69 results about "Nursing care quality" patented technology

The invention relates to the technical field of medical care, in particular to a pediatric care quality evaluation method based on multi-modal data interaction. The method comprises the steps of multi-modal data acquisition, data preprocessing, nursing behavior feature analysis, infant state evaluation, and nursing quality scoring and feedback. According to the scheme, the multi-source heterogeneous data in the nursing process is collected, the ResNet50 model, the Glove model and the Mel-frequency cepstral coefficient are used for preprocessing and feature extraction of the multi-modal data of the image, the audio and the text, and the integrity and the analysis efficiency of feature fusion are improved; according to the scheme, a multi-granularity feature interactive fusion method is adopted, key features in the nursing process are extracted and fused from multiple dimensions, and the nursing behavior features and the infant state features are comprehensively obtained, so that the accuracy and the intelligent level of nursing quality evaluation are remarkably improved, and real-time monitoring and scientific feedback support of the nursing process are achieved.

The invention discloses a medical care data intelligent evaluation system based on multi-modal data fusion, and belongs to the technical field of medical care. The problems that subjective deviation exists in the prior art, evaluation results of different medical workers on the same patient may be different, the medical data source is single, and patient information cannot be comprehensively reflected are solved. Through real-time feedback of nursing personnel, the frequency of abnormal data in a feedback result within a period of time is analyzed, so that the updating frequency of the model is dynamically adjusted, and misjudgment caused by model deviation is reduced; according to the method, the abnormal data in the multi-modal data are identified by calculating Z-score, the time sequence data are set to be high priority, and the abnormal data at the high priority are preferentially fed back to the nursing personnel, so that the response speed of the nursing personnel to abnormal conditions is increased, the distribution of nursing resources is optimized, and the nursing efficiency is improved. Therefore, nursing personnel can deal with emergencies in time, and nursing quality and patient safety are improved.

The invention discloses an anesthesia awakening state prediction method and system, and the method comprises the steps: firstly constructing a standard prediction model, then obtaining an actual physiological parameter set, generating an actual recovery state parameter set according to the actual physiological parameter set, and generating an initial recovery curve in the standard prediction model; generating a minimum verification circle, and performing primary correction on the initial recovery curve through the minimum verification circle to obtain a corrected recovery curve; according to the correction recovery curve and a standard prediction model, initial prediction waking time is calculated, according to the actual recovery state parameter set and the correction recovery curve, a composite deviation rate is generated, according to the composite deviation rate, secondary correction is carried out on the initial prediction waking time, and prediction waking time is obtained. According to the method, accurate positioning of the wake-up point is realized by correcting the intersection point of the recovery curve and the standard prediction model, and early warning is performed in time, so that the work pressure of medical staff is reduced, the orderly development of medical work can be ensured, and the nursing quality and the operation efficiency of a wake-up ward can be improved.

The invention discloses an emergency rescue room nursing resource dynamic scheduling method and system based on demand prediction, and relates to the technical field of resource dynamic scheduling. The method comprises the following steps: collecting and preprocessing historical emergency room data, and constructing a multi-dimensional feature data set; respectively training an improved GRU model and a Transform model for high-precision prediction of patient inflow and triage level distribution in a future time period, and quantifying a prediction result as standard nursing time; based on real-time nurse data, a multi-target optimization model with the purposes of minimizing patient waiting time, balancing nurse loads, controlling cost and meeting preferences is built, a Pareto optimal scheduling scheme set is solved and generated through a genetic algorithm, and a manager selects a final scheme according to the actual situation; according to the invention, the conversion from passive response to active accurate scheduling is realized, and the operation efficiency, the resource utilization rate and the nursing quality of the emergency rescue room are effectively improved.

A system and method for facilitating a member journey through healthcare service by augmenting stewardship workflow across multiple service areas is disclosed. The system and method includes augmenting the healthcare stewardship workflow by standardizing the healthcare service practices, increasing the quality of care for patients, improving the workflow efficiency of healthcare personnel, reducing the costs associated with providing healthcare services, and enabling the ease of regulatory compliance using machine learning techniques. The system and method provides the healthcare personnel with access to healthcare-relevant and fact-based artificial intelligence powered by machine learning for decision support opportunities to drive recommended care pathways.

The invention provides a multi-mode intelligent analysis internal fistula postoperative rehabilitation nursing method and system, and belongs to the technical field of medical nursing and artificial intelligence crossing. The application aims to solve the problems of single monitoring dimension, subjective risk judgment and static homogenization of the nursing scheme in the existing internal arteriovenous fistula postoperative nursing. The method comprises the following steps: acquiring multi-modal data related to a wound state and a hemodynamic state of an internal arteriovenous fistula; processing the multi-modal data to generate standardized feature data which can be analyzed; generating a risk assessment result about the health condition of the internal arteriovenous fistula; and a preset nursing scheme is dynamically adjusted based on a risk assessment result. According to the method and the device, multi-modal data are fused and an intelligent algorithm is used for collaborative analysis, so that the accuracy and early stage of risk identification can be realized, the individuation and high efficiency of a nursing scheme are realized, and the nursing quality is improved.

The invention relates to a nursing home priority service response method, system and device based on digital twinning, and the method comprises the following steps: collecting health data of old people and state data of nursing personnel, and carrying out the preprocessing of the data; constructing an old people health state dynamic model, a nursing resource dynamic model and an environment path model; coupling the three models to form a digital twin model; calculating a service response priority based on the health score, the waiting time attenuation and the medical history characteristics of the elderly; according to the service response priority, scheduling the matched nursing personnel to carry out service response; and collecting a service execution result after the nursing personnel completes the task, updating the digital twinborn model based on the service execution result, and dynamically adjusting a scheduling strategy. According to the invention, real-time mapping and dynamic optimization of the health state of the elderly, the position of the nursing personnel and the environment path information in the nursing home are realized, and the service response efficiency, the resource scheduling accuracy and the nursing quality are remarkably improved.

The invention relates to the technical field of extubation action recognition and early warning systems, and discloses a patient unplanned extubation action recognition and early warning system based on wrist strap equipment, the system comprises the wrist strap equipment worn on the wrist of a patient, and the equipment is internally provided with an action sensor, a processor and a communication module. The action sensor is used for detecting hand actions of a patient, the processor analyzes data of the sensor to recognize non-planned extubation actions, and once potential extubation actions are recognized, the system immediately gives out early warning to medical staff in a sound-light alarm and wireless communication mode. The method has the advantages of high recognition accuracy, real-time early warning, protection of patient privacy, reduction of burden of medical staff, improvement of medical safety and the like, is suitable for various patients in hospitals, particularly patients in intensive care units, is beneficial to reduction of the incidence rate of non-planned tube drawing events, reduction of adverse nursing events, reduction of harm to the patients, and is beneficial to popularization and application. The nursing quality is improved and the satisfaction degree is improved.

The invention provides a nursing quality management and control system based on multi-modal data, relates to the field of intelligent nursing, and adopts a data processing technology based on artificial intelligence to perform comprehensive analysis on a set described by acquired nursing feedback texts and an environment state image of a target inpatient area. Therefore, nursing feedback text association semantics related to a plurality of target patient objects and environment state characteristics of the target inpatient area are captured, and nursing quality management suggestions are intelligently generated based on remarkable interaction representation information between two cross-modal data including the nursing feedback semantics and the environment state of the inpatient area. Therefore, more accurate and effective nursing quality management suggestions can be provided, and more scientific and reasonable nursing quality management can be realized.

The invention relates to an intelligent nursing and monitoring device used after glaucoma filtration, and belongs to the technical field of medical instruments, the intelligent nursing and monitoring device comprises a rigid main frame, the inner side of the rigid main frame is provided with a flexible sealing gasket, the upper portion of the rigid main frame is integrated with a self-adaptive positioning system, and the left side and the right side of the rigid main frame are connected with directional physical nursing execution systems; a microenvironment humidity monitoring system is embedded in the ball head, and the rear side of the frame is connected with an intelligent central control system. The self-adaptive positioning system accurately recognizes eyeball and filtered bubble areas, the directional physical nursing execution system reproduces standardized nursing operation, the microenvironment humidity monitoring system verifies the nursing effect in real time, and the intelligent central control system overall plans all the systems to cooperate and supports remote data transmission. The device can solve the problems of inaccurate postoperative nursing, lagged effect feedback and poor patient compliance, improves the nursing quality, assists in improving the success rate of an operation, and is suitable for families and clinical nursing scenes.

The application discloses a medical care data intelligent evaluation system based on multi-modal data fusion and belongs to the technical field of medical care. The application solves the problems that the existing technology has subjective bias, the evaluation results of different medical staffs for the same patient can be different, and the medical data source is single and cannot comprehensively reflect the patient information. Through the real-time feedback of nursing staff, the frequency of model update is dynamically adjusted by combining the frequency of abnormal data in the feedback results in a period of time, so as to reduce the misjudgment caused by model bias; the abnormal data in the multi-modal data is identified by calculating Z-score, the time series data is set as high priority, and the abnormal data in the high priority is preferentially fed back to the nursing staff, which not only improves the response speed of the nursing staff in the face of abnormal conditions, but also optimizes the allocation of nursing resources, so that the nursing staff can more timely handle the emergency, thereby improving the nursing quality and patient safety.

The invention relates to a nursing device for hemodialysis patients, and belongs to the technical field of medical nursing devices. In order to solve the problems that in the prior art, cost is high, and numbness cannot be improved through active movement, an arm arc-shaped bearing piece, an auxiliary massage mechanism, a hand training piece, an angle adjusting mechanism and a debugging mechanism are arranged, the arm arc-shaped bearing piece is used for supporting the arm of a patient, and the auxiliary massage mechanism is arranged on one side of the arm arc-shaped bearing piece and communicates with the arm arc-shaped bearing piece; the hand training piece is connected to one end of the arc-shaped arm bearing piece, the angle adjusting mechanism is arranged at the bottom of the arc-shaped arm bearing piece and connected with the hand training piece, and the angle adjusting mechanism is matched with the hand training piece to adjust the angle of the arc-shaped arm bearing piece. The debugging mechanism is arranged on the auxiliary massage mechanism and connected with the hand training piece through an air guide pipe. According to the device, the massage strength can be adjusted according to individual requirements of a patient, the arm of the patient can bend and stretch at a micro angle during massage, numbness of the arm during dialysis is avoided, and the nursing quality is improved.

The invention belongs to the technical field of artificial intelligence, and particularly relates to a dynamic body position adjusting and nursing method for elderly disabled people, which comprises the following steps: S1, acquiring multi-dimensional health data including physiological data, skin data and clinical data; s2, establishing a correlation model of the body position combination strategy and the occurrence rate of the pressure sores, and mining the correlation of the body position combination strategy and the health risk; s3, constructing a dynamic body position strategy library, and associating a body position combination strategy with the corresponding multi-dimensional health data by associating a fuzzy weight function; s4, performing comprehensive analysis by adopting a CNN-RNN-Attention fusion model, and accurately evaluating the occurrence state grade of the pressure sores; and S5, performing intelligent execution of the body position combination. According to the invention, the timeliness and accuracy of nursing are greatly improved, the occurrence rate of pressure sores is effectively reduced by 60%, and the nursing quality is remarkably improved.

This invention provides an intelligent anti-extubation vest and its application control method. Through sensor fusion and intelligent control technologies, it upgrades traditional passive fixation to an active protection system, shifting from "post-event handling" to "pre-event warning." Clinical trials show that it can reduce unplanned extubation rates, shorten nurse response times, and significantly improve the safety and quality of care for thoracic surgery patients. This invention achieves active protection through a closed-loop control system of "real-time monitoring - automatic clamping - multi-level alarms," ​​realizing an active anti-extubation mechanism and improving fixation reliability.

The invention discloses an intelligent monitoring and tracing system for intravenous medication allocation nursing quality, and relates to the technical field of intelligent nursing management, and the system comprises a time anchoring module, a conflict sensing module, a number fusing module, a dual-factor code forming module and an entropy gate regulation and control module. The time anchoring module is used for constructing a unified time anchoring chain and establishing a number pool monitoring system; and recording traceability code generation request frequency and request node distribution in a time slice corresponding to the unified time anchoring chain, and generating a high-concurrency interval list according to a recording result. Dynamic hierarchical management of traceability code generation is realized through time anchoring and a conflict perception mechanism, a high-concurrency area is identified in advance, dispersed scheduling is carried out, and code uniqueness and traceability chain continuity are ensured. In combination with serial number fusing, two-factor coding and entropy gate regulation and control mechanisms, cross-node non-repeated coding and adaptive load adjustment are realized, the collision risk is reduced, and the safety and stability of medication tracing are improved.

The invention relates to an optimal evidence-based laparoscopic postoperative shoulder pain standardized nursing process optimization method and device, and the method comprises the steps: collecting the baseline data of a patient before the laparoscopic operation, and the baseline data comprises the demographic information, the medical history information and the operation information; inputting the baseline data of the patient into the trained preoperative individualized shoulder pain risk prediction and grading model, and predicting a risk grading result of the patient; inputting the risk grading result into a trained optimal evidence-based medical evidence rule engine model, and outputting a perioperative period nursing intervention scheme; the optimal evidence-based medical evidence rule engine model comprises a rule engine tree, an intervention strategy library, an intra-operative optimization module, a postoperative analgesia module and a postoperative rehabilitation module. Through the optimal evidence-based medical evidence rule engine model, the nursing intervention scheme in the perioperative period is intelligently output according to the risk level of the patient, and the nursing quality is remarkably improved.

An integrated labor management system is used to monitor laboring patients and their fetus or fetuses during labor and delivery. The system is intended to reduce complications, improve quality labor care and, ultimately, reduce adverse maternal and neonatal outcomes. The system is designed for labor monitoring by caregivers such as obstetricians, nurses, and midwives. By integrating the technologies described, the integrated care delivery system provides a low-cost, fit-for-purpose, highly interoperable and customizable labor management technology package for LMIC settings.

This invention discloses an intelligent fluid intake and output management tool, relating to the field of medical device technology. The platform includes: a fluid intake and output measurement module for real-time collection of patient intake and output data; a data transmission module for transmitting the intake and output data to a mobile management terminal; a fluid intake and output conversion module for acquiring intake and output fluid data; and a data entry module for recording the intake and output fluid data and generating a fluid intake and output report. This invention solves the technical problem of inaccurate patient fluid intake and output records in clinical nursing due to subjective confusion in measurement methods and duplicate or missed recordings. It achieves the technical effect of improving the accuracy and convenience of recording, reducing human error, and ensuring the quality of basic nursing care by automatically converting fluid data and generating standardized fluid intake and output reports.

The invention relates to an ICU bedside pressure sore risk image identification and early warning method. The method comprises the following steps: continuously acquiring images at a preset frame rate before and after the same skin area of a patient is pressed and decompressed to obtain a sequence; extracting color, brightness or texture features of the region from the sequence, comparing the color, brightness or texture features with baseline features before decompression, if a recovery threshold is met, judging that the region is reversible, otherwise, judging that the region is limited in recovery when continuous deviation exceeds a first time length; calculating regional displacement and deformation within a second duration under the condition that the limited state is recovered, and judging that the compression is hidden and continuous when the displacement is smaller than a threshold value; and comparing the characteristics of the region before and after body position adjustment or nursing intervention, and if the characteristics are not improved or deteriorated, outputting a pressure sore high-risk early warning. The method does not need an additional contact type sensor, is suitable for continuous and non-invasive monitoring beside an ICU bedside, can provide early warning in the early stage of formation of pressure sores and even before macroscopic injuries occur, and helps nurses to take targeted intervention measures in time, so that the occurrence rate of the pressure sores is reduced, and the nursing quality and the working efficiency of the ICU are improved.

The invention discloses an intelligent lying and defecating nursing system and method, and relates to the technical field of medical nursing, and the system comprises a lying toilet unit, a camera unit, a washing and nursing unit, a flushing unit, a suction unit and a drying unit; the camera unit is used for acquiring images of a dirt bearing base of the lying toilet unit in real time, acquiring cleaning management data in the lying excrement nursing process through a sensor array arranged on the lying toilet unit, and calculating and analyzing to obtain a flushing index and a cleaning index of the excrement flushing unit; according to the method, a cleaning index multi-dimensional evaluation mechanism is introduced, so that quantitative judgment on the cleaning degree is realized; the flushing amount threshold value and the cleaning upper limit threshold value are set, cleaning is automatically stopped when the cleaning degree reaches the standard after single-time flushing, and when the cleaning degree does not reach the standard, the amount of clean water extracted again is dynamically adjusted based on the first cleaning coefficient and the second cleaning coefficient, the dirt receiving base is cleaned again, and the lying defecation nursing quality of a user is greatly improved.

The invention discloses a grading intelligent evaluation system and method for patients in an anesthesia recovery period, belongs to the technical field of anesthesia, and solves the problems that subtle changes of numerous physiological parameters of the patients are difficult to comprehensively and continuously monitor by adopting a traditional evaluation mode and depending on self-evaluation of indexes of a monitor and the like at present; the method comprises the following steps: collecting physical sign monitoring data of a patient in real time based on a sensor and an Internet of Things technology, carrying out multi-dimensional parallel evaluation analysis on the physical sign monitoring data of the patient by an anesthesia recovery period patient evaluation model, and outputting an evaluation analysis result of the patient. Judging whether the real-time state evaluation level exceeds a preset patient risk threshold value or not; according to the method, the anesthesia recovery period patient evaluation model is used for carrying out multi-dimensional parallel evaluation analysis on the physical sign monitoring data of the patient, the nursing grading requirement of the patient is judged in an intelligent mode, objectivity and scientificity of nursing grading decision making are ensured, nursing quality is improved, complication risks are reduced, and meanwhile the comfort degree and satisfaction degree of the patient are improved.

The present invention relates to a nursing home priority service response method, system and device based on digital twins, comprising the following steps: collecting health data of the elderly and status data of caregivers, and preprocessing the data; constructing a dynamic model of the elderly's health status, a dynamic model of care resources and an environmental path model; coupling the above three models to form a digital twin model; calculating the service response priority based on the elderly's health score, waiting time decay and medical history characteristics; scheduling matching caregivers to respond to the service according to the service response priority; collecting the service execution results after the caregivers complete the task, and based on the service execution results, updating the digital twin model and dynamically adjusting the scheduling strategy. The present invention realizes real-time mapping and dynamic optimization of the health status of the elderly, the location of caregivers and the environmental path information in the nursing home, significantly improving the service response efficiency, resource scheduling accuracy and care quality.

The invention relates to the field of nursing management, and discloses a neurosurgical nursing management system based on cloud computing, which is used for solving the problem of data conflict or data synchronization delay when nursing management is carried out according to patient information, and comprises the following steps: monitoring and collecting initial multi-source data; the multi-source data comprises vital sign data, postoperative medication records, nursing observation records and postoperative image data, performing synchronous processing on the initial multi-source data to obtain synchronous multi-source data, performing data conflict processing on the synchronous multi-source data to obtain actual multi-source data, and storing the actual multi-source data into a database; according to the method, the actual multi-source data is subjected to data integration to obtain patient integration information, data analysis is performed according to the patient integration information, health early warning is generated, personalized nursing tasks are designed according to the patient integration information, and the tasks are allocated to related nursing personnel, so that the accuracy of acquiring the patient information is effectively improved, and the nursing quality and the treatment effect are improved.

The utility model belongs to the technical field of medical supplies, and particularly discloses a constraint robe for delirium patients. The robe comprises a robe body, a lining is arranged in the robe body, fixing assemblies are arranged on the two sides of the robe body and the two sides of the lining, the lining is located in the robe body, the two sides of the robe body are connected with gloves, and restraining assemblies are arranged in the two gloves. The situation that a patient takes off a pulse oxygen clamp in gloves and digs out the net face end is avoided, the nursing problem after a delirium patient is covered with a quilt is solved, the observation blind area of a nurse is reduced, the patient is prevented from rubbing off a pipeline in the quilt, stimulation caused by the fact that the patient lifts the quilt due to body temperature changes after the operation is avoided, and therefore the adverse effect on postoperative recovery is reduced. Meanwhile, nurses can conveniently observe the condition of the patient, unnecessary stimulation of the patient is reduced, more comprehensive and effective constraint and protection are provided for the delirium patient, and the nursing quality and the rehabilitation effect of the patient are improved.

The invention discloses an intent recognition system and method for disabled old people based on gaze and environment interaction, and belongs to the technical field of intelligent old people care and artificial intelligence. The invention aims to solve the problem of difficult communication of disabled old people caused by language and dyskinesia. The system comprises a multi-modal data acquisition unit which is used for acquiring staring target sequences and multi-dimensional situation information such as physiology, time, space and the like of old people; the situation feature fusion and construction unit is used for integrating the multi-source heterogeneous data into structured comprehensive situation representation; the core of the intention reasoning unit is a large language model, and the intention reasoning unit is used for carrying out deep semantic understanding and logical reasoning on the comprehensive situation and generating a candidate intention list with confidence; and the man-machine interaction output unit is used for presenting the recognition result to nursing personnel. According to the method, the staring behaviors and the rich situation information are deeply fused, the powerful reasoning ability of the large language model is utilized, the complex and dynamic intentions of the disabled old people can be accurately recognized in a natural and low-cognitive-load mode, and the communication efficiency and the nursing quality are remarkably improved.

The invention relates to a full-automatic sound control respiratory tract sputum cleaning device special for old people, and belongs to the technical field of medical instruments, the device comprises a fixed base, an inflatable flexible limiting pillow integrated with a multi-mode sensor is arranged on the fixed base, and the inflatable flexible limiting pillow is used for supporting the head of a patient and collecting physiological signals; the double-shaft linkage positioning mechanism is arranged above the fixed base, comprises a horizontal sliding base and a semi-arc sliding arch frame, and is used for driving the execution assembly to move; the execution assembly comprises an automatic telescopic sputum aspirator and an infrared vision fusion positioning module and is used for accurate positioning and operation. The central controller is integrated in the equipment and used for processing multi-mode signals, intelligently making decisions and coordinating actions of all mechanisms. The respiratory tract secretion state early-stage automatic identification and on-demand intervention can be achieved, safe and soft whole-process automatic sputum clearing operation is completed through accurate positioning and force feedback control, the aspiration pneumonia risk is effectively reduced, the discomfort of a patient and the workload of nursing personnel are relieved, and the nursing quality and efficiency are improved.

The utility model discloses a portable nursing inspection tour assembly, which belongs to the technical field of medical instruments and comprises a machine body, a clamping plate, a machine cover, a switch button, a lithium battery block, a telescopic nurse watch, a charging port, a lamp hose, a tricolor lamp and a pupil contrast ring. Through cooperative use of the machine body, the clamping plate, the machine cover, the switch button, the lithium battery block, the telescopic nurse watch, the charging port, the lamp hose, the three-color lamp and the pupil contrast ring, the telescopic nurse watch, the three-color lamp and the pupil contrast ring are integrated into an integrated portable inspection tour device, so that the inspection tour device is guided by clinical requirements; therefore, clinical requirements can be taken as a guide, light source scene division precise adaptation and tool integration are achieved, patient experience and nurse occupational health are both considered, nursing quality and efficiency are improved, the problems that nurses are inconvenient to operate, and nursing operation efficiency is low are solved, and practicability of the device is improved.

The invention relates to the technical field of image processing, in particular to an intelligent medical care interaction platform system based on an image processing technology. The method comprises the following modules: a data acquisition module, a target identification module, a nursing behavior identification module and an auxiliary prompt module. The method specifically comprises the following steps: respectively acquiring local camera data and infrared sensing data of a ward area; according to the local camera data, a to-be-nursed target and a nursing execution target are identified, and the effective behavior interaction time of the nursing execution target and the to-be-nursed target is determined in combination with the infrared sensing data; comparing the interaction behavior characteristics in the effective behavior interaction time with a preset nursing behavior label, and determining the suitability of the current nursing behavior type; and screening a connection nursing behavior tag from the nursing behavior tags according to the suitability of the current nursing behavior type. Under high-frequency nursing scenes such as intensive care, omission risk and operation error rate can be reduced, and nursing safety and nursing quality are integrally improved.

The invention relates to the technical field of medical nursing, discloses a nurse hierarchical management system for gynecological nursing management, and aims to scientifically and objectively evaluate the nurse ability and perform task allocation and personalized training according to the nurse ability. The system comprises a nurse information input module used for collecting nurse basic information and the like; the ability evaluation module is used for constructing a model to evaluate professional skills and comprehensive ability of nurses; the task distribution module is used for matching according to the ability evaluation result and the nursing task requirement; the training suggestion module is used for providing personalized training suggestions by adopting a decision tree algorithm; and the performance management module is used for performing performance evaluation according to the task completion condition and the training progress. According to the system, through data analysis and an optimization algorithm, reasonable distribution of nurse resources is realized, the nursing quality is improved, the growth requirements of different nurses are met, and a scientific and efficient solution is provided for gynecological nursing management.

The utility model relates to the technical field of medical instruments, and particularly discloses a ventricular drainage tube placing frame which comprises a sliding frame, a sliding seat is connected to the outer side of the sliding frame in a sliding mode, an adjusting ring is connected to the outer side of the sliding frame in a threaded mode, a limiting column is arranged on the outer side of the sliding frame, and a laser positioner is arranged at one end of the sliding seat. A graduated scale is fixedly connected to the top end of the sliding seat, a hook frame is slidably connected to the outer side of the graduated scale, an adjusting mechanism used for adjusting the height of the hook frame is arranged in the hook frame and comprises a rotating column, a rotating piece and an extrusion block, and the outer side of the rotating column is in threaded connection with the interior of the hook frame. Adjustment can be carried out according to the specific condition of a patient, visual inspection and operation depending on feeling are not needed any more, the ventricular drainage tube can be placed more accurately, the operation method of nurses is unified, the operation method is more standardized, and the nursing quality is improved.