Method of continuous prediction of patient severity of illness, mortality, and length of stay

A technology for patients and patient information, applied in the fields of disease diagnosis, patient-specific data, measurement devices, etc., can solve problems such as inaccurate prediction, and achieve the effect of improving accuracy and quality

Active Publication Date: 2013-07-10
KONINKLIJKE PHILIPS ELECTRONICS NV
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  • Abstract
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  • Claims
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AI Technical Summary

Problems solved by technology

[0003] The inventors observed that when predicting the length of hospital stay or the probability of death of a patient after the patient has been in intensive care for a few days, the prediction is less accurate

Method used

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  • Method of continuous prediction of patient severity of illness, mortality, and length of stay
  • Method of continuous prediction of patient severity of illness, mortality, and length of stay
  • Method of continuous prediction of patient severity of illness, mortality, and length of stay

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Embodiment Construction

[0015] refer to figure 1 , a patient (not shown) is monitored by various medical monitoring devices or sensors 10 that measure physiological parameters of the patient directly or in a laboratory and generate physiological data indicative thereof. These medical monitoring devices 10 may include electrocardiography (ECG) instruments with ECG electrodes, IV fluid pumps, blood pressure sensors, SpO2 sensors, pulse sensors, thermometers, respiration sensors, exhaled gas sensors, and the like. Other medical monitoring devices 10 may be associated with the patient, and not all of the aforementioned medical monitoring devices 10 are necessarily associated with the patient at any given time. It should be appreciated that while only two medical monitoring devices 10 are illustrated, many more are contemplated. As used herein, a medical monitoring device refers to a data source indicative of a patient's health status and the like. Electronics for receiving signals from the medical moni...

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Abstract

A method for predicting a patient's outcome variable, such as a probability of mortality / recovery, includes accessing at least one of a plurality past patients' data fields including physiological and / or laboratory data, and a time of stay indicating how long each patient had been under care at the time. An outcome variable estimation algorithm is generated by data mining from a plurality of past patients' physiological and / or laboratory data, corresponding time of stay, and associated outcome variables. A current patient's outcome variable is determined from the current patient's physiological and / or laboratory data, the current time of stay, and the outcome variable estimation algorithm.

Description

technical field [0001] The present application relates to a system or method for predicting outcome variables such as length of hospital stay, mortality, need for specific treatment, and disease severity of a patient in a healthcare setting. It finds particular application in improving and optimizing the prediction of patient length of stay or probability of death within a healthcare setting, and will be described with particular reference to this application. However, it will be appreciated that it may also find application in intensive care units, post-anesthesia care units, general care units, recovery rooms, operating rooms, and the like. Background technique [0002] Currently, a patient recovery / mortality prediction system such as the SAPS (Simplified Acute Physiology) system is typically run at the time of patient admission. Estimates of a patient's length of stay or probability of death by weighting a combination of several admission criteria including lethal signs ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00G16H10/60
CPCG16H50/30G16H50/50G16H50/70G16H50/20G16H10/60G16H10/20G16Z99/00G06F18/00G01N2800/52G06N5/01
Inventor M·赛义德
Owner KONINKLIJKE PHILIPS ELECTRONICS NV
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