Patient Procedure Surveillance System with Priority-Based File Segmentation
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Solution Overview
Problem
Current healthcare documentation systems face challenges in accurately and efficiently documenting patient medical procedures, leading to incomplete billing and reduced reimbursement due to bandwidth constraints and the inability to distinguish between pertinent and non-pertinent surveillance data, resulting in substantial administrative burdens and potential quality of care issues.
Innovation Solution
A patient surveillance system that utilizes video and audio documentation, autonomously sensing the presence of healthcare professionals to create prioritized medical procedure files, storing them in nonvolatile memory for later retrieval, and transmitting them to a central database, thereby ensuring comprehensive and timely documentation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If comprehensive video and audio surveillance data is collected for all patient procedures, then complete documentation is achieved, but data storage and retrieval become inefficient due to inability to distinguish pertinent from non-pertinent data
Solution Approach 1:
The system segments surveillance data into different priority levels (pertinent medical procedure data versus routine surveillance data) using motion detection algorithms and event triggers. This segmentation allows the system to separately manage and retrieve only relevant documentation data without searching through all collected surveillance information.
Solution Approach 2:
The system extracts and isolates pertinent medical procedure data from the broader surveillance data stream using motion sensors, audio analysis, and event-triggered capture. By extracting only the relevant portions, the system enables efficient retrieval of documentation data without the overhead of processing entire surveillance datasets.
2Reliability
If manual documentation of medical procedures is performed by healthcare professionals, then accurate procedural records can be created, but administrative burden and time consumption increase substantially
Solution Approach 1:
The system performs self-service documentation by automatically detecting medical procedures through motion sensors, audio analysis, and event triggers, then capturing and storing the relevant video and audio data without requiring manual intervention from healthcare professionals. This eliminates the administrative burden while maintaining documentation accuracy.
Solution Approach 2:
The system replaces the manual mechanical process of documentation with automated electronic detection and capture systems. Motion sensors, audio sensors, and processors automatically identify and record procedural events, substituting human manual documentation efforts with automated technological systems.
3Loss of information
If all surveillance data is transmitted to central databases, then comprehensive records are maintained, but bandwidth constraints and transmission time become limiting factors
Solution Approach 1:
The system extracts and transmits only the pertinent medical procedure data to central databases, rather than transmitting all surveillance data. This extraction based on motion detection, event triggers, and procedural identification significantly reduces bandwidth consumption while maintaining complete procedural records.
Solution Approach 2:
The system segments surveillance data into transmit-worthy procedural data and non-critical routine data. Only the segmented procedural portions are transmitted to central databases, optimizing bandwidth usage while ensuring complete documentation of medical procedures.
4Reliability
If detailed documentation of every medical procedure is maintained, then reimbursement accuracy improves, but the complexity of documentation systems and processes increases
Solution Approach 1:
The documentation system performs self-service by automatically identifying, capturing, and organizing procedural data based on sensor inputs and event triggers. This automation maintains detailed documentation for accurate reimbursement without requiring complex manual documentation processes or extensive administrative infrastructure.
Data Source
AI summary
The local surveillance sub-system recognizes that a patient medical procedure has or will soon commence by sensing the presence of a healthcare professional in or near the surveillance area, and in response, creates a separate patient medical procedure A/V file for the surveillance data that will be captured. A dedicated procedure remote may be provided for receiving manual interactions from HC professionals present for a procedure or, alternatively, the local surveillance sub-system may autonomously interact with a personal security token device possessed by the HC professional. A procedure data file is also created that holds all of the pertinent information concerning the procedure that is known by the local surveillance sub-system. The patient procedure surveillance A/V file is given a higher priority than ordinary surveillance data captured by the local surveillance sub-system and is then copied to a nonvolatile memory.