Context-Aware Patient Flow System Using RTLS Auto-ID Tags
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Solution Overview
Problem
The complexity and cost of healthcare delivery processes in clinical environments lead to increased opportunities for human error and higher staff-related expenses, with the patient registration process being lengthy and prone to transcription errors.
Innovation Solution
A context-aware system utilizing non-attached kiosks or self-service terminals (SSTs) that leverage real-time locating system (RTLS) data and clinical data sources to streamline patient flow, automate processes, and reduce human intervention, employing auto-ID patient tags for efficient and accurate patient registration, navigation, and discharge, while utilizing existing communication infrastructure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual patient registration and data transcription processes are used, then patients can be registered and information can be documented, but the process becomes lengthy, repetitive, and prone to transcription errors
Solution Approach 1:
The system enables patients to self-register and self-document information through automated kiosk interfaces. Patients input their own demographic and medical information directly into the system, eliminating the need for manual transcription by healthcare staff and reducing errors associated with manual data entry
Solution Approach 2:
The patent replaces manual mechanical processes (paper forms, handwriting, physical file handling) with electronic automated systems. Digital forms replace paper-based documentation, and automated data capture systems replace manual transcription, thereby improving accuracy and reducing time loss
2Ease of manufacture
If paper-based forms are used for patient documentation, then patient information can be recorded, but the process requires frequent transcription and increases the risk of data entry errors
Solution Approach 1:
The system creates digital copies of patient information directly in electronic format. Instead of transcribing from paper to electronic systems, the original data is captured digitally from the source, eliminating transcription errors and ensuring data integrity throughout the healthcare workflow
Solution Approach 2:
The patent extracts the transcription step entirely from the documentation process. By implementing direct electronic data capture at the point of care, the system removes the intermediate manual transcription step that causes errors and information loss
3Extent of automation
If auto-ID tags are assigned and deleted frequently for patient registration, then real-time patient location tracking is enabled, but the system requires frequent maintenance and computer system intervention
Solution Approach 1:
The system enables automatic tag assignment and deletion without requiring manual computer system intervention. The kiosk automatically manages RTLS tag distribution to patients upon registration and reclaims tags upon discharge, reducing maintenance burden and improving automation
Solution Approach 2:
The patent implements an automated tag recovery system that automatically collects and sanitizes RTLS tags after patient discharge. Tags are automatically returned to the pool for reuse, eliminating the need for frequent manual maintenance and computer system intervention for tag management
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system enhances the efficiency and safety of healthcare delivery by reducing human error, lowering operational costs, and improving the accuracy of patient data management through automated processes and real-time monitoring.
Implementation Method 1
Such tags emit radio-frequency (RF) and other signals such as infrared (IR) signals. The signals are used to establish the real-time location of the patients in a real-time locating system.
Implementation Method 2
Such tags emit radio-frequency (RF) and other signals such as infrared (IR) signals.
Data Source
AI summary
A context-aware method and system for facilitating the delivery of healthcare to patients within a clinical environment monitored by real-time locating apparatus including auto-ID patient tags where patients having tags are located within the environment in real time by the apparatus are provided. The system includes a plurality of self-service units where one or more of the units is configured to store a plurality of auto-ID patient tags and where the one or more of the units includes a dispensing mechanism to dispense stored tags. The system further includes a control computer subsystem coupled to the at least one of the units and including at least one user interface. The subsystem still further includes a processor operable to execute software instructions and a memory operable to store software instructions accessible by the processor. The subsystem still further includes a set of software instructions stored in the memory to at least partially perform the steps of: identifying an incoming patient; assigning a stored auto-ID patient tag to the identified patient to obtain a tag assignment; transmitting a signal over a communication channel to an electronic medical record subsystem to link the tag assignment to a medical record of the patient whereby the patient becomes a linked patient; and controlling the dispensing mechanism to dispense a stored tag to the linked patient.