Method and system for a distributed analytical and diagnostic software over the intranet and internet environment

• US 20020107452A1
• Filed: 08/09/2001
• Published: 08/08/2002
• Est. Priority Date: 08/09/2000
• Status: Active Grant

• Current Assignee: Clinical Microsystems Intl.
• Original Assignee: Clinical Microsystems Intl.
• Inventors: Kwong, Manlik
• Granted Patent: US 6,917,829 B2
• Time in Patent Office: Days
• US Class Current: 600/509
• CPC Class Codes: A61B 5/0002 Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network A61B5/07 takes precedence; transmission systems for measured values G08C; transmission H04B; transmission of digital information H04L; wireless communication networks H04W
• CPC Class Codes: A61B 5/412 Detecting or monitoring sepsis
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 15/00 ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders

Abstract

An apparatus for monitoring the medical condition of a patient, including a monitoring device which during use monitors one or more clinical features of the patient; a predictive instrument arranged to receive output from the monitoring device and programmed to compute a probability of a medical outcome or diagnosis based on the monitored one or more clinical features, the predictive instrument further programmed to compute that probability by executing an algorithm which models the medical outcome or diagnosis; and an interface through which a user enters information characterizing the patient, wherein the predictive instrument is further programmed to request that algorithm from a remote location.

Claims

1. An apparatus for monitoring the medical condition of a patient, said apparatus comprising:

a monitoring device which during use monitors one or more clinical features of the patient;

a predictive instrument arranged to receive output from the monitoring device and programmed to compute a probability of a medical outcome or diagnosis based on the monitored one or more clinical features, said predictive instrument further programmed to compute said probability by executing an algorithm which models said medical outcome or diagnosis; and

an interface through which a user enters information characterizing the patient, wherein said predictive instrument is further programmed to request said algorithm from a remote location.

2. The apparatus of claim 1 wherein the monitoring device is an electrocardiograph.

3. The apparatus of claim 2 wherein the algorithm enables the predictive instrument to compute said probability using a regression equation.

4. The apparatus of claim 3 wherein the regression equation is of the form:

5. The apparatus of claim 4 wherein P is a probability of acute cardiac ischemia.

6. An apparatus for enabling a remotely located predictive instrument to compute a probability of a medical outcome or diagnosis based on monitored one or more clinical features of a patient, said apparatus comprising:

a data storage area which stores a plurality of different algorithms, each of which models a corresponding medical outcome or diagnosis; and

a server which is programmed to respond to a request from a remote device by retrieving a selected one of said plurality of different algorithms from said data storage and forwarding the selected algorithm to the remote device.

7. The apparatus of claim 6 wherein the request contains a patient profile and the server identifies which of the plurality of different algorithms is the selected algorithm based on the received patient profile.

8. A method for evaluating a medical condition of a patient, said method comprising:

receiving input characterizing the patient;

electronically retrieving from a remote location, an algorithm for computing a probability of a medical outcome or diagnosis;

monitoring one or more clinical features of a patient; and

using the retrieved algorithm to compute the probability of the medical outcome or diagnosis for the patient and based on the monitored features.