CN112735547A - Hospital background management system based on big data - Google Patents
Hospital background management system based on big data Download PDFInfo
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- CN112735547A CN112735547A CN202110020616.5A CN202110020616A CN112735547A CN 112735547 A CN112735547 A CN 112735547A CN 202110020616 A CN202110020616 A CN 202110020616A CN 112735547 A CN112735547 A CN 112735547A
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- G—PHYSICS
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- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
- G16H10/60—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
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Abstract
The invention provides a hospital background management system based on big data, which comprises: the recording module is used for recording diagnosis and treatment data of a patient in a hospital; the storage module is used for storing the input diagnosis and treatment data into a diagnosis and treatment database and carrying out classified management on the diagnosis and treatment data in the diagnosis and treatment database; the analysis module is used for analyzing and processing the diagnosis and treatment data in the diagnosis and treatment database based on the big data analysis model of the specific item to obtain the analysis result of the specific item; and the display module is used for displaying the analysis result of the specific project. The invention is beneficial to improving the local utilization of the diagnosis and treatment data of the hospital and improving the utilization diversity of the diagnosis and treatment data resources.
Description
Technical Field
The invention relates to the technical field of hospital background management, in particular to a hospital background management system based on big data.
Background
At present, with the development of informatization technology, hospitals can establish an independent data management system to manage the diagnosis and treatment data of patients acquired in the daily medical diagnosis and treatment process. However, most of the existing data management systems of hospitals only implement the functions of storing and calling and consulting data, and the utilization of medical data resources still needs to be improved.
Disclosure of Invention
In order to solve the problems, the invention aims to provide a hospital background management system based on big data.
The purpose of the invention is realized by adopting the following technical scheme:
the invention discloses a hospital background management system based on big data, which comprises:
the recording module is used for recording diagnosis and treatment data of a patient in a hospital;
the storage module is used for storing the input diagnosis and treatment data into a diagnosis and treatment database and carrying out classified management on the diagnosis and treatment data in the diagnosis and treatment database;
the analysis module is used for analyzing and processing the diagnosis and treatment data in the diagnosis and treatment database based on the big data analysis model of the specific item to obtain the analysis result of the specific item;
and the display module is used for displaying the analysis result of the specific project.
Further, the diagnosis and treatment data comprises basic information of the patient, diagnosis and treatment behavior data and time stamp information.
Further, the logging module comprises:
the input unit is used for a doctor to input diagnosis and treatment data of a patient and transmits the input diagnosis and treatment data to the storage module;
and the scanning unit is used for scanning the paper diagnosis and treatment information recording list to obtain a scanned image, performing character recognition according to the scanned image to obtain diagnosis and treatment data corresponding to the scanned image, and transmitting the obtained diagnosis and treatment data to the storage module.
Further, the logging module further comprises:
and the formatting unit is used for formatting the diagnosis and treatment data acquired by the input unit or the scanning unit according to a set format template.
Further, the scanning unit further includes:
and the image enhancement unit is used for carrying out enhancement processing on the acquired scanning image.
Further, the image enhancement unit specifically includes:
performing wavelet transformation on the scanned image based on the set wavelet basis and the set decomposition scale to obtain a low-frequency wavelet coefficient and a high-frequency wavelet coefficient of the scanned image;
and performing enhancement processing on the acquired low-frequency wavelet coefficient, wherein the adopted enhancement processing function is as follows:
in the formula (I), the compound is shown in the specification,
represents the kth low-frequency wavelet coefficient of the j layer after the enhancement processing, dj，kRepresents the kth low-frequency wavelet coefficient of the jth layer, mean (| d)j|) represents the average of the absolute values of the low-frequency wavelet coefficients in the j-th layer; mu represents the set regulatory factor, where mu ∈ [0.01,0.1 ]]And r represents a set amplitude factor, wherein r ∈ [0.95,1.05 ]]；
Performing threshold processing on the obtained high-frequency wavelet coefficient to obtain the high-frequency wavelet coefficient subjected to threshold processing;
and reconstructing the low-frequency wavelet coefficient after the enhancement processing and the high-frequency wavelet coefficient after the threshold processing to obtain a scanning image after the enhancement processing.
Further, the display module includes:
and the display unit is used for displaying the analysis result output by the analysis module.
The invention has the beneficial effects that:
according to the hospital background management system, the input module is arranged, so that doctors, laboratory technicians and the like can input diagnosis and treatment data of a patient into the system in the process of diagnosing and treating the patient, the input diagnosis and treatment data are stored through the storage module, and a local diagnosis and treatment database of a hospital is constructed; based on the diagnosis and treatment database established, the analysis module is arranged to analyze the diagnosis and treatment data in the diagnosis and treatment database based on the big data analysis model according to different analysis requirements, corresponding analysis results are obtained and then displayed through the display module, so that a manager can further analyze the diagnosis and treatment data of the patient based on the hospital, the analysis results are obtained, the local utilization of the diagnosis and treatment data of the hospital is improved, and the utilization diversity of diagnosis and treatment data resources is improved.
Drawings
The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, other drawings can be obtained on the basis of the following drawings without inventive effort.
Fig. 1 is a frame structure diagram of a hospital background management system based on big data according to an embodiment of the present invention.
Detailed Description
The invention is further described in connection with the following application scenarios.
Referring to fig. 1, an embodiment of the present invention provides a hospital background management system based on big data, including:
the recording module is used for recording diagnosis and treatment data of a patient in a hospital;
the storage module is used for storing the input diagnosis and treatment data into a diagnosis and treatment database and carrying out classified management on the diagnosis and treatment data in the diagnosis and treatment database;
the analysis module is used for analyzing and processing the diagnosis and treatment data in the diagnosis and treatment database based on the big data analysis model of the specific item to obtain the analysis result of the specific item;
and the display module is used for displaying the analysis result of the specific project.
In the embodiment, the hospital background management system is provided with the input module, so that doctors, laboratory staff and the like can input diagnosis and treatment data of a patient into the hospital background management system in the diagnosis and treatment process of the patient, and the input diagnosis and treatment data are stored through the storage module to construct a local diagnosis and treatment database of the hospital; based on the diagnosis and treatment database established, the analysis module is arranged to analyze the diagnosis and treatment data in the diagnosis and treatment database based on the big data analysis model according to different analysis requirements, corresponding analysis results are obtained and then displayed through the display module, so that a manager can further analyze the diagnosis and treatment data of the patient based on the hospital, the analysis results are obtained, the local utilization of the diagnosis and treatment data of the hospital is improved, and the utilization diversity of diagnosis and treatment data resources is improved.
Further, the diagnosis and treatment data comprises basic information of the patient, diagnosis and treatment behavior data and time stamp information.
The basic information of the patient comprises the age, the sex and other data of the patient, which can be used for analysis and classification statistics; the diagnosis and treatment behavior data comprises diagnosis results, the diagnosis results comprise diagnosis data obtained under the condition of disease diagnosis and treatment, the diagnosis data comprise confirmed disease types, disease classifications, disease information and the like, and the detection information comprises examination index types and corresponding data obtained under the condition of examination and treatment. And the timestamp information is the recording time of the diagnosis and treatment data.
Further, the analysis module includes:
and the statistical unit is used for carrying out classified statistics on the diagnosis and treatment data in the diagnosis and treatment database and generating statistical results aiming at different projects.
The diagnosis data in the diagnosis database is based on label information with different items (such as patient age, sex, disease information, etc.).
Further, the analysis module includes:
the model building unit is used for selecting a training sample and an analysis sample from the diagnosis and treatment data stored in the diagnosis and treatment database, and training a big data analysis model of a specific item according to the obtained training sample; and inputting the analysis sample into a trained analysis model of the specific project to obtain an analysis result of the specific project.
Wherein the specific items can comprise epidemic outbreak trend, newly-added and diagnosed patient variation trend of specific diseases, population detection index prediction of the age group and the like.
In one scenario, an analysis module can acquire specified diagnosis and treatment data from a diagnosis and treatment database according to analysis requirements, train an analysis model of a specific item (such as epidemic disease outbreak prediction, specified age group health change trend prediction and the like) according to the acquired diagnosis and treatment data, and simultaneously select corresponding data (such as diagnosis and treatment data infected with a certain epidemic patient in a period of time and data of a certain age group aiming at a certain detection index in different periods of time) from the diagnosis and treatment database and input the corresponding data into the trained model for analysis and processing to acquire a corresponding analysis result. The diagnosis and treatment data stored in the local diagnosis and treatment database constructed based on the hospital can be deeply analyzed and utilized, and the diversity utilization level of the diagnosis and treatment data is improved.
Further, the logging module comprises:
the input unit is used for a doctor to input diagnosis and treatment data of a patient and transmits the input diagnosis and treatment data to the storage module;
and the scanning unit is used for scanning the paper diagnosis and treatment information recording list to obtain a scanned image, performing character recognition according to the scanned image to obtain diagnosis and treatment data corresponding to the scanned image, and transmitting the obtained diagnosis and treatment data to the storage module.
The input module provides abundant diagnosis and treatment information input modes so as to meet the requirements of doctors/laboratory staff on the input of patient diagnosis and treatment data.
The hospital is provided with a computer device (input unit) for a doctor, and the diagnosis and treatment data of a patient are input into the hospital background management system in the diagnosis and treatment process of the patient by the doctor. Meanwhile, after a test person detects a certain detection item for a patient, a paper test result is scanned through a scanner (scanning unit) to obtain a scanned image, and further, specific characters and data information in the test list are identified based on the scanner, so that corresponding diagnosis and treatment data are obtained and input into a hospital background management system.
Further, the logging module further comprises:
and the formatting unit is used for formatting the diagnosis and treatment data acquired by the input unit or the scanning unit according to a set format template.
The method is characterized in that for the recorded diagnosis and treatment data, the diagnosis and treatment data comprise multi-dimensional characteristic quantities, and a formatting unit is further arranged to convert the recorded diagnosis and treatment data into a preset data format and then store the preset data format in a diagnosis and treatment database, so that subsequent classification management of the diagnosis and treatment data is facilitated.
Further, the scanning unit further includes:
and the image enhancement unit is used for carrying out enhancement processing on the acquired scanning image.
Further, the image enhancement unit specifically includes:
performing wavelet transformation on the scanned image based on the set wavelet basis and the set decomposition scale to obtain a low-frequency wavelet coefficient and a high-frequency wavelet coefficient of the scanned image;
and performing enhancement processing on the acquired low-frequency wavelet coefficient, wherein the adopted enhancement processing function is as follows:
in the formula (I), the compound is shown in the specification,
represents the kth low-frequency wavelet coefficient of the j layer after the enhancement processing, dj，kRepresents the kth low-frequency wavelet coefficient of the jth layer, mean (| d)j|) represents the average of the absolute values of the low-frequency wavelet coefficients in the j-th layer; mu represents the set regulatory factor, where mu ∈ [0.01,0.1 ]]And r represents a set amplitude factor, wherein r ∈ [0.95,1.05 ]]；
Performing threshold processing on the obtained high-frequency wavelet coefficient to obtain the high-frequency wavelet coefficient subjected to threshold processing;
and reconstructing the low-frequency wavelet coefficient after the enhancement processing and the high-frequency wavelet coefficient after the threshold processing to obtain a scanning image after the enhancement processing.
Wherein, threshold processing is carried out on the obtained high-frequency wavelet coefficient, and the adopted threshold function is as follows:
in the formula, gj，kAnd
respectively representing the kth high-frequency wavelet coefficient of the jth layer before and after threshold processing; alpha is a threshold adjustment factor, alpha is more than or equal to 1.5 and less than or equal to 3.5, beta is an inhibition factor, omegajIndicating the set threshold for the jth layer wavelet decomposition.
In the above embodiment, the quality of the scanned image can be improved by performing enhancement processing on the scanned image.
It should be noted that, functional units/modules in the embodiments of the present invention may be integrated into one processing unit/module, or each unit/module may exist alone physically, or two or more units/modules are integrated into one unit/module. The integrated units/modules may be implemented in the form of hardware, or may be implemented in the form of software functional units/modules.
From the above description of embodiments, it is clear for a person skilled in the art that the embodiments described herein can be implemented in hardware, software, firmware, middleware, code or any appropriate combination thereof. For a hardware implementation, a processor may be implemented in one or more of the following units: an Application Specific Integrated Circuit (ASIC), a Digital Signal Processor (DSP), a Digital Signal Processing Device (DSPD), a Programmable Logic Device (PLD), a Field Programmable Gate Array (FPGA), a processor, a controller, a microcontroller, a microprocessor, other electronic units designed to perform the functions described herein, or a combination thereof. For a software implementation, some or all of the procedures of an embodiment may be performed by a computer program instructing associated hardware. In practice, the program may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a computer. Computer-readable media can include, but is not limited to, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.
Finally, it should be noted that the above embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the protection scope of the present invention, although the present invention is described in detail with reference to the preferred embodiments, it should be analyzed by those skilled in the art that modifications or equivalent substitutions can be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims (7)
1. A hospital background management system based on big data is characterized by comprising:
the recording module is used for recording diagnosis and treatment data of a patient in a hospital;
the storage module is used for storing the input diagnosis and treatment data into a diagnosis and treatment database and carrying out classified management on the diagnosis and treatment data in the diagnosis and treatment database;
the analysis module is used for analyzing and processing the diagnosis and treatment data in the diagnosis and treatment database based on the big data analysis model of the specific item to obtain the analysis result of the specific item;
and the display module is used for displaying the analysis result of the specific project.
2. The big-data based hospital background management system according to claim 1, wherein the clinical data includes patient basic information, clinical behavior data and time stamp information.
3. The big-data-based hospital background management system according to claim 2, wherein the entry module comprises:
the input unit is used for a doctor to input diagnosis and treatment data of a patient and transmits the input diagnosis and treatment data to the storage module;
and the scanning unit is used for scanning the paper diagnosis and treatment information recording list to obtain a scanned image, performing character recognition according to the scanned image to obtain diagnosis and treatment data corresponding to the scanned image, and transmitting the obtained diagnosis and treatment data to the storage module.
4. The big-data-based hospital background management system according to claim 3, wherein the entry module further comprises:
and the formatting unit is used for formatting the diagnosis and treatment data acquired by the input unit or the scanning unit according to the set format template.
5. The big-data based hospital background management system according to claim 4, wherein the scanning unit further comprises:
and the image enhancement unit is used for carrying out enhancement processing on the acquired scanning image.
6. The big-data-based hospital background management system according to claim 5, wherein the image enhancement unit specifically comprises:
performing wavelet transformation on the scanned image based on the set wavelet basis and the set decomposition scale to obtain a low-frequency wavelet coefficient and a high-frequency wavelet coefficient of the scanned image;
and performing enhancement processing on the acquired low-frequency wavelet coefficient, wherein the adopted enhancement processing function is as follows:
in the formula (I), the compound is shown in the specification,
indicating after enhancement treatmentj layers of k low frequency wavelet coefficient, dj,kRepresents the kth low-frequency wavelet coefficient of the jth layer, mean (| d)j|) represents the average of the absolute values of the low-frequency wavelet coefficients in the j-th layer; mu represents the set regulatory factor, where mu ∈ [0.01,0.1 ]]And r represents a set amplitude factor, wherein r ∈ [0.95,1.05 ]]；
Performing threshold processing on the obtained high-frequency wavelet coefficient to obtain the high-frequency wavelet coefficient subjected to threshold processing;
and reconstructing the low-frequency wavelet coefficient after the enhancement processing and the high-frequency wavelet coefficient after the threshold processing to obtain a scanning image after the enhancement processing.
7. The big-data-based hospital background management system according to claim 6, wherein the display module comprises:
and the display unit is used for displaying the analysis result output by the analysis module.
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Cited By (2)
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| CN113628728A (en) * | 2021-08-17 | 2021-11-09 | 广州辉博信息技术有限公司 | Pelvic cavity prolapse data display method and device and storage medium |
| CN117637093A (en) * | 2024-01-25 | 2024-03-01 | 西南医科大学附属医院 | Patient information management method and system based on intelligent medical treatment |
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| CN109411039A (en) * | 2018-10-16 | 2019-03-01 | 广州益牛科技有限公司 | A kind of managing medical information platform |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113628728A (en) * | 2021-08-17 | 2021-11-09 | 广州辉博信息技术有限公司 | Pelvic cavity prolapse data display method and device and storage medium |
| CN117637093A (en) * | 2024-01-25 | 2024-03-01 | 西南医科大学附属医院 | Patient information management method and system based on intelligent medical treatment |
| CN117637093B (en) * | 2024-01-25 | 2024-04-12 | 西南医科大学附属医院 | Patient information management method and system based on intelligent medical treatment |
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