CN114300073A - Clinical patient monitoring method, system and computer storage medium - Google Patents
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Abstract
The invention provides a clinical patient monitoring method, a system and a computer storage medium. Wherein the clinical patient monitoring method comprises: s1, establishing a diagnosis database, a test database and a real-time physical sign database; s2, acquiring target data aiming at a clinical patient based on the established diagnosis database, the established examination database and the real-time physical sign database; s3, inputting the target data into the diagnosis model and outputting the diagnosis result; and S4, pushing corresponding clinical treatment measures by searching data in the expert database based on the output diagnosis result. According to the clinical patient monitoring method, the database related to the physical sign conditions of the patient is established, the target data in the database are collected based on the related database, the target data and the standard threshold data are compared in real time, the related physical sign conditions of the clinical patient can be continuously monitored, and the problems that monitoring is not timely and coping is not appropriate in the prior art are solved.
Description
Technical Field
The present invention relates to the field of clinical monitoring technologies, and in particular, to a method and a system for monitoring a clinical patient, and a computer storage medium.
Background
In the process of diagnosing and treating clinical patients, disorders of fluid, electrolytes, acid-base metabolism and the like are quite common clinically, and the problems can cause the physiological functions of the cardiovascular system and the nervous system of the patients and the substance metabolism of organisms to be obstructed, thereby seriously endangering the lives of the patients. Therefore, the clinical needs to closely monitor the liquid balance, electrolyte balance, acid-base balance and the like and correct the balance in time.
The existing clinical monitoring mode mainly adopts a mode that manual monitoring is taken as a main mode and equipment is taken as an auxiliary mode. However, because various means of balance monitoring are greatly different from methods and intervention means are various, manual monitoring is easy to miss and is not timely enough, and medical staff with low cost often have the problem of inadequate response. Therefore, it is necessary to provide a further solution to the above problems.
Disclosure of Invention
The present invention is directed to a method, system and computer storage medium for clinical patient monitoring that overcome the deficiencies of the prior art.
In order to solve the technical problems, the technical scheme of the invention is as follows:
a method of clinical patient monitoring, comprising:
s1, establishing a diagnosis database, a test database and a real-time physical sign database;
s2, acquiring target data aiming at a clinical patient based on the established diagnosis database, the established examination database and the real-time physical sign database;
s3, inputting the target data into the diagnosis model and outputting the diagnosis result;
and S4, pushing corresponding clinical treatment measures by searching data in the expert database based on the output diagnosis result.
As an improvement of the clinical patient monitoring method of the present invention, establishing a diagnostic database, a test database, and a real-time signs database for a clinical patient includes:
packing the diagnosis data of the patient into electronic medical record data, and inputting the packed electronic medical record data into an electronic medical record system database;
collecting detection data generated aiming at a patient, and inputting the detection data into a laboratory information system database;
physical sign data generated for a patient is collected and entered into a clinical care system database.
As an improvement of the clinical patient monitoring method of the present invention, the acquiring of the target data for the clinical patient comprises:
s21, respectively searching relevant data aiming at clinical patients in the diagnosis database, the inspection database and the real-time physical sign database;
and S22, extracting target data aiming at the clinical patient from the relevant data of the clinical patient according to the preset data type and the starting time.
As an improvement of the clinical patient monitoring method of the invention, the data types are data related to at least one of human body fluid balance, electrolyte balance and acid-base balance.
As an improvement of the clinical patient monitoring method, the diagnosis model carries out diagnosis calculation on target data according to the following calculation method:
s31, comparing the target data with a corresponding lower threshold, if the target data is smaller than the lower threshold, outputting a first diagnosis result representing the imbalance of the physical sign condition of the clinical patient, otherwise, executing the step S32;
and S32, comparing the target data with the corresponding upper threshold, if the target data is larger than the upper threshold, outputting a second diagnosis result representing the imbalance of the physical sign conditions of the clinical patient, and otherwise, outputting a third diagnosis result representing the balance of the physical sign conditions of the clinical patient.
As an improvement of the clinical patient monitoring method of the present invention, the performing diagnostic calculations on the target data further comprises:
and grouping the target data according to preset data types, and comparing each group of target data with a standard threshold range corresponding to the corresponding data type.
As an improvement of the clinical patient monitoring method, the expert database stores the clinical treatment measures corresponding to the diagnosis results in advance, and the corresponding clinical treatment measures are pushed according to the corresponding relation between the diagnosis results and the clinical treatment measures in the expert database.
As an improvement of the clinical patient monitoring method of the present invention, the pushing of the corresponding clinical treatment measures further comprises:
and searching corresponding clinical treatment measures according to the corresponding relation between the diagnosis result and the clinical treatment measures in the expert database, sequencing the various clinical treatment measures according to a preset priority level when the clinical treatment measures are various, and pushing the various clinical treatment measures which are sequenced.
In order to solve the technical problems, the technical scheme of the invention is as follows:
a clinical patient monitoring system, comprising:
the database establishing module is used for establishing a diagnosis database, a test database and a real-time physical sign database;
a target data acquisition module for acquiring target data for clinical patients based on the established diagnosis database, examination database and real-time physical sign database;
the diagnosis module is used for inputting the target data into the diagnosis model and outputting a diagnosis result;
and the treatment module is used for pushing corresponding clinical treatment measures by searching data in the expert database based on the output diagnosis result.
In order to solve the technical problems, the technical scheme of the invention is as follows:
a computer storage medium having stored therein computer program instructions which, when executed by a processor, are capable of implementing a clinical patient monitoring method as described above.
Compared with the prior art, the invention has the beneficial effects that:
according to the clinical patient monitoring method, the database related to the physical sign conditions of the patient is established, the target data in the database are collected based on the related database, the target data and the standard threshold data are compared in real time, the related physical sign conditions of the clinical patient can be continuously monitored, and the problems that monitoring is not timely and coping is not appropriate in the prior art are solved.
On the application level, by adopting the clinical patient monitoring method, an accurate nutrition target can be set according to the actual state of illness of the patient, and the patient is helped to better reach the nutrition condition through nutrition intervention and medical advice correction. Therefore, the treatment is more accurate and effective, and various adverse effects caused by substandard nutritional status are prevented. Meanwhile, a large amount of objective structured data can be automatically collected for later-stage scientific research and analysis.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic flow chart of a method of monitoring a clinical patient according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of a clinical patient monitoring method according to the present invention, which is taken as an example of the conventional examination result of the blood of a patient and the observation result of the physical signs of the patient;
FIG. 3 is a block diagram of a clinical patient monitoring system according to an embodiment of the present invention.
Detailed Description
The technical solutions in 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 obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, an embodiment of the present invention provides a clinical patient monitoring method, which includes:
and S1, establishing a diagnosis database, a test database and a real-time physical sign database.
As shown in table 1 (an example of diagnostic data), the diagnostic database corresponds to diagnostic data of a patient, and the data may be derived from data recorded at the time of patient inquiry, and may further reflect the physical condition of the patient. In one embodiment, establishing a diagnostic database for a clinical patient comprises: and packaging the diagnosis data of the patient into electronic medical record data, and inputting the packaged electronic medical record data into an electronic medical record system database.
| Patient coding | Diagnostic prefix | Diagnosis of | Diagnostic suffix | Diagnostic coding | Diagnosis time |
| 2123594 | Severe degree | Muscular weakness | Middle stage | G70.001 | 2020/9/14 |
TABLE 1
As shown in table 2 (an example of test data), the test database corresponds to test data of a patient, and the data indirectly reflects the physical condition of the patient through experimental detection of a sample (blood sample, urine sample, etc.) from the patient. In one embodiment, establishing test data for a clinical patient comprises: test data generated for the patient is collected and entered into a laboratory information system database.
TABLE 2
As shown in table 3 (an example of the test data), the real-time sign database corresponds to real-time sign data of the patient, which can be derived from data recorded in daily clinical care, so as to reflect the sign status of the patient in real time. In one embodiment, establishing a real-time signs database for a clinical patient comprises: physical sign data generated for a patient is collected and entered into a clinical care system database.
| Patient's health | Encoding | Item | Time of acquisition | Results | Unit of |
| 2116926 | PM_HR | Heart rate | 2020/5/19 18:00 | 40 | bpm |
| 2102532 | PM_T | Body temperature | 2020/5/19 18:00 | 80 | ℃ |
| 2102532 | PM_CVP | Central venous pressure | 2020/5/19 18:00 | 80 | mmHg |
TABLE 3
And S2, acquiring target data aiming at the clinical patient based on the established diagnosis database, the test database and the real-time sign database.
Because the associated data of the patient is stored in the corresponding databases, the target data for the clinical patient can be collected according to the requirement, so that the target data can be compared with the preset standard threshold data in real time.
Specifically, acquiring target data for a clinical patient includes:
and S21, respectively searching relevant data aiming at the clinical patient in a diagnosis database, a test database and a real-time physical sign database.
And S22, extracting target data aiming at the clinical patient from the relevant data of the clinical patient according to the preset data type and the starting time.
When searching for relevant data, firstly, the relevant data is positioned to the position of the relevant clinical patient relevant data storage. Then, according to the required data category associated with the corresponding physical sign condition and the starting time required to be monitored, corresponding target data is extracted from the located stored data.
In one embodiment, the data type is data associated with at least one of fluid balance, electrolyte balance, and acid-base balance of the human body.
Specifically, the fluid balance is mainly monitored for intake, output, osmotic pressure, and central venous pressure of the patient, and the relevant data are derived from the monitoring of the medical order, vital signs of the patient, and the like. For electrolyte balance, the values of serum sodium and serum potassium of patients are mainly monitored, and the related data are derived from tests on the patients and the like. For acid-base equilibrium, the patient's pH, HCO are monitored primarily-3、PaCO2BE, etc., derived from patient tests. Therefore, the method is beneficial to closely monitoring liquid balance, electrolyte balance, acid-base balance and the like, and timely collecting relevant measures.
Therefore, on the application level, by adopting the clinical patient monitoring method, an accurate nutrition target can be set according to the actual state of illness of the patient, and the patient is helped to better reach the nutrition condition through nutrition intervention and medical advice correction. Therefore, the treatment is more accurate and effective, and various adverse effects caused by substandard nutritional status are prevented. Meanwhile, a large amount of objective structured data can be automatically collected for later-stage scientific research and analysis.
And S3, inputting the target data into the diagnosis model and outputting the diagnosis result.
The diagnosis model is used for comparing the acquired target data with standard threshold data, and further judging whether the physical sign condition of the detected clinical patient is normal or not in real time. Therefore, the problems that omission is easy to occur and timeliness is not enough in manual monitoring in the prior art can be solved.
Correspondingly, the diagnosis model carries out diagnosis calculation on the target data according to the following calculation method:
s31, comparing the target data with a corresponding lower threshold, if the target data is smaller than the lower threshold, outputting a first diagnosis result representing the imbalance of the physical sign condition of the clinical patient, otherwise, executing the step S32;
and S32, comparing the target data with the corresponding upper threshold, if the target data is larger than the upper threshold, outputting a second diagnosis result representing the imbalance of the physical sign conditions of the clinical patient, and otherwise, outputting a third diagnosis result representing the balance of the physical sign conditions of the clinical patient.
The first diagnostic result and the second diagnostic result represent the situation that the target data is out of the threshold data range. And the third diagnostic result represents that the target is within the threshold data range. According to the above-mentioned judgement result and considering the related index, it can further output the correspondent diagnosis result.
As shown in fig. 2, step S3 will be described below by taking the patient blood routine examination result and the patient sign observation result as examples, and determining whether or not the patient has water and sodium disorders.
Specifically, patient sign data is input and Na is tested+Whether or not it is in the range of 135mmol/L to 145 mmol/L.
When Na is present+Less than or equal to 135mmol/L, and low volume, it indicates the corresponding sign condition is hypotonic dehydration; when Na is present+Less than or equal to 135mmol/L, and low or high volume, it indicates that the corresponding sign condition is water poisoning; when Na is present+Less than or equal to 135mmol/L, and if the volume is normal, the corresponding sign condition is the primary hyponatremia.
When 135mmol/L is less than Na+If the concentration is less than 145mmol/L and no dehydration occurs, the corresponding sign condition is normal. When 135mmol/L is less than Na+If the concentration is less than 145mmol/L and dehydration occurs, the corresponding sign condition is isotonic dehydration.
When Na is present+If the concentration is more than 135mmol/L and the dehydration phenomenon does not exist, the corresponding physical sign condition is hypertonic dehydration; when Na is present+If the concentration is more than 135mmol/L and dehydration occurs, the corresponding sign condition is Cushing syndrome.
Further, when the target data includes data associated with a plurality of data types, performing the diagnostic calculation on the target data further includes:
and grouping the target data according to preset data types, and comparing each group of target data with a standard threshold range corresponding to the corresponding data type. Therefore, different types of target data are grouped and respectively calculated, and a plurality of groups of corresponding detection results can be output.
And S4, pushing corresponding clinical treatment measures by searching data in the expert database based on the output diagnosis result.
The expert database stores clinical treatment measures corresponding to different diagnosis results in advance, and the clinical treatment measures are verified reliable measures. Therefore, the problem that medical staff with low annual cost in the prior art often have inadequate treatment can be solved.
Specifically, since the expert database stores the clinical treatment measures corresponding to the diagnosis results in advance, the diagnosis results output in step S3 may be pushed according to the correspondence between the diagnosis results and the clinical treatment measures in the expert database.
Furthermore, in consideration of the diversity of the physical condition manifestations of clinical patients, pushing the corresponding clinical treatment measures further comprises:
and searching corresponding clinical treatment measures according to the corresponding relation between the diagnosis result and the clinical treatment measures in the expert database, sequencing the various clinical treatment measures according to a preset priority level when the clinical treatment measures are various, and pushing the various clinical treatment measures which are sequenced.
Thus, by ordering the clinical treatment measures, it is advantageous to preferentially execute the clinical treatment measures of higher priority. Therefore, the method is favorable for preferentially solving and balancing symptoms which have larger influence on the physical sign conditions of clinical patients. In addition, the sequence of the pushed various clinical treatment measures can be dynamically adjusted according to actual requirements.
For example, taking the above conventional examination result of blood of a patient and the observation result of physical signs of the patient as an example, when the diagnosis result is hypotonic dehydration, by looking up the data in the expert database, the corresponding clinical treatment measures can be pushed as follows: 1) and supplementing hypertonic liquid such as normal saline and 10% NaCl. 2) Extracellular water loss was severe, and signs of circulatory failure were noted.
When the diagnosis result is water poisoning, by searching the data in the expert database, the pushing of the corresponding clinical treatment measures may be: 1) limiting water intake; 2) diuresis, dehydration and hemofiltration; 3) and preventing and treating cerebral edema.
When the diagnosis result is primary hyponatremia, by searching data in the expert database, the corresponding clinical treatment measures can be pushed as follows: 1) and supplementing high-concentration NaCl. 2) And appropriately restricting the water intake. 3) Use of a diuretic. 4) It is usually caused by endocrine diseases, and attention is paid to etiology and treatment.
As shown in fig. 3, based on the same technical concept, another embodiment of the present invention also provides a clinical patient monitoring system 100, which includes: a database building module 10, a target data acquisition module 20, a diagnosis module 30 and a treatment module 40.
Specifically, the database building module 10 is used to build a diagnosis database, a test database, and a real-time physical sign database.
The target data acquisition module 20 is configured to acquire target data for clinical patients based on the established diagnosis database, the examination database, and the real-time physical sign database.
The diagnostic module 30 is used to input target data into the diagnostic model and output diagnostic results.
The treatment module 40 is used for pushing the corresponding clinical treatment measures by searching the data in the expert database based on the output diagnosis results.
In the embodiment of the present invention, a clinical patient monitoring system including a database establishing module, a target data acquiring module, a diagnosing module, and a treating module is a virtual system corresponding to a clinical patient monitoring method, and the virtual system may be a functional module built in a hospital HIS system.
Based on the same technical concept, another embodiment of the present invention also provides a computer storage medium having computer program instructions stored therein, wherein the computer program instructions, when executed by a processor, can implement the clinical patient monitoring method as described above.
The processor may be an integrated circuit chip having signal processing capabilities. The Processor may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like. The Processor may also be other general purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The various methods, steps, and logic blocks disclosed in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
As will be appreciated by one of skill in the art, embodiments of the present invention may be provided as a method, computer apparatus, or computer program product. Accordingly, embodiments of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
Embodiments of the present invention are described with reference to flowchart illustrations and/or block diagrams of methods, computer apparatus, or computer program products according to embodiments of the invention. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing terminal to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal, create means for implementing the functions specified in the flowchart and/or flowchart block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing terminal to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart.
The present invention provides a method for linking entities for internet services, a computer device, and a computer-readable storage medium, wherein the method, the computer device, and the computer-readable storage medium are applied to a specific embodiment to explain the principles and embodiments of the present invention, and the description of the embodiment is only used to help understand the method and the core idea of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (10)
1. A method of clinical patient monitoring, the method comprising:
s1, establishing a diagnosis database, a test database and a real-time physical sign database;
s2, acquiring target data aiming at a clinical patient based on the established diagnosis database, the established examination database and the real-time physical sign database;
s3, inputting the target data into the diagnosis model and outputting the diagnosis result;
and S4, pushing corresponding clinical treatment measures by searching data in the expert database based on the output diagnosis result.
2. The clinical patient monitoring method of claim 1, wherein establishing a diagnostic database, an examination database, and a real-time signs database for a clinical patient comprises:
packing the diagnosis data of the patient into electronic medical record data, and inputting the packed electronic medical record data into an electronic medical record system database;
collecting detection data generated aiming at a patient, and inputting the detection data into a laboratory information system database;
physical sign data generated for a patient is collected and entered into a clinical care system database.
3. The clinical patient monitoring method of claim 1, wherein the acquiring target data for a clinical patient comprises:
s21, respectively searching relevant data aiming at clinical patients in the diagnosis database, the inspection database and the real-time physical sign database;
and S22, extracting target data aiming at the clinical patient from the relevant data of the clinical patient according to the preset data type and the starting time.
4. A clinical patient monitoring method according to claim 3, wherein said data categories are data associated with at least one of human fluid balance, electrolyte balance, acid-base balance.
5. The clinical patient monitoring method of claim 1, wherein the diagnostic model performs diagnostic calculations on the target data according to the following calculation method:
s31, comparing the target data with a corresponding lower threshold, if the target data is smaller than the lower threshold, outputting a first diagnosis result representing the imbalance of the physical sign condition of the clinical patient, otherwise, executing the step S32;
and S32, comparing the target data with the corresponding upper threshold, if the target data is larger than the upper threshold, outputting a second diagnosis result representing the imbalance of the physical sign conditions of the clinical patient, and otherwise, outputting a third diagnosis result representing the balance of the physical sign conditions of the clinical patient.
6. The clinical patient monitoring method of claim 5, wherein performing diagnostic calculations on the target data further comprises:
and grouping the target data according to preset data types, and comparing each group of target data with a standard threshold range corresponding to the corresponding data type.
7. The clinical patient monitoring method according to claim 1, wherein the expert database stores clinical treatment measures corresponding to the diagnosis results in advance, and the corresponding clinical treatment measures are pushed according to the correspondence between the diagnosis results and the clinical treatment measures in the expert database.
8. The clinical patient monitoring method of claim 7, wherein the pushing the corresponding clinical treatment measures further comprises:
and searching corresponding clinical treatment measures according to the corresponding relation between the diagnosis result and the clinical treatment measures in the expert database, sequencing the various clinical treatment measures according to a preset priority level when the clinical treatment measures are various, and pushing the various clinical treatment measures which are sequenced.
9. A clinical patient monitoring system, comprising:
the database establishing module is used for establishing a diagnosis database, a test database and a real-time physical sign database;
a target data acquisition module for acquiring target data for clinical patients based on the established diagnosis database, examination database and real-time physical sign database;
the diagnosis module is used for inputting the target data into the diagnosis model and outputting a diagnosis result;
and the treatment module is used for pushing corresponding clinical treatment measures by searching data in the expert database based on the output diagnosis result.
10. A computer storage medium having stored thereon computer program instructions which, when executed by a processor, are capable of implementing a clinical patient monitoring method according to any one of claims 1 to 8.
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| CN117831633A (en) * | 2023-12-15 | 2024-04-05 | 江苏和福生物科技有限公司 | Bladder cancer biomarker extraction method based on diagnosis model |
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