133 results about "Hospital information system" patented technology

The invention relates to the technical field of medical decision, and discloses a medical decision support system based on a knowledge graph, and the system comprises a knowledge graph construction module which constructs an initial knowledge graph based on a medical ontology library, and the knowledge graph comprises entities and association relationships of diseases, symptoms and drugs; the data acquisition module is used for acquiring data from an electronic medical record, wearable equipment, a medical literature library and a hospital information system and normalizing the data through a standardized protocol; the dynamic knowledge updating module is used for processing normalized data through an incremental graph neural network; a multi-source knowledge fusion module; a context awareness module; a dynamic deduction module; and a decision optimization closed loop module. And triggering a preset clinical rule in real time based on the pathological state of the patient, dynamically adjusting the intensity value of the related edge in the factor graph, and persistently storing the intensity value back to the knowledge graph, so that logic adaptation and individualized experience precipitation of general medical knowledge in a special pathological state are realized, and the individualized treatment accuracy is ensured.

The invention relates to the technical field of treatment scheme optimization, and provides an emergency treatment critical patient first-aid path optimization method and system based on big data, and the method comprises the steps: building a standardized event sequence through extracting historical diagnosis and treatment data of a hospital information system, and analyzing the time sequence correlation between events through a graph structure mining technology, key diagnosis and treatment nodes and high and low frequency paths are identified, and a layered first-aid path state transition network is constructed based on the key diagnosis and treatment nodes and high and low frequency paths. When a real-time patient is processed, the system matches an electronic health record of the patient with a network core state, dynamically plans a subsequent standard transfer path, and avoids a low-frequency risk path marked as a taboo, so that an emergency path optimization scheme of risk avoidance and path dynamic optimization is realized, and the treatment efficiency of emergency critical patients is improved. The treatment effect is improved, and the bad prognosis risk is reduced.

The invention discloses an inpatient falling early warning and intervention method based on environmental perception, and the method comprises the steps: continuously obtaining the video frames of a patient through a camera, and extracting the coordinates and confidence of seventeen key points through a pre-training deep learning posture estimation model; respectively processing the time sequence and the space-time diagram by using a hierarchical time sequence convolutional network branch and a graph neural network branch, and generating a visual behavior feature vector; in the same risk assessment period, bidirectional cross-modal attention fusion is carried out on the physiological feature vector and the visual feature vector collected by the wearable device, and a multi-modal fusion feature vector is output; then combining historical state features and static archive features in a hospital information system, carrying out unified modeling through a Transform encoder, and mapping to fall risk probability distribution; and when the risk is judged to be high, an intervention instruction is immediately issued to an intelligent sickbed or ward falling prevention execution mechanism through an Internet of Things protocol, and a perception-decision-intervention closed loop is completed.

The invention relates to a smart hospital collaborative diagnosis and treatment management method and system, and the method comprises the steps: receiving the appointment registration information of a patient, building a data mapping relation with a hospital information system based on the appointment registration information, and generating a corresponding treatment identifier; after the patient arrives at the hospital, information of the sign-in patient is collected, a sign-in sequence is established, and according to appointment registration information and diagnosis and treatment service data parameters corresponding to the sign-in patient, a treatment serial number is dynamically distributed and a waiting prompt is pushed; after the doctor receives the diagnosis, generating an examination item list based on the preliminary diagnosis information input by the doctor, obtaining the real-time state and queuing data of equipment required by each examination in the examination item list, constructing an execution time window of examination items, generating an optimal examination sequence, and pushing an examination guide path to the patient terminal; and after the patient finishes seeing a doctor, generating a personalized propaganda and education task list according to the diagnosis and treatment information of each stage, and pushing the personalized propaganda and education task list to the patient terminal. The method has the effect of improving the hospital operation efficiency.

The invention discloses an operation and maintenance knowledge base analysis system and method based on deep learning, and is applied to unified operation and maintenance management of a hospital information system and medical equipment. The system collects operation and maintenance data such as operation logs, monitoring indexes, alarm events, work orders, maintenance records and the like, constructs a minute-level time window through equipment identification and technology triggering time, and merges multi-source heterogeneous data into operation and maintenance sub-events and operation and maintenance events. Log, index and text feature extraction is performed on each operation and maintenance sub-event, multi-modal feature fusion is performed to generate an operation and maintenance event feature vector, the operation and maintenance event feature vector is stored in a vector index database and is associated with an operation and maintenance knowledge graph, and similar historical event retrieval and root cause and processing scheme recommendation of a new operation and maintenance event are realized. In combination with the adoption and processing results of recommended schemes by operation and maintenance personnel, the system performs hierarchical management on the operation and maintenance knowledge and performs incremental updating on the feature modeling network, so that the operation and maintenance knowledge retrieval accuracy and the fault positioning efficiency are improved.

The invention discloses a medical informatization data intelligent analysis system based on a large model, and belongs to the technical field of medical informatization and artificial intelligence, and the system comprises a data collection and standardization module, a medical knowledge graph construction module, a knowledge enhancement inference analysis module, a data quality evaluation module and a structured output module. The system collects multi-source heterogeneous medical data from an electronic medical record system, a laboratory information system, a medical image information system and a hospital information system, performs standardization processing, automatically constructs a medical knowledge graph, and performs intelligent analysis and reasoning on the medical data by using a knowledge retrieval enhanced medical field large language model. Meanwhile, the data quality is evaluated in four dimensions of integrity, accuracy, timeliness and relevance, and finally a structured analysis report is generated. The multi-source medical data can be effectively integrated, the accuracy and interpretability of medical data analysis are improved, and intelligent support is provided for clinical decision making.

The invention relates to the technical field of medical big data analysis, and discloses a hospital medical record data anomaly analysis method based on big data. According to the method, multi-source medical record data including diagnosis and treatment event records, nursing operation sequences and patient sign monitoring streams in a hospital information system are collected, and structured reforming is carried out. And constructing a medical record element interaction graph based on the reformed data, and detecting an abnormal state conduction path between the data elements through the graph model. And performing hierarchical traceability calculation according to the detected conduction path, positioning an abnormal source and generating a positioning report, and finally outputting a calibration instruction set according to the report. According to the method, the abnormal conduction chain is systematically identified from the correlation perspective, and the root source of the abnormality can be automatically and accurately traced, so that the logicality and the positioning accuracy of the medical record data abnormality analysis are improved.

The invention relates to the technical field of medical information, and discloses an outpatient service reservation management system based on big data, and the system comprises a global heterogeneous data fusion and management module which is responsible for obtaining data and capturing a real-time event through a hospital information system, an electronic medical record system and a real-time sign-in system, and performing cleaning and standardization processing on the data, and constructing a unified patient portrait model. According to the technical scheme, a dynamic doctor-seeing time length prediction model is called to carry out personalized calculation on the time length required by a single appointment, and an initial appointment queue formed by elastic time blocks with different time lengths is generated based on a calculation result, so that the technical effect of accurately matching appointment time length distribution with the actual demand of a patient is achieved; compared with the technical scheme that the out-call time of doctors is uniformly divided into fixed-length time units in the prior art, the defect that time resources of the doctors are idle or follow-up patient queues wait for a long time due to the fact that the preset duration and the actual duration are disjointed is overcome.

The invention discloses an infusion state and vital sign intelligent monitoring method based on multi-modal fusion, and relates to the technical field of sign monitoring, and the method comprises the following steps: respectively collecting infusion dripping speed, pipeline liquid state, infusion pressure and breathing and heart rate signals of a patient; filtering the original signal of each sensor; key features are extracted from the processed signals, wherein the key features comprise parameters including the average dripping speed, the liquid existence proportion, the pressure change rate, the respiratory rate and the heart rate; carrying out normalization and confidence weighted fusion on the extracted infusion and vital sign characteristics, calculating an infusion state index and a vital sign index, and further obtaining a combined abnormal index; performing three-level anomaly judgment according to the fused index; monitoring data and alarm information are uploaded to a hospital information system in real time. By introducing a judgment algorithm based on multi-modal data fusion and confidence coefficient weighting, monitoring and graded alarming of the infusion state and the vital signs of the patient can be achieved.

The invention discloses an image report process AI quality control system based on data fusion and a dynamic rule engine, and the system comprises a data layer module which is used for integrating multi-source data from an image archiving and communication system, a radiation information system and a hospital information system, and carrying out the preprocessing of the data, and forming a high-quality training data pool; furthermore, the image archiving and communication system obtains historical images in a DICOM format and corresponding report data; the radiation information system collects examination application information and doctor diagnosis information. According to the image report process AI quality control system based on data fusion and the dynamic rule engine, full-dimension and high-efficiency accurate quality control is realized: the system can perform comprehensive automatic screening of grammar, text, logic consistency and image-text relevance on an image report by integrating natural language processing, computer vision and a cross-modal matching technology; error correction response time is shortened to a second level from several minutes of each case of traditional manual auditing, and quality control efficiency is remarkably improved.

The invention relates to a gynaecology and obstetrics information processing method and system based on the Internet, and the method comprises the following steps: collecting the doctor seeing data of a gynaecology and obstetrics patient through an Internet terminal, and carrying out the structural marking of key fields to form a structural data table; performing symptom classification based on the table, judging examination requirements, and generating an examination item list; obtaining an examination result through a hospital information system, and integrating the examination result with the structured data table to form a patient comprehensive file; and sending a sharing request to a preset collaborative department based on the archive, and after obtaining a complete feedback opinion, performing supplementary archiving to form a shared archived archive, thereby solving the technical problems that an existing information processing mode generally depends on manual input and experience judgment, and the subjectivity is strong and the standardization degree is insufficient in links such as symptom identification and examination item recommendation.

The invention provides an anesthesia auxiliary system supporting personalized administration and risk early warning. A hardware adaptation layer of the anesthesia auxiliary system adopts a general protocol and a customized driving mode; the data layer realizes acquisition, cleaning, storage and sharing of multi-source data, constructs an anesthesia whole-process data pool, and provides data support for algorithm operation; the core function layer utilizes an algorithm to run through the whole process of decision making, early warning and control to realize intelligent anesthesia management; and the interaction layer adopts a professional mode and concise mode double-interface design, so that the use requirements of different scenes are met, and the operation efficiency is improved. A multi-modal data acquisition-decision support-drug infusion control-risk early warning-data tracing full-closed-loop software system is designed, a layered decoupling architecture is adopted, and anesthesia equipment and a hospital information system are in butt joint through a standardized interface. According to the core improvement point, multi-modal data acquisition is supplemented, a data closed loop is perfected, algorithms such as off-line reinforcement learning, LSTM look-ahead early warning and fuzzy logic control are mainly integrated, and data driving and knowledge driving double-wheel decision making is achieved.

The invention relates to the technical field of medical instruments, in particular to an intelligent weighing mattress system integrating pressure sensing and data processing and a weighing method. The method comprises the following steps that a pressure sensor array collects pressure distribution signals in real time and converts the pressure distribution signals into corresponding analog electric signals; the controller receives the analog electric signals output by the pressure sensor array, performs analog-to-digital conversion processing and performs filtering processing to obtain filtered effective digital pressure data; the controller performs calibration operation on the effective digital pressure data and performs data fusion processing in combination with the mounting position parameter and the sensitivity parameter corresponding to the mattress body so as to calculate real-time weight data of the bearing object; the data transmission module receives the real-time weight data output by the controller, carries out packaging processing, sends a generated weight data transmission packet to a hospital information system for unpacking and analysis, and generates a weight monitoring report. According to the invention, the weight of a bedridden patient can be monitored in real time and uploaded to a hospital information system.

The invention relates to the technical field of maternal and fetal medicine, in particular to a regional maternal and fetal medicine congenital structure anomaly risk assessment system based on big data. A regional feature quantification module; a risk assessment model module; an interpretability analysis module; and a streaming update module. According to the scheme, deep integration and unified representation of individual information and regional macroscopic attributes of pregnant and lying-in women are realized by constructing a multi-source heterogeneous data fusion and regional feature quantification mechanism. The system adopts a multi-protocol interface to access a hospital information system, an environment monitoring platform and a health statistics database, completes standardized cleaning and integrated processing of cross-domain data, and converts multi-dimensional indexes such as regional environment, medical resources, social economy and the like into low-dimensional dense feature vectors through a macroscopic data aggregation and ridge regression coding technology. The feature expression ability and the regional adaptability of the model are significantly enhanced, and effective data are provided for evaluating the risk of the innate structure anomaly of pregnant and lying-in women under different geographical backgrounds.

The invention provides a hospital information system user authority management method, electronic equipment and a program product, and relates to the technical field of computers. The method disclosed by the invention comprises the following steps: in response to a user login event, acquiring permission information of a user from an RBAC module of a hospital information system; based on the permission information, generating a permission description in a natural language description form; adding the permission description into a system cue word, and inputting the system cue word into a large language model; receiving an input request of a user; calling a large language model to process the input request, and generating a tool calling request; according to the permission information of the user, performing permission verification on the tool calling request to obtain a permission verification result; and managing the user permission according to the permission verification result.

The application discloses an osteoporosis risk grading prediction method based on clinical prior logic gating, acquires multi-modal clinical data of a patient to obtain a standardized feature vector group, constructs and trains an osteoporosis risk grading prediction neural network model, including a double-flow feature coding module, a logic gating fusion module and a cascaded classification prediction module, inputs the standardized feature vector group after splicing processing to the trained neural network model, and outputs an osteoporosis risk grading prediction result. The application converts the diagnosis logic in the clinical guideline into an attention gating mechanism in the neural network by designing a double-flow architecture, and combines a screening-grading cascaded strategy, so that the existing structured data (demography, test single, medical history) in the hospital information system can be directly used to realize low-cost, high-precision and clinically interpretable osteoporosis risk grading without additional image examination.

The invention relates to the technical field of medical informatization, in particular to a comprehensive rehabilitation service informatization integration method and system, and the method comprises the steps: obtaining multi-source heterogeneous patient rehabilitation data distributed in a hospital information system, a rehabilitation evaluation system, rehabilitation treatment equipment, wearable equipment and an electronic medical record; performing standardization processing on the multi-source heterogeneous patient rehabilitation data based on a preset unified rehabilitation data model; analyzing, cleaning and mapping the multi-source heterogeneous patient rehabilitation data into standardized patient rehabilitation data conforming to a unified rehabilitation data model in real time through a special data adapter deployed in a multi-protocol data interface layer; and by using a bidirectional synchronous data bus based on an event-driven architecture, issuing the standardized patient rehabilitation data to a specified rehabilitation device or client through the bidirectional synchronous data bus and an instruction generated by the central data warehouse. According to the invention, multi-source heterogeneous data from different systems and devices can be integrated to form a comprehensive, continuous and real-time health view for patients.

The application discloses a bedside in-and-out hospital one-stop settlement method based on a ward nurse station and a hospital information system thereof, wherein a medical insurance settlement special line is extended and connected to the ward nurse station, and multiple operation permissions such as in-hospital registration, medical insurance settlement, fee collection and discharge handling are configured for nurses; the nurses complete patient identity verification, in-hospital registration and prepayment collection in front of the patient bed through a nursing PDA; after a doctor issues a discharge order, the system automatically pushes the task to the nurse station, the nurse initiates a settlement instruction, the system automatically calls a medical insurance interface to complete real-time segmented settlement and generates an electronic settlement sheet; the patient completes more refund and less supplement through aggregated payment, and the remaining prepayment is returned along the original route; the system prints a settlement voucher and automatically updates a bed state, the application moves the in-and-out hospital settlement service to the bedside, realizes zero running and zero queuing of the patient, significantly improves settlement efficiency and speeds up bed turnover, and simultaneously guarantees medical insurance compliance and operation safety through abnormal interception and biological recognition verification.

The embodiment of the invention discloses a hospital information system access control method and system based on multi-factor authentication, and the method comprises the steps: obtaining an access request of a user for a hospital information system, and determining a medical data type corresponding to the access request; constructing a multi-factor authentication candidate factor set; respectively acquiring a privacy intruding attribute and a security contribution attribute of each authentication factor; constructing a partial order relationship between authentication factors on the premise that the privacy invasion attribute and the security contribution attribute have conflict constraints, and eliminating the authentication factors dominated by other authentication factors on the privacy invasion attribute and the security contribution attribute at the same time to generate a non-dominated authentication factor set; selecting authentication factors from different attribute types from the non-dominated authentication factor set to form an authentication factor combination; and authenticating the access request based on the authentication factor combination, and controlling the access authority to the hospital information system according to an authentication result. According to the invention, access control considering privacy protection and system security is realized.

The invention discloses a multi-source information warning and reminding system and method for a smart ward, and the system comprises a data collection and processing module, a data fusion and analysis module, a data warning and reminding module, a warning data storage module, and a user interaction module. The data fusion and analysis module is connected with the data collection and processing module and the data warning and reminding module, and the warning data storage module and the user interaction module are both connected with the data warning and reminding module. By integrating the Internet of Things equipment and the hospital information system, the state of a patient is comprehensively perceived, the data fusion and intelligent analysis technology is utilized to carry out accurate risk study and judgment, efficient warning is realized through a collaborative distribution mechanism, the system is continuously self-optimized according to processing feedback of medical staff, and the medical staff can carry out medical care on the patient. An intelligent clinical decision support closed loop is constructed, conversion from passive response to active early warning is realized, and the method has the characteristics of comprehensiveness, accuracy and high efficiency.

This invention provides an intelligent delivery room care system integrating multimodal environmental control based on sound, light, and temperature, belonging to the field of medical care equipment technology. By integrating multimodal environmental sensing and control capabilities based on sound, light, and temperature, combined with real-time analysis of the mother's physiological and behavioral states, this invention achieves intelligent, personalized, and contextualized management of the delivery room environment. Its main advantages include: significantly reducing the mother's anxiety and pain perception during childbirth, increasing the success rate of natural childbirth; reducing the burden of environmental control operations on medical staff, improving nursing efficiency; supporting adaptive environmental switching across multiple stages and scenarios, meeting the needs of the entire cycle from labor to postpartum recovery; ensuring the dignity of the mother and data security through non-invasive monitoring and privacy protection design; and a modular system design that facilitates integration with existing hospital information systems (HIS) and intelligent ward platforms.

The invention discloses a doctor shift change data processing method and device, terminal equipment and a storage medium. The method comprises the following steps: acquiring a plurality of shift exchange data; wherein each piece of shift change data comes from a hospital information system, a laboratory information system, an image archiving and communication system, a surgical anesthesia information management system or a mobile nursing information system; searching a corresponding target data matching rule from a data matching rule base according to all the shift exchange data; determining a corresponding target data processing strategy according to the target data matching rule; and processing all the shift change data according to the target data processing strategy. The shift change data is automatically processed according to the data matching rule, and time and labor cost are greatly saved.

The invention discloses a VTE occurrence risk assessment device. The device comprises a data acquisition module, a data analysis module and an early warning module, the data acquisition module is used for automatically acquiring the age, height and weight of the patient from the hospital information system, acquiring the past medical history, operation duration, family history and symptom signs of the patient from the electronic medical record system and acquiring the laboratory examination result of the patient from the laboratory information system when the evaluation time arrives; the data analysis module automatically evaluates the VTE occurrence risk level of the patient according to the obtained data; and the early warning module automatically generates a corresponding alarm message when the VTE occurrence risk level of the patient is a high risk level, and visually displays the alarm message. According to the method and the system, the assessment result of the VTE generation risk is generated by automatically analyzing related data, so that the time cost of manual acquisition and statistics of nurses is greatly reduced, and the assessment efficiency of the VTE generation risk is improved.

This application discloses a method and system for access control of a hospital information system based on multi-factor authentication. The method includes: obtaining a user's access request to the hospital information system and determining the medical data type corresponding to the access request; constructing a set of candidate multi-factor authentication factors; obtaining the privacy intrusion attribute and security contribution attribute of each authentication factor; under the premise of conflict constraints between the privacy intrusion attribute and the security contribution attribute, constructing a partial order relationship between the authentication factors and eliminating authentication factors that are simultaneously dominated by other authentication factors in both the privacy intrusion attribute and the security contribution attribute, to generate a set of non-dominated authentication factors; selecting authentication factors from different attribute types from the set of non-dominated authentication factors to form an authentication factor combination; authenticating the access request based on the authentication factor combination, and controlling access permissions to the hospital information system according to the authentication result. This application achieves access control that balances privacy protection and system security.

Cardiopulmonary resuscitation demands rapid and precise responses, particularly in hospital emergency departments. The "Automated Resuscitation Trolley Alert and Drug Dosage System" is designed as an add-on compatible with various resuscitation trolleys. The system features a powerful central processing unit, a liquid-resistant capacitive touchscreen, an audio-visual alert system with high-power LEDs, and communication modules for hospital network integration. It uses artificial intelligence and machine learning algorithms to calculate drug dosages based on patient information and monitoring data. The audio-visual alert system reduces medical team response times in emergencies. Connectivity to hospital information systems enables quick access to patient data and automatic logging of actions. By enhancing precision and speed in drug administration, minimizing human errors, and improving team coordination, this invention significantly improves the quality of emergency services and the success rate of resuscitation procedures.

This invention discloses a method and apparatus for intelligent task navigation and multi-dimensional collaborative management, applicable to the optimization and execution control of complex workflows, such as hospital information systems and intelligent systems. The method achieves personalized task generation, multi-role collaborative task allocation, and dynamic monitoring and optimization in complex scenarios by constructing a multi-level knowledge graph, applying the fully discrete finite element method, the nonlinear GCR-type Krylov subspace method, and the unfitted Green's function method.

The application provides a hospital intelligent guiding system based on a dynamic programming algorithm, and belongs to the technical field of computer data processing.The system precisely calculates the underlying physical movement cost by using an edge computing gateway combined with an A* algorithm, and fuses the underlying physical movement cost with the estimated waiting time pulled from a hospital information system in real time, thereby constructing a multi-dimensional space value map.The system solves a Hamilton circuit problem with constraints by using a dynamic programming algorithm, can plan a global optimal access sequence with the least overall time consumption for a patient with multiple to-be-handled tasks at one time, greatly reduces the patient's in-hospital blind groping, invalid return and long-time queuing and waiting, can capture a state update vector in real time, instantaneously executes local deep optimization with the current node of the patient as a new starting point, and pushes the dynamically adjusted alternative scheme to a terminal, thereby effectively avoiding the patient from being trapped in a long-time stagnation dilemma due to information lag.

The invention discloses a multi-dimensional physiological signal monitoring system for mental stress of nursing personnel. The system comprises a signal acquisition module, a context acquisition module, a processing analysis module and an output module. The signal acquisition module is used for acquiring multi-dimensional physiological data such as an electrocardiosignal, a motion signal and an environment signal of a nurse in real time; the context acquisition module acquires a clinical operation log from a hospital information system; the processing analysis module is used for distinguishing psychological pressure from physiological interference through a multi-modal signal fusion filtering technology, intelligently associating an effective pressure event with clinical operation and determining the context of a pressure source; and the output module is used for generating a personalized pressure analysis report and a management instrument panel containing the clinical work context. The problems that in the prior art, pressure monitoring specificity is poor, and a pressure source is unknown are solved, accurate monitoring and intelligent source tracing of the psychological pressure of nursing personnel in a real clinical environment are achieved, and a scientific basis is provided for individual pressure management and organization health intervention.

The invention provides a diagnosis and treatment full-cycle intelligent closed-loop management method and system, and relates to a data processing technology and analysis of early-stage data uploaded by an electronic information system, the electronic information system can be a hospital information system, an electronic medical record system, a laboratory information system and the like, permission information is responded, and a state comparison structure is constructed; constructing a standard comparison structure based on the reference data, performing branch comparison on the state comparison structure and the standard comparison structure, and generating comparison information for early warning of high-risk medium and high risks; executing corresponding stage operation based on the progress stage of the comparison information, wherein the progress stage comprises a preoperative stage, a middle stage and a later stage of anesthesia induction; the method comprises the steps of performing visualization processing on perioperative period management and stage operation corresponding to the perioperative period management, generating a visual time sequence chain, receiving change information of an electronic information system user side on the visual time sequence chain, generating a visual feedback chain and performing medium-high risk early warning.

The application discloses an integrated intelligent mobile nursing cart, which comprises a cart body and an intelligent part arranged on the cart body, wherein the intelligent part comprises a code scanner, a display screen, an RFID reader-writer, a wireless communication module and an electronic information operation layer; the display screen, the RFID reader-writer and the wireless communication module are connected with the electronic information operation layer respectively; the code scanner is connected with the display screen; the wireless communication module is connected with a hospital data exchange platform through a wireless network; the electronic information operation layer sends a query request to each business system and receives returned data through the hospital data exchange platform, and meanwhile, the nursing execution result is returned to the hospital data exchange platform. The application integrates a high-performance electronic information operation layer, optimizes a nursing service process, improves the clinical nursing work efficiency, reduces the work load of nurses, realizes the sharing of all information in the whole nursing process through multi-port input, integrates medical nursing resources, and realizes the deep integration with a hospital information system.