CN111667900A - Clinical blood transfusion evaluation system and evaluation method - Google Patents
Clinical blood transfusion evaluation system and evaluation method Download PDFInfo
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- CN111667900A CN111667900A CN202010513818.9A CN202010513818A CN111667900A CN 111667900 A CN111667900 A CN 111667900A CN 202010513818 A CN202010513818 A CN 202010513818A CN 111667900 A CN111667900 A CN 111667900A
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- 239000008280 blood Substances 0.000 title claims abstract description 180
- 210000004369 blood Anatomy 0.000 title claims abstract description 180
- 238000011156 evaluation Methods 0.000 title abstract description 11
- 230000001915 proofreading effect Effects 0.000 claims abstract description 15
- 238000000034 method Methods 0.000 claims description 10
- 238000009534 blood test Methods 0.000 claims description 9
- 238000012360 testing method Methods 0.000 claims description 9
- 201000010099 disease Diseases 0.000 claims description 7
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims description 7
- 238000003062 neural network model Methods 0.000 claims description 6
- 238000013528 artificial neural network Methods 0.000 description 2
- 238000004159 blood analysis Methods 0.000 description 2
- 239000010836 blood and blood product Substances 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012549 training Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 229940125691 blood product Drugs 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
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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
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/10—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
- G16H20/17—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients delivered via infusion or injection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/22—Indexing; Data structures therefor; Storage structures
- G06F16/2282—Tablespace storage structures; Management thereof
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/23—Updating
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2457—Query processing with adaptation to user needs
-
- 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
- G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
- G16H40/20—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
Abstract
The invention discloses a clinical blood transfusion evaluation system, comprising: the transfusion request input module is used for inputting a transfusion request, and the transfusion request is basic information of a patient to be transfused; the transfusion recommendation table generation module is used for generating a corresponding transfusion recommendation table by adopting a transfusion recommendation model constructed based on historical transfusion data according to the input transfusion request; the blood transfusion recommendation table proofreading module is used for realizing the proofreading of the basic information of the patient carried in the blood transfusion request and the data carried in the blood transfusion recommendation table based on the proofreading module model, and is also used for manually revising the data of the blood transfusion recommendation table; the blood transfusion request sheet generation module is used for generating a corresponding blood transfusion request sheet according to the blood transfusion request table after the team finishes; and the blood bank inventory updating module is used for updating the blood bank inventory data according to the identification and entry result of the blood transfusion application form. The invention can well avoid the condition of insufficient blood transfusion quantity or excessive blood transfusion quantity, and provides guarantee for the blood transfusion safety of patients.
Description
Technical Field
The invention relates to a medical system, in particular to a clinical blood transfusion evaluation system and a clinical blood transfusion evaluation method.
Background
Blood transfusion management is always a very important part in clinical medical management, and especially under the condition that blood and blood products are increasingly scarce, the control of blood transfusion quantity and the management of blood transfusion types are not only related to the effective and reasonable application of the blood products, but also related to the life safety and guarantee of patients.
However, different hospitals and doctors have prescriptions for different blood types and different blood volumes, and due to the lack of expert system support, insufficient blood volume or excessive blood volume can easily occur.
How to construct an expert system becomes a difficult problem for blood management.
Disclosure of Invention
In order to solve the problems, the invention provides a clinical blood transfusion evaluation system and a clinical blood transfusion evaluation method, which can well avoid the situation of insufficient blood transfusion quantity or excessive blood transfusion quantity.
In order to achieve the purpose, the invention adopts the technical scheme that:
a clinical blood transfusion assessment system comprising:
the transfusion request input module is used for inputting a transfusion request, and the transfusion request is basic information of a patient to be transfused;
the transfusion recommendation table generation module is used for generating a corresponding transfusion recommendation table by adopting a transfusion recommendation model constructed based on historical transfusion data according to the input transfusion request;
the blood transfusion recommendation table proofreading module is used for realizing the proofreading of the basic information of the patient carried in the blood transfusion request and the data carried in the blood transfusion recommendation table based on the proofreading module model, and is also used for manually revising the data of the blood transfusion recommendation table;
the blood transfusion request sheet generation module is used for generating a corresponding blood transfusion request sheet according to the blood transfusion request table after the team finishes;
and the blood bank inventory updating module is used for updating the blood bank inventory data according to the identification and entry result of the blood transfusion application form.
Further, the basic information of the patient to be transfused comprises the name, sex, age, weight, height, blood type, result of the big blood test, result of the illness test and name of the operation.
Furthermore, the blood transfusion recommendation table generation module calls a corresponding blood transfusion recommendation model according to the operation name based on the nearest neighbor classifier, inputs the result of the major blood examination and the result of the disease examination into the blood transfusion recommendation model to obtain a blood transfusion recommendation table group, and outputs a final blood transfusion recommendation table according to the patient name, the sex, the age, the weight, the height and the blood type based on the nearest neighbor classifier.
Further, the blood transfusion recommendation model adopts an inclusion _ V3 deep neural network model.
Further, still include:
and the blood bank inventory early warning module is used for starting when the blood bank inventory data falls into a preset threshold, and realizing the sending of the early warning short message in a form of automatic short message editing and sending, wherein the content of the early warning short message comprises the current blood bank inventory data.
The invention also provides a clinical blood transfusion evaluation method, which comprises the following steps:
s1, inputting a blood transfusion request, and generating a corresponding blood transfusion recommendation table according to the blood transfusion request by adopting a blood transfusion recommendation model constructed based on historical blood transfusion data;
s2, manually and sequentially checking and revising the information of the blood transfusion recommendation table based on the checking model;
s3, generating a corresponding blood transfusion request sheet based on the blood transfusion recommendation table after the proofreading is finished;
and S4, updating the stock data of the blood bank based on the identification result of the transfusion application form.
Further, the step S1 specifically includes the following steps:
s11, inputting a transfusion request, and calling a corresponding transfusion recommendation model according to the operation name based on the nearest classifier;
s12, inputting the result of the big blood test and the result of the disease condition test into the blood transfusion recommendation model to obtain a blood transfusion recommendation table set;
and S13, selecting the transfusion recommendation table with the highest similarity from the transfusion recommendation table group as a final transfusion recommendation table according to the name, the sex, the age, the weight, the height and the blood type of the patient based on the nearest neighbor classifier.
Further, in step S2, the basic information of the patient loaded in the blood transfusion request and the data loaded in the blood transfusion recommendation table are firstly collated based on the collation model, and then the data in the blood transfusion recommendation table is revised manually, and during the manual revision, the query of the corresponding data can be realized through the data query column and the access server.
Further, the method also comprises the step of sending the early warning short message in a form of automatic short message editing and sending when the inventory data of the blood bank falls into a preset threshold.
Further, the blood transfusion recommendation model adopts an inclusion _ V3 deep neural network model.
The invention has the following beneficial effects:
1) a blood transfusion recommendation model is established based on historical blood transfusion data, pre-recommendation of a blood transfusion recommendation table is realized based on the blood transfusion recommendation model, and then a blood transfusion application form is revised in a manual revision mode, so that the condition of insufficient blood transfusion quantity or excessive blood transfusion quantity is well avoided.
2) The basic information of the patient carried in the blood transfusion request and the data carried in the blood transfusion recommendation table are collated based on the collation model, so that the error of the blood transfusion application table information can be well avoided, and certain guarantee is provided for the safety of blood transfusion.
3) The blood bank inventory updating module is used for completing updating of the blood bank inventory data according to the identification and entry result of the blood transfusion application form, the blood bank inventory early warning module is started when the blood bank inventory data fall into a preset threshold, sending of the early warning short message is achieved in the form of automatic short message editing and sending, accurate updating of the blood bank inventory data can be achieved, and meanwhile medical staff can be reminded to make corresponding blood bank management policies in time.
Drawings
Fig. 1 is a system block diagram of a clinical blood transfusion evaluation system according to example 1 of the present invention.
FIG. 2 is a flow chart of a method for clinical transfusion assessment in example 2 of the present invention.
Detailed Description
The present invention will be described in detail with reference to specific examples. The following examples will assist those skilled in the art in further understanding the invention, but are not intended to limit the invention in any way. It should be noted that variations and modifications can be made by persons skilled in the art without departing from the spirit of the invention. All falling within the scope of the present invention.
Example 1
As shown in fig. 1, an embodiment of the present invention provides a clinical blood transfusion assessment system, including a server, a client connected to the server via the internet, where the client implements collection and assessment of clinical blood transfusion data and sends the collected data and assessment results to the server, and the server stores data received from different account numbers in a database to form a meticulous control chain, where:
the transfusion request input module is used for inputting a transfusion request, and the transfusion request is basic information of a patient to be transfused; the basic information of the patient to be transfused comprises the name, sex, age, weight, height, blood type, large blood test result, illness state test result, operation name and the like of the patient;
the transfusion recommendation table generation module is used for generating a corresponding transfusion recommendation table by adopting a transfusion recommendation model constructed based on historical transfusion data according to the input transfusion request; specifically, the blood transfusion recommendation table generation module calls a corresponding blood transfusion recommendation model according to the operation name based on the nearest neighbor classifier, then inputs the result of the major blood examination and the result of the disease examination into the blood transfusion recommendation model to obtain a blood transfusion recommendation table group, and outputs a final blood transfusion recommendation table according to the name, the sex, the age, the weight, the height and the blood type of the patient based on the nearest neighbor classifier;
the blood transfusion recommendation table proofreading module is used for realizing the proofreading of the basic information of the patient carried in the blood transfusion request and the data carried in the blood transfusion recommendation table based on the proofreading module model, and is also used for manually revising the data of the blood transfusion recommendation table;
the blood transfusion request sheet generation module is used for generating a corresponding blood transfusion request sheet according to the blood transfusion request table after the team finishes;
the blood bank inventory updating module is used for updating the blood bank inventory data according to the identification and entry result of the blood transfusion application form;
the blood bank inventory early warning module is used for starting when the blood bank inventory data falls into a preset threshold, and realizing the sending of the early warning short message in a form of automatic short message editing and sending, wherein the content of the early warning short message comprises the current blood bank inventory data;
and the central processing module is used for coordinating the work of the modules.
In this embodiment, the blood transfusion recommendation model is an inclusion _ V3 deep neural network model, and is obtained by training an inclusion _ V3 deep neural network with historical blood transfusion data, where the historical blood transfusion data includes patient name, sex, age, weight, height, blood type, blood amount, large blood test result, disease test result, and operation name.
Example 2
As shown in fig. 2, the embodiment of the present invention provides a method for evaluating clinical blood transfusion, comprising the following steps:
s1, inputting a blood transfusion request, and generating a corresponding blood transfusion recommendation table according to the blood transfusion request by adopting a blood transfusion recommendation model constructed based on historical blood transfusion data;
s2, manually and sequentially checking and revising the information of the blood transfusion recommendation table based on the checking model;
s3, generating a corresponding blood transfusion request sheet based on the blood transfusion recommendation table after the proofreading is finished;
s4, updating the stock data of the blood bank based on the recognition result of the blood transfusion request form;
and S5, when the stock data of the blood bank falls into a preset threshold, starting the early warning module of the blood bank stock, and realizing the sending of the early warning short message in a form of automatic short message editing and sending.
In this embodiment, the step S1 specifically includes the following steps:
s11, inputting a transfusion request, and calling a corresponding transfusion recommendation model according to the operation name based on the nearest classifier;
s12, inputting the result of the big blood test and the result of the disease condition test into the blood transfusion recommendation model to obtain a blood transfusion recommendation table set;
and S13, selecting the transfusion recommendation table with the highest similarity from the transfusion recommendation table group as a final transfusion recommendation table according to the name, the sex, the age, the weight, the height and the blood type of the patient based on the nearest neighbor classifier.
In this embodiment, in step S2, the basic information of the patient loaded in the blood transfusion request and the data loaded in the blood transfusion recommendation table are firstly collated based on the collation model, then the data in the blood transfusion recommendation table is revised manually, and during the manual revision, the query of the corresponding data is realized through the data query column and the access server.
In this embodiment, the blood transfusion recommendation model is an inclusion _ V3 deep neural network model, and is obtained by training an inclusion _ V3 deep neural network with historical blood transfusion data, where the historical blood transfusion data includes patient name, sex, age, weight, height, blood type, blood amount, large blood test result, disease test result, and operation name.
The foregoing description of specific embodiments of the present invention has been presented. It is to be understood that the present invention is not limited to the specific embodiments described above, and that various changes or modifications may be made by one skilled in the art within the scope of the appended claims without departing from the spirit of the invention. The embodiments and features of the embodiments of the present application may be combined with each other arbitrarily without conflict.
Claims (10)
1. A clinical blood transfusion assessment system, characterized by: the method comprises the following steps:
the transfusion request input module is used for inputting a transfusion request, and the transfusion request is basic information of a patient to be transfused;
the transfusion recommendation table generation module is used for generating a corresponding transfusion recommendation table by adopting a transfusion recommendation model constructed based on historical transfusion data according to the input transfusion request;
the blood transfusion recommendation table proofreading module is used for realizing the proofreading of the basic information of the patient carried in the blood transfusion request and the data carried in the blood transfusion recommendation table based on the proofreading module model, and is also used for manually revising the data of the blood transfusion recommendation table;
the blood transfusion request sheet generation module is used for generating a corresponding blood transfusion request sheet according to the blood transfusion request table after the team finishes;
and the blood bank inventory updating module is used for updating the blood bank inventory data according to the identification and entry result of the blood transfusion application form.
2. A clinical transfusion assessment system according to claim 1, wherein: the basic information of the patient to be transfused comprises the name, sex, age, weight, height, blood type, large blood test result, illness state test result and operation name of the patient.
3. A clinical transfusion assessment system according to claim 1, wherein: the blood transfusion recommendation table generation module calls a corresponding blood transfusion recommendation model according to the operation name based on the nearest classifier, then inputs the result of the big blood test and the result of the illness state test into the blood transfusion recommendation model to obtain a blood transfusion recommendation table set, and outputs a final blood transfusion recommendation table according to the name, the sex, the age, the weight, the height and the blood type of the patient based on the nearest classifier.
4. A clinical transfusion assessment system according to claim 1, wherein: the blood transfusion recommendation model adopts an inclusion _ V3 deep neural network model.
5. A clinical transfusion assessment system according to claim 1, wherein: further comprising:
and the blood bank inventory early warning module is used for starting when the blood bank inventory data falls into a preset threshold, and realizing the sending of the early warning short message in a form of automatic short message editing and sending, wherein the content of the early warning short message comprises the current blood bank inventory data.
6. A method of clinical blood transfusion assessment, comprising: the method comprises the following steps:
s1, inputting a blood transfusion request, and generating a corresponding blood transfusion recommendation table according to the blood transfusion request by adopting a blood transfusion recommendation model constructed based on historical blood transfusion data;
s2, manually and sequentially checking and revising the information of the blood transfusion recommendation table based on the checking model;
s3, generating a corresponding blood transfusion request sheet based on the blood transfusion recommendation table after the proofreading is finished;
and S4, updating the stock data of the blood bank based on the identification result of the transfusion application form.
7. A method of clinical transfusion assessment according to claim 6, characterized by: the step S1 specifically includes the following steps:
s11, inputting a transfusion request, and calling a corresponding transfusion recommendation model according to the operation name based on the nearest classifier;
s12, inputting the result of the big blood test and the result of the disease condition test into the blood transfusion recommendation model to obtain a blood transfusion recommendation table set;
and S13, selecting the transfusion recommendation table with the highest similarity from the transfusion recommendation table group as a final transfusion recommendation table according to the name, the sex, the age, the weight, the height and the blood type of the patient based on the nearest neighbor classifier.
8. A method of clinical transfusion assessment according to claim 6, characterized by: in step S2, the basic information of the patient loaded in the blood transfusion request and the data loaded in the blood transfusion recommendation table are firstly collated based on the collation model, and then the data in the blood transfusion recommendation table is revised manually, and when the data is revised manually, the corresponding data can be queried by accessing the server through the data query column.
9. A method of clinical transfusion assessment according to claim 6, characterized by: and the step of sending the early warning short message in a form of automatic short message editing and sending when the inventory data of the blood bank falls into a preset threshold.
10. A method of clinical transfusion assessment according to claim 6, characterized by: the blood transfusion recommendation model adopts an inclusion _ V3 deep neural network model.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| SU1199650A1 (en) * | 1983-07-27 | 1985-12-23 | Ленинградский Завод Медицинских Полимеров | Device for manufacturing filtering unit of dropper in single-action blood transfusion system |
| RU2255655C1 (en) * | 2004-02-13 | 2005-07-10 | Попов Михаил Юрьевич | Blood sampling apparatus |
| CN104331778A (en) * | 2014-11-20 | 2015-02-04 | 重庆图珀信息技术有限公司 | Intelligent management control method for clinical blood transfusion electronic information system |
| CN108511057A (en) * | 2018-02-28 | 2018-09-07 | 北京和兴创联健康科技有限公司 | Transfusion volume model foundation and prediction technique, device, equipment and its storage medium |
-
2020
- 2020-06-08 CN CN202010513818.9A patent/CN111667900A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| SU1199650A1 (en) * | 1983-07-27 | 1985-12-23 | Ленинградский Завод Медицинских Полимеров | Device for manufacturing filtering unit of dropper in single-action blood transfusion system |
| RU2255655C1 (en) * | 2004-02-13 | 2005-07-10 | Попов Михаил Юрьевич | Blood sampling apparatus |
| CN104331778A (en) * | 2014-11-20 | 2015-02-04 | 重庆图珀信息技术有限公司 | Intelligent management control method for clinical blood transfusion electronic information system |
| CN108511057A (en) * | 2018-02-28 | 2018-09-07 | 北京和兴创联健康科技有限公司 | Transfusion volume model foundation and prediction technique, device, equipment and its storage medium |
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Application publication date: 20200915 |