CN112164463A - Hospital patient illness state high-risk early warning system, method, medium, equipment and terminal - Google Patents
Hospital patient illness state high-risk early warning system, method, medium, equipment and terminal Download PDFInfo
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- CN112164463A CN112164463A CN202011096194.1A CN202011096194A CN112164463A CN 112164463 A CN112164463 A CN 112164463A CN 202011096194 A CN202011096194 A CN 202011096194A CN 112164463 A CN112164463 A CN 112164463A
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
- G16H10/60—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
Abstract
The invention belongs to the technical field of high-risk early warning of illness states, and discloses a high-risk early warning system, a method, a medium, equipment and a terminal for hospital patients, wherein a high-risk early warning trigger identification system for illness states is introduced; based on data of serious adverse events occurring in a common ward of an adult in 1 year, the worst values of common physiological parameters (body temperature, pulse, systolic pressure, respiration, consciousness and blood oxygen saturation) of a patient 24 hours before the occurrence of the events are collected, important factors influencing the change of the disease conditions are discussed, disease condition early warning scores, disease condition severity grading and disease condition grading reaction strategies which accord with the characteristics of people in Xinjiang are established, so that an early disease condition early warning working process and a programmed monitoring scheme are obtained, a high-risk disease condition early warning information system based on Xinjiang characteristics is obtained, an electronic medical record system of a hospital is connected, and the method is applied to the common ward, so that early recognition and management of clinical medical care personnel on potential critical patients are improved, the occurrence of unexpected medical adverse events of the hospital is reduced, and the safety of the patient is guaranteed.
Description
Technical Field
The invention belongs to the technical field of high-risk early warning of illness states, and particularly relates to a high-risk early warning system, method, medium, equipment and terminal for hospital patients.
Background
The prior art is mostly used in ICU and emergency department in domestic hospitals and is not used in common ward. The severity of the patient is always evaluated according to the degree of severity of the patient, and the method is unscientific, objective and inaccurate in judgment and is easily influenced by the knowledge and subjective judgment of doctors and nurses.
In summary, the problems of the prior art are as follows: 1. patients with "potential critical illness" who cannot find common disease areas; 2. there is no objective evaluation standard for the disease condition, and doctors and nurses have medical risk due to untimely observation of the disease condition caused by different recognition degrees of the disease condition.
The prior art can not improve the early identification and management of clinical medical care personnel to potential critical patients, can not reduce the occurrence of unexpected adverse medical events in hospitals, and can ensure the safety of patients.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a hospital patient illness state high-risk early warning system, method, medium, equipment and terminal.
The invention is realized by intelligent software which is formed by combining a scoring table, a voice prompt system and a patient programmed monitoring scheme based on the combination of common physiological parameters (MEWS) of patients and index parameters of orthopedics department and a hospital nursing medical record system. The software setting is divided into a main interface and a prompt interface. The main interface is an interface for inputting patient information and MEWS combined orthopedics special index parameters, and a prompt interface is automatically popped up after the patient information and MEWS combined orthopedics special index parameters are input, so that the score value, the early warning level and the corresponding monitoring scheme are displayed. And displaying corresponding colors according to the score interface, and prompting the level attention of medical staff. The software has the advantages of being simple, convenient and easy to operate, capable of obtaining required parameters beside a patient bed, completing grading and disease condition judgment of the patient in minutes, beneficial to early and fast identifying potential critically ill patients and carrying out standardized treatment, reducing the incidence rate of serious unexpected adverse events, guaranteeing the safety of the patient and saving medical resources.
The invention also provides a high-risk early warning system for the patient condition of the hospital, which comprises:
the data entry recognition and alarm module is used for designing different alarm interfaces according to the principle of a traffic signal lamp, and orange is a secondary early warning and needs to be paid attention to; red is a first-level early warning and needs to be paid high attention or processed in time;
and the information query module is used for completing the query work of the MEWS information of the patient, and the dynamic change of the MEWS score of the patient can be seen on the electronic medical record and is displayed in the form of a trend chart.
And the information query module is also used for finishing the query work of the MEWS information, obtaining the dynamic change of the MEWS score and displaying the dynamic change in the form of a trend graph.
The invention also aims to provide a method for early warning of high risk of illness of a patient in a hospital, which comprises the following steps:
constructing an illness state high-risk early warning index based on MEWS;
constructing a disease high-risk early warning system;
and (3) application and evaluation of the disease high-risk early warning system.
Further, the construction of the high-risk early warning index of the disease condition comprises the following steps:
collecting the worst value of the physiological parameters, calculating the scores of the NEWS and the MEWS, and analyzing the important factors of the disease change by adopting a regression analysis method; screening influence factors with high ROC value as early warning indexes of the disease condition on the basis of the MEWS score; determining parameter ranges of the indexes by adopting a decision tree analysis method and through classregree function of an MATLAB mathematical platform, forming revised MEWS by using a '0, 1, 2 and 3' weighting and classifying system, and comparing the resolution, sensitivity and specificity of the revised NEWS and MEWS by using a ROC curve method.
Further, the construction of the disease high-risk early warning system comprises the following steps:
obtaining different degrees of disease change interception points by adopting an ROC curve method, and constructing disease severity grading by combining a literature method and expert opinions; constructing an illness state grading reaction strategy by adopting Delphi method inquiry; the content of the inquiry includes: the method comprises the steps of grading early warning and warning color, reaction speed, quality of a responder, observation frequency, nursing level and care strategy.
It is a further object of the invention to provide a computer device comprising a memory and a processor, the memory storing a computer program which, when executed by the processor, causes the processor to perform the steps of:
constructing an illness state high-risk early warning index based on MEWS;
constructing a disease high-risk early warning system;
and (3) application and evaluation of the disease high-risk early warning system.
It is another object of the present invention to provide a computer-readable storage medium storing a computer program which, when executed by a processor, causes the processor to perform the steps of:
constructing an illness state high-risk early warning index based on MEWS;
constructing a disease high-risk early warning system;
and (3) application and evaluation of the disease high-risk early warning system.
The invention also aims to provide an information data processing terminal, which is used for realizing the early warning method for the high risk of the illness state of the hospital patient.
The invention also aims to provide the high-risk early warning terminal for the patient condition, which is used for realizing the high-risk early warning method for the patient condition of the hospital.
The invention has the advantages and positive effects that: by using scientific and objective disease condition evaluation standards, a unified assessment early warning system is established in a common ward of a hospital, so that the early identification and management of clinical medical care personnel in the common ward on a patient with a potential critical disease are improved, the occurrence of unexpected medical adverse events of the hospital is further reduced, the clinical curative effect of the patient is improved, and the family and social burdens are relieved.
Introducing a technology of a high-risk early warning trigger identification system of the state of an illness; based on data of serious adverse events (unplanned ICU transition, unexpected death and unplanned reoperation) in a common disease area of an adult in the past 1 year of Xinjiang medical university, collecting the worst value of common physiological parameters (body temperature, pulse, systolic pressure, respiration, consciousness and blood oxygen saturation) of a patient 24 hours before the occurrence of the event, discussing important factors influencing the change of the disease condition, establishing an early warning score, a disease severity grading (light, medium and heavy) and a disease grading reaction strategy according with the characteristics of people in the Xinjiang area so as to obtain an early warning work flow and a programmed monitoring scheme of the disease condition, obtain a high-risk early warning information system based on Xinjiang characteristics, connect an electronic medical record system of the hospital, and apply the system to the common disease area, improve the early recognition and management of clinical medical care personnel on potentially critical patients, and reduce the occurrence of the unexpected medical adverse events in the hospital, the safety of the patient is guaranteed.
Drawings
FIG. 1 is a schematic structural diagram of a hospital patient critical early warning system according to an embodiment of the present invention;
in the figure: 1. a data entry identification and alarm module; 2. and an information inquiry module.
Fig. 2 is a flowchart of a hospital patient high-risk condition early warning method according to an embodiment of the present invention.
Fig. 3 is a flow chart of an implementation of the early warning method for high risk of hospital patient illness according to the embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The invention integrates subject theories of management, nursing science, informatics, statistics and the like in the construction of the high-risk early warning system for the patients in the hospital, and has theoretical innovation. The generated high-risk early warning system for the hospital patients is scientifically verified in reasonability and feasibility, and has high popularization and application values.
The following detailed description of the principles of the invention is provided in connection with the accompanying drawings.
As shown in fig. 1, the early warning system for high risk of illness of a patient in a hospital provided by the embodiment of the invention comprises:
the data entry recognition and alarm module 1 is used for designing different alarm interfaces according to the principle of a traffic signal lamp, and orange is a secondary early warning and needs to be paid attention to; red is a first-level early warning and needs to be paid high attention or processed in time;
and the information query module 2 is used for completing the query work of the MEWS information of the patient, and the dynamic change of the MEWS score of the patient can be seen on the electronic medical record and is displayed in the form of a trend chart.
As shown in fig. 2, the early warning system for high risk of illness of a patient in a hospital provided by the embodiment of the invention comprises the following steps:
constructing an illness state high-risk early warning index based on MEWS;
constructing a disease high-risk early warning system;
and (3) application and evaluation of the disease high-risk early warning system.
The high-risk early warning system for the patient's condition of the hospital provided by the embodiment of the invention completes serious grading of the condition of the patient, constructs a grading reaction strategy, completes the early warning system for the condition of the patient and is embedded into a medical record information system of the hospital for use; data were obtained for not less than 300 patients on unscheduled transfers to ICU rates, unexpected mortality, unexpected reoperation rates, final patient returns and average hospital days, average hospital costs, etc.
In the embodiment of the invention, the high-risk early warning system for the patient in the hospital aims at early finding potential critical patients in a common ward, and enabling nurses to call doctors and take corresponding intervention measures as soon as possible. At present, the used disease condition early warning scores are revised early warning scores (MEWS) which are introduced abroad, the collection of relevant data in Xinjiang area is further perfected, the collected data are verified, and a disease condition early warning score and patient disease condition high-risk early warning system suitable for the Xinjiang area is established.
The invention mainly comprises 3 parts: (1) constructing an early warning index of high risk of illness in Xinjiang area based on MEWS; (2) constructing a high-risk early warning system for the patient condition of the hospital; (3) and (3) application and evaluation of the disease high-risk early warning system.
1.1 construction of high-risk early warning index of illness state in Xinjiang area
The method is based on data of serious adverse events (unplanned ICU transfer, unexpected death and unplanned reoperation) in the common disease area of adults in the past 1 year of Xinjiang medical university, collects the worst value of common physiological parameters (body temperature, pulse, systolic pressure, respiration, mind and blood oxygen saturation) of a patient 24 hours before the event occurs, calculates the scores of NEWS and MEWS, and adopts a regression analysis method to discuss important factors influencing the change of the patient's condition; screening influence factors with high ROC value as early warning indexes of the hospital illness state on the basis of MEWS scores through discussion of experts (including ICU doctors, nursing experts and statistical experts); a decision tree analysis method is adopted, the parameter range of each index meeting the characteristics of Xinjiang people is determined through the classregree function of the MATLAB mathematical platform, and the revised MEWS is formed by using the '0, 1, 2 and 3' weight assigning system, namely the early-stage disease warning score suitable for the characteristics of hospitals. And comparing the resolution, sensitivity and specificity of the revised NEWS and MEWS by using an ROC curve method to evaluate the application value of the revised NEWS and MEWS.
1.2 construction of high-risk early warning system for patient illness state in hospital
The content of the invention is based on application evaluation data, different degrees of disease change interception points are obtained by adopting an ROC curve method, and the disease severity grades (light, medium and heavy) are constructed by adopting a literature method and combining expert opinions; based on the classification of the severity of the illness, the nursing department and the medical department organize the disease, and invite the experts (including ICU doctors and nursing experts) in Hunan ya Hospital of the southern China university to adopt the Delphi method to inquire and construct an illness classification reaction strategy. The content of the inquiry includes: the method comprises the steps of grading early warning and warning color, reaction speed, quality of a responder, observation frequency, nursing level and care strategy. And based on the established tracking triggering early warning system, an electronic medical record system of the sixth subsidiary hospital of Xinjiang medical university is docked by adopting an information technology. The data acquisition and synchronization are realized by adopting manual input and/or the butt joint of data interfaces in the mobile medical care equipment in the common ward and the electronic medical record system; an Oracle10g database product and a disaster recovery backup technology are adopted to establish an illness state early warning database to realize data storage and ensure data safety; and the front-end web application of the database system is realized by adopting technologies such as java and jsp through a B/S architecture. And tracking and triggering an early warning process of an early warning system. (see FIG. 3)
1.3 application and evaluation of high-risk early warning system for disease conditions
According to the application of the high-risk disease early warning system, pre-intervention and post-intervention contrast studies are adopted to compare the pre-intervention (2016, 6 and 5 months 2017) and post-intervention (2018, 6 and 5 months 2019) indexes such as ICU ratio, unexpected mortality, unplanned reoperation rate, average interval time from change of disease conditions to change of ICU, final return of patients, average hospitalization day, average hospitalization cost and nursing workload such as frequent disease observation, so that the application effect evaluation is carried out.
It should be noted that the embodiments of the present invention can be realized by hardware, software, or a combination of software and hardware. The hardware portion may be implemented using dedicated logic; the software portions may be stored in a memory and executed by a suitable instruction execution system, such as a microprocessor or specially designed hardware. Those skilled in the art will appreciate that the apparatus and methods described above may be implemented using computer executable instructions and/or embodied in processor control code, such code being provided on a carrier medium such as a disk, CD-or DVD-ROM, programmable memory such as read only memory (firmware), or a data carrier such as an optical or electronic signal carrier, for example. The apparatus and its modules of the present invention may be implemented by hardware circuits such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., or by software executed by various types of processors, or by a combination of hardware circuits and software, e.g., firmware.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (9)
1. The utility model provides a patient's state of an illness high-risk early warning system of hospital, its characterized in that, patient's state of an illness high-risk early warning system of hospital includes:
the data entry recognition and alarm module is used for designing different alarm interfaces according to the principle of a traffic signal lamp, and orange is a secondary early warning and needs to be paid attention to; red is a first-level early warning and needs to be paid high attention or processed in time;
and the information query module is used for completing the query work of the MEWS information of the patient, and the dynamic change of the MEWS score of the patient can be seen on the electronic medical record and is displayed in the form of a trend chart.
2. The hospital patient high-risk condition early warning system of claim 1, wherein the information query module is further configured to complete query of the MEWS information, obtain dynamic changes of the MEWS score, and display the dynamic changes in the form of a trend graph.
3. The method for early warning of high risk of illness of hospital patient according to the system for early warning of high risk of illness of hospital patient of claim 1, wherein the method for early warning of high risk of illness of hospital patient comprises:
constructing an illness state high-risk early warning index based on MEWS;
constructing a disease high-risk early warning system;
and (3) application and evaluation of the disease high-risk early warning system.
4. The method for early warning of high risk of medical condition of hospital patient according to claim 4, wherein the construction of the early warning index of high risk of medical condition comprises:
collecting the worst value of the physiological parameters, calculating the scores of the NEWS and the MEWS, and analyzing the important factors of the disease change by adopting a regression analysis method; screening influence factors with high ROC value as early warning indexes of the disease condition on the basis of the MEWS score; determining parameter ranges of the indexes by adopting a decision tree analysis method and through classregree function of an MATLAB mathematical platform, forming revised MEWS by using a '0, 1, 2 and 3' weighting and classifying system, and comparing the resolution, sensitivity and specificity of the revised NEWS and MEWS by using a ROC curve method.
5. The method for early warning of high risk of medical condition of hospital patient according to claim 4, wherein the construction of the early warning system of high risk of medical condition comprises:
obtaining different degrees of disease change interception points by adopting an ROC curve method, and constructing disease severity grading by combining a literature method and expert opinions; constructing an illness state grading reaction strategy by adopting Delphi method inquiry; the content of the inquiry includes: the method comprises the steps of grading early warning and warning color, reaction speed, quality of a responder, observation frequency, nursing level and care strategy.
6. A computer device, characterized in that the computer device comprises a memory and a processor, the memory storing a computer program which, when executed by the processor, causes the processor to carry out the steps of:
constructing an illness state high-risk early warning index based on MEWS;
constructing a disease high-risk early warning system;
and (3) application and evaluation of the disease high-risk early warning system.
7. A computer-readable storage medium storing a computer program which, when executed by a processor, causes the processor to perform the steps of:
constructing an illness state high-risk early warning index based on MEWS;
constructing a disease high-risk early warning system;
and (3) application and evaluation of the disease high-risk early warning system.
8. An information data processing terminal, characterized in that, the information data processing terminal is used for realizing the early warning method for high risk of illness of hospital patients according to any one of claims 4-6.
9. An illness state high-risk early warning terminal, which is used for realizing the hospital patient illness state high-risk early warning method according to any one of claims 4-6.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114358212A (en) * | 2022-01-25 | 2022-04-15 | 电子科技大学 | Cancer prearrangement index data analysis system based on K-means |
| CN117612725A (en) * | 2024-01-23 | 2024-02-27 | 南通大学附属医院 | Respirator alarm management method and system for intensive care unit |
-
2020
- 2020-10-14 CN CN202011096194.1A patent/CN112164463A/en active Pending
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114358212A (en) * | 2022-01-25 | 2022-04-15 | 电子科技大学 | Cancer prearrangement index data analysis system based on K-means |
| CN114358212B (en) * | 2022-01-25 | 2024-01-30 | 电子科技大学 | Cancer prescriptions index data analysis system based on K-means |
| CN117612725A (en) * | 2024-01-23 | 2024-02-27 | 南通大学附属医院 | Respirator alarm management method and system for intensive care unit |
| CN117612725B (en) * | 2024-01-23 | 2024-03-29 | 南通大学附属医院 | Respirator alarm management method and system for intensive care unit |
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