CN115547444A - Osteoporosis fracture patient data reading method and system - Google Patents
Osteoporosis fracture patient data reading method and system Download PDFInfo
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Abstract
The invention provides a method and a system for reading data of a patient with osteoporosis and fracture, which relate to the technical field of management data processing, and the method comprises the following steps: connecting a user medical record management terminal to analyze user information, acquiring a read keyword set, and constructing a bone database; storing the bone database as a preliminary user clue set into a cloud processor; collecting regularly and outputting a bone data distribution library; obtaining a screening parameter matrix; inputting a high risk group identification model, and positioning users according to a bone data distribution library to obtain a positioning user set; and identifying the positioning user set, generating a high risk group list, and performing tracking management. The technical problem of the management inefficiency that medical treatment user data read leads to being difficult to carry out the high efficiency to osteoporosis fracture patient and aims at the diagnosis pursuit is solved, has reached and has utilized dual parameter location user, promotes medical data and reads efficiency, realizes accurate, high-efficient to carry out the localization tracking's to the patient technical effect.
Description
Technical Field
The invention relates to the technical field of management data processing, in particular to a method and a system for reading data of a patient with osteoporosis and fracture.
Background
Osteoporosis fracture patient is high because of skeleton fragility, osteoporosis fracture healing cycle is long, osteoporosis fracture patient data volume is big for the managerial efficiency that osteoporosis fracture patient's case history data read can't guarantee, and electronic medical record system's popularization provides new thinking for osteoporosis fracture patient case history data management, but, inevitable, it is high to have osteoporosis fracture patient data to call and read gained data redundancy, the problem that unable pertinence solution case history data managerial efficiency is low.
The technical problem that the management efficiency of reading medical user data is low, so that the targeted visit tracking of an osteoporosis and fracture patient is difficult to perform efficiently exists in the prior art.
Disclosure of Invention
The application provides a method and a system for reading data of an osteoporosis fracture patient, solves the technical problems that the management efficiency of medical user data reading is low, and the targeted visit tracking of the osteoporosis fracture patient is difficult to realize in a high-efficiency manner, achieves the purpose of positioning the user by utilizing dual parameters, improves the medical data reading efficiency, and realizes the technical effect of accurately and efficiently positioning and tracking the patient.
In view of the above problems, the present application provides a data reading method and system for osteoporotic fracture patients.
In a first aspect of the application, a method for reading data of a patient with osteoporosis fracture is provided, wherein the method is applied to a medical informatization management system, the system is in communication connection with a user medical record management terminal and a cloud processor, and the method includes: connecting the user medical record management terminal to analyze the user information to obtain a read keyword set; collecting data by using the read keyword set to construct a bone database; storing the bone database as a preliminary user clue set into the cloud processor, wherein the cloud processor comprises a periodic timing acquisition model; performing timing acquisition according to the periodic timing acquisition model in the cloud processor, and outputting a bone data distribution library; acquiring a screening parameter matrix, wherein the screening parameter matrix is a matrix formed by management screening parameters and/or medical parameters for identifying high-risk users; inputting the screening parameter matrix into a high risk group identification model, and positioning users according to the bone data distribution base embedded in the high risk group identification model to obtain a positioning user set; and identifying the positioning user set to generate a high risk group list, and performing tracking management by using the high risk group list.
In a second aspect of the application, there is provided a data reading system for patients with osteoporotic fracture, wherein the system comprises: the data analysis unit is used for connecting the user medical record management terminal to analyze the user information and obtain a read keyword set; the data acquisition unit is used for acquiring data by using the read keyword set to construct a bone database; the data storage unit is used for storing the bone database as a preliminary user clue set into a cloud processor, wherein the cloud processor comprises a periodic timing acquisition model; the timing acquisition unit is used for carrying out timing acquisition according to the periodic timing acquisition model in the cloud processor and outputting a bone data distribution base; the system comprises a parameter screening unit, a parameter selecting unit and a parameter selecting unit, wherein the parameter screening unit is used for acquiring a screening parameter matrix, and the screening parameter matrix is a matrix formed by management screening parameters and/or medical parameters for identifying high-risk users; the user positioning unit is used for carrying out user positioning according to the bone data distribution base embedded in the high risk group identification model and inputting the screening parameter matrix into the high risk group identification model, so as to obtain a positioning user set; and the tracking management unit is used for identifying the positioning user set, generating a high risk group list and carrying out tracking management on the high risk group list.
One or more technical solutions provided in the present application have at least the following technical effects or advantages:
because the user information is analyzed by the connected user medical record management terminal, a read keyword set is obtained; performing data acquisition by reading the keyword set to construct a bone database; storing the bone database as a preliminary user clue set into a cloud processor; performing timing acquisition according to a periodic timing acquisition model in the cloud processor, and outputting a bone data distribution library; obtaining a screening parameter matrix; inputting the screening parameter matrix into a high risk group identification model, and positioning users according to a bone data distribution base embedded in the high risk group identification model to obtain a positioning user set; and identifying the positioning user set to generate a high risk group list, and performing tracking management by using the high risk group list. According to the embodiment of the application, the technical effects of positioning the user by using dual parameters, improving the medical data reading efficiency and accurately and efficiently positioning and tracking the patient are achieved.
Drawings
FIG. 1 is a schematic flow chart of a data reading method for an osteoporotic fracture patient according to the present application;
FIG. 2 is a schematic flow chart of a method for reading data of an osteoporotic fracture patient according to the present application to obtain a set of positioning users;
FIG. 3 is a schematic diagram of a process for obtaining a screening parameter matrix according to the data reading method for patients with osteoporosis and fracture;
fig. 4 is a schematic structural diagram of a data reading system for patients with osteoporosis fracture.
Description of reference numerals: the system comprises a data analysis unit 11, a data acquisition unit 12, a data storage unit 13, a timing acquisition unit 14, a parameter screening unit 15, a user positioning unit 16 and a tracking management unit 17.
Detailed Description
The application provides a method and a system for reading data of an osteoporosis fracture patient, solves the technical problems that the management efficiency of medical user data reading is low, and the targeted visit tracking of the osteoporosis fracture patient is difficult to realize in a high-efficiency manner, achieves the purpose of positioning the user by utilizing dual parameters, improves the medical data reading efficiency, and realizes the technical effect of accurately and efficiently positioning and tracking the patient.
Example one
As shown in fig. 1, the present application provides a method for reading data of a patient with osteoporosis fracture, wherein the method is applied to a medical informatization management system, the system is in communication connection with a user medical record management terminal and a cloud processor, and the method includes:
step S100: connecting the user medical record management terminal to analyze the user information to obtain a read keyword set;
step S200: performing data acquisition by using the read keyword set to construct a bone database;
specifically, the user medical record management terminal is an information sending terminal and is used for recording and sending data information of a user side, a data mark retrieval engine is embedded in the data management terminal and can retrieve and read the data information recorded by the user side and perform keyword highlighting marking on the retrieved and read information, highlighting modes corresponding to the keyword highlighting marking include other highlighting modes such as thickening, adding a lower transverse line and the like, keywords corresponding to the keyword highlighting marking include but are not limited to bone density, bone fragility, trabecular bone, cortical bone and cancellous bone, correspondingly, elements of a read keyword set can be user bone density information, user bone fragility information, user trabecular bone information, user cortical bone information and user cancellous bone information, highlighting and marking are preferably verified by using the keywords, and technical support is provided for extracting and customizing analysis efficiency of the user information by setting the keywords.
Specifically, the elements in the read keyword set are used as mark information, data collection is sequentially performed in a storage unit of the medical information management system, specifically, the user fracture information in the read keyword set is used as a mark signal, highlighting is performed in the storage unit of the medical information management system, after the highlighting is completed, the bone fragility information of the user is used as a mark signal, the highlighting is performed in the storage unit of the medical information management system, after all the elements in the read keyword set are marked, data collection is performed, objects with highlight mark types not lower than half of the element types of the read keyword set in the collected highlight mark results (odd number is rounded up), it is simply that if the elements in the read keyword set are 5, the corresponding highlight mark types in the highlight mark results corresponding to the data collection objects in the read keyword set are not lower than 3, the data collection objects can be objects corresponding to the bone fragility information of the user, the trabecular bone trabecular information of the user and the bone quality information of the user, the data collection database is specifically described, the bone quality information collection information of the medical information collection database is provided, and the bone quality database is provided by the medical information collection database.
Step S300: storing the bone database as a preliminary user clue set into the cloud processor, wherein the cloud processor comprises a periodic timing acquisition model;
step S400: performing timing acquisition according to the periodic timing acquisition model in the cloud processor, and outputting a bone data distribution library;
specifically, the bone database is stored into the cloud processor as a preliminary user clue set through the communication connection between the cloud processor and a medical information management system, wherein the cloud processor comprises a periodic timing acquisition model, the elements of the preliminary user cue set are object cue information of the data acquisition object, the object clue information comprises object age information, object sex information, object height information, object weight information and other basic information, the object can be further screened by combining the preliminary user clue set with the user basic information in the user information, the combination with preset basic information can be limited, screening the object clue information, limiting the preset basic information to be customized by the related management user of the data reading system of the osteoporosis fracture patient, the preset basic information limit may include, but is not limited to, an age gap threshold, a height gap threshold, a weight gap threshold of the subject from the user, based on the preset basic information limit, performing user screening on the bone database, determining a preliminary user clue set, setting the preset basic information limit and preset acquisition frequency in the periodic timing acquisition model, storing the bone database as the preliminary user clue set to the input end of the periodic timing acquisition model in the cloud processor, performing data timing acquisition and screening, and providing a model basis for data processing, the bone database is screened, so that the adaptability of user information and screened data information is improved, the cloud processor comprises a periodic timing acquisition model, through the cloud processor, the data processing efficiency of the data reading system for the osteoporosis fracture patient can be effectively ensured.
Specifically, according to preset acquisition frequency set inside the periodic timing acquisition model in the cloud processor, timing acquisition is carried out, data information to be acquired is synchronously integrated, a bone data distribution base is output, the bone data distribution base is the output of the periodic timing acquisition model, the model basis of the periodic timing acquisition model is a data screening model, the data screening model is screened with the preset acquisition frequency through preset basic information limitation, screening parameters are obtained through multiple times of verification optimization, the data distribution condition of the bone data distribution base corresponds to the preset acquisition frequency, timing acquisition is carried out, the bone data distribution base is obtained, and data support is provided for subsequent data analysis.
Step S500: acquiring a screening parameter matrix, wherein the screening parameter matrix is a matrix formed by management screening parameters and/or medical parameters for identifying high-risk users;
specifically, a medical parameter data set is set, elements of the medical parameter data set include, but are not limited to, lumbar vertebra fracture medical parameters, hip fracture medical parameters, proximal humerus fracture medical parameters, and distal radius fracture medical parameters, the management screening parameters are action limitation management parameters of a user, the elements of the management screening parameters include, but are not limited to, user parameters of wheelchair assisted actions, user parameters of double-crutcher assisted actions, user parameters of single-crutcher assisted actions, and user parameters of fixed assisted actions (fixed through plaster and bandage), the identified high-risk users are users who are confirmed to be osteoporosis fracture patients, the screening parameter matrix is a matrix formed by the management screening parameters and/or medical parameters identifying high-risk users, data index mapping is performed based on parameter index types, a screening parameter matrix is obtained, a basis is provided for subsequent data processing through the screening parameter matrix, data screening is performed through matrix establishment, and support is provided for multidimensional data screening.
Step S600: inputting the screening parameter matrix into a high risk group identification model, and positioning users according to the bone data distribution library embedded in the high risk group identification model to obtain a positioning user set;
further, as shown in fig. 2, the embodiment of the present application further includes:
step S610: connecting the user medical record management terminal, and collecting a user fracture data sample set;
step S620: performing fracture data standardization on the fracture data sample set, performing fracture characteristic data annotation on high risk groups according to the standardized sample set, and outputting annotated fracture data;
step S630: generating a training data set according to the marked fracture data;
step S640: training a high risk group recognition model by taking the training data set as a reference mark, and building the high risk group recognition model;
step S650: and inputting the screening parameter matrix into the high risk group identification model to obtain the positioning user set.
Specifically, the high risk group identification model is a data identification matching model, the screening logic of the high risk group identification model is determined through the screening parameter matrix, the screening dimension of the high risk group identification model is consistent with the screening parameter matrix, the screening parameter matrix comprises screening parameter upper limits and screening parameter lower limits of multiple groups of screening parameters, the screening parameter matrix is input into the high risk group identification model, the screening parameter upper limits and the screening parameter lower limits of the multiple groups of screening parameters in the screening parameter matrix are extracted, and according to the bone data distribution library embedded in the high risk group identification model, user positioning is carried out, a positioning user set is obtained, and support is provided for ensuring accurate positioning and screening of users.
Further specifically, the medical information management system is in communication connection with a user medical record management terminal, data screening, extracting and collecting are performed after other disease types of the user medical record management terminal are ignored, a user fracture data sample set is collected and obtained, the data obtained by data extraction and collection is data information recorded by medical records related to fracture of a user, elements of the user fracture data sample set are fracture data of each user, fracture data are subjected to standardization processing through fracture data types, the fracture data sample set is subjected to fracture data standardization processing, the standardized sample set is a unified fracture data standard, fracture characteristic data labeling of high risk groups is performed according to the standardized sample set, fracture characteristic data labeling results are obtained, the fracture characteristic data labeling results are set as fracture labeling data, data output is performed from the user medical record management terminal and output to the medical information management system, the BP back propagation model is used as a training data set, the elements in the high risk group data set are sequentially input into the BP back propagation model for data labeling, the BP back propagation model is used as a training data set, and a high risk group identification precision identification index is set; and inputting the screening parameter matrix into the high risk group identification model, identifying and positioning the high risk group by a user, acquiring the positioning user set, and providing support for ensuring the identification and positioning accuracy of the high risk group by building the high risk group identification model.
Further, as shown in fig. 3, the embodiment of the present application further includes:
step S651: acquiring a preset high-risk index;
step S652: performing parameter combination analysis on the management screening parameters and the medical parameters according to the preset high-risk indexes, and determining a matrix distribution ratio, wherein the matrix distribution ratio is the ratio of the management screening parameters to the medical parameters in the screening parameter matrix;
step S653: determining the number of management screening parameters and the number of medical parameters according to the matrix distribution ratio;
step S654: and acquiring the screening parameter matrix based on the management screening parameter quantity and the medical parameter quantity.
Specifically, the preset high-risk index may include, but is not limited to, lumbar vertebra fracture medical parameters and wheelchair-assisted action user parameters, the preset high-risk index may be set in a user-defined manner in combination with a degree of limitation of free movement of a user, the preset high-risk index is set in a user-defined manner by a manager associated with the data reading system for the osteoporotic fracture patient, the preset high-risk index is obtained, a parameter combination analysis is performed on the management screening parameters and the medical parameters according to the preset high-risk index, the combination analysis simply refers to determining an occupation ratio of the management screening parameters and the medical parameters in a screening parameter matrix, combining the occupation ratio of the management screening parameters and the medical parameters, obtaining a matrix distribution occupation ratio, performing index reverse search in the matrix distribution occupation ratio, and determining the number of the management screening parameters and the number of the medical parameters, wherein the occupation ratio of the management screening parameters and the number of the medical parameters and the combination management screening parameters and the occupation ratio of the medical parameters have consistency; and acquiring the screening parameter matrix based on the number of the management screening parameters and the number of the medical parameters, so as to provide support for ensuring the index precision in the screening parameter matrix and ensure the integrity of the screening parameter matrix.
Further, the embodiment of the present application further includes:
step S654-1: connecting a user medical record management terminal, extracting management items of the user medical record information, and generating a management parameter screening library;
step S654-2: extracting and identifying keywords from medical areas in medical record information of a user to obtain a medical keyword identification result;
step S654-3: generating a medical parameter screening library according to the medical keyword recognition result;
step S654-4: and acquiring the screening parameter matrix according to the management parameter screening library and the medical parameter screening library.
Specifically, management items of user medical record information are extracted through communication connection between a medical information management system and a user medical record management terminal, the management items of the user medical record information include but are not limited to administration management information of medical advice of a user medical record and privacy management information of the user medical record, the administration management information of the medical advice of the user medical record mainly aims at administration management of components of allergic drugs, which are common and can be strong acid, strong base and certain components with strong irritation, the privacy management information of the user medical record includes but is not limited to user identity card information and user residence place information, the management items of the user medical record information are obtained, and a management parameter screening library is generated through the management items of the medical record information of the user; the medical area can be related medical categories such as a detection report and a diagnosis result in the medical record information of the user, the medical area in the medical record information of the user is extracted and keyword identification is carried out, a medical keyword identification result is obtained, the medical keyword identification result, namely the marking result is highlighted in the medical area in the medical record information of the user, the medical keyword identification result is taken as marking retrieval information, retrieval and extraction are carried out in the bone database, and a medical parameter screening library is generated; and performing parameter combination analysis on the management parameter screening library and the medical parameter screening library to obtain the screening parameter matrix, and providing basic support for ensuring the stability of the number of the management screening parameters and the number of the medical parameters through the management parameter screening library and the medical parameter screening library.
Step S700: and identifying the positioning user set to generate a high risk group list, and tracking and managing the high risk group list.
Further, tracking and managing the list of high risk people, wherein the step S700 further includes:
step S710: acquiring a follow-up diagnosis database by tracking the diagnosis of the user on the high risk group list;
step S720: according to the re-diagnosis database and the bone database, carrying out secondary identification on high risk groups, and outputting a secondary high risk group list;
step S730: and generating a management partition according to the secondary high risk group list, and performing user partition management according to the management partition.
Specifically, the positioning user set is identified, the operations are repeated, each osteoporotic fracture patient of the data reading system for osteoporotic fracture patients is identified one by one, after the data identification is completed, a high risk group list is generated, tracking management is performed on the high risk group list, the tracking management comprises re-diagnosis reminding management and medication course tracking management, and support is provided for improving data reading management efficiency of osteoporotic fracture patients.
Further specifically, the method can be used for carrying out diagnosis tracking through registration diagnosis records of a user to obtain a diagnosis state record, carrying out diagnosis tracking on each osteoporosis and fracture patient one by one based on the high risk group list to obtain a re-diagnosis database, marking the re-diagnosis times of each osteoporosis and fracture patient according to the re-diagnosis database and the bone database, wherein the secondary identification of the high risk group is a re-diagnosis frequency marking signal, the condition that the osteoporosis and fracture patient does not follow medical advice to see a doctor is simply explained, the recovery period corresponding to the low frequency and few times osteoporosis and fracture patient is short, the osteoporosis and fracture patient with common mild disease needs to be supplemented with trace elements such as calcium elements, the recovery period corresponding to the osteoporosis and fracture patient with high frequency and multiple times is long, the osteoporosis and fracture patient with common severe disease needs to be hospitalized, the re-diagnosis is carried out for multiple times at high frequency, the secondary identification of the high risk group list is output according to the re-diagnosis database and the bone database based on the secondary identification of the high risk group; and generating a management subarea by using the secondary high-risk group list, and managing and subarea the osteoporosis fracture patients, so as to provide technical support for improving the management efficiency of the osteoporosis fracture patients.
Further, the embodiment of the application comprises:
step S731: identifying according to the secondary high risk group list and the high risk group list, and outputting a secondary high risk group list;
step S732: and removing the high risk group identification information of the next high risk group list, and storing the users in the next high risk group list into a second management partition for management.
Specifically, in order to ensure the integrity of the scheme, after tracking of a high risk group list is completed, tracking management needs to be performed on the secondary high risk group list, the secondary high risk group list is in a secondary state of the high risk group list, the secondary high risk group list is output by comparing the secondary high risk group list with the high risk group list, after tracking of the high risk group list is completed, high risk group identification information of the secondary high risk group list needs to be removed, users in the secondary high risk group list are stored in a secondary management subarea for tracking management, and through updating of the list, support is provided for ensuring iteration of tracking the management group list.
Further, the embodiment of the application comprises:
step S810: tracking the diagnosis of the user according to the high risk group list to obtain a correlation diagnosis database, wherein the correlation diagnosis database is the diagnosis information of the user in other departments except the bone department;
step S820: acquiring a correlation parameter matrix according to the correlation clinic database, wherein the correlation parameter matrix is a matrix formed by management screening parameters and/or medical parameters based on clinic information of a correlation department;
step S830: and updating the matrix of the screening parameter matrix by using the correlation parameter matrix.
Specifically, in order to ensure the integrity of the screening parameter matrix, the correlated diagnosis data is the diagnosis data of complications of the osteoporotic fracture patient, which is commonly known, the diagnosis data of complications includes but is not limited to sputum accumulation (caused by long-time bed rest of the fracture patient), clinopticity pneumonia (caused by long-time bed rest of the fracture patient), and tissue avascular necrosis (caused by long-time bed rest of the fracture patient), the user defined by the high risk group list is located, the user diagnosis tracking is performed, and a correlated diagnosis database is obtained, the correlated diagnosis database is the diagnosis information of other departments except the osteoporotic department for the user, the diagnosis information of the other departments is the diagnosis data, the matrix formed by managing parameters and/or medical parameters is formed according to the correlated diagnosis database in combination with the type of correlated parameters, the correlated parameter matrix is a matrix formed by forming management parameters and/or medical parameters based on the diagnosis information of the correlated department, the screening parameter matrix is updated by supplementing the row and column type of the screening parameter matrix, the updating matrix is provided for updating the integration matrix, and the screening parameter matrix is updated by a merging support technology, and the reading the integration data of the screening parameter matrix is provided for improving the accuracy of the reading and the integration technology.
In summary, the method and system for reading data of osteoporosis fracture patients provided by the present application have the following technical effects:
because the connected user medical record management terminal is adopted to analyze the user information, a read keyword set is obtained, data acquisition is carried out, and a bone database is constructed; storing the bone database as a preliminary user clue set into a cloud processor; carrying out timing acquisition according to the periodic timing acquisition model, and outputting a bone data distribution library; obtaining a screening parameter matrix; inputting the screening parameter matrix into a high risk group identification model, and positioning users according to a bone data distribution library to obtain a positioning user set; and identifying the positioning user set, generating a high risk group list, and performing tracking management. The application provides the osteoporosis fracture patient data reading method and system, the user is positioned by using double parameters, the medical data reading efficiency is improved, and the technical effect of accurately and efficiently positioning and tracking the patient is achieved.
Because the method adopts the mode of tracking the doctor seeing of the user by the list of the high risk group, the database of the re-diagnosis is obtained; and combining the bone database to carry out secondary identification on the high risk group, outputting a secondary high risk group list, generating a management subarea, carrying out user subarea management according to the management subarea, and providing technical support for improving the management efficiency of the osteoporosis and fracture patients.
Because the identification is carried out according to the secondary high risk group list and the high risk group list, the secondary high risk group list is output; and removing the high risk group identification information of the second highest risk group list, and storing the users in the second highest risk group list into a second management subarea for management. And through updating the list, support is provided for ensuring the iteration of tracking and managing the crowd list.
Example two
Based on the same inventive concept as the data reading method for patients with osteoporosis fracture in the previous embodiment, as shown in fig. 4, the present application provides a data reading system for patients with osteoporosis fracture, wherein the system comprises:
the data analysis unit 11 is used for connecting a user medical record management terminal to analyze user information and obtain a read keyword set;
the data acquisition unit 12 is used for performing data acquisition by using the read keyword set to construct a bone database;
the data storage unit 13 is used for storing the bone database as a preliminary user clue set into a cloud processor, wherein the cloud processor comprises a periodic timing acquisition model;
the timing acquisition unit 14 is used for performing timing acquisition according to the periodic timing acquisition model in the cloud processor and outputting a bone data distribution database;
the parameter screening unit 15 is configured to obtain a screening parameter matrix, where the screening parameter matrix is a matrix formed by management screening parameters and/or medical parameters for identifying high-risk users;
a user positioning unit 16, wherein the user positioning unit 16 is configured to perform user positioning according to the screening parameter matrix input into the high risk group identification model and according to the bone data distribution base embedded in the high risk group identification model, and acquire a positioning user set;
and the tracking management unit 17 is used for identifying the positioning user set, generating a high risk group list, and performing tracking management on the high risk group list.
Further, the system comprises:
the diagnosis tracking unit is used for tracking the diagnosis of the user according to the high risk group list to acquire a related diagnosis database, wherein the related diagnosis database is the diagnosis information of the user in departments other than the bone department;
the relevant parameter acquisition unit is used for acquiring a relevant parameter matrix according to the relevant clinic database, wherein the relevant parameter matrix is a matrix formed by management screening parameters and/or medical parameters based on clinic information of a relevant department;
and the matrix updating unit is used for performing matrix updating on the screening parameter matrix by using the associated parameter matrix.
Further, the system comprises:
a review database acquisition unit, configured to acquire a review database by tracking the visit of the user to the high risk group list;
the secondary identification unit is used for carrying out secondary identification on the high risk group according to the review database and the bone database and outputting a secondary high risk group list;
and the management partition unit is used for generating a management partition according to the secondary high risk group list and performing user partition management according to the management partition.
Further, the system comprises:
the list identification unit is used for identifying according to the secondary high risk group list and the high risk group list and outputting a secondary high risk group list;
and the list identification and removal unit is used for removing the high risk group identification information of the secondary high risk group list and storing the users in the secondary high risk group list into a secondary management partition for management.
Further, the system comprises:
the data sample acquisition unit is used for connecting the user medical record management terminal and acquiring a user fracture data sample set;
the standardized processing unit is used for carrying out standardized processing on the fracture data through the fracture data sample set, carrying out high risk group fracture characteristic data labeling according to the standardized sample set and outputting labeled fracture data;
the training data generating unit is used for generating a training data set according to the marked fracture data;
the high risk group identification unit is used for carrying out high risk group identification model training by taking the training data set as a reference mark and building the high risk group identification model;
and the user positioning unit is used for inputting the screening parameter matrix into the high risk group identification model to obtain the positioning user set.
Further, the system comprises:
the system comprises a preset high-risk index acquisition unit, a data acquisition unit and a data processing unit, wherein the preset high-risk index acquisition unit is used for acquiring a preset high-risk index;
the management screening unit is used for performing parameter combination analysis on the management screening parameters and the medical parameters according to the preset high-risk indexes and determining a matrix distribution ratio, wherein the matrix distribution ratio is the ratio of the management screening parameters to the medical parameters in the screening parameter matrix;
the parameter quantity determining unit is used for determining the quantity of management screening parameters and the quantity of medical parameters according to the matrix distribution ratio;
a screening parameter matrix construction unit configured to acquire the screening parameter matrix based on the number of management screening parameters and the number of medical parameters.
Further, the system comprises:
the management item extraction unit is used for connecting a user medical record management terminal, extracting management items of the user medical record information and generating a management parameter screening library;
a keyword recognition result acquisition unit, configured to acquire a medical keyword recognition result by extracting and recognizing a medical region in the medical history information of the user;
the screening library production unit is used for generating a medical parameter screening library according to the medical keyword identification result;
and the screening parameter matrix obtaining unit is used for obtaining the screening parameter matrix according to the management parameter screening library and the medical parameter screening library.
The specification and drawings are merely illustrative of the present application, and various modifications and combinations can be made thereto without departing from the spirit and scope of the application. Such modifications and variations of the present application are within the scope of the claims of the present application and their equivalents, and the present application is intended to include such modifications and variations.
Claims (8)
1. The method for reading the data of the osteoporosis fracture patient is applied to a medical informatization management system, the system is in communication connection with a user medical record management terminal and a cloud processor, and the method comprises the following steps:
connecting the user medical record management terminal to analyze the user information to obtain a read keyword set;
performing data acquisition by using the read keyword set to construct a bone database;
storing the bone database as a preliminary user clue set into the cloud processor, wherein the cloud processor comprises a periodic timing acquisition model;
performing timing acquisition according to the periodic timing acquisition model in the cloud processor, and outputting a bone data distribution library;
acquiring a screening parameter matrix, wherein the screening parameter matrix is a matrix formed by management screening parameters and/or medical parameters for identifying high-risk users;
inputting the screening parameter matrix into a high risk group identification model, and positioning users according to the bone data distribution library embedded in the high risk group identification model to obtain a positioning user set;
and identifying the positioning user set to generate a high risk group list, and tracking and managing the high risk group list.
2. The method of claim 1, wherein the method further comprises:
tracking the diagnosis of the user according to the high risk group list to obtain a correlation diagnosis database, wherein the correlation diagnosis database is the diagnosis information of the user in other departments except the bone department;
acquiring a correlation parameter matrix according to the correlation clinic database, wherein the correlation parameter matrix is a matrix formed by management screening parameters and/or medical parameters based on clinic information of a correlation department;
and updating the matrix of the screening parameter matrix by using the correlation parameter matrix.
3. The method of claim 1, wherein tracking management is performed with the list of high risk groups, the method further comprising:
acquiring a follow-up diagnosis database by tracking the diagnosis of the user on the high risk group list;
according to the re-diagnosis database and the bone database, carrying out secondary identification on high risk groups, and outputting a secondary high risk group list;
and generating a management partition according to the secondary high risk group list, and performing user partition management according to the management partition.
4. The method of claim 3, wherein the method further comprises:
identifying according to the secondary high risk group list and the high risk group list, and outputting a secondary high risk group list;
and removing the high risk group identification information of the next high risk group list, and storing the users in the next high risk group list into a second management partition for management.
5. The method of claim 1, wherein the method further comprises:
connecting the user medical record management terminal, and collecting a user fracture data sample set;
performing fracture data standardization processing on the fracture data sample set, performing fracture characteristic data labeling on high risk groups according to the standardized sample set, and outputting labeled fracture data;
generating a training data set according to the marked fracture data;
training a high risk group recognition model by taking the training data set as a reference mark, and building the high risk group recognition model;
and inputting the screening parameter matrix into the high risk group identification model to obtain the positioning user set.
6. The method of claim 5, wherein a screening parameter matrix is obtained, the method further comprising:
acquiring a preset high-risk index;
performing parameter combination analysis on the management screening parameters and the medical parameters according to the preset high-risk indexes, and determining a matrix distribution ratio, wherein the matrix distribution ratio is the ratio of the management screening parameters to the medical parameters in the screening parameter matrix;
determining the number of management screening parameters and the number of medical parameters according to the matrix distribution ratio;
and acquiring the screening parameter matrix based on the management screening parameter quantity and the medical parameter quantity.
7. The method of claim 6, wherein the method further comprises:
connecting a user medical record management terminal, extracting management items of the user medical record information, and generating a management parameter screening library;
extracting and identifying keywords from medical areas in medical record information of a user to obtain a medical keyword identification result;
generating a medical parameter screening library according to the medical keyword recognition result;
and acquiring the screening parameter matrix according to the management parameter screening library and the medical parameter screening library.
8. An osteoporotic fracture patient data reading system, said system comprising:
the data analysis unit is used for connecting the user medical record management terminal to analyze the user information and obtain a read keyword set;
the data acquisition unit is used for carrying out data acquisition by using the read keyword set to construct a bone database;
the data storage unit is used for storing the bone database as a preliminary user clue set into a cloud processor, wherein the cloud processor comprises a periodic timing acquisition model;
the timing acquisition unit is used for carrying out timing acquisition according to the periodic timing acquisition model in the cloud processor and outputting a bone data distribution base;
the system comprises a parameter screening unit, a parameter selecting unit and a parameter selecting unit, wherein the parameter screening unit is used for acquiring a screening parameter matrix, and the screening parameter matrix is a matrix formed by management screening parameters and/or medical parameters for identifying high-risk users;
the user positioning unit is used for carrying out user positioning according to the bone data distribution base embedded in the high risk group identification model and inputting the screening parameter matrix into the high risk group identification model, so as to obtain a positioning user set;
and the tracking management unit is used for identifying the positioning user set, generating a high risk group list and carrying out tracking management on the high risk group list.
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