CN112331355B - Disease type evaluation table generation method and device, electronic equipment and storage medium - Google Patents
Disease type evaluation table generation method and device, electronic equipment and storage medium Download PDFInfo
- Publication number
- CN112331355B CN112331355B CN202011351134.XA CN202011351134A CN112331355B CN 112331355 B CN112331355 B CN 112331355B CN 202011351134 A CN202011351134 A CN 202011351134A CN 112331355 B CN112331355 B CN 112331355B
- Authority
- CN
- China
- Prior art keywords
- target
- diagnosis
- treatment
- disease type
- current
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 title claims abstract description 197
- 201000010099 disease Diseases 0.000 title claims abstract description 196
- 238000011156 evaluation Methods 0.000 title claims abstract description 96
- 238000000034 method Methods 0.000 title claims abstract description 49
- 238000011282 treatment Methods 0.000 claims abstract description 369
- 238000003745 diagnosis Methods 0.000 claims abstract description 321
- 238000004590 computer program Methods 0.000 claims description 4
- 239000003814 drug Substances 0.000 description 99
- 239000003795 chemical substances by application Substances 0.000 description 15
- 229940079593 drug Drugs 0.000 description 15
- 238000010586 diagram Methods 0.000 description 12
- 238000004458 analytical method Methods 0.000 description 11
- 230000006870 function Effects 0.000 description 11
- 230000003287 optical effect Effects 0.000 description 6
- 238000012545 processing Methods 0.000 description 6
- 206010012601 diabetes mellitus Diseases 0.000 description 5
- 230000000144 pharmacologic effect Effects 0.000 description 5
- 230000008569 process Effects 0.000 description 5
- 238000011269 treatment regimen Methods 0.000 description 5
- HVYWMOMLDIMFJA-DPAQBDIFSA-N cholesterol Chemical compound C1C=C2C[C@@H](O)CC[C@]2(C)[C@@H]2[C@@H]1[C@@H]1CC[C@H]([C@H](C)CCCC(C)C)[C@@]1(C)CC2 HVYWMOMLDIMFJA-DPAQBDIFSA-N 0.000 description 4
- 208000024891 symptom Diseases 0.000 description 3
- 230000001960 triggered effect Effects 0.000 description 3
- 102000017011 Glycated Hemoglobin A Human genes 0.000 description 2
- 108010014663 Glycated Hemoglobin A Proteins 0.000 description 2
- 239000008280 blood Substances 0.000 description 2
- 210000004369 blood Anatomy 0.000 description 2
- 230000036772 blood pressure Effects 0.000 description 2
- 235000012000 cholesterol Nutrition 0.000 description 2
- 208000029078 coronary artery disease Diseases 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 230000002093 peripheral effect Effects 0.000 description 2
- 230000000644 propagated effect Effects 0.000 description 2
- 230000000717 retained effect Effects 0.000 description 2
- UFTFJSFQGQCHQW-UHFFFAOYSA-N triformin Chemical compound O=COCC(OC=O)COC=O UFTFJSFQGQCHQW-UHFFFAOYSA-N 0.000 description 2
- WQZGKKKJIJFFOK-GASJEMHNSA-N Glucose Natural products OC[C@H]1OC(O)[C@H](O)[C@@H](O)[C@@H]1O WQZGKKKJIJFFOK-GASJEMHNSA-N 0.000 description 1
- 206010020772 Hypertension Diseases 0.000 description 1
- 230000002411 adverse Effects 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 230000002888 effect on disease Effects 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 239000000835 fiber Substances 0.000 description 1
- 239000008103 glucose Substances 0.000 description 1
- 230000001771 impaired effect Effects 0.000 description 1
- 230000008676 import Effects 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000002483 medication Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 239000013307 optical fiber Substances 0.000 description 1
- 230000008707 rearrangement Effects 0.000 description 1
- 238000012552 review Methods 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000001502 supplementing effect Effects 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 230000001225 therapeutic effect Effects 0.000 description 1
- 230000003313 weakening effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
-
- 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
-
- 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
-
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Public Health (AREA)
- Primary Health Care (AREA)
- Data Mining & Analysis (AREA)
- Epidemiology (AREA)
- General Health & Medical Sciences (AREA)
- Theoretical Computer Science (AREA)
- Databases & Information Systems (AREA)
- Chemical & Material Sciences (AREA)
- Biomedical Technology (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Medicinal Chemistry (AREA)
- Computational Linguistics (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Pathology (AREA)
- Medical Treatment And Welfare Office Work (AREA)
Abstract
The invention discloses a method and a device for generating a disease type evaluation table, electronic equipment and a storage medium. The method comprises the steps of obtaining a target disease type in a target medical record template, and calling at least one target diagnosis and treatment factor corresponding to the target disease type from a pre-established target database; respectively calling the target diagnosis and treatment parameters of each target diagnosis and treatment factor according to the fetch path corresponding to the at least one target diagnosis and treatment factor; and importing each target diagnosis and treatment parameter into a content editing control corresponding to the corresponding target diagnosis and treatment factor, and generating a medical record evaluation table corresponding to the target disease type. By the technical scheme of the embodiment of the invention, the medical record evaluation table is flexibly configured, and the working efficiency of doctors is greatly improved.
Description
Technical Field
The embodiment of the invention relates to the technical field of medical treatment, in particular to a method and a device for generating a disease type evaluation table, electronic equipment and a storage medium.
Background
At present, when determining the disease type corresponding to the medical record sheet, the disease type corresponding to the medical record sheet can be determined by processing the disease information recorded in the medical record sheet based on the memory of a doctor.
The method is adopted to determine that the medical record lacks of deep combination with the hospital informatization system and does not obviously shorten the path of solving the problem of a clinician, only has the effects of supplementing clinical scenes and solving special problems, and has less effect of improving the medical efficiency and quality.
Disclosure of Invention
The invention provides a method, a device, electronic equipment and a storage medium for generating a disease type evaluation table, which are used for realizing flexible configuration of a medical record evaluation table and greatly improving the working efficiency of doctors.
The invention provides a method, a device, electronic equipment and a storage medium for generating a disease type evaluation table, which are used for realizing automatic generation of a generation report of the disease type evaluation table, are convenient to operate, effectively reduce the working intensity of testers and improve the working efficiency.
In a first aspect, an embodiment of the present invention provides a method for generating a disease type evaluation table, where the method includes:
acquiring a target disease type in a target medical record template, and calling at least one target diagnosis and treatment factor corresponding to the target disease type from a pre-established target database;
respectively calling the target diagnosis and treatment parameters of each target diagnosis and treatment factor according to the fetch path corresponding to the at least one target diagnosis and treatment factor;
And importing each target diagnosis and treatment parameter into a content editing control corresponding to the corresponding target diagnosis and treatment factor, and generating a medical record evaluation table corresponding to the target disease type.
In a second aspect, an embodiment of the present invention further provides a device for generating a disease type evaluation table, where the device includes:
the target diagnosis and treatment factor acquisition module is used for acquiring target disease types in the target medical record template and calling at least one target diagnosis and treatment factor corresponding to the target disease types from a pre-established target database;
the target diagnosis and treatment parameter acquisition module is used for respectively calling the target diagnosis and treatment parameters of each target diagnosis and treatment factor according to the fetch path corresponding to the at least one target diagnosis and treatment factor;
the medical record evaluation table generation module is used for importing each target diagnosis and treatment parameter into a content editing control corresponding to the corresponding target diagnosis and treatment factor to generate a medical record evaluation table corresponding to the target disease type
In a third aspect, an embodiment of the present invention further provides an electronic device, including:
one or more processors;
storage means for storing one or more programs,
when the one or more programs are executed by the one or more processors, the one or more processors implement a method for generating a disease seed evaluation table according to any embodiment of the present invention.
In a fourth aspect, an embodiment of the present invention further provides a computer readable storage medium, on which a computer program is stored, which when executed by a processor, implements the method for generating a disease seed evaluation table provided by any embodiment of the present invention.
According to the technical scheme, the target disease type in the target medical record template is obtained, and at least one target diagnosis and treatment factor corresponding to the target disease type is called from a pre-established target database; respectively calling the target diagnosis and treatment parameters of each target diagnosis and treatment factor according to the fetch path corresponding to the at least one target diagnosis and treatment factor; each target diagnosis and treatment parameter is imported into a content editing control corresponding to the corresponding target diagnosis and treatment factor to generate a medical record evaluation table corresponding to the target disease type, so that the problem that the path of a clinician for solving the problem is not obviously shortened in the method for determining the disease type corresponding to the medical record list in the prior art is solved, the medical record evaluation table is flexibly generated by configuring the target diagnosis and treatment factor, and the working efficiency of the doctor is greatly improved.
Drawings
In order to more clearly illustrate the technical solution of the exemplary embodiments of the present invention, a brief description is given below of the drawings required for describing the embodiments. It is obvious that the drawings presented are only drawings of some of the embodiments of the invention to be described, and not all the drawings, and that other drawings can be made according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flow chart of a method for generating a disease seed evaluation table according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a disease seed evaluation table according to a first embodiment of the present invention;
fig. 3 is a flow chart of a method for generating a disease seed evaluation table according to a second embodiment of the present invention;
fig. 4 is a schematic diagram of establishing a diagnosis and treatment factor to be selected according to a second embodiment of the present invention;
FIG. 5 is a schematic diagram of target diagnosis and treatment factor association according to a third embodiment of the present invention;
FIG. 6 is a schematic view of a list of medical record evaluation tables according to a third embodiment of the present invention;
fig. 7 is a schematic structural diagram of a device for generating a disease seed evaluation table according to a fifth embodiment of the present invention;
fig. 8 is a schematic structural diagram of an electronic device according to a sixth embodiment of the present invention.
Detailed Description
The invention is described in further detail below with reference to the drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting thereof. It should be further noted that, for convenience of description, only some, but not all of the structures related to the present invention are shown in the drawings.
Example 1
Fig. 1 is a flowchart of a method for generating a disease type evaluation table according to a first embodiment of the present invention, where the present embodiment is applicable to a situation where a physician generates a disease type evaluation table according to a target medical record template. The method may be performed by a disease type assessment table generating means, which may be implemented in software and/or hardware. As shown in fig. 1, the method specifically includes the following steps:
S110, acquiring a target disease type in a target medical record template, and calling at least one target diagnosis and treatment factor corresponding to the target disease type from a pre-established target database.
In the embodiment of the invention, the diagnosis case of the on-site patient can be used as a target medical record template. The target medical record template can be the current visit case of the patient or the historical visit case of the patient. The type of disease currently being evaluated may be regarded as the target type of disease. For example, the target disease type may be diabetes, hypertension, and Coronary Artery Disease (CAD) and the like. The target database may be a pre-established database in which various types of diseases and various diagnosis and treatment factors corresponding to the various types of diseases are stored. The target diagnostic factor may be at least one diagnostic factor associated with the target disease type, which is a major element affecting diagnosis and treatment of the target disease type, for example, when the target disease type is diabetes, the target diagnostic factor may be a blood glucose, glycosylated hemoglobin, blood pressure, total cholesterol, triglyceride, and the like. Accordingly, the number of target diagnostic factors may include one or more.
Specifically, the target disease type is obtained from the target medical record template, and after the target disease type is determined, at least one target diagnosis and treatment factor corresponding to the target disease type can be called from a pre-established database storing diagnosis and treatment factors.
Optionally, determining at least one target code bound to the target disease type according to the target disease type; and retrieving the target diagnosis and treatment factors corresponding to the target codes from a target database.
Wherein the target code is a unique identification of the target diagnosis and treatment factor corresponding to the target disease type, and the target code can be, but is not limited to, a name, a number or a character string formed by at least one of a number, a letter and a character of each target disease type. The diagnosis and treatment factors associated with the same disease type can comprise a plurality of diagnosis and treatment factors, and correspondingly, the number of codes bound with the target disease type can also comprise a plurality of codes.
According to the type of the target disease, the target codes corresponding to the target diagnosis and treatment factors can have an association relation. For the sake of clearly describing the technical solution of this embodiment, it may be described by taking any target diagnosis and treatment factor corresponding to the type of the target disease as an example.
Specifically, determining a target code of a current target diagnosis and treatment factor corresponding to the target disease type, matching the target code with codes corresponding to diagnosis and treatment factors in a pre-established database, and determining the diagnosis and treatment factor corresponding to the code with the matching result of the current target code as the target diagnosis and treatment factor when the matching result is consistent.
S120, respectively calling the target diagnosis and treatment parameters of each target diagnosis and treatment factor according to the fetch path corresponding to at least one target diagnosis and treatment factor.
The access path is a local storage path of diagnosis and treatment parameters corresponding to diagnosis and treatment factors, or a storage path corresponding to detection results of each diagnosis and treatment factor. The target diagnosis and treatment parameters are diagnosis and treatment parameters corresponding to the target diagnosis and treatment factors. The target diagnosis and treatment parameter can be a specific numerical value or a corresponding index value, and optionally, if a diabetic patient, the index value 1 indicates mild, the index value 2 indicates moderate and the like. And according to the fetch path corresponding to each target diagnosis and treatment factor, the corresponding target diagnosis and treatment parameters can be fetched.
Optionally, for each target diagnosis and treatment factor, determining a current access path associated with the current target diagnosis and treatment factor, and calling a target diagnosis and treatment parameter corresponding to the user basic information according to the current access path and the user basic information in the target medical record template.
The user basic information may be identification information of the patient, such as name, phone number, and identification card number. In order to accurately acquire diagnosis and treatment parameters of a certain user, the user basic information can enable the identification card number of the user, namely a unique identifier for representing the identity of the user.
Specifically, taking the example of obtaining the target parameter of any one of the target diagnosis and treatment factors. After the case template is structured according to the diagnosis and treatment factors, corresponding diagnosis and treatment parameters can be called according to the fetch path corresponding to each diagnosis and treatment factor and the basic information of the user. The advantage of calling the corresponding diagnosis and treatment factors according to the basic information of the user is that the diagnosis and treatment parameters of the user can be accurately called.
S130, importing each target diagnosis and treatment parameter into a content editing control corresponding to the corresponding target diagnosis and treatment factor, and generating a medical record evaluation table corresponding to the target disease type.
The content editing control is a control for editing target diagnosis and treatment parameters corresponding to the target diagnosis and treatment factors. The content editing control is located on the target page and can be used for editing target diagnosis and treatment parameters corresponding to the target diagnosis and treatment factors. The medical record evaluation list is a statistical list of at least one target diagnosis and treatment factor corresponding to the target case type. After the diagnosis and treatment parameters are called, the diagnosis and treatment parameters can be automatically imported into the corresponding diagnosis and treatment factors.
Specifically, diagnosis and treatment parameters corresponding to the target diagnosis and treatment factors can be imported into controls corresponding to the diagnosis and treatment factors in the case template to generate a medical record evaluation table corresponding to the target disease type.
The target disease type is diabetes, diagnosis factors associated with diabetes including blood sugar, glycosylated hemoglobin, blood pressure, total cholesterol, triglyceride and the like are determined, a number taking path corresponding to each diagnosis factor can be determined, corresponding diagnosis parameters are obtained based on the number taking path, and the diagnosis parameters are imported into a medical record template to generate a medical record evaluation table, wherein the specific medical record evaluation table is shown in fig. 2.
According to the technical scheme, the target disease type in the target medical record template is obtained, and at least one target diagnosis and treatment factor corresponding to the target disease type is called from a pre-established target database; respectively calling the target diagnosis and treatment parameters of each target diagnosis and treatment factor according to the fetch path corresponding to at least one target diagnosis and treatment factor; each target diagnosis and treatment parameter is imported into a content editing control corresponding to the corresponding target diagnosis and treatment factor to generate a medical record evaluation table corresponding to the target disease type, so that the problem that the path of a clinician for solving the problem is not obviously shortened in the method for determining the disease type corresponding to the medical record list in the prior art is solved, the medical record evaluation table is flexibly generated by configuring the target diagnosis and treatment factor, and the working efficiency of the doctor is greatly improved.
Example two
Fig. 3 is a flowchart of a method for generating a disease type evaluation table according to a second embodiment of the present invention, where, based on the foregoing embodiments, a to-be-selected diagnosis and treatment factor corresponding to each disease type in a target database and a retrieval path corresponding to each to-be-selected diagnosis and treatment factor may be established, so that after determining the target disease type, a target diagnosis and treatment factor may be determined from to-be-selected diagnosis and treatment factors in the target database, and corresponding diagnosis and treatment parameters may be retrieved according to the retrieval path of the target diagnosis and treatment factor. The explanation of "wherein the same or corresponding terms as those of the above embodiments are not repeated here.
Referring to fig. 3, the method for generating a disease seed evaluation table provided in this embodiment includes:
before describing the scheme of the embodiment, an application scenario is described in an exemplary way: in order to enable a doctor to accurately make diagnosis of a disease type or evaluation of treatment according to each test result in a case of a patient to be diagnosed, the technical scheme of the embodiment of the invention stores each disease type and at least one diagnosis and treatment factor corresponding to each disease type in the preset database in an associated manner, when the doctor needs a disease of a certain user, at least one target diagnosis and treatment factor corresponding to the target disease type and corresponding target diagnosis and treatment parameters can be acquired from the target database, so that a medical record evaluation table is generated according to each diagnosis and treatment factor and diagnosis and treatment parameters, the doctor can quickly evaluate each disease type, and the working efficiency of the doctor is greatly improved.
S210, at least one diagnosis and treatment factor to be selected, which is associated with each disease type, in a target database is established.
In an embodiment of the present invention, the diagnosis and treatment factor to be selected may be a diagnosis and treatment factor to be associated with the target disease type.
In order to determine the diagnosis and treat factors associated with each disease type, the diagnosis and treat factors corresponding to each disease type may be edited according to a knowledge base or doctor experience. Optionally, for each disease type, if the input of the current diagnosis and treatment factor corresponding to the current disease type is detected, judging whether the current diagnosis and treatment factor is included in the target database; and generating the diagnosis and treatment factors to be selected which are associated with the current disease type according to the judging result and the current diagnosis and treatment factors.
Specifically, when the current diagnosis and treatment factor is determined to correspond to the current disease type and the input operation of the current diagnosis and treatment factor in the target database is triggered, whether the current diagnosis and treatment factor is included in the target database is judged, and according to the judging result and the current diagnosis and treatment factor, the diagnosis and treatment factor to be selected which is related to the current disease type is generated.
Optionally, if the target database includes the current diagnosis and treatment factor, the current diagnosis and treatment factor is selected, and the current diagnosis and treatment factor is adjusted relative to the code to be selected and the path to be selected corresponding to the current disease type. If the target database does not contain the current diagnosis and treatment factors, the current diagnosis and treatment factors are customized, and a to-be-selected access path and a to-be-selected code corresponding to the current diagnosis and treatment factors are set.
Specifically, the adjusting the code to be selected corresponding to the current diagnosis and treatment factor relative to the current disease type may be modifying the code of the current diagnosis and treatment factor with different identifications, and using the modified code as the code to be selected corresponding to the current diagnosis and treatment factor relative to the current disease type, so that the current diagnosis and treatment factor and the current disease type are stored in a database in an associated manner. Before adjusting the access path corresponding to the current diagnosis and treatment factor, judging whether the access path of the current diagnosis and treatment factor can correctly acquire diagnosis and treatment parameters corresponding to the current diagnosis and treatment factor. If the diagnosis and treatment parameters corresponding to the current diagnosis and treatment factors can be successfully obtained, not adjusting the access path corresponding to the current diagnosis and treatment factors, and taking the current access path as the to-be-selected access path corresponding to the current diagnosis and treatment factors relative to the current disease types. If the diagnosis and treatment parameters corresponding to the current diagnosis and treatment factors cannot be successfully obtained, setting an access path corresponding to the current diagnosis and treatment factors, taking the adjusted access path as a to-be-selected access path corresponding to the current diagnosis and treatment factors relative to the current disease type, and setting corresponding to-be-selected codes and to-be-selected access paths according to the to-be-selected diagnosis and treatment factors as shown in a schematic diagram of the to-be-selected diagnosis and treatment factors in FIG. 4.
Optionally, establishing a corresponding relation among the current diagnosis and treatment factors, the to-be-selected access path and the to-be-selected codes, and taking the current diagnosis and treatment factors as to-be-selected diagnosis and treatment factors corresponding to the current disease type in the target database.
Specifically, an association relationship among the current diagnosis and treatment factors, the to-be-selected access paths corresponding to the current diagnosis and treatment factors and the to-be-selected codes corresponding to the current diagnosis and treatment factors is established according to the current disease type, for example, the association relationship is correspondingly stored in a preset storage position of the current disease type.
Optionally, the diagnosis and treatment factors to be selected are stored in a variable library in the target database, the codes to be selected and the access paths to be selected corresponding to the diagnosis and treatment factors to be selected are stored in the access paths of a rule library in the target database, so that the diagnosis and treatment factors corresponding to the target disease types are called from the variable library, and diagnosis and treatment parameters corresponding to the diagnosis and treatment factors are obtained from the access paths of the rule library.
In the embodiment of the invention, the variable database is a database which is preset in the target database and stores diagnosis and treatment factors to be selected. The rule base is a database which is preset in the target database and stores the codes to be selected and the paths to be selected corresponding to the diagnosis and treatment factors to be selected.
Specifically, the current diagnosis and treatment factors, the codes to be selected and the access paths to be selected corresponding to the current diagnosis and treatment factors are stored in preset positions in a target database, so that the diagnosis and treatment factors corresponding to the target disease types are called from a variable library, and diagnosis and treatment parameters corresponding to the diagnosis and treatment factors are obtained from the access paths of a rule library.
S220, acquiring a target disease type in a target medical record template, and calling at least one target diagnosis and treatment factor corresponding to the target disease type from a pre-established target database.
S230, respectively calling the target diagnosis and treatment parameters of each target diagnosis and treatment factor according to the fetch path corresponding to at least one target diagnosis and treatment factor.
S240, importing each target diagnosis and treatment parameter into a content editing control corresponding to the corresponding target diagnosis and treatment factor, and generating a medical record evaluation table corresponding to the target disease type.
According to the technical scheme, at least one diagnosis and treatment factor to be selected which is associated with each disease type in a target database is established; acquiring a target disease type in a target medical record template, and calling at least one target diagnosis and treatment factor corresponding to the target disease type from a pre-established target database; respectively calling the target diagnosis and treatment parameters of each target diagnosis and treatment factor according to the fetch path corresponding to at least one target diagnosis and treatment factor; each target diagnosis and treatment parameter is imported into a content editing control corresponding to the corresponding target diagnosis and treatment factor to generate a medical record evaluation table corresponding to the target disease type, so that the problem that the path of a clinician for solving the problem is not obviously shortened in the method for determining the disease type corresponding to the medical record list in the prior art is solved, the medical record evaluation table is flexibly generated by configuring the target diagnosis and treatment factor, and the working efficiency of the doctor is greatly improved.
Example III
This embodiment may be an alternative embodiment based on the foregoing embodiments, where explanations of terms that are the same as or corresponding to the foregoing embodiments are not repeated herein. The method for generating the disease type evaluation table provided by the embodiment comprises the following steps:
when the input target diagnosis and treatment factors corresponding to the target disease type are detected, at least one target diagnosis and treatment factor is acquired from each diagnosis and treatment factor stored in the preset position in the target database, and when the target diagnosis and treatment factors associated with the target disease type are included in the database, the target diagnosis and treatment factors associated with the target disease type are selected as shown in a schematic diagram of the target diagnosis and treatment factor association in fig. 5.
When the database does not include the target diagnosis and treatment factors related to the target disease type, specifically, as shown in the schematic diagram of the establishment of the diagnosis and treatment factors to be selected in fig. 4, the target diagnosis and treatment factors are established, corresponding codes to be selected and paths to be selected are set, the type of the target diagnosis and treatment factors are selected, the rule conditions of the current target diagnosis and treatment factors are set according to online experience, and the rule conditions are stored in the preset position in the target database after the establishment of the target diagnosis and treatment factors is completed.
And generating a medical record evaluation table corresponding to the target disease type according to each target diagnosis and treatment factor associated with the target disease type and the target diagnosis and treatment parameter corresponding to each diagnosis and treatment factor. Specifically, as shown in fig. 6, if the target diagnosis and treatment factors in the current medical record evaluation table are consistent with other diagnosis and treatment factors in other medical record evaluation tables, the generated list schematic diagram of each medical record evaluation table is related to the medical record evaluation table corresponding to the other diagnosis and treatment factors in the current medical record evaluation table.
According to the technical scheme, the target disease type in the target medical record template is obtained, and at least one target diagnosis and treatment factor corresponding to the target disease type is called from a pre-established target database; respectively calling the target diagnosis and treatment parameters of each target diagnosis and treatment factor according to the fetch path corresponding to the at least one target diagnosis and treatment factor; each target diagnosis and treatment parameter is imported into a content editing control corresponding to the corresponding target diagnosis and treatment factor to generate a medical record evaluation table corresponding to the target disease type, so that the problem that the path of a clinician for solving the problem is not obviously shortened in the method for determining the disease type corresponding to the medical record list in the prior art is solved, the medical record evaluation table is flexibly generated by configuring the target diagnosis and treatment factor, and the working efficiency of the doctor is greatly improved.
Example IV
As an alternative embodiment of the foregoing embodiment, after determining the medical record evaluation table, the server may acquire contents in the medical record evaluation table, generate corresponding target rule conditions according to the target diagnosis and treatment factors in the evaluation table, determine at least one recommended treatment plan and an interception treatment plan including the target rule conditions from the rule base based on the generated target rule conditions, and determine a target recommended treatment plan according to the names of agents in the recommended treatment plan and the interception treatment plan, and specific embodiments thereof may be referred to as follows. Wherein, the technical terms identical to or corresponding to the above embodiments are not repeated herein.
The method of the embodiment provided by the embodiment specifically includes:
obtaining information of each disease in the medical record evaluation table and a target name of the disease; retrieving at least one target rule comprising the information of each disease from a pre-established rule base according to the target name; the rule base comprises rules corresponding to various disease names, and each disease name comprises at least one rule; the recommended treatment scheme and the interception treatment scheme corresponding to each target rule are called, and attribute information of the names of the medicines to be used in each recommended treatment scheme is obtained; determining a target recommended treatment scheme and a recommended copy corresponding to the target recommended treatment scheme according to the names of the medicaments to be removed, the names of the medicaments to be used and the attribute information of the names of the medicaments to be used in the interception treatment scheme; the recommendation copies include recommendation analysis.
The medical record evaluation table can comprise collected disease information and target names of diseases. The condition information may be information related to disease symptoms, such as: basic information, inspection information, past history, and the like. The target name of the disease corresponds to the disease type and may be a disease name.
The rule base has a certain difference with the rule base, the difference is mainly that the rule base is a rule base for storing the access paths, the rule base is a rule base for storing the rule conditions,
the rule base may be determined based on a priori knowledge recorded in a plurality of books and medical record information of a plurality of validated treatment protocols. The rule base may include rules corresponding to various disease names, each including at least one rule. The target rule is a rule determined in a rule base according to each disorder information. The recommended treatment plan and the interception treatment plan are pre-stored in a rule base, correspond to each rule, and may be one or more. The recommended treatment scheme is a treatment scheme for treating the symptoms corresponding to the scheme, the interception treatment scheme is a treatment scheme which cannot be used when treating the corresponding symptoms, and the interception treatment scheme can also be determined according to basic information.
Specifically, the text information in each content editing control in the medical record evaluation list is extracted by keywords, and the extracted keywords are respectively combined, so that the treatment condition for recommending the treatment scheme can be obtained. Further, according to the target name, a rule corresponding to the target name may be determined from a rule base established in advance. Among the rules corresponding to the target names, a rule including the treatment condition information is taken as a target rule. The determining of the at least one target rule may be to take a rule in the rule base containing the treatment condition as the at least one target rule if the rule in the rule base corresponding to the target name contains the treatment condition.
Since the corresponding treatment conditions generated from the keyword combination are at least one, and the corresponding rule determined in the library according to each treatment condition may be plural, at least one target rule may be determined from the rule library. To save time in determining at least one target rule in the rule base, the determination may be determined in parallel from a plurality of treatment conditions.
Specifically, according to each target rule, a recommended treatment scheme and an interception treatment scheme corresponding to the target rule can be determined in the rule base, each medicament name in the recommended treatment scheme is used as a medicament name to be used, and then attribute information corresponding to each medicament name to be used is determined.
Specifically, according to the names of the medicines to be removed and the names of the medicines to be used in the interception treatment scheme, the names of the medicines to be removed in the names of the medicines to be used can be removed, so that adverse effects on diseases of patients can be avoided when the medicines are used. Further, agents whose pharmacological actions are mutually enhanced can be retained according to attribute information of the names of the respective agents to be used, so as to enhance the efficacy. Agents whose pharmacological actions are mutually impaired or repelled may also be retained one to avoid interactions between agents affecting the therapeutic effect.
For a more accurate determination of the target recommended treatment and the recommended copy corresponding to the target recommended treatment, the following steps may be referred to:
step one, acquiring the names of the medicines to be used in each recommended treatment scheme, combining the same names of the medicines to be used to obtain the names of the medicines to be screened, and removing the names of the medicines to be removed from the names of the medicines to be screened to obtain the names of the target medicines to be determined. The medicament name to be screened is a medicament name obtained by combining the same medicaments in the medicaments to be used, and the target medicament name to be determined is a medicament name obtained by removing the medicaments to be removed from the medicaments to be screened.
Specifically, since there may be a case where the names of the medicines to be used in the recommended treatment schemes obtained according to different target rules are the same, the same names of the medicines to be used may be combined to reduce the existence of redundant medicine names. And taking the combined medicament names to be used as medicament names to be screened, further removing the medicament names to be removed from the medicament names to be screened, and determining the rest medicament names as target medicament names to be determined.
And step two, acquiring attribute information of each target medicament name to be determined, and determining the target medicament name according to the attribute information.
The target medicament name is a medicament name which is further screened and determined according to the pharmacological information of each target medicament to be determined, and the pharmacological information can be the medicament name with the same medicament efficacy, or can be the medicament name with the medicament with the efficacy mutually enhanced, mutually weakened or mutually exclusive.
Specifically, attribute information of each target medicament name to be determined is obtained, wherein the attribute information can comprise medicament efficacy and pharmacological actions, one of medicament names with the same efficacy in the target medicament names to be determined can be reserved, all medicament names with mutually enhanced efficacy can be reserved, and medicaments with mutual rejection or mutual weakening in the target medicament names to be determined can be processed to reserve one of the medicament names. The medicine name determined after the above-described processing is taken as the target medicine name.
In order to determine the target medicament names more accurately according to the attribute information, medicament components, medicament functions and tabu information of each target medicament name to be determined can be obtained, and at least two medicament names to be selected with conflicting medicament components are screened out according to the medicament components, the medicament functions and the tabu information of each target medicament name to be determined, and at least two medicament names to be reserved with the same medicament functions are screened out; one to-be-selected-agent name and to-be-reserved-agent name are reserved from at least two to-be-selected-agent names and at least two to-be-reserved-agent names.
The medicine components can be information such as names and proportions of various medicinal materials composing the medicine, the medicine functions are types of diseases which can be treated by the medicine, and the tabu information is medicine components which conflict with the medicine components.
Specifically, the medicament components, medicament functions and tabu information in attribute information corresponding to the target medicament names to be determined are obtained, medicament names with conflicting medicament components are determined in all the target medicament names to be determined according to the medicament components, medicament functions and tabu information of the target medicament names to be determined, and the medicament names are used as a group of medicament names to be selected, wherein each group of medicament names to be selected comprises at least two medicament names to be selected. And the medicament names with the same medicament functions are used as a group of medicament names to be reserved, and each group of medicament names to be reserved comprises at least two medicament names to be reserved. Further, in each group of the to-be-selected medicament names and the to-be-reserved medicament names, one to-be-selected medicament name and one to-be-reserved medicament name are reserved so as to eliminate medicament names with the same functions and medicament names with conflicting medicament components.
Generating a target recommended treatment scheme based on the target medicament name, and taking recommendation analysis corresponding to the target recommended treatment scheme as content in a recommendation copy; and analyzing the content in the recommended copy by interception corresponding to the interception treatment scheme.
Specifically, the target agents may be combined to generate the target recommended treatment plan based on the target agents, and the target agents may be determined from extraction from the rule base to determination as to the analysis process of the target agents, and the analysis process of the target agents may be used as a recommendation analysis corresponding to the target recommended treatment plan, so that the physician may clearly understand the cause of recommending the target agents, and the recommendation analysis may be used as the content in the recommendation copy. For a target recommended treatment regimen, the intercept analysis corresponding to the intercept treatment regimen may be taken as content in the recommended copy to enable the physician to learn why certain medications were not used.
And step four, feeding back the target recommended treatment scheme and recommended copy to the target terminal equipment.
The target terminal device may be a terminal device used by a doctor in diagnosis and treatment, and may be a fixed terminal or a mobile terminal.
Specifically, in order to enable the physician to obtain the target recommended treatment plan and the recommended copy to provide the patient with an appropriate treatment plan, the generated target recommended treatment plan and recommended copy may be fed back to the target terminal device. When a physician reads the target recommended treatment regimen and the recommended copy, the physician can learn why the treatment regimen was recommended and why other treatment regimens were not recommended to provide assistance to the physician.
Optionally, when the operation of triggering the recommended copy is detected, a recommended analysis process corresponding to the target recommended treatment scheme and an interception analysis corresponding to the interception treatment scheme are displayed on a display interface of the target terminal device.
Specifically, the target recommended treatment scheme may be displayed on a display interface of the target terminal device, and a display control corresponding to the target recommended treatment scheme exists on the display interface, when the display control is triggered, an operation of a recommended copy is triggered, and a recommended analysis process and an interception analysis process in the recommended copy are displayed on the display interface of the target terminal device for a doctor to review.
According to the technical scheme, the target disease type in the target medical record template is obtained, and at least one target diagnosis and treatment factor corresponding to the target disease type is called from a pre-established target database; respectively calling the target diagnosis and treatment parameters of each target diagnosis and treatment factor according to the fetch path corresponding to the at least one target diagnosis and treatment factor; the method comprises the steps of importing each target diagnosis and treatment parameter into a content editing control corresponding to a corresponding target diagnosis and treatment factor to generate a medical record evaluation table corresponding to the target disease type, after the medical record evaluation table is determined, obtaining the content in the medical record evaluation table by a server, generating corresponding target rule conditions according to the target diagnosis and treatment factors in the evaluation table, determining at least one recommended treatment scheme and interception treatment scheme comprising the target rule conditions from a rule base based on the generated target rule conditions, and determining a target recommended treatment scheme according to the recommended treatment scheme and medicament names in the interception treatment scheme, thereby solving the problem that the path of a clinician for solving the problem in the method for determining the disease type corresponding to the medical record list in the prior art is not obviously shortened, realizing flexible generation of the medical record evaluation table by configuring the target diagnosis and treatment factors, flexible modification of the evaluation rules, and fast and efficient recommendation of the treatment scheme matched with the medical record evaluation table for a user, and greatly improving the working efficiency of a doctor.
The following is an embodiment of a disease type evaluation table generation device provided by the embodiment of the present invention, which belongs to the same inventive concept as the disease type evaluation table generation method of the above embodiments, and details which are not described in detail in the embodiment of the disease type evaluation table generation device may refer to the embodiment of the disease type evaluation table generation method.
Example five
Fig. 7 is a schematic structural diagram of a device for generating a disease type evaluation table according to a fifth embodiment of the present invention, where the present embodiment is applicable to a situation where a physician generates a disease type evaluation table according to a target medical record template. The specific structure of the disease type evaluation table generation device comprises: a target diagnosis and treatment factor acquisition module 310, a target diagnosis and treatment parameter acquisition module 320 and a medical record evaluation table generation module 330. Wherein:
the target diagnosis and treatment factor obtaining module 310 is configured to obtain a target disease type in the target medical record template, and retrieve at least one target diagnosis and treatment factor corresponding to the target disease type from a pre-established target database.
The target diagnosis and treatment parameter obtaining module 320 is configured to respectively call the target diagnosis and treatment parameters of each target diagnosis and treatment factor according to the access path corresponding to at least one target diagnosis and treatment factor.
The medical record evaluation table generating module 330 is configured to import each target diagnosis and treatment parameter into a content editing control corresponding to a corresponding target diagnosis and treatment factor, and generate a medical record evaluation table corresponding to a target disease type.
According to the technical scheme, the target disease type in the target medical record template is obtained, and at least one target diagnosis and treatment factor corresponding to the target disease type is called from a pre-established target database; respectively calling the target diagnosis and treatment parameters of each target diagnosis and treatment factor according to the fetch path corresponding to at least one target diagnosis and treatment factor; each target diagnosis and treatment parameter is imported into a content editing control corresponding to the corresponding target diagnosis and treatment factor to generate a medical record evaluation table corresponding to the target disease type, so that the problem that the path of a clinician for solving the problem is not obviously shortened in the method for determining the disease type corresponding to the medical record list in the prior art is solved, the medical record evaluation table is flexibly generated by configuring the target diagnosis and treatment factor, the evaluation rule is flexibly modified, and the working efficiency of the doctor is greatly improved.
Based on the above technical solution, the target diagnosis and treatment factor obtaining module 310 includes:
And the target code determining unit is used for determining at least one target code bound with the target disease type according to the target disease type.
And the target diagnosis and treatment factor determining unit is used for retrieving the target diagnosis and treatment factor corresponding to at least one target code from the target database.
Based on the above technical solution, the target diagnosis and treatment parameter obtaining module 320 includes:
the target diagnosis and treatment parameter acquisition unit is used for determining a current access path associated with the current target diagnosis and treatment factors and calling target diagnosis and treatment parameters corresponding to the user basic information according to the current access path and the user basic information in the target medical record template.
On the basis of the technical scheme, the device further comprises:
the diagnosis and treatment factors to be selected building module is used for building at least one diagnosis and treatment factor to be selected which is associated with each disease type in the target database, so that when the medical record evaluation table corresponding to the target disease type is generated, the medical record evaluation table corresponding to the target disease type is called from the target database.
On the basis of the technical scheme, the diagnosis and treatment factor establishment module to be selected comprises:
the diagnosis and treatment factor determining submodule is used for judging whether the target database comprises the current diagnosis and treatment factors or not according to various disease types if the current diagnosis and treatment factors corresponding to the current disease types are detected to be input;
And the diagnosis and treatment factor to be selected generation sub-module is used for generating diagnosis and treatment factors to be selected which are associated with the current disease type according to the judgment result and the current diagnosis and treatment factors.
On the basis of the technical scheme, the diagnosis and treatment factor generation sub-module to be selected comprises:
the adjusting unit is used for selecting the current diagnosis and treatment factor if the target database comprises the current diagnosis and treatment factor, and adjusting the code to be selected and the path to be selected corresponding to the current diagnosis and treatment factor relative to the current disease type.
The setting unit is used for customizing the current diagnosis and treatment factors if the target database does not contain the current diagnosis and treatment factors, and setting a to-be-selected access path and a to-be-selected code corresponding to the current diagnosis and treatment factors.
The diagnosis and treatment factor to be selected generating unit is used for establishing a corresponding relation among the current diagnosis and treatment factors, the path to be selected and the code to be selected, and taking the current diagnosis and treatment factors as the diagnosis and treatment factors to be selected corresponding to the current disease type in the target database.
On the basis of the above technical solution, the diagnosis and treatment factor generating unit to be selected includes:
the storage subunit is used for storing the diagnosis and treatment factors to be selected into a variable library in the target database, storing codes to be selected and access paths to be selected corresponding to the diagnosis and treatment factors to be selected into access paths of a rule library in the target database, so as to call the diagnosis and treatment factors corresponding to the target disease types from the variable library, and acquiring diagnosis and treatment parameters corresponding to the diagnosis and treatment factors from the access paths of the rule library.
The generation device of the disease type evaluation table provided by the embodiment of the invention can execute the generation method of the disease type evaluation table provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.
It should be noted that, in the embodiment of the disease type evaluation table generating apparatus, each unit and module included are only divided according to the functional logic, but not limited to the above-mentioned division, so long as the corresponding functions can be implemented; in addition, the specific names of the functional units are also only for distinguishing from each other, and are not used to limit the protection scope of the present invention.
Example six
Fig. 8 is a schematic structural diagram of an electronic device according to a sixth embodiment of the present invention. Fig. 8 illustrates a block diagram of an exemplary electronic device 12 suitable for use in implementing embodiments of the present invention. The electronic device 12 shown in fig. 8 is merely an example and should not be construed as limiting the functionality and scope of use of embodiments of the present invention.
As shown in fig. 8, the electronic device 12 is in the form of a general purpose computing electronic device. Components of the electronic device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, a bus 18 that connects the various system components, including the system memory 28 and the processing units 16.
Bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, and a local bus using any of a variety of bus architectures. By way of example, and not limitation, such architectures include Industry Standard Architecture (ISA) bus, micro channel architecture (MAC) bus, enhanced ISA bus, video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.
Electronic device 12 typically includes a variety of computer system readable media. Such media can be any available media that is accessible by electronic device 12 and includes both volatile and nonvolatile media, removable and non-removable media.
The system memory 28 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM) 30 and/or cache memory 32. The electronic device 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from or write to non-removable, nonvolatile magnetic media (not shown in FIG. 8, commonly referred to as a "hard disk drive"). Although not shown in fig. 8, a magnetic disk drive for reading from and writing to a removable non-volatile magnetic disk (e.g., a "floppy disk"), and an optical disk drive for reading from or writing to a removable non-volatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In such cases, each drive may be coupled to bus 18 through one or more data medium interfaces. The system memory 28 may include at least one program product having a set (e.g., at least one) of program modules configured to carry out the functions of the embodiments of the invention.
A program/utility 40 having a set (at least one) of program modules 42 may be stored in, for example, system memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment. Program modules 42 generally perform the functions and/or methods of the embodiments described herein.
The electronic device 12 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), one or more devices that enable a user to interact with the electronic device 12, and/or any devices (e.g., network card, modem, etc.) that enable the electronic device 12 to communicate with one or more other computing devices. Such communication may occur through an input/output (I/O) interface 22. Also, the electronic device 12 may communicate with one or more networks such as a Local Area Network (LAN), a Wide Area Network (WAN) and/or a public network, such as the Internet, through a network adapter 20. As shown in fig. 8, the network adapter 20 communicates with other modules of the electronic device 12 over the bus 18. It should be appreciated that although not shown in fig. 8, other hardware and/or software modules may be used in connection with electronic device 12, including, but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, data backup storage systems, and the like.
The processing unit 16 executes various functional applications and sample data acquisition by running a program stored in the system memory 28, for example, implementing the steps of a method for generating a disease type evaluation table provided in the present embodiment, the method for generating a disease type evaluation table includes:
acquiring a target disease type in a target medical record template, and calling at least one target diagnosis and treatment factor corresponding to the target disease type from a pre-established target database;
respectively calling the target diagnosis and treatment parameters of each target diagnosis and treatment factor according to the fetch path corresponding to at least one target diagnosis and treatment factor;
and importing each target diagnosis and treatment parameter into a content editing control corresponding to the corresponding target diagnosis and treatment factor, and generating a medical record evaluation table corresponding to the target disease type.
Of course, those skilled in the art will appreciate that the processor may also implement the technical solution of the sample data obtaining method provided in any embodiment of the present invention.
Example seven
The seventh embodiment provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements, for example, the steps of a method for generating a disease type evaluation table provided by the embodiment, the method for generating a disease type evaluation table including:
Acquiring a target disease type in a target medical record template, and calling at least one target diagnosis and treatment factor corresponding to the target disease type from a pre-established target database;
respectively calling the target diagnosis and treatment parameters of each target diagnosis and treatment factor according to the fetch path corresponding to at least one target diagnosis and treatment factor;
and importing each target diagnosis and treatment parameter into a content editing control corresponding to the corresponding target diagnosis and treatment factor, and generating a medical record evaluation table corresponding to the target disease type.
The computer storage media of embodiments of the invention may take the form of any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium may be, for example, but not limited to: an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, either in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).
It will be appreciated by those of ordinary skill in the art that the modules or steps of the invention described above may be implemented in a general purpose computing device, they may be centralized on a single computing device, or distributed over a network of computing devices, or they may alternatively be implemented in program code executable by a computer device, such that they are stored in a memory device and executed by the computing device, or they may be separately fabricated as individual integrated circuit modules, or multiple modules or steps within them may be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.
Note that the above is only a preferred embodiment of the present invention and the technical principle applied. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, while the invention has been described in connection with the above embodiments, the invention is not limited to the embodiments, but may be embodied in many other equivalent forms without departing from the spirit or scope of the invention, which is set forth in the following claims.
Claims (7)
1. A method for generating a disease type evaluation table, comprising:
acquiring a target disease type in a target medical record template, and retrieving at least one target diagnosis and treatment factor corresponding to the target disease type from a pre-established target database, wherein the target diagnosis and treatment factor is at least one diagnosis and treatment factor associated with the target disease type;
respectively calling the target diagnosis and treatment parameters of each target diagnosis and treatment factor according to the fetch path corresponding to the at least one target diagnosis and treatment factor;
importing each target diagnosis and treatment parameter into a content editing control corresponding to a corresponding target diagnosis and treatment factor, and generating a medical record evaluation table corresponding to the target disease type;
for each disease type, if the input of the current diagnosis and treatment factor corresponding to the current disease type is detected, judging whether the current diagnosis and treatment factor is included in the target database;
if the target database comprises the current diagnosis and treatment factors, selecting the current diagnosis and treatment factors, and adjusting the current diagnosis and treatment factors relative to codes to be selected and the number taking paths to be selected corresponding to the current disease types; or alternatively, the first and second heat exchangers may be,
If the target database does not contain the current diagnosis and treatment factors, customizing the current diagnosis and treatment factors, and setting a to-be-selected access path and a to-be-selected code corresponding to the current diagnosis and treatment factors;
establishing a corresponding relation among the current diagnosis and treatment factors, the to-be-selected access path and the to-be-selected codes, and taking the current diagnosis and treatment factors as to-be-selected diagnosis and treatment factors corresponding to the current disease type in the target database;
when a medical record evaluation list corresponding to a target disease type is generated, retrieving the medical record evaluation list corresponding to the target disease type from the target database.
2. The method of claim 1, wherein retrieving at least one target diagnostic factor corresponding to a target disease type from a pre-established target database comprises:
determining at least one target code bound to the target disease type according to the target disease type;
and retrieving a target diagnosis and treatment factor corresponding to the at least one target code from the target database.
3. The method of claim 1, wherein the separately retrieving the target diagnostic parameters of each target diagnostic factor according to the retrieval path corresponding to the at least one target diagnostic factor comprises:
And determining a current access path associated with the current target diagnosis and treatment factors according to the target diagnosis and treatment factors, and calling target diagnosis and treatment parameters corresponding to the user basic information according to the current access path and the user basic information in the target medical record template.
4. The method according to claim 1, wherein said taking the current medical factor as a to-be-selected medical factor corresponding to the current disease type in the target database comprises:
storing the diagnosis and treatment factors to be selected into a variable library in the target database, storing codes to be selected and access paths to be selected corresponding to the diagnosis and treatment factors to be selected into access paths of a rule library in the target database, so as to call the diagnosis and treatment factors corresponding to the target disease types from the variable library, and obtaining diagnosis and treatment parameters corresponding to the diagnosis and treatment factors from the access paths of the rule library.
5. A disease type evaluation table generating apparatus, comprising:
the target diagnosis and treatment factor acquisition module is used for acquiring a target disease type in a target medical record template, and invoking at least one target diagnosis and treatment factor corresponding to the target disease type from a pre-established target database, wherein the target diagnosis and treatment factor is at least one diagnosis and treatment factor associated with the target disease type;
The target diagnosis and treatment parameter acquisition module is used for respectively calling the target diagnosis and treatment parameters of each target diagnosis and treatment factor according to the fetch path corresponding to the at least one target diagnosis and treatment factor;
the medical record evaluation table generation module is used for importing each target diagnosis and treatment parameter into a content editing control corresponding to the corresponding target diagnosis and treatment factor to generate a medical record evaluation table corresponding to the target disease type;
the diagnosis and treatment factor determining module is used for judging whether the target database comprises the current diagnosis and treatment factors or not according to the types of the diseases if the current diagnosis and treatment factors corresponding to the current types of the diseases are detected to be input;
the adjusting module is used for selecting the current diagnosis and treatment factor if the target database comprises the current diagnosis and treatment factor, and adjusting the code to be selected and the number taking path to be selected corresponding to the current diagnosis and treatment factor relative to the current disease type;
the setting module is used for customizing the current diagnosis and treatment factors if the target database does not contain the current diagnosis and treatment factors, and setting a to-be-selected access path and a to-be-selected code corresponding to the current diagnosis and treatment factors;
the diagnosis and treatment factor to be selected generation module is used for establishing a corresponding relation among the current diagnosis and treatment factors, the path of the number to be selected and the codes to be selected, and taking the current diagnosis and treatment factors as the diagnosis and treatment factors to be selected corresponding to the current disease type in the target database;
And the medical record evaluation table retrieving module is used for retrieving the medical record evaluation table corresponding to the target disease type from the target database when the medical record evaluation table corresponding to the target disease type is generated.
6. An electronic device, comprising:
one or more processors;
storage means for storing one or more programs,
when the one or more programs are executed by the one or more processors, the one or more processors are caused to implement the method of generating a disease seed assessment table according to any one of claims 1-4.
7. A computer-readable storage medium, on which a computer program is stored, characterized in that the program, when executed by a processor, implements a method of generating a disease seed assessment table according to any one of claims 1-4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011351134.XA CN112331355B (en) | 2020-11-26 | 2020-11-26 | Disease type evaluation table generation method and device, electronic equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011351134.XA CN112331355B (en) | 2020-11-26 | 2020-11-26 | Disease type evaluation table generation method and device, electronic equipment and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112331355A CN112331355A (en) | 2021-02-05 |
| CN112331355B true CN112331355B (en) | 2024-03-19 |
Family
ID=74308973
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011351134.XA Active CN112331355B (en) | 2020-11-26 | 2020-11-26 | Disease type evaluation table generation method and device, electronic equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112331355B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114580367B (en) * | 2022-03-11 | 2023-01-20 | 上海柯林布瑞信息技术有限公司 | Clinical business rule template generation method and device |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103605760A (en) * | 2013-11-25 | 2014-02-26 | 方正国际软件有限公司 | Medical record query method and medical record query system |
| CN104166667A (en) * | 2013-05-17 | 2014-11-26 | 株式会社日立制作所 | Analysis system and health business support method |
| CN106874643A (en) * | 2016-12-27 | 2017-06-20 | 中国科学院自动化研究所 | Build the method and system that knowledge base realizes assisting in diagnosis and treatment automatically based on term vector |
| CN110070925A (en) * | 2019-03-11 | 2019-07-30 | 张宏家 | A kind of generation method of electronic health record, device and electronic equipment |
| CN110675924A (en) * | 2019-08-19 | 2020-01-10 | 医渡云（北京）技术有限公司 | Method and device for automatically generating case report table, readable medium and electronic equipment |
| CN111192691A (en) * | 2019-12-25 | 2020-05-22 | 南京医睿科技有限公司 | Method and device for determining medical evaluation table, readable medium and electronic equipment |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11562323B2 (en) * | 2009-10-01 | 2023-01-24 | DecisionQ Corporation | Application of bayesian networks to patient screening and treatment |
-
2020
- 2020-11-26 CN CN202011351134.XA patent/CN112331355B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104166667A (en) * | 2013-05-17 | 2014-11-26 | 株式会社日立制作所 | Analysis system and health business support method |
| CN103605760A (en) * | 2013-11-25 | 2014-02-26 | 方正国际软件有限公司 | Medical record query method and medical record query system |
| CN106874643A (en) * | 2016-12-27 | 2017-06-20 | 中国科学院自动化研究所 | Build the method and system that knowledge base realizes assisting in diagnosis and treatment automatically based on term vector |
| CN110070925A (en) * | 2019-03-11 | 2019-07-30 | 张宏家 | A kind of generation method of electronic health record, device and electronic equipment |
| CN110675924A (en) * | 2019-08-19 | 2020-01-10 | 医渡云（北京）技术有限公司 | Method and device for automatically generating case report table, readable medium and electronic equipment |
| CN111192691A (en) * | 2019-12-25 | 2020-05-22 | 南京医睿科技有限公司 | Method and device for determining medical evaluation table, readable medium and electronic equipment |
Non-Patent Citations (3)
| Title |
|---|
| 慢性病赋能量表的汉化及在社区中老年慢性病患者中的信效度分析;李璇;Nicola Small;王晓艳;曹阳;刘宴伟;雷清梅;朱亚芳;彭娟;周宏珍;;中国全科医学(10);全文 * |
| 电子病历临床决策系统在住院诊疗过程中的应用效果;郑金龙;穆大力;李晓东;解芳;李昊;宫辉;曹永斌;朱潇;连九峥;王越;福华东;党军红;强京红;;中国病案(05);全文 * |
| 超声造影联合血管生成相关因子对乳腺病变微血管生成的评价;魏玺;李莹;朱鹰;张晟;;中华临床医师杂志(电子版)(01);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112331355A (en) | 2021-02-05 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| JP7010946B2 (en) | Systems and methods that facilitate computational analysis of health status | |
| RU2662205C2 (en) | Extension of clinical guidelines based on clinical expert recommendations | |
| JP2002511159A (en) | Computerized medical diagnosis system using list-based processing | |
| CN112331298A (en) | Method and device for issuing prescription, electronic equipment and storage medium | |
| US20120053957A1 (en) | Tool for detecting inconsistencies and omissions in documented justification for medical services | |
| CN110689939A (en) | Recommendation method and device for medication sequence, readable medium and electronic equipment | |
| EP3895180A1 (en) | Providing personalized health care information and treatment recommendations | |
| CN114613523A (en) | Doctor allocation method, device, storage medium and equipment for on-line medical inquiry | |
| US20170364640A1 (en) | Machine learning algorithm to automate healthcare communications using nlg | |
| CN111863243A (en) | Method and device for pre-inquiry of pharmacy, storage medium and electronic equipment | |
| JP2018194926A (en) | Diagnostic information management system | |
| CN112447270A (en) | Medication recommendation method, device, equipment and storage medium | |
| CN112331355B (en) | Disease type evaluation table generation method and device, electronic equipment and storage medium | |
| CN114330272A (en) | Medical record template generation method and device, electronic equipment and storage medium | |
| CN112309587A (en) | On-line inquiry method, system, server and storage medium | |
| CN112309579A (en) | Method and device for recommending treatment scheme, electronic equipment and storage medium | |
| CN116719926A (en) | Congenital heart disease report data screening method and system based on intelligent medical treatment | |
| US20150248527A1 (en) | Prompting medication safety technology | |
| JP2022512259A (en) | Systems and methods for guideline compliance | |
| JP2014199557A (en) | Medical examination support system | |
| JP5941217B2 (en) | Cleansing data management method and computer system | |
| CA3083090A1 (en) | Medical examination support apparatus, and operation method and operation program thereof | |
| CN112331356A (en) | Method and device for recommending treatment scheme, electronic equipment and storage medium | |
| CN114913956A (en) | Repeated medication reminding method and device based on knowledge graph and electronic equipment | |
| CN114678092A (en) | Nursing recording method, terminal, system and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |