CN111341440B - Method for intelligent diagnosis and treatment and intelligent diagnosis and treatment system - Google Patents
Method for intelligent diagnosis and treatment and intelligent diagnosis and treatment system Download PDFInfo
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- CN111341440B CN111341440B CN202010128795.XA CN202010128795A CN111341440B CN 111341440 B CN111341440 B CN 111341440B CN 202010128795 A CN202010128795 A CN 202010128795A CN 111341440 B CN111341440 B CN 111341440B
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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
- G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Abstract
The invention discloses a method for intelligent diagnosis and treatment, which comprises the following steps: responding to the input instruction, and acquiring diagnosis and treatment parameters and personal information corresponding to the input instruction; generating diagnosis and treatment information according to the diagnosis and treatment parameters and the personal information; and responding to the diagnosis instruction and/or the nursing instruction, and acquiring matched first diagnosis and treatment content and/or second diagnosis and treatment content output from the diagnosis and treatment information. The invention also discloses an intelligent diagnosis and treatment system, and the method and the system disclosed by the invention can obviously improve the disease diagnosis efficiency and medical care quality of doctors, optimize the medical care flow and improve the nursing work efficiency.
Description
Technical Field
The invention belongs to the technical field of medical information, and particularly relates to a method for intelligent diagnosis and treatment and an intelligent diagnosis and treatment system.
Background
With the increasing number of patients, doctors mostly need to face a plurality of patients, which can prolong the outpatient time of the doctors, but the consultation time of each patient is too short, misdiagnosis is easy to occur or the doctors need to repeatedly check for a plurality of times, and the waste of medical resources and treatment time is caused. Moreover, for nursing staff, the situation facing a plurality of patients can exist, so that nursing steps are disordered, the patients cannot be timely and correctly nursed, and recovery of the illness state of the patients is not facilitated.
Disclosure of Invention
The invention aims to solve the technical problems of providing a method for intelligent diagnosis and treatment and an intelligent diagnosis and treatment system, which can obviously improve the efficiency of diagnosing symptoms and the medical care quality of doctors, optimize the medical care flow and improve the nursing work efficiency.
To solve the above technical problem, a first aspect of the present invention discloses a method for intelligent diagnosis and treatment, the method comprising: responding to the input instruction, and acquiring diagnosis and treatment parameters and personal information corresponding to the input instruction; generating diagnosis and treatment information according to the diagnosis and treatment parameters and the personal information; and responding to the diagnosis instruction and/or the nursing instruction, and acquiring matched first diagnosis and treatment content and/or second diagnosis and treatment content output from the diagnosis and treatment information.
In some embodiments, generating the diagnostic information from the diagnostic parameters and the personal information includes: acquiring historical clinical information and/or current clinical information associated with the personal information; carrying out correlation screening on diagnosis and treatment parameters in historical clinical information and/or current clinical information to generate clinical information; and generating diagnosis and treatment information according to the diagnosis rules and the clinical information.
In some embodiments, the diagnostic rules include: distributing a plurality of disease categories with mapping relations for each branch system; assigning clinical information with a mapping relation to each disease name of the disease category; and distributing diagnosis and treatment information with a mapping relation to the clinical information.
In some embodiments, the method further comprises outputting a plurality of relevant clinical information according to the diagnostic rules and the historical clinical information; and acquiring the determined clinical information to generate diagnosis and treatment information.
In an embodiment, the method further comprises: outputting a plurality of related condition categories according to the diagnostic rules and the current clinical information; screening a plurality of related disorder categories according to the historical clinical information, generating a determined disorder category, and acquiring corresponding diagnosis and treatment information according to the determined disorder category and the diagnosis rules.
In some embodiments, the first medical context is a combination of one or more of a condition name, a treatment principle, a treatment method corresponding to the diagnostic instructions; the second diagnosis and treatment content is one or a combination of a plurality of symptoms names, nursing measures and nursing notes corresponding to nursing instructions.
The second aspect of the invention discloses a system for intelligent diagnosis and treatment, which comprises: the information acquisition module is used for responding to the input instruction, acquiring diagnosis and treatment parameters and personal information corresponding to the input instruction, and the processing module is used for generating diagnosis and treatment information according to the diagnosis and treatment parameters and the personal information; the display module is used for responding to the diagnosis instruction and/or the nursing instruction and acquiring matched first diagnosis and treatment content and/or second diagnosis and treatment content output from the diagnosis and treatment information.
In some embodiments, the processing module comprises: an acquisition unit configured to acquire historical clinical information and/or current clinical information associated with the personal information; the screening unit is used for screening the correlation degree of the diagnosis and treatment parameters in the historical clinical information and/or the current clinical information to generate clinical information; and the generating unit is used for generating diagnosis and treatment information according to the diagnosis rules and the clinical information. .
The third aspect of the invention discloses a device for intelligent diagnosis and treatment, which comprises:
a memory storing executable program code;
a processor coupled to the memory;
the processor invokes the executable program code stored in the memory to perform the method for intelligent diagnosis and treatment according to any one of the first aspect of the present invention.
A fourth aspect of the invention discloses a computer storage medium storing computer instructions which, when invoked, are adapted to carry out the method for intelligent diagnosis and treatment according to any of the first aspects of the invention.
Compared with the prior art, the invention has the beneficial effects that:
by implementing the invention, clinical guidance can be provided for medical care, and the clinical actual condition of a patient can be combined through only a single diagnosis and treatment parameter, and the useful diagnosis and treatment information can be intelligently screened for clinical diagnosis and bidirectional selection of clinical care, so that the disease diagnosis efficiency and medical care quality of doctors can be remarkably improved, the medical care flow is optimized, and the nursing work efficiency is improved.
Drawings
Fig. 1 is a schematic flow chart of a method for intelligent diagnosis and treatment according to an embodiment of the present invention;
FIG. 2 is a flow chart of another method for intelligent diagnosis and treatment according to an embodiment of the present invention;
FIG. 3 is a flow chart of another method for intelligent diagnosis and treatment according to an embodiment of the present invention;
fig. 4 is a schematic diagram of an intelligent diagnosis and treatment system according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of an intelligent diagnosis and treatment device according to an embodiment of the present invention.
Detailed Description
For a better understanding and implementation, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is apparent that the described embodiments are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or modules is not necessarily limited to those steps or modules that are expressly listed or inherent to such process, method, article, or apparatus.
The embodiment of the invention discloses a method for intelligent diagnosis and treatment and an intelligent diagnosis and treatment system, which can obviously improve the efficiency of diagnosing symptoms and the medical care quality of doctors, optimize the medical care flow and improve the nursing work efficiency.
Example 1
Referring to fig. 1, fig. 1 is a schematic flow chart of a method for intelligent diagnosis and treatment according to an embodiment of the present invention. The method described in fig. 1 may be applied to a medical networking system, and optionally, the medical networking system may be a local area network system used by a hospital or a custom system used by a family doctor, which is not limited in the embodiment of the present invention. As shown in fig. 1, the method for intelligent diagnosis and treatment may include the steps of:
101. and responding to the input instruction, and acquiring diagnosis and treatment parameters and personal information corresponding to the input instruction.
The diagnosis parameters include index parameters such as blood pressure detection value, blood glucose detection value, and hemoglobin detection value, and the number of diagnosis parameters is not limited to the number of diagnosis parameters, and the following steps can be performed by inputting a single diagnosis parameter. Personal information includes patient name, sex, age, hospital number, etc.
Optionally, as a preferred implementation manner, the personal information acquisition mode can be manually input in a mode of inputting instructions, and can also be directly input by a synchronous hospital system, and the imported personal information, namely the patient admitted in the past, can be directly extracted.
102. And generating diagnosis and treatment information according to the diagnosis and treatment parameters and the personal information.
First, historical clinical information and/or current clinical information associated with personal information is obtained. For the historical clinical information which is already registered in the medical system and is related to the personal information, the historical clinical information can be directly obtained through the medical system in a networking way, namely, the personal information is input into the medical system, and the past clinical information of a patient can be obtained. For patients initially registered in the medical system, the doctor will ask them to manually record the current clinical information of the patient. For patients with new symptoms, the historical clinical information and the current clinical information related to the personal information can be acquired at the same time, so that the obtained diagnosis and treatment information is more accurate.
Further, correlation screening is performed on the acquired historical clinical information and the current clinical information on the diagnosis and treatment parameters to generate clinical information, wherein the correlation screening refers to screening the acquired diagnosis and treatment parameters, such as blood pressure values and blood glucose values, and information related to the diagnosis and treatment parameters contained in the historical clinical information and the current clinical information, for example, the diagnosis and treatment parameters contained in an input instruction are 33.0mmol/L of blood glucose values, and the fluctuation range of the blood glucose values or symptoms related to the floating of the blood glucose values of the patient are screened out from the historical clinical information and the current clinical information and extracted as clinical information.
Further, diagnosis and treatment information is automatically generated according to the diagnosis rules and the clinical information. Wherein the diagnostic rules include: distributing a plurality of disease categories with mapping relations for each branch system; assigning clinical information with a mapping relation to each disease name of the disease category; and distributing diagnosis and treatment information with a mapping relation to the clinical information. The diagnostic rules may be implemented as a knowledge base for medical personnel to learn.
The diagnostic rules can be found in the following embodiments:
different branch systems are taken as main units and extend downwards in a tree diagram. The branching system includes: one or more combinations of respiratory system, digestive system, circulatory system, endocrine system, etc.
Taking the circulatory system as an example, the following conditions include, for example, hypertension, coronary heart disease, acute cerebrovascular disease, heart failure, arrhythmia, rheumatic heart disease, or a combination of one or more of them. For different clinical information manifestations of different disease categories, for example heart failure, clinical information includes fatigue, significantly reduced exercise endurance, exertional dyspnea, nocturnal paroxysmal dyspnea, sitting up breathing, wheezing, dysphoria, frequent coughing and profuse pink foamy sputum, etc. In order to overcome the problem that in the prior art, only a single intelligent medical system for doctor face diagnosis is provided, and no professional guidance is provided for nursing staff, different diagnosis and treatment information is distributed for different clinical information, and the diagnosis and treatment information consists of two parts, including a first diagnosis and treatment content and a second diagnosis and treatment content.
Optionally, the first medical content includes one or more of a disease name, a treatment principle, a treatment method; the second medical treatment includes one or more of a name of the condition, a care measure, and a care notice.
Illustratively, the first diagnosis and treatment content included for diagnosis and treatment information diagnosed as a condition diabetic ketoacidosis according to the above-described clinical information and diagnosis rules is:
name of the condition: disease diabetic ketoacidosis
The treatment principle is as follows: correcting water and electrolyte imbalance, correcting acidosis, supplementing insulin to promote glucose utilization, and finding and removing stress factors inducing ketoacidosis.
The treatment method comprises the following steps: fluid infusion is in principle rapid and slow. When the blood sugar is more than 16.7 mmol/L, adding insulin by using normal saline, and performing intravenous drip at the speed of 500-1000 ml/h; when the blood sugar is 13.9 mmol/L, the blood sugar is monitored regularly, and the intravenous drip of glucose liquid and insulin can be changed, so that the speed is reduced. When the blood pH is 7.0 or the blood is accompanied by high blood potassium, an alkaline drug, preferably sodium bicarbonate solution, should be administered. The dosage is not too much, the speed is not too fast, and insulin can not be put into alkaline solution, so as to avoid the invalidation of the medicine.
Other: symptomatic treatment and elimination of causes.
The second diagnosis and treatment content is as follows:
name of the condition: disease diabetic ketoacidosis
Nursing measures:
1. absolute bed rest should be immediately matched with rescue treatment.
2. And a venous access is quickly established, water, electrolyte and acid-base imbalance are corrected, and ketosis symptoms are corrected.
3. Regular insulin is administered following the order. The small dose of insulin should be administered with correct aspiration to reduce the occurrence of hypoglycemia, hypokalemia, and cerebral edema.
4. The method is used for assisting in treating induced diseases and complications, closely observing vital signs, mind and pupils (see the conventional coma nursing), and assisting in measuring and recording blood sugar.
5. Diet care fasting, and change diabetic semifluid or diabetic diet after symptom relief
6. Preventing infection, caring oral cavity and skin, keeping skin clean, preventing bedsore and secondary infection, and keeping private parts clean for female patient
7. The nursing of neuropathy, controlling diabetes, applying a great deal of vitamin B local massage and physiotherapy, and preventing injury for the person with vanishing skin feeling.
As a preferred embodiment, after diagnosis and treatment information is automatically generated according to diagnosis rules and clinical information, other diagnosis information is also generated by screening according to personal information. For example, if the patient has too high blood sugar, the diagnosis information obtained by singly inputting the blood sugar value of the diagnosis parameters comprises diagnosis of diabetes (several types of diabetes), abnormal glucose tolerance, hyperthyroidism and the like, but if the patient is female and pregnant, the diagnosis information is further screened according to the diagnosis rules to determine that the diagnosis information is gestational diabetes. If the patient is male, the diagnosis of gestational diabetes is excluded, but is considered as other diagnostic information. Therefore, the determined diagnosis and treatment information can be more accurate, and learning of a training doctor and the like is facilitated.
103. And responding to the diagnosis instruction and/or the nursing instruction, and acquiring matched first diagnosis and treatment content and/or second diagnosis and treatment content output from the diagnosis and treatment information.
After the diagnosis and treatment information is acquired, two interactive key options of 'medical' and 'nursing' are set after the diagnosis and treatment information is acquired, and a doctor or a nursing staff can select through clicking a display screen or voice interaction. When the "medical" option is selected, a diagnosis instruction is formed, and when the diagnosis instruction is received, a first diagnosis and treatment content including a disease name, a treatment principle, a treatment method and the like can be acquired.
Optionally, when the "care" option is selected, a care instruction is formed, and when the care instruction is received, a second diagnosis and treatment content including a disease name, a care measure and a care notice can be acquired.
Alternatively, when the "medical" and "care" options are simultaneously selected, a first diagnosis and treatment content including a name of a disorder, a treatment principle, a treatment method, and the like, and a second diagnosis and treatment content including a name of a disorder, a care measure, and care notice are acquired.
According to the method for intelligent diagnosis and treatment provided by the embodiment, clinical guidance can be provided for medical care and professional guidance can also be provided for nursing staff. The intelligent diagnosis and treatment system can be combined with the clinical actual condition of a patient only by single diagnosis and treatment parameters, and can intelligently screen out useful diagnosis and treatment information for clinical diagnosis and bidirectional selection of clinical care, so that the disease diagnosis efficiency and medical care quality of doctors can be remarkably improved, the medical care flow is optimized, and the nursing work efficiency is improved.
Example two
Referring to fig. 2, fig. 2 is a flow chart of a method for intelligent diagnosis and treatment according to an embodiment of the present invention. The method described in fig. 2 may be applied to a medical networking system, and optionally, the medical networking system may be a local area network system used by a hospital or a custom system used by a family doctor, which is not limited in the embodiment of the present invention. As shown in fig. 2, the method for intelligent diagnosis and treatment may include the steps of:
201. and responding to the input instruction, and acquiring personal information corresponding to the input instruction.
Wherein the personal information includes patient name, sex, age, hospitalization number, etc.
Optionally, as a preferred implementation manner, the personal information acquisition mode can be manually input in a mode of inputting instructions, and can also be directly input by a synchronous hospital system, and the imported personal information, namely the patient admitted in the past, can be directly extracted.
202. A plurality of relevant clinical information is output based on the diagnostic rules and the historical clinical information. In this embodiment, the default patient is already registered in the medical system, and the historical clinical information associated with the personal information may be directly obtained by networking through the medical system, i.e., the personal information is input into the medical system, so that the past clinical information of the patient, i.e., the historical clinical information, is obtained.
Wherein the diagnostic rules include: distributing a plurality of disease categories with mapping relations for each branch system; assigning clinical information with a mapping relation to each disease name of the disease category; and distributing diagnosis and treatment information with a mapping relation to the clinical information. The diagnostic rules may be implemented as a knowledge base for medical personnel to learn.
The diagnostic rules can be found in the following embodiments:
different branch systems are taken as main units and extend downwards in a tree diagram. The branching system includes: one or more combinations of respiratory system, digestive system, circulatory system, endocrine system, etc.
Taking the circulatory system as an example, the following conditions include, for example, hypertension, coronary heart disease, acute cerebrovascular disease, heart failure, arrhythmia, rheumatic heart disease, or a combination of one or more of them. For different clinical information manifestations of different disease categories, for example heart failure, clinical information includes fatigue, significantly reduced exercise endurance, exertional dyspnea, nocturnal paroxysmal dyspnea, sitting up breathing, wheezing, dysphoria, frequent coughing and profuse pink foamy sputum, etc. In order to overcome the problem that in the prior art, only a single intelligent medical system for doctor face diagnosis is provided, and no professional guidance is provided for nursing staff, different diagnosis and treatment information is distributed for different clinical information, and the diagnosis and treatment information consists of two parts, including a first diagnosis and treatment content and a second diagnosis and treatment content.
Relevant clinical manifestations can be correspondingly acquired according to the historical clinical information of the patient, and multiple clinical manifestations are provided for users to select in a popup window mode.
203. And acquiring the determined clinical information to generate diagnosis and treatment information.
When the user selects the determined clinical information in a plurality of clinical manifestations, more accurate diagnosis and treatment information is generated according to the determined clinical information and the diagnosis rules.
For example, when the disease name obtained according to the historical clinical information and the diagnostic rule is diabetes, clinical information such as polydipsia, polyphagia, polyuria, weight loss, dry mouth, bitter taste, blood sugar fluctuation range and the like is automatically popped up for the user to select, and the user (doctor and nursing staff) selects polydipsia, polyphagia and polyuria according to the description of the patient or the observation of the patient, so that three clinical manifestations are checked, and diagnosis and treatment information which is more in line with the current disease state of the patient is directly obtained.
204. And responding to the diagnosis instruction and/or the nursing instruction, and acquiring matched first diagnosis and treatment content and/or second diagnosis and treatment content output from the diagnosis and treatment information. After the diagnosis and treatment information is acquired, two interactive key options of 'medical' and 'nursing' are set after the diagnosis and treatment information is acquired, and a doctor or a nursing staff can select through clicking a display screen or voice interaction. When the "medical" option is selected, a diagnosis instruction is formed, and when the diagnosis instruction is received, a first diagnosis and treatment content including a disease name, a treatment principle, a treatment method and the like can be acquired.
Optionally, when the "care" option is selected, a care instruction is formed, and when the care instruction is received, a second diagnosis and treatment content including a disease name, a care measure and a care notice can be acquired.
Alternatively, when the "medical" and "care" options are simultaneously selected, a first diagnosis and treatment content including a name of a disorder, a treatment principle, a treatment method, and the like, and a second diagnosis and treatment content including a name of a disorder, a care measure, and care notice are acquired.
According to the method for intelligent diagnosis and treatment provided by the embodiment, clinical guidance can be provided for medical care and professional guidance can also be provided for nursing staff. The intelligent diagnosis and treatment system can be combined with the clinical actual condition of a patient only by single diagnosis and treatment parameters, and can intelligently screen out useful diagnosis and treatment information for clinical diagnosis and bidirectional selection of clinical care, so that the disease diagnosis efficiency and medical care quality of doctors can be remarkably improved, the medical care flow is optimized, and the nursing work efficiency is improved.
Example III
Referring to fig. 3, fig. 3 is a flow chart of a method for intelligent diagnosis and treatment according to an embodiment of the present invention. The method described in fig. 3 may be applied to a medical networking system, or alternatively, the medical networking system may be a local area network system used by a hospital, or may be a custom system used by a family doctor, which is not limited in the embodiment of the present invention. As shown in fig. 3, the method for intelligent diagnosis and treatment may include the steps of:
301. and responding to the input instruction, and acquiring personal information corresponding to the input instruction.
Wherein the personal information includes patient name, sex, age, hospitalization number, etc.
Optionally, as a preferred implementation manner, the personal information acquisition mode can be manually input in a mode of inputting instructions, and can also be directly input by a synchronous hospital system, and the imported personal information, namely the patient admitted in the past, can be directly extracted.
302. A plurality of related condition categories are output based on the diagnostic rules and current clinical information.
Wherein the diagnostic rules include: distributing a plurality of disease categories with mapping relations for each branch system; assigning clinical information with a mapping relation to each disease name of the disease category; and distributing diagnosis and treatment information with a mapping relation to the clinical information. The diagnostic rules may be implemented as a knowledge base for medical personnel to learn.
The diagnostic rules can be found in the following embodiments:
different branch systems are taken as main units and extend downwards in a tree diagram. The branching system includes: one or more combinations of respiratory system, digestive system, circulatory system, endocrine system, etc.
Taking the circulatory system as an example, the following conditions include, for example, hypertension, coronary heart disease, acute cerebrovascular disease, heart failure, arrhythmia, rheumatic heart disease, or a combination of one or more of them. For different clinical information manifestations of different disease categories, for example heart failure, clinical information includes fatigue, significantly reduced exercise endurance, exertional dyspnea, nocturnal paroxysmal dyspnea, sitting up breathing, wheezing, dysphoria, frequent coughing and profuse pink foamy sputum, etc. In order to overcome the problem that in the prior art, only a single intelligent medical system for doctor face diagnosis is provided, and no professional guidance is provided for nursing staff, different diagnosis and treatment information is distributed for different clinical information, and the diagnosis and treatment information consists of two parts, including a first diagnosis and treatment content and a second diagnosis and treatment content.
For the patients initially registered in the medical system, the doctor inquires the patients, and the current clinical information of the patients such as polydipsia, polyphagia, emaciation and the like is manually recorded, so that the patients can be prompted to be primarily diagnosed into a plurality of related diseases such as diabetes, hyperthyroidism and the like according to the diagnosis rules.
303. Screening the plurality of related disorder categories according to the historical clinical information to generate a determined disorder category output. The historical clinical information may invoke patient records in the medical system, and when combined with more detailed recent historical clinical information, may narrow down the diagnostic scope, generating a final category of disorders.
304. And acquiring corresponding diagnosis and treatment information according to the determined disease category and the diagnosis rules.
305. And responding to the diagnosis instruction and/or the nursing instruction, and acquiring matched first diagnosis and treatment content and/or second diagnosis and treatment content output from the diagnosis and treatment information. After the diagnosis and treatment information is acquired, two interactive key options of 'medical' and 'nursing' are set after the diagnosis and treatment information is acquired, and a doctor or a nursing staff can select through clicking a display screen or voice interaction. When the "medical" option is selected, a diagnosis instruction is formed, and when the diagnosis instruction is received, a first diagnosis and treatment content including a disease name, a treatment principle, a treatment method and the like can be acquired.
Optionally, when the "care" option is selected, a care instruction is formed, and when the care instruction is received, a second diagnosis and treatment content including a disease name, a care measure and a care notice can be acquired.
Alternatively, when the "medical" and "care" options are simultaneously selected, a first diagnosis and treatment content including a name of a disorder, a treatment principle, a treatment method, and the like, and a second diagnosis and treatment content including a name of a disorder, a care measure, and care notice are acquired.
According to the method for intelligent diagnosis and treatment provided by the embodiment, clinical guidance can be provided for medical care and professional guidance can also be provided for nursing staff. The intelligent diagnosis and treatment system can be combined with the clinical actual condition of a patient only by single diagnosis and treatment parameters, and can intelligently screen out useful diagnosis and treatment information for clinical diagnosis and bidirectional selection of clinical care, so that the disease diagnosis efficiency and medical care quality of doctors can be remarkably improved, the medical care flow is optimized, and the nursing work efficiency is improved.
Example IV
Referring to fig. 4, fig. 4 is a schematic diagram of an intelligent diagnosis and treatment system according to an embodiment of the present invention. Wherein. As shown in fig. 4, the intelligent diagnosis and treatment system includes:
the information acquisition module 401 is configured to respond to an input instruction, and acquire diagnosis and treatment parameters and personal information corresponding to the input instruction.
The processing module 402 is configured to generate diagnosis and treatment information according to the diagnosis and treatment parameters and the personal information.
The display module 403 is configured to obtain, in response to a diagnosis instruction and/or a care instruction, a matched first diagnosis and treatment content and/or a second diagnosis and treatment content output from the diagnosis and treatment information.
As an optional implementation manner, in the information acquisition module 401, the personal information includes a patient name, a sex, an age, a hospitalization number, etc., and the acquisition mode of the personal information may be manually input by a mode of inputting an instruction, or may be directly input by a synchronous hospital system, and the personal information which is already input, that is, the patient admitted in the past, may be directly extracted.
Further, the processing module includes 402: the acquisition unit 4021 is configured to acquire historical clinical information and/or current clinical information associated with personal information. The module is realized as follows: for the historical clinical information which is already registered in the medical system and is related to the personal information, the historical clinical information can be directly obtained through the medical system in a networking way, namely, the personal information is input into the medical system, and the past clinical information of a patient can be obtained. For patients initially registered in the medical system, the doctor will ask them to manually record the current clinical information of the patient. For patients with new symptoms, the historical clinical information and the current clinical information related to the personal information can be acquired at the same time, so that the obtained diagnosis and treatment information is more accurate.
The screening unit 4022 is configured to perform correlation screening on the clinical information and/or the current clinical information of the diagnosis and treatment parameter, so as to generate clinical information. The module is realized as follows: and performing correlation screening on the diagnosis and treatment parameters in the acquired historical clinical information and the current clinical information to generate clinical information, wherein the correlation screening refers to screening the acquired diagnosis and treatment parameters, such as blood pressure values, blood glucose values and information related to the diagnosis and treatment parameters contained in the historical clinical information and the current clinical information, for example, the diagnosis and treatment parameters contained in an input instruction are 33.0mmol/L of blood glucose values, and the fluctuation range of the blood glucose values or symptoms related to the floating of the blood glucose values of the patient are screened in the historical clinical information and the current clinical information and extracted as the clinical information.
The generating unit 4023 is configured to generate diagnosis and treatment information according to the diagnosis rules and the clinical information.
Wherein the diagnostic rules include: distributing a plurality of disease categories with mapping relations for each branch system; assigning clinical information with a mapping relation to each disease name of the disease category; and distributing diagnosis and treatment information with a mapping relation to the clinical information. The diagnostic rules may be implemented as a knowledge base for medical personnel to learn.
The diagnostic rules can be found in the following embodiments:
different branch systems are taken as main units and extend downwards in a tree diagram. The branching system includes: one or more combinations of respiratory system, digestive system, circulatory system, endocrine system, etc.
Taking the circulatory system as an example, the following conditions include, for example, hypertension, coronary heart disease, acute cerebrovascular disease, heart failure, arrhythmia, rheumatic heart disease, or a combination of one or more of them. For different clinical information manifestations of different disease categories, for example heart failure, clinical information includes fatigue, significantly reduced exercise endurance, exertional dyspnea, nocturnal paroxysmal dyspnea, sitting up breathing, wheezing, dysphoria, frequent coughing and profuse pink foamy sputum, etc. In order to overcome the problem that in the prior art, only a single intelligent medical system for doctor face diagnosis is provided, and no professional guidance is provided for nursing staff, different diagnosis and treatment information is distributed for different clinical information, and the diagnosis and treatment information consists of two parts, including a first diagnosis and treatment content and a second diagnosis and treatment content.
Optionally, the first medical content includes one or more of a disease name, a treatment principle, a treatment method; the second medical treatment includes one or more of a name of the condition, a care measure, and a care notice.
Illustratively, the first diagnosis and treatment content included for diagnosis and treatment information diagnosed as a condition diabetic ketoacidosis according to the above-described clinical information and diagnosis rules is:
name of the condition: disease diabetic ketoacidosis
The treatment principle is as follows: correcting water and electrolyte imbalance, correcting acidosis, supplementing insulin to promote glucose utilization, and finding and removing stress factors inducing ketoacidosis.
The treatment method comprises the following steps: fluid infusion is in principle rapid and slow. When the blood sugar is more than 16.7 mmol/L, adding insulin by using normal saline, and performing intravenous drip at the speed of 500-1000 ml/h; when the blood sugar is 13.9 mmol/L, the blood sugar is monitored regularly, and the intravenous drip of glucose liquid and insulin can be changed, so that the speed is reduced. When the blood pH is 7.0 or the blood is accompanied by high blood potassium, an alkaline drug, preferably sodium bicarbonate solution, should be administered. The dosage is not too much, the speed is not too fast, and insulin can not be put into alkaline solution, so as to avoid the invalidation of the medicine.
Other: symptomatic treatment and elimination of causes.
The second diagnosis and treatment content is as follows:
name of the condition: disease diabetic ketoacidosis
Nursing measures:
1. absolute bed rest should be immediately matched with rescue treatment.
2. And a venous access is quickly established, water, electrolyte and acid-base imbalance are corrected, and ketosis symptoms are corrected.
3. Regular insulin is administered following the order. The small dose of insulin should be administered with correct aspiration to reduce the occurrence of hypoglycemia, hypokalemia, and cerebral edema.
4. The method is used for assisting in treating induced diseases and complications, closely observing vital signs, mind and pupils (see the conventional coma nursing), and assisting in measuring and recording blood sugar.
5. Diet care fasting, and change diabetic semifluid or diabetic diet after symptom relief
6. Preventing infection, caring oral cavity and skin, keeping skin clean, preventing bedsore and secondary infection, and keeping private parts clean for female patient
7. The nursing of neuropathy, controlling diabetes, applying a great deal of vitamin B local massage and physiotherapy, and preventing injury for the person with vanishing skin feeling.
As a preferred embodiment, after diagnosis and treatment information is automatically generated according to diagnosis rules and clinical information, other diagnosis information is also generated by screening according to personal information. For example, if the patient has too high blood sugar, the diagnosis information obtained by singly inputting the blood sugar value of the diagnosis parameters comprises diagnosis of diabetes (several types of diabetes), abnormal glucose tolerance, hyperthyroidism and the like, but if the patient is female and pregnant, the diagnosis information is further screened according to the diagnosis rules to determine that the diagnosis information is gestational diabetes. If the patient is male, the diagnosis of gestational diabetes is excluded, but is considered as other diagnostic information. Therefore, the determined diagnosis and treatment information can be more accurate, and learning of a training doctor and the like is facilitated.
According to the system provided by the embodiment, clinical guidance can be provided for medical care and professional guidance can also be provided for nursing staff. The intelligent diagnosis and treatment system can be combined with the clinical actual condition of a patient only by single diagnosis and treatment parameters, and can intelligently screen out useful diagnosis and treatment information for clinical diagnosis and bidirectional selection of clinical care, so that the disease diagnosis efficiency and medical care quality of doctors can be remarkably improved, the medical care flow is optimized, and the nursing work efficiency is improved.
Example five
Referring to fig. 5, fig. 5 is a schematic structural diagram of an intelligent diagnosis and treatment device according to an embodiment of the invention. As shown in fig. 5, the apparatus may include:
a memory 501 in which executable program codes are stored;
a processor 502 coupled to the memory 501;
the processor 502 invokes executable program code stored in the memory 501 for performing the method for intelligent diagnosis and treatment described in any one of the first or third embodiments.
Example six
The embodiment of the invention discloses a computer readable storage medium storing a computer program for electronic data exchange, wherein the computer program causes a computer to execute the method for intelligent diagnosis and treatment described in any one of the first or third embodiments.
Example seven
An embodiment of the present invention discloses a computer program product comprising a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to perform the method for intelligent diagnosis and treatment described in the first or third embodiment.
The embodiments described above are merely illustrative, wherein the modules illustrated as separate components may or may not be physically separate, and the components shown as modules may or may not be physical, i.e., may be located in one place, or may be distributed over a plurality of network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above detailed description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course by means of hardware. Based on such understanding, the foregoing technical solutions may be embodied essentially or in part in the form of a software product that may be stored in a computer-readable storage medium including Read-Only Memory (ROM), random-access Memory (Random Access Memory, RAM), programmable Read-Only Memory (Programmable Read-Only Memory, PROM), erasable programmable Read-Only Memory (Erasable Programmable Read Only Memory, EPROM), one-time programmable Read-Only Memory (OTPROM), electrically erasable programmable Read-Only Memory (EEPROM), compact disc Read-Only Memory (Compact Disc Read-Only Memory, CD-ROM) or other optical disc Memory, magnetic disc Memory, tape Memory, or any other medium that can be used for computer-readable carrying or storing data.
Finally, it should be noted that: the embodiment of the invention discloses a method for intelligent diagnosis and treatment and an intelligent diagnosis and treatment system, which are only disclosed as preferred embodiments of the invention, and are only used for illustrating the technical scheme of the invention, but not limiting the technical scheme; although the invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art will understand that; the technical scheme recorded in the various embodiments can be modified or part of technical features in the technical scheme can be replaced equivalently; such modifications and substitutions do not depart from the spirit and scope of the corresponding technical solutions.
Claims (6)
1. A method for intelligent medical treatment, the method being used in a medical networking system, the method comprising:
responding to an input instruction, and acquiring diagnosis and treatment parameters and personal information corresponding to the input instruction;
generating diagnosis and treatment information according to the diagnosis and treatment parameters and the personal information, wherein the method comprises the following steps: acquiring historical clinical information and/or current clinical information associated with the personal information; performing correlation screening on the diagnosis and treatment parameters in the historical clinical information and/or the current clinical information to generate clinical information; generating diagnosis and treatment information according to the diagnosis rules and the clinical information; wherein the diagnostic rule includes: distributing a plurality of disease categories with mapping relations for each branch system; assigning clinical information with a mapping relation to each disease name of the disease category; distributing diagnosis and treatment information with a mapping relation to the clinical information;
responding to diagnosis instructions and/or nursing instructions formed by the selection of doctors and/or nursing staff, and acquiring matched first diagnosis and treatment contents and/or second diagnosis and treatment contents output from the diagnosis and treatment information;
wherein the first diagnosis and treatment content is one or a combination of more of a disease name, a treatment principle and a treatment method corresponding to the diagnosis instruction;
the second diagnosis and treatment content is one or a combination of a plurality of symptoms names, nursing measures and nursing notes corresponding to the nursing instructions.
2. The method for intelligent diagnosis and treatment according to claim 1, further comprising:
outputting a plurality of relevant clinical information according to the diagnostic rules and the historical clinical information;
and acquiring the determined clinical information to generate diagnosis and treatment information.
3. The method for intelligent diagnosis and treatment according to claim 2, characterized in that the method further comprises:
outputting a plurality of related condition categories according to the diagnostic rules and the current clinical information;
screening the plurality of related disorder categories according to the historical clinical information to generate a determined disorder category;
and acquiring corresponding diagnosis and treatment information according to the determined disease category and the diagnosis rules.
4. A system for intelligent diagnosis and treatment, the system comprising:
the information acquisition module is used for responding to the input instruction and acquiring diagnosis and treatment parameters and personal information corresponding to the input instruction;
the processing module is used for generating diagnosis and treatment information according to the diagnosis and treatment parameters and the personal information, and comprises the following steps: an acquisition unit configured to acquire historical clinical information and/or current clinical information associated with the personal information; the screening unit is used for carrying out correlation screening on the diagnosis and treatment parameters in the historical clinical information and/or the current clinical information to generate clinical information; the generation unit is used for generating diagnosis and treatment information according to the diagnosis rules and the clinical information; wherein the diagnostic rule includes: distributing a plurality of disease categories with mapping relations for each branch system; assigning clinical information with a mapping relation to each disease name of the disease category; distributing diagnosis and treatment information with a mapping relation to the clinical information;
the display module is used for responding to diagnosis instructions and/or nursing instructions formed by the selection of doctors and/or nursing staff and acquiring matched first diagnosis and treatment contents and/or second diagnosis and treatment contents from the diagnosis and treatment information;
wherein the first diagnosis and treatment content is one or a combination of more of a disease name, a treatment principle and a treatment method corresponding to the diagnosis instruction;
the second diagnosis and treatment content is one or a combination of a plurality of symptoms names, nursing measures and nursing notes corresponding to the nursing instructions.
5. An intelligent diagnostic device, the device comprising:
a memory storing executable program code;
a processor coupled to the memory;
the processor invokes the executable program code stored in the memory to perform the method for intelligent medical treatment as claimed in any one of claims 1-3.
6. Computer storage medium, characterized in that it stores computer instructions for executing the method for intelligent diagnosis and treatment according to any one of claims 1-3 when called.
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