121 results about "Hospital system" patented technology

The invention discloses a peritoneal dialysis anti-blocking high-circulation nursing device for pediatric nephropathy patients, and belongs to the technical field of medical nursing. Comprising the following modules: a multi-mode sensing module for collecting pressure, flow velocity, turbidity, vibration spectrum and temperature data in a catheter in real time; the signal optimization processing module highlights weak features of potential blockage and improves data quality; the feature fusion analysis module is used for comprehensively evaluating the state of the catheter; the AI prediction analysis module is used for predicting the occurrence probability, the position and the possible time window of blockage; the risk early warning and intervention module is used for sending out graded early warning signals according to the prediction result and generating personalized anti-blocking intervention suggestions; the micro-fluidic execution module inhibits formation of initial sediments through a micro-pulse technology and dynamic fluid mechanics adjustment, and effectively reduces the risk of blockage; and the remote medical support module provides visual data visualization and intervention suggestions, supports remote monitoring and emergency intervention, and is seamlessly integrated with a hospital system while ensuring data security.

The invention relates to the technical field of medical data integration, in particular to a block chain and AI-based medical whole industry data asset integration system and method. Comprising a data acquisition layer, a block chain right confirmation layer, a federal learning analysis layer, a data asset transaction platform and a supply chain traceability optimization module. The data acquisition layer comprises an edge computing node, a data cleaning engine and a desensitization algorithm are built in the edge computing node, and the edge computing node is used for carrying out localized cleaning and desensitization processing on hospital HIS system data, medicine RFID data, medicine research and development experiment data and medical image data; the block chain right confirmation layer constructs a medical data asset account book based on an alliance chain architecture, the asset account book comprises a data hash record, a contributor identity identifier and a use authorization log, and an integrated intelligent contract module is used for dynamic right management; according to the invention, medical data islands can be broken, and safe integration and efficient utilization of cross-domain data are realized.

The invention belongs to the technical field of biological sample sorting, and discloses a visual identification control system for automatic sorting of biological samples, through cooperation of a multi-modal sensing acquisition unit and a knowledge graph multi-dimensional identification unit, condensed water of a frozen sample tube can be penetrated to accurately identify label and molecular characteristics, and'condensed water shielding 'and'label damage' are distinguished; meanwhile, a sample preprocessing state is associated, and samples which do not meet requirements are automatically intercepted. Compared with the prior art, manual secondary verification is not needed, sorting dislocation caused by optical interference of smear glass slides is thoroughly solved, the sorting precision and efficiency of mixed samples are remarkably improved, and diversified sample treatment requirements in clinical detection are met; the full-link twin operation and maintenance unit integrates key data in a sorting process through a block chain technology, and is interconnected and intercommunicated with a hospital LIS system and a sample storage system; and when the subsequent storage environment of the sample is abnormal, the quality state of the sorting stage can be reversely associated, and the compliance auditing vulnerability is eliminated.

The invention belongs to the technical field of medical informatization, and particularly relates to a medical insurance medication rationality interception system and method based on deep reinforcement learning and an FP-Growth algorithm, and the method comprises the following steps: S1, receiving electronic prescription data transmitted by a hospital HIS system in real time; s2, according to original diagnosis information in the prescription, performing standardization processing to obtain a diagnosis set; according to the original medicine information in the prescription, cleaning and integrating to obtain a medicine set; s3, based on an FP-Growth association rule algorithm, performing diagnosis-drug association analysis and drug-drug association analysis on the diagnosis set and the drug set, and identifying a low-association prescription according to a preset condition and marking the low-association prescription as a suspicious prescription; s4, starting deep reinforcement learning analysis on the suspicious prescription through DRL decision optimization, and outputting a prescription reinforcement learning feature set; and S5, outputting a prescription qualitative analysis result and a corresponding confidence score according to the prescription reinforcement learning feature set.

The invention discloses an intelligent medical inquiry and medical record generation method and system based on multi-technology fusion, and the system comprises a specialized dynamic pre-inquiry module which is used for sequentially executing the analysis of a patient chief complaint, the matching of a dynamic template, the intelligent inquiry and the completion and verification of a knowledge graph according to a chief complaint text inputted by a patient, and obtaining the comprehensive information of the patient; the dual-drive medical risk control module is used for performing dominant and recessive risk identification based on a rule engine and a large model in combination with an RAG knowledge base according to the comprehensive information of the patient, and realizing a collaborative early warning closed loop; the voice structuring and medical record generation module is used for executing double-track voice separation and transcription, specialized structuring processing and multi-source data fusion and EMR template matching in the dialogue process of the patient and the doctor to generate a structured electronic medical record; and the system integration and performance optimization module is used for adapting to a hospital HIS / EMR system through a standardized interface and executing data preloading and cache optimization to guarantee the response performance of the system.

The invention discloses a 3D holographic image knowledge base interactive playing method for diabetic education, and the method comprises the steps: firstly obtaining patient data of a hospital HIS system and a wearable device, and carrying out the classification, preprocessing and data fusion, thereby obtaining an encrypted standardized data set; and then multi-dimensional feature groups are extracted, knowledge base education contents are matched, and a personalized scheme is generated. And carrying out structural processing on the scheme, constructing a 3D model and a scene resource library, rendering the scheme into a holographic image format, optimizing the scheme, and outputting a material set. And then configuring a calibration material set, scheduling and playing, realizing immersive learning, and generating interaction data and feedback information. And finally, evaluating a learning effect by combining clinical indexes, and dynamically updating and optimizing the knowledge base. By means of 3D holography and multi-mode interaction, intuition, interactivity and individuation of diabetic education are improved, and the self-management ability is enhanced.

The invention discloses an AI optimal storage system with an automatic storage function and capable of being connected with a hospital HIS system, and relates to the technical field of medical information management and data storage, the AI optimal storage system comprises a data input end, a data processing end, an HIS system docking module, an automatic storage strategy generation end, a cache management end, a data security and authority control module and a user interface end; the data input end is responsible for receiving and collecting medical data from all systems of a hospital, and the medical data comprise operation images, medical images, patient electronic medical records and monitoring data. The data processing end is used for preprocessing input data, and the preprocessing comprises format conversion, data cleaning, compression and duplicate removal. The intelligent degree of data storage is remarkably improved, remarkable effects are achieved in the aspects of data management efficiency, cross-system integration, postoperative risk management, data safety and the like, and the high-standard requirements of modern hospitals for operation data storage, analysis and management are met.

The invention relates to the technical field of internet hospitals, in particular to an internet hospital-based preoperative information input system, which comprises a patient end information acquisition module, a cloud data processing module and a hospital end management system. The patient end realizes multi-dimensional information input and classification, the cloud end performs intelligent analysis and structured storage by using OCR and natural language processing technologies, and the hospital end provides risk assessment, medicine taking reminding and state tracking functions. The system is seamlessly connected with a hospital system through a medical history docking interface, so that the information acquisition efficiency, the automatic processing capability and the preoperative management intelligent level are remarkably improved, a scientific basis is provided for a doctor to make an operation plan, and the patient experience is optimized.

The invention provides a decision supervision support method based on evidence-based medicine knowledge management, and relates to the technical field of evidence-based medicine, and the method comprises the following steps: obtaining an evidence set for describing an entity relationship between exposure factors and / or intervention measures and an outcome index, using the evidence set to construct a first entity relationship graph as quantitative representation of the entity relationship; when the new evidence appears, updating the edge weight according to the quality score of the new evidence by adopting an incremental learning algorithm, and generating a second entity relation graph; the hospital system uses the second entity relation graph to carry out diagnosis and treatment to obtain real-time clinical feedback information; and adjusting the edge weight of the second entity relation graph according to real-time clinical feedback information of the multi-party hospital system to obtain a comprehensive decision support quantitative relation. According to the method, the problem that the medical decision supervision support is lagged due to the fact that the relation between the exposure factor and / or the intervention measure and the outcome index is difficult to dynamically update according to the retrieved new evidence in the prior art is solved.

The invention provides a data analysis processing method and system for a hospital HIS system, and belongs to the technical field of energy storage devices, and the method specifically comprises the steps: determining a coincidence time period according to the coincidence condition of a quality inspection analysis recommendation time period of medical records of each hospital department and a time period of a doctor of the hospital department with infectious disease diagnosis and treatment, and when the quality inspection analysis recommendation time periods of the hospital departments belong to the overlapping time periods, determining the quality inspection processing time periods of the medical records of the hospital departments based on the distribution data and the registration data of the hospital departments in different quality inspection analysis recommendation time periods in the overlapping time periods, thereby improving the quality inspection processing efficiency.

The invention relates to the technical field of computers, discloses a data sharing method and system for patients suffering from metabolic acidosis, and aims to solve the problem of out-of-control safety caused by extensive authority, bare transmission and traceless behaviors in cross-institution medical data circulation. A dynamic authority strategy based on roles and scenes is constructed by extracting and standardizing patient diagnosis and treatment data from a hospital system; end-to-end encrypted transmission is realized through bidirectional authentication and a temporary session key; establishing a three-layer block chain type audit log tracking access, a secret key and a data flow direction; dynamic desensitization, quality verification, cache acceleration and intelligent contract extension mechanisms are integrated, and a visual authority topology monitoring and credit scoring system is supplemented. According to the technical scheme, data field-level accurate authorization, encryption and anti-theft in the whole transmission process, traceability in the whole operation period and use compliance self-feedback are achieved, and the scientific research value of clinical data is released to the maximum extent while the privacy safety of a patient is effectively guaranteed.

The invention relates to the technical field of medical care, and provides an electronic medical record-based nursing system, which comprises a heterogeneous data integration module for acquiring multi-source heterogeneous electronic medical record data from a hospital HIS (hospital information system), wearable monitoring equipment and a nursing operation terminal and outputting cleaned and standardized data; the feature association module is used for receiving the cleaned and standardized data to generate a spatial-temporal feature association matrix and storing a feature topological graph; the dynamic decision-making module is used for processing the feature incidence matrix based on the deep space-time fusion network to generate a nursing decision-making vector; the scheme execution monitoring module is used for collecting nursing operation data flow in real time, calculating and executing deviation degree parameters and feeding back the parameters; the abnormity intervention module analyzes and executes deviation degree parameters to trigger the dynamic decision module to execute nursing scheme reconstruction; the multi-terminal cooperation module is used for converting the nursing decision vector into an equipment instruction set and feeding back an equipment state; and the secure storage module is used for encrypting and storing the feature topological graph and the decision knowledge graph and providing model parameter version management.

The invention discloses a medical consumable full life cycle management system based on large model application, and relates to the field of medical consumable intelligent management. The system comprises an identity verification module which is used for realizing pre-operation and post-operation personnel verification and authority control based on multi-mode identification; the image acquisition module is used for integrating RFID (Radio Frequency Identification Device) identification, image identification and a certification OCR (Optical Character Recognition) technology, acquiring pre-operation and post-operation consumable information and constructing a corresponding information set; the consumable use state recognition module is used for constructing difference parameters based on the preoperative and postoperative information set, judging the consumable use state and outputting a use and remaining list; and the SPD integration and return management module is in butt joint with a hospital SPD system, performs state screening and tracing binding based on the remaining consumable list, automatically generates return information, and realizes consumable life cycle closed-loop management. Through the multi-modal technology, whole-course tracing and automatic management of consumables are realized, the working efficiency is improved, manual intervention is reduced, the return flow is optimized, and the data accuracy and efficient execution of the flow are ensured.

The invention discloses a medical incorruption risk prevention and control system and method based on multi-source data fusion, and relates to the technical field of information processing.The medical incorruption risk prevention and control method comprises the steps that system operation log data, ICD coding data and medicine catalog data in a hospital system are obtained, standardization processing is conducted on the ICD coding data and the medicine catalog data, and an initial incidence relation is established; constructing a medical encoder, and inputting data to obtain corresponding feature vectors; calculating the association strength of the codes and the drugs, generating an association feature vector, and inputting compliance and non-compliance data into a support vector machine classifier to train an association verification model; inputting system operation log data into the model to obtain an operation matching degree, and if the operation matching degree is lower than a threshold, triggering early warning; and obtaining a continuous operation time sequence of an operator, calculating the deviation between the time interval and the historical average interval, and triggering early warning if the deviation exceeds a threshold value. According to the method, through multi-source data fusion and an intelligent model, accurate prevention and control of medical incorruption risks are realized, and the supervision efficiency is improved.

The application relates to the technical field of medical care, and provides a nursing system based on electronic medical records, which comprises a heterogeneous data integration module, which obtains multi-source heterogeneous electronic medical record data from a hospital HIS system, a wearable monitoring device and a nursing operation terminal and outputs the data after cleaning and standardization; a feature correlation module, which receives the data after cleaning and standardization to generate a space-time feature correlation matrix and stores a feature topology graph; a dynamic decision module, which processes the feature correlation matrix based on a deep space-time fusion network to generate a nursing decision vector; a scheme execution monitoring module, which collects nursing operation data streams in real time, calculates an execution deviation parameter and feeds back the execution deviation parameter; an abnormal intervention module, which analyzes the execution deviation parameter to trigger the dynamic decision module to execute nursing scheme reconstruction; a multi-terminal cooperation module, which converts the nursing decision vector into a device instruction set and feeds back a device state; and a safe storage module, which encrypts and stores the feature topology graph and a decision knowledge graph and provides model parameter version management.

The invention relates to the technical field of medical management, and discloses a medical specialist ability index evaluation method, which is characterized by comprising the following steps: data acquisition: collecting multi-dimensional information; constructing an index system, and establishing a multi-dimensional evaluation system; weight distribution: determining a weight coefficient by adopting a scientific method; and calculating a specialist ability index through comprehensive scoring model calculation. The system is characterized in that data acquisition is completed through a hospital system and a database; the basic capability indexes comprise equipment configuration and the like; clinical ability indexes comprise diagnosis and treatment quantity and the like; the scientific research capability indexes comprise scientific research projects and the like; the service capability indexes comprise patient satisfaction and the like; the specialized ability index has a specific calculation formula. The method has the advantages that comprehensive, scientific and dynamic assessment of the clinical specialized ability of the medical institution is realized through the specialized ability assessment method based on multi-dimensional data acquisition, objective weight distribution and a quantitative scoring model.

The invention provides a medical material supply chain management method and system based on an HRP system of a hospital, and the method constructs a multi-dimensional data set and a medical consumable association diagram based on clinical events, consumable delivery and logistics data in the HRP system of the hospital. The system establishes a state evolution model for a specific clinical event to predict a dynamic trend of a supply chain, and defines a critical early warning region accordingly. According to the method, state point tracks of consumable and logistics data are monitored in real time, when the state point tracks are close to a critical early warning area, it is judged that a corresponding clinical event is activated, and a crisis index is calculated. If the crisis index is low, calling an evolution model to carry out macroscopic prediction; and if the index is high, deep fusion prediction is carried out by combining the evolution model and the consumable association graph, and the demands of all related consumables are accurately deduced. And finally, generating and sending a deployment instruction based on a prediction result. According to the method, intelligent transformation of the medical material supply chain from passive response to active prediction and accurate allocation is realized.

The invention discloses a potential nephropathy prediction electronic nose system and method based on machine learning, and belongs to the technical field of medical detection. According to the system, ammonia concentration and temperature and humidity parameters in exhaled air of a human body are collected through a multi-mode sensor module, baseline calibration, flow velocity compensation and noise filtering are carried out in combination with a data preprocessing module, and a standardized characteristic matrix is generated. The machine learning prediction model adopts a Bayesian deep learning or integrated learning algorithm, inputs an ammonia concentration peak value, an integral area and temperature and humidity parameters, outputs a nephropathy risk probability and stage prediction, and quantifies key influence factors through an SHAP value (for example, a high-risk alarm is triggered when an ammonia concentration contribution degree is greater than or equal to 60%). The system is equipped with a real-time GUI interaction interface, dynamically displays a risk thermodynamic diagram and multi-dimensional data overlay analysis, and supports clinicians to feed back and correct. And the data iteration module realizes continuous optimization of the model through an encrypted cloud storage and incremental learning framework (Online SGD). A heterogeneous sensor array (such as a Fe2Mo3O8 / MoO2 (at) MoS2 composite material) and a dynamic temperature and humidity compensation technology are adopted, so that the detection stability is remarkably improved, and the clinical misdiagnosis rate is reduced. The system can be integrated in a portable device or a hospital system, is suitable for community screening, emergency triage and remote medical scenes, and has the advantages of noninvasive, high-precision and cross-mechanism collaborative diagnosis.

The invention discloses an intelligent hospital integrated system and method based on credential environment data element driving, and belongs to the technical field of medical information system management, the system comprises a cloud platform and a plurality of clients, and the cloud platform is in communication connection with each client; the cloud platform is provided with a data platform, a service platform and a technical platform; the data platform comprises a medical data generation module which is used for carrying out standardization processing on medical information from different medical units; the business platform comprises a plurality of business processing modules; the plurality of business processing modules are mutually independent and operate independently; the business processing module performs data interaction with the data lake; the technical platform comprises a framework and component module, a platform research and development module, a log monitoring module and a data early warning module; the data formats of all medical units are standardized, a standard interface module is arranged, repeated labor is reduced to the maximum extent, and sharing and sharing are achieved.

The invention belongs to the technical field of intelligent medical big data disease risk prediction, and provides a VTE risk prediction method and system based on gradient increasing, and the method comprises the following steps: collecting a sample feature data group through a hospital system; preprocessing the collected sample feature data; performing correlation analysis on the processed sample feature data; calculating a risk threshold value of the numerical type sample features; establishing a machine learning model by adopting a gradient increasing algorithm; testing a model prediction effect; and performing VTE risk prediction by using a gradient increasing model. According to the method, feature data related to VTE diseases are doubly screened by combining feature importance ranking of the Pearson's correlation coefficient and the gradient increasing model, and linear and nonlinear correlation features are captured at the same time; the problems of prediction deviation and insufficient interpretability caused by one-sided feature screening and separation of threshold setting from diagnosis and treatment practice of an existing machine learning model are solved.

The invention discloses a hierarchical medical electronic business card system and an information aggregation method thereof, the system comprises a front-end layer, a business module layer, an external hospital system layer and a block chain layer, the business module layer comprises a two-dimensional code generation and identification module used for generating an anti-counterfeiting verifiable doctor exclusive two-dimensional code based on multi-dimensional hash and a block chain; the doctor information aggregation display module is used for aggregating the multi-source information and dynamically displaying the multi-source information; and the communication interface access module is used for intelligently scheduling multiple communication channels. According to the method, the unification of digital identities of doctors, credible authentication and efficient aggregation of information are realized, the problems of doctor information dispersion, communication channel splitting and the like in the prior art are solved, and the doctor-patient connection efficiency and the digital management level of doctor services are remarkably improved.

An endoscope apparatus includes an endoscope and processing circuitry. The endoscope includes an imaging device disposed at a distal end of an insertion portion and configured to capture endoscopic images when the endoscope is inserted into a human body. The processing circuitry is configured to determine, based on image changes of the endoscopic images, whether each endoscopic image is a non-observation target image or an observation target image, detect a specific region based on image characteristics in endoscopic images determined as the non-observation target images, determine images including the specific region among the non-observation target images as correction target images, determine a directional relationship between a direction of the imaging device and an anatomical orientation of the human body, based on the correction target images, andperform direction standardization processing based on the directional relationship, thereby standardizing orientations of the correction target images based on the anatomical orientation.

The invention provides a hospital infection operation intelligent training system and method based on ST-GCN and AR fusion, and relates to the technical field of mobile medical training and artificial intelligence crossing. The system comprises a cloud management platform which uniformly governs SOP and AR scenes, performs score configuration, courses and schedules, completes data storage and ETL, performs intelligent analysis and report output, issues configuration to edges and AR, and is in butt joint with an in-hospital system; the multispectral visual acquisition subsystem is used for performing object environment recognition and pollution visualization based on synchronous calibration and a region of interest; the edge calculation unit executes preprocessing, space-time diagram construction and ST-GCN reasoning, and outputs an AR visualization instruction and a structured result; the user client supports billboard auditing, management configuration, appointment learning and process control. The system solves the problems of non-uniform standard subjectivity, low scene reduction degree, high organization cost, difficulty in hierarchical assessment of high-order capability and the like, and improves the coverage rate, fairness and clinical operation level.

The invention discloses a health data linkage management system for pregnant and lying-in women in a large perinatal period, and belongs to the technical field of intelligent data management. The system comprises a multi-source heterogeneous data access and standardization gateway which is used for connecting household equipment and a hospital system and standardizing original data through a deep cleaning engine; a data fusion and association unit of the central data processing server fuses multi-source data according to a time sequence by relying on a gestational week management unit, and a multi-modal health analysis engine is combined with a clinical rule and a machine learning model to carry out early warning, risk prediction and personalized analysis; and the multi-terminal interaction platform provides a fusion data view and a closed-loop management tool based on role permission. According to the invention, equipment and hospital information islands are broken through, and through high-quality data management and'rule + AI 'fusion analysis, accurate and foresight management and efficient cooperation of the full-cycle health state of pregnant and lying-in women are realized.

The invention relates to the technical field of medical instrument logistics management, and discloses a logistics system and method of a redisinfection instrument recovery robot based on a hospital HIS (hospital information system), and the system comprises an HIS data interface module, a dynamic path planning module, a task distribution module, an instrument identification module, a recovery processing module and the like. The HIS data interface module obtains the use record of the repeated disinfection instrument; the dynamic path planning module plans a path based on a multi-target ant colony optimization algorithm; the task allocation module allocates tasks by using a game theory model; the instrument identification module identifies instruments by adopting a radio frequency identification and visual fusion algorithm; and the recovery processing module processes the instruments according to the pollution level and updates the inventory state of the HIS system. The recovery efficiency and accuracy of the recovery instrument are improved, deep fusion with an HIS system is achieved, hospital logistics management is optimized, the labor cost is reduced, and the practical value is remarkable.

The embodiment of the invention discloses a medical information management system, method and device, a storage medium and equipment.The basic information of a user is collected and stored through a medical information management center, the medical information management center serves as a unified information management center of different hospitals, the user does not need to repeatedly input the basic information when seeing a doctor in the different hospitals, and the user experience is improved. A hospital only needs to inquire and obtain the basic information of the user from the medical information management center, and the process of seeing a doctor by the user can be effectively simplified. Moreover, when the medical information management center provides the basic information of the user to the hospital system, the basic information of the user is provided after desensitization processing, and privacy leakage of the user is also avoided.

Provided is a method of operating an integrated monitoring server operated by at least one processor, the method including: receiving waveform-type respiratory mechanics information in real time from a ventilator of a patient that is installed at a remote location, and transmitting the real-time received waveform-type respiratory mechanics information to a hospital system connected to the server through a dedicated line or mobile terminals of medical personnel connected to the server through an internet.

The invention relates to the medical field of urinary surgery, in particular to a fault diagnosis software system of an intelligent urinary surgery catheterization device, which is characterized in that an original data stream is collected by a unified timestamp, and normalized data is obtained through cross-brand semantic adaptation; utilizing inertial measurement exogenous input to suppress body motion artifacts and generating channel credibility; forming structured features based on second-order scattering and cross-channel attention; outputting pressure and flow velocity prediction under a physically constrained reversible and neural differential hybrid model, and inverting potential physical parameters; uncertainty calibration is carried out in combination with a brand-level calibration set, and a fault occurrence probability and a predicted failure time interval are given; a channel fault can be diagnosed and identified in cooperation with self-inspection and fault separation, and sound-light alarm and cross-terminal routing are achieved through arrangement of a system in a hospital. The system is suitable for bedside continuous monitoring and multi-brand deployment, and realizes robust diagnosis and short-term prediction under unified semantics.

The present invention relates to a labeling device, specifically a test tube labeling device, including an outer shape component, a storage component, a conveying component, a label component and a labeling component, wherein the storage component is fixed inside the outer shape component, the conveying component is fixed inside the outer shape component, the label component is fixed inside the outer shape component, the labeling component includes a fixed plate, a pipe clamp and a rotating component, the pipe clamp includes a rack, a limit plate is fixed on the top of the rack, a connecting frame is fixed on one side of the rack, a rotating shaft is rotatably connected to one side of the connecting frame, a rotating wheel is fixed on one side of the rotating shaft, and the rotating component includes a connecting plate, which is fixed on one side of the limit plate. The present invention clamps the test tube by the labeling component, and uses a motor to drive the rubber shaft to rotate, so that the test tube also rotates, and at the same time, the printer can receive patient information uploaded by the hospital system, and then print various patient information on the label, and the label is attached to the test tube through the continuous rotation of the test tube.

The invention relates to the technical field of medical informatization, and discloses a nursing reward performance data element standard construction and structured acquisition method, which comprises the following steps: acquiring nursing work scene parameters; defining a data element identifier, a data type and a constraint condition; constructing a directed graph structure data element relation model; determining a collection target data element through the event monitor; using a multi-source data interface to obtain nursing work records; and carrying out structured processing and transmission. According to the method, the data acquisition error rate is reduced through structural data element constraint and an automatic verification mechanism; a data element standard library and a pushing mechanism are adopted, so that the weight parameter adjusting time is shortened; the labor cost is reduced by multi-source data interface integration; the nurse satisfaction degree is improved through dynamic weight calculation; the directed graph data element relation model enhances the business change adaptation capability of the hospital system and shortens the transformation period.