automatically saved and timestampted, for one or more of: AI and ML enabled clinical decision support (CDS) functions, AI and ML enabled remote monitoring and supervision functions, AI and ML enabled generative medical note writing and editing, AI and ML enabled “big data”’ analytics, AI and ML enabled controlled drug chain of custody monitoring, AI and ML enabled administrative and inventory functions, AI and ML enabled apps, AI and ML enabled quality assurance, and AI and ML enabled medical research. 
     
     
         17 . The automated data consolidation system of  claim 8 , wherein the at least one digital camera is a sensor. 
     
     
         18 . An automated data consolidation system, the automated data consolidation system comprising:
 at least one digital camera configured to produce and transmit digital data; and   processing circuitry in communication with the at least one digital camera to automatically receive the digital data, the processing circuitry and software configured to:
 performing at least one of machine learning (ML) and artificial intelligence (AI) analysis to identify specific visual elements of an image of the digital data by matching a subject image of the digital data to known images stored in an image library, wherein the identified specific visual elements of the image constitute dose events or response events; 
 add time indicia to each identified specific visual elements; and 
 automatically save results of the analysis, the matched specific visual elements of the image, or the image itself to an electronic record or database; 
 create a written note based on the matched specific visual elements; and 
 save the written note in an electronic medical record. 
   
     
     
         19 . The automated data consolidation system of  claim 18 , wherein the written note includes documentation of a medical procedure, a medical therapy, a medical examination or a surgery. 
     
     
         20 . The automated data consolidation system of  claim 18 , wherein the written note includes a standardized template note that can be quickly edited for customization to a patient. 
     
     
         21 . The automated data consolidation system of  claim 18 , wherein the written note is configured to include a customized template note written by a clinician that can be quickly edited for further customization to a patient. 
     
     
         22 . The automated data consolidation system of  claim 18 , wherein the written note is a customized AI generated note. 
     
     
         23 . The automated data consolidation system of  claim 18 , wherein the processing circuitry and software is configured to apply consistent data standards, consistent data formatting, consistent data fields, or consistent data labeling and timestamping, to produce data for AI and ML analysis and research. 
     
     
         24 . The automated data consolidation system of  claim 18 , wherein the processing circuitry and software is configured to use the digital data, after being automatically saved and timestamped for one or more of: AI and ML enabled clinical decision support (CDS) functions, AI and ML enabled remote monitoring and supervision functions, AI and ML enabled generative medical note writing and editing, AI and ML enabled “big data”’ analytics, AI and ML enabled controlled drug chain of custody monitoring, AI and ML enabled administrative and inventory functions, AI and ML enabled apps, AI and ML enabled quality assurance, and AI and ML enabled medical research. 
     
     
         25 . The automated data consolidation system of  claim 18 , wherein the at least one digital camera is a sensor. 
     
     
         26 . An automated data consolidation system, the automated data consolidation system comprising:
 at least one digital camera configured to produce digital data; and   processing circuitry in wired or wireless electrical communication with the digital camera to receive the digital data, wherein the digital data is automatically delivered to the processing circuitry and software, and wherein the processing circuitry and software is configured to:
 performing at least one of machine learning (ML) and artificial intelligence (AI) analysis to identify specific visual elements of an image of the digital data by matching a subject image of the digital data to known images stored in an image library, wherein the identified specific visual elements of the image constitute dose events or response events; 
 add time stamps or other indicators of time to the identified specific visual elements so that the digital data can be temporally correlated during subsequent big data or clinical decision support analysis; 
 automatically save information provided by the matched specific visual elements of the image or the image itself to an electronic record or database; and 
 use the data, after being automatically saved and timestamped, for one or more of: AI and ML enabled clinical decision support (CDS) functions, AI and ML enabled remote monitoring and supervision functions, AI and ML enabled generative medical note writing and editing, AI and ML enabled “big data” analytics, AI and ML enabled controlled drug chain of custody monitoring, AI and ML enabled administrative and inventory functions, AI and ML enabled apps, AI and ML enabled quality assurance, and AI and ML enabled medical research.