Discharge readiness index

An icon and risk technology, applied in health index calculation, instrumentation, calculation, etc., can solve problems such as affecting patient readmission, irrelevant patient stability, and inability to effectively capture by predictive models.

Inactive Publication Date: 2014-03-12
KONINKLJIJKE PHILIPS NV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] Further, there appears to be a significant factor unrelated to patient stability at departure that affects patient readmission to the ICU and cannot be effectively captured in predictive models

Method used

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Experimental program
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Embodiment Construction

[0022] refer to figure 1 and figure 2 , the information technology (IT) infrastructure of the intensive care unit (ICU) includes one or more clinical data generators 12, optionally a patient information system 14, a clinical decision support system (CDSS) 16, one or more clinical data User 18 and so on. Suitably, the components of the IT infrastructure 10 are interconnected via a communication network 20 such as the Internet, a local area network, a wide area network, a wireless network or the like.

[0023] The clinical data generator 12 generates patient data for a respective patient being cared for in the ICU. Said patient data suitably includes data indicative of one or more physiological parameters, such as heart rate, temperature, blood oxygen saturation, level of consciousness, anxiety, pain, urine output, and the like. The patient data can be generated continuously and / or upon the occurrence of events, such as timer events, user input events, and the like. Further...

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Abstract

A system (16) assesses the readiness of a patient to be discharged from an intensive care unit (ICU), hospital or other monitored clinical care setting to a less intensively monitored location. The system (16) includes one or more processor (46). The processors (46) are programmed to receive patient data for patients. Risks of death from discharge for the patients are calculated using a first predictive model of risk of death. Further, risks of readmission from discharge for the patients are calculated using a second predictive model of risk of readmission. Risks of death and/or risks of readmission for one or more of the patients are presented to a clinician or clinicians in different groups of risk to supplement discharge decisions by clinicians.

Description

technical field [0001] This application relates to clinical decision making. It is particularly suitable for use in connection with clinical decision support systems and will be described with particular reference to clinical decision support systems. However, it should be understood that it is also applicable to other usage scenarios and is not necessarily limited to the aforementioned applications. Background technique [0002] Prolonged stay durations in monitored clinical settings such as intensive care units (ICUs) lead to numerous adverse clinical and economic consequences. The average cost of a day for a hospital to accommodate a patient in an ICU bed is roughly three times higher than in a general hospital bed. Assuming patients receive a constant quality of care, reducing the length of stay (LOS) increases hospital throughput by improving throughput and increasing the number of patients who can be cared for. Patients also benefit from shorter stays due to the cha...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00
CPCG06F19/345G06F19/3431G16H50/20G16H50/30
Inventor O·巴达维
Owner KONINKLJIJKE PHILIPS NV
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