An intelligent monitoring and tracing management method for SPD medical consumables in operating rooms

Abstract

The present invention relates to the technical field of consumables management, and discloses an intelligent monitoring and tracing management method for SPD medical consumables in an operating room; the method comprises: if entering a tracing management state, extracting a tracing feature from a retrieval event, marking a tracing node, obtaining comprehensive retrieval data of the tracing node, calculating a node abnormality coefficient, issuing an early warning tracing prompt, marking an abnormal node, marking an abnormal parameter of the abnormal node, and formulating a tracing management mode according to the abnormal node; compared with the prior art, the present invention can simulate and display the retrieval and use process of consumables in retrieval and use in an integrated manner, and can accurately identify the abnormal points of consumables in the process of retrieval and use, formulate a tracing management mode that conforms to the abnormal retrieval and use of consumables, and achieve the effect of accurately tracing the original position of the abnormal situation of the consumables in retrieval and use, thereby ensuring that the medical consumables in the operating room can be efficiently monitored and traced.

Description

Technical Field

[0001] The present invention relates to the technical field of consumables management, and more specifically, to an intelligent monitoring and tracing management method for SPD medical consumables in an operating room. Background Art

[0002] SPD refers to the supply and distribution management of operating rooms. It is the specific application of the concept of integrated logistics supply in hospital logistics management under the background of "zero consumables markup" in public hospitals. It achieves the effect of full-process, full-process and traceable management, thereby facilitating the efficient, precise and low-cost management of medical consumables, and effectively reducing the hospital's investment cost in the management of medical consumables.

[0003] The patent application with reference publication number CN118262886A discloses an intelligent monitoring and tracing management system for medical consumables in operating rooms SPD, which monitors the path tracing status and inventory management status of consumables, thereby comprehensively analyzing the risk level of abnormal consumable management in the system, generating risk warning signals for timely abnormal repair processing, thereby improving the accuracy and refinement of consumable monitoring and tracing management, and then building a dynamic storage management solution for consumables, generating inventory management signals for dynamic optimal setting of consumable reserves, and then deeply analyzing and obtaining the predicted consumption of consumables within the prediction period, and comparing and adjusting in combination with the actual consumption of consumables, thereby continuously and automatically optimizing and upgrading the accuracy of the prediction model, reserving consumables according to the prediction model, avoiding overdue waste caused by excessive inventory, and achieving cost reduction and efficiency improvement of consumable inventory management;

[0004] The existing monitoring and tracing management method traces the path positioning points and movement processes of consumables, obtains and outputs the consumable path information, and realizes abnormal analysis, inventory management, consumable prediction and model optimization processes. Since the amplitude of the change in the path of the consumables during the entire retrieval and use process is random, the length of the consumable traceability path will also change accordingly. When the length of the traceability path is large, there are more data points on the traceability path that can be used for data collection and analysis, resulting in a larger range of data collection and a larger amount of data collection, which reduces the accuracy of data collection and cannot provide accurate and reasonable data support for subsequent abnormal retrieval and use of consumables. It is not conducive to the tracing operation of the original position of the abnormal retrieval and use of consumables, and reduces the monitoring and tracing management efficiency of medical consumables.

[0005] In view of this, the present invention proposes an intelligent monitoring and tracing management method for SPD medical consumables in an operating room to solve the above problems. Summary of the invention

[0006] In order to overcome the above-mentioned defects of the prior art and to achieve the above-mentioned purpose, the present invention provides the following technical solution: an intelligent monitoring and tracing management method for SPD medical consumables in an operating room, applied to an SPD platform, comprising:

[0007] S1: Identify the event status of the retrieved event, which includes the retrieved state and the unretrieved state, and determine whether to enter the traceability management state according to the ratio of the number of retrieved events with the unretrieved state to the total number of retrieved events;

[0008] S2: If the traceability management state is entered, the traceability features are extracted from the retrieved events, the traceability path is planned according to the traceability features, and the traceability nodes are marked in the traceability path;

[0009] S3: Obtain the comprehensive retrieval data of the traceability node, which includes the in-and-out consumption value, the ratio of the in-stock time and the retrieval ratio, and calculate the node abnormality coefficient based on the comprehensive retrieval data;

[0010] S4: Compare the node abnormality coefficient with the preset node abnormality threshold, and determine whether to issue an early warning traceability prompt based on the comparison result;

[0011] S5: If an early warning traceability prompt is issued, a traceability management mode is developed according to the number of abnormal nodes, abnormal parameters are marked from the comprehensive retrieved data, and traceability management of abnormal parameters is performed under the traceability management mode.

[0012] Furthermore, the method for identifying the called state and the uncalled state includes:

[0013] Mark all consumables record events in the database one by one, and query the remark words of all consumables record events through the attribute management system to obtain i remark words;

[0014] The keywords of i remark words are identified one by one through natural language processing technology, and the remark words with keywords such as borrowing, retrieval, expenditure and use are recorded as valid words, and the consumables record events corresponding to the valid words are recorded as retrieval events. A call event;

[0015] Through the status management system, query one by one A status box for the call event is marked a first state value and a second state value of a state box;

[0016] Identify the event state of the calling event corresponding to the state box in which the first state value and the second state value are both 1 as the called state;

[0017] When the first state value and the second state value are not both 1, the event state of the calling event corresponding to the state box is identified as a not called state.

[0018] Furthermore, the method for determining whether to enter the traceability management state includes:

[0019] The number of call events whose event status is the called state is counted, recorded as the call quantity value, and the call quantity value is compared with the total number of call events to obtain the call ratio value;

[0020] The expression for retrieving the percentage value is:

[0021] ;

[0022] In the formula, is the effective proportion value, To retrieve the value;

[0023] When the effective ratio Greater than or equal to the preset effective ratio threshold When the system enters the traceability management state;

[0024] When the effective ratio Less than the preset effective ratio threshold When the traceability management state is not entered, it is determined.

[0025] Furthermore, the traceability features include time features, location features and authority features, and the extraction methods of the time features, location features and authority features include:

[0026] Query the database one by one A data frame of retrieved events, marked The record phrases of the data frame are obtained Record phrases;

[0027] Through natural language processing technology, we can identify The semantics of the recorded phrases are arranged in sequence to generate semantic line groups, and the keywords in the semantic line groups are identified one by one;

[0028] The semantics with the keywords of time, moment and timeliness are recorded as time features, and k time features are obtained;

[0029] The semantics with the keywords of place, location and space are recorded as place features, and k place features are obtained;

[0030] The semantics with the keywords of authority, identity and level are recorded as authority features, and k authority features are obtained.

[0031] Furthermore, the marking method of the traceability node includes:

[0032] Combine and aggregate the time features, location features, and authority features belonging to the same retrieval event to obtain k feature combinations;

[0033] Marking k location points corresponding to the location features on the electronic map in sequence to obtain k initial points, and constructing interpretation frames having a first interpretation unit and a second interpretation unit on the k initial points respectively;

[0034] Import the time feature and the authority feature in the same feature combination as the k location features into the first interpretation unit and the second interpretation unit of the initial point respectively, and obtain k path points;

[0035] According to the order of the time features in the path points, the k path points are numbered in sequence, and a connecting line is established between two adjacent numbered path points to generate a tracing path;

[0036] Identify the attribute states of time features, location features, and authority features corresponding to k path points one by one, and record the path points whose attribute states are all qualified attributes as traceability nodes, and obtain A traceability node.

[0037] Furthermore, the method for obtaining the in-and-out consumption value includes:

[0038] Through the warehouse management system, we can check the consumables one by one. The in-and-out logs of each tracing node can be tracked, and the in-and-out status of the in-and-out logs can be identified;

[0039] Record the in-and-out logs with the status of expenditure and entry as expenditure logs and entry logs respectively, and obtain Expenditure logs and Entries log;

[0040] Through the database to query the consumables one by one Expenditure logs and The number of entries in the log is obtained Expenditure value and Enter the value, The expenditure value and After subtracting the input values ​​one by one, we get The consumption value of inbound and outbound storage;

[0041] The expression of the in-and-out consumption value is:

[0042] ;

[0043] In the formula, For the The inbound and outbound consumption value of each traceability node, For the The expenditure value of the traceability node, For the The entry value of a traceability node.

[0044] Furthermore, the method for obtaining the in-stock time ratio includes:

[0045] Query one by one by timestamp Expenditure logs and The first time that consumables are spent and consumables are entered into the log, respectively. The expenditure time and An entry moment;

[0046] Will Expenditure time to The time between the entry moments is recorded as the expenditure time, and the Length of expenditure;

[0047] Query one by one by timestamp The time corresponding to the time feature in the traceability node is obtained to obtain u candidate moments. After arranging the u candidate moments in chronological order, the candidate moment in the middle is selected and recorded as the node moment to obtain Node moments;

[0048] The duration between two adjacent node moments is counted one by one, recorded as the node duration, and the maximum value of the node duration is recorded as the inventory cycle;

[0049] In the library cycle, After subtracting the expenditure time, we get The length of time in the library and The in-stock time is compared with the in-stock cycle to obtain The ratio of the time in stock;

[0050] The expression of the in-stock time ratio is:

[0051] ;

[0052] In the formula, For the The ratio of the in-stock time of the traceability nodes, is the inventory cycle, For the The expenditure duration of each traceability node.

[0053] Furthermore, the method for obtaining the percentage value includes:

[0054] Through the warehouse management system, all the in-and-out logs are queried, and the in-and-out logs with both expenditure logs and entry logs are recorded as valid logs, and the consumables are counted one by one. The number of valid logs on the traceability node is obtained Valid call values;

[0055] The in-and-out logs that do not have both expenditure logs and entry logs are recorded as invalid logs, and the consumables are counted one by one. The number of invalid logs on the traceback node is obtained Invalid call value;

[0056] Will The valid call values ​​are respectively After adding the invalid call values, we get Get the total value and The valid call values ​​are respectively Compare the total values ​​and get The percentage value is retrieved;

[0057] The expression for retrieving the percentage value is:

[0058] ;

[0059] In the formula, For the The call ratio of the traceability nodes, For the The effective call value of the traceability node, For the Invalid call value for a traceback node.

[0060] Furthermore, the expression of the node abnormality coefficient is:

[0061] ;

[0062] In the formula, For the The node anomaly coefficient of the traceable node, , , is a weight factor greater than 0;

[0063] The determination methods for whether to issue an early warning traceability prompt include:

[0064] Will Node abnormality coefficient The preset node abnormality threshold Compare;

[0065] when Greater than or equal to When the warning is issued, the The traceability nodes are recorded as abnormal nodes, and n abnormal nodes are obtained;

[0066] when Less than When the warning is not issued, it is determined that no warning traceability prompt will be issued.

[0067] Furthermore, the traceability management mode includes a combined traceability mode and an independent traceability mode. The formulation methods of the combined traceability mode and the independent traceability mode include:

[0068] According to the order of the traceability node marking, all traceability nodes are numbered in ascending order, and the numbers of the n abnormal nodes are recorded as abnormal numbers;

[0069] Count the number of abnormal nodes whose abnormal numbers are in adjacent order to obtain adjacent values;

[0070] When the adjacent value is greater than the traceability calibration value, a combined traceability mode is developed;

[0071] When the adjacent value is less than or equal to the traceability calibration value, an independent traceability mode is formulated;

[0072] The marking methods for abnormal parameters include:

[0073] Compare the in-and-out consumption values, in-stock time ratios, and retrieval ratios in the comprehensive retrieval data of n abnormal nodes with the consumption safety value, time safety value, and retrieval safety value one by one;

[0074] When the in-and-out consumption value is greater than the consumption safety value, the in-and-out consumption value is recorded as an abnormal parameter;

[0075] When the in-stock time ratio is less than the time safety value, the in-stock time ratio is recorded as an abnormal parameter;

[0076] When the call ratio is greater than the call safety value, the call ratio is recorded as an abnormal parameter;

[0077] The methods for traceability management of abnormal parameters include:

[0078] When the combined tracing mode is formulated, the abnormal parameters of n abnormal nodes are summarized in turn to generate n abnormal data packets;

[0079] At the same time, the original positions of the abnormal parameters in n abnormal data packets are traced through the SPD platform, and the traced original positions are bound to the corresponding abnormal data packets one by one to obtain n combined traceability sources;

[0080] When an independent tracing mode is developed, the abnormal parameters of n abnormal nodes are arranged in sequence to generate n abnormal data rows;

[0081] According to the order in which the abnormal data rows are arranged, the original positions of the abnormal parameters in the n abnormal data rows are traced through the SPD platform, and the traced original positions are bound to the corresponding abnormal parameters one by one to obtain n independent traceability sources.

[0082] The technical effects and advantages of the intelligent monitoring and tracing management method for SPD medical consumables in operating rooms of the present invention are as follows:

[0083] The present invention identifies the event status of the retrieval event, determines whether to enter the traceability management mode, extracts the traceability feature from the retrieval event, plans the traceability path according to the traceability feature, marks the traceability node in the traceability path, obtains the comprehensive retrieval data of the traceability node, and calculates the node abnormality coefficient according to the comprehensive retrieval data, compares the node abnormality coefficient with the preset node abnormality threshold, determines whether to issue an early warning traceability prompt, marks the abnormal node, marks the abnormal parameters of the abnormal node, formulates the traceability management mode according to the abnormal node, and performs traceability management of the abnormal parameters under the traceability management mode; compared with the prior art, by extracting the traceability features of medical consumables during the retrieval and use process, the influencing data of the consumables during the retrieval and use process can be represented, and the traceability features can be used to A traceability path is constructed to simulate the overall process of retrieval and use of consumables, and it is used as the data collection object for subsequent safety monitoring of consumable scheduling and use, thereby clarifying the data collection scope of consumables retrieval and use and improving the accuracy of data collection. At the same time, the node abnormality coefficient is calculated by comprehensive retrieval data, so that the abnormal points of consumables in the process of retrieval and use can be accurately identified. At the same time, a traceability management model that is consistent with the abnormal retrieval and use of consumables is formulated, so that the original location of the abnormal situation of consumables in retrieval and use can be accurately traced, ensuring that the medical consumables in the operating room can be fully and accurately monitored and traced, preventing the loss and management confusion of medical consumables in the process of retrieval and use, thereby improving the management efficiency of medical consumables. BRIEF DESCRIPTION OF THE DRAWINGS

[0084] Figure 1 A schematic diagram of a process for intelligent monitoring and tracing management of SPD medical consumables in an operating room provided in the first embodiment of the present invention;

[0085] Figure 2 A schematic diagram of an intelligent monitoring and tracing management system for SPD medical consumables in an operating room provided in the second embodiment of the present invention;

[0086] Figure 3 A schematic diagram of a structural diagram of an electronic device provided in Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0087] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0088] Example 1: Please refer to Figure 1 As shown, the method for intelligent monitoring, tracing and managing medical consumables in an operating room SPD described in this embodiment is applied to the SPD platform, and includes:

[0089] S1: Filter out the consumables retrieval events from the database, identify the event status of the retrieval events, and determine whether to enter the traceability management state;

[0090] Retrieval events refer to events stored in the database that can comprehensively represent the overall process of retrieval and use of medical consumables, thereby representing the data information related to the supply and management process of consumables and serving as the basis for further processing of consumables;

[0091] After filtering out the consumables call events, it is necessary to identify whether the call events are in the state of being called for use, that is, to identify the event status of the call events so that the event status can indicate whether the consumables in each call event are called for use;

[0092] The event status includes the called state and the uncalled state; the called state means that the consumables corresponding to the called event have records of being called and used, and the uncalled state means that the consumables corresponding to the called event do not have records of being called and used, so that the calling events of different consumables can be accurately distinguished;

[0093] The identification method of the called state and the uncalled state includes:

[0094] Mark all consumables record events in the database one by one, and query the remark words of all consumables record events through the attribute management system to obtain i remark words; consumables record events refer to data record events about any changes in consumables in the past time period stored in the database, which can comprehensively represent all changes in consumables; and remark words are the true representation of key change information in consumables record events, and achieve the effect of simplifying cumbersome changes;

[0095] The keywords of i remark words are identified one by one through natural language processing technology, and the remark words with keywords such as borrowing, retrieval, expenditure and use are recorded as valid words, and the consumables record events corresponding to the valid words are recorded as retrieval events. A call event;

[0096] Through the status management system, query one by one A status box for the call event is marked The first state value and the second state value of a state box; the state box is used to truly indicate whether the call situation in the call event satisfies the state management system, the first state value is used to indicate the authenticity of the call event, and the second state value is used to indicate the rationality of the call event; the first state value and the second state value are 0 and 1 respectively, when the first state value and the second state value are both 0, it indicates that the authenticity and rationality of the call event are both in a negative state, and when the first state value and the second state value are both 1, it indicates that the authenticity and rationality of the call event are both in a positive state;

[0097] Identify the event state of the calling event corresponding to the state box in which the first state value and the second state value are both 1 as the called state;

[0098] When the first state value and the second state value are not both 1, the event state of the calling event corresponding to the state box is identified as a not called state.

[0099] After identifying the event status of the retrieved event, it can be determined whether to enter the next traceability management state based on the number of different types of event statuses, so that the SPD platform can only execute subsequent execution steps when it enters the traceability management state, otherwise it cannot perform subsequent execution steps.

[0100] The methods for determining whether to enter the traceability management state include:

[0101] The number of call events whose event status is the called state is counted, recorded as the call quantity value, and the call quantity value is compared with the total number of call events to obtain the effective proportion value;

[0102] The expression of effective proportion is:

[0103] ;

[0104] In the formula, is the effective proportion value, To retrieve the value;

[0105] When the effective ratio Greater than or equal to the preset effective ratio threshold , it means that a large number of consumables have been used in the retrieval event. At this time, the retrieval event needs to be traced back to the next step, and it is determined to enter the traceability management state; the preset effective proportion threshold is used to represent the minimum value of the effective proportion value when entering the traceability management state, which can effectively distinguish the size of the effective proportion value, so as to accurately determine whether to enter the traceability management state;

[0106] When the proportion value is retrieved Less than the preset effective ratio threshold , it means that the number of consumables used in the retrieval event is small. At this time, there is no need to perform the next traceability operation on the retrieval event, and it is determined not to enter the traceability management state.

[0107] When entering the traceability management state, the next traceability operation can be carried out, and the medical consumables in the operating room can be inspected and traced. When not entering the traceability management state, the next traceability operation will not be carried out.

[0108] S2: Extract traceability features from the retrieved events, plan a traceability path based on the traceability features, and mark traceability nodes in the traceability path;

[0109] The traceability feature is used to identify the features that affect the safety and stability of the consumables during the retrieval process, and serves as the basis for the subsequent construction of the traceability path, so as to monitor the whole process and the whole cycle of the consumables retrieval process in the retrieval event;

[0110] The traceability features include time features, location features, and authority features; the time feature is used to indicate the time when the consumables are retrieved and used in the retrieval event, and to provide timeline support for the subsequent traceability path; the location feature is used to indicate the location where the consumables are retrieved and used in the retrieval event, and to provide spatial support for the subsequent traceability path; the authority feature is used to indicate the identity of the person who retrieved the consumables in the retrieval event, and to provide authority level support for the subsequent traceability path;

[0111] The extraction methods of time features, location features and authority features include:

[0112] Query the database one by one A data frame of retrieved events, marked The record phrases of the data frame are obtained A record phrase; the data frame is used to represent the data contained in the retrieved event as a whole, while the record phrase is the smallest unit that constitutes the data frame and is used to represent specific data;

[0113] Through natural language processing technology, we can identify The semantics of the recorded phrases are arranged in sequence to generate semantic line groups, and the keywords in the semantic line groups are identified one by one;

[0114] The semantics with the keywords of time, moment and timeliness are recorded as time features, and k time features are obtained;

[0115] The semantics with the keywords of place, location and space are recorded as place features, and k place features are obtained;

[0116] The semantics with the keywords of authority, identity and level are recorded as authority features, and k authority features are obtained.

[0117] After obtaining the time features, location features and authority features, a traceability path can be developed based on the time features, location features and authority features, so that the traceability path can fully represent the retrieval and use process of the consumables in the retrieval event, and provide a basis for data collection for the safety and reliability of the subsequent retrieval and use of consumables;

[0118] After planning the tracking path, in order to facilitate the analysis of the safety and reliability performance data during the use of consumables, it is necessary to mark the appropriate collection points on the traceability path and record the collection points as traceability nodes, so that the traceability nodes can be used as the object points for data collection;

[0119] The marking methods of traceability nodes include:

[0120] Combine and aggregate the time features, location features, and authority features belonging to the same retrieval event to obtain k feature combinations;

[0121] Mark the location points corresponding to k location features on the electronic map in sequence to obtain k initial points, and construct interpretation boxes with a first interpretation unit and a second interpretation unit on the k initial points respectively; the interpretation box is a basic structure for constructing path points, and specific interpretation information can be imported into the interpretation box to interpret it, while the first interpretation unit and the second interpretation unit are basic units for constructing the interpretation box and serve as position limits for the imported interpretation information;

[0122] Import the time feature and the authority feature in the same feature combination as the k location features into the first interpretation unit and the second interpretation unit of the initial point respectively, and obtain k path points;

[0123] According to the order of the time features in the path points, the k path points are numbered in sequence, and a connecting line is established between two adjacent numbered path points to generate a tracing path;

[0124] Identify the attribute states of time features, location features, and authority features corresponding to k path points one by one, and record the path points whose attribute states are all qualified attributes as traceability nodes, and obtain The attribute status is used to indicate whether the attribute of the path point has passed the qualified inspection. The attribute status includes qualified attributes and unqualified attributes. Unqualified attributes indicate that the attribute of the path point has not passed the qualified inspection, and qualified attributes indicate that the attribute of the path point has passed the qualified inspection.

[0125] It should be noted that after the traceability node is marked, the traceability node at this time can be used as the object point for subsequent data collection, thereby providing the original data basis for subsequent consumables monitoring and traceability management, and ensuring the rationality and accuracy of the original data collection object.

[0126] S3: Obtain the comprehensive retrieval data of the traceability node, and calculate the node abnormality coefficient based on the comprehensive retrieval data. The comprehensive retrieval data includes the in-and-out consumption value, the in-stock time ratio, and the retrieval ratio value;

[0127] Comprehensive retrieval data refers to data that can comprehensively represent the retrieval and use of consumables in the retrieval event at each traceability node, thereby accurately representing the overall use of consumables. When consumables are put in and out of the warehouse, retrieved, consumed, or filled at the traceability node, the comprehensive retrieval data will change accordingly, and represent the subsequent retrieval and use safety of consumables on the traceability path;

[0128] Comprehensive retrieval data includes in-and-out consumption value, in-stock time ratio and retrieval ratio;

[0129] The in-and-out consumption value refers to the amount of consumables consumed during the retrieval and storage process of each traceability node, which can be used to represent the consumption of consumables at the traceability node. The larger the in-and-out consumption value, the more consumables consumed during the retrieval and storage process of each traceability node. At this time, the probability of abnormalities in the retrieval and use of consumables is greater, and the consumables need to strengthen monitoring and traceability management, and the node abnormality coefficient is greater;

[0130] The methods for obtaining the inbound and outbound consumption values ​​include:

[0131] Through the warehouse management system, we can check the consumables one by one. The in-and-out logs of each tracing node can be identified, and the in-and-out status of the in-and-out logs can be identified; the in-and-out status is used to truly indicate whether the in-and-out logs belong to out-and-in, and facilitates the subsequent accurate calculation of the in-and-out consumption value. The in-and-out status includes expenditure and entry;

[0132] Record the in-and-out logs with the status of expenditure and entry as expenditure logs and entry logs respectively, and obtain Expenditure logs and Entries log;

[0133] Through the database to query the consumables one by one Expenditure logs and The number of entries in the log is obtained Expenditure value and Enter the value, The expenditure value and After subtracting the input values ​​one by one, we get The consumption value of inbound and outbound storage;

[0134] The expression of the in-and-out consumption value is:

[0135] ;

[0136] In the formula, For the The inbound and outbound consumption value of each traceability node, For the The expenditure value of the traceability node, For the The entry value of a traceability node.

[0137] The in-stock time ratio refers to the ratio of the time that the consumables are stored in the material library during the retrieval and storage process at each traceability node to the total time, which can be used to indicate the length of time that the consumables are in the library at the traceability node. The larger the in-stock time ratio, the larger the ratio of the time that the consumables are stored in the material library during the retrieval and storage process at each traceability node to the total time. At this time, the probability of abnormalities in the retrieval and use of consumables is smaller, and the consumables do not need to strengthen monitoring and traceability management, and the node abnormality coefficient is smaller;

[0138] Methods for obtaining the in-stock time ratio include:

[0139] Query one by one by timestamp Expenditure logs and The first time that consumables are spent and consumables are entered into the log, respectively. The expenditure time and An entry moment;

[0140] Will Expenditure time to The time between the entry moments is recorded as the expenditure time, and the Length of expenditure;

[0141] Query one by one by timestamp The time corresponding to the time feature in the traceability node is obtained to obtain u candidate moments. After arranging the u candidate moments in chronological order, the candidate moment in the middle is selected and recorded as the node moment to obtain Node moments;

[0142] The duration between two adjacent node moments is counted one by one, recorded as the node duration, and the maximum value of the node duration is recorded as the inventory cycle;

[0143] In the library cycle, After subtracting the expenditure time, we get The length of time in the library and The in-stock time is compared with the in-stock cycle to obtain The ratio of the time in stock;

[0144] The expression of the in-stock time ratio is:

[0145] ;

[0146] In the formula, For the The ratio of the in-stock time of the traceability nodes, is the inventory cycle, For the The expenditure duration of each traceability node.

[0147] The call ratio value refers to the ratio of the number of consumables called at each traceability node to the total number of calls in the call event, which can be used to indicate the frequency of the call of consumables at the traceability node. The larger the call ratio value, the more times the consumables are called at each traceability node. At this time, the probability of abnormality in the call and use of consumables is greater, and the consumables need to strengthen monitoring and traceability management, and the node abnormality coefficient is greater;

[0148] Methods for obtaining the percentage value include:

[0149] Through the warehouse management system, all the in-and-out logs are queried, and the in-and-out logs with both expenditure logs and entry logs are recorded as valid logs, and the consumables are counted one by one. The number of valid logs on the traceability node is obtained Valid call values;

[0150] The in-and-out logs that do not have both expenditure logs and entry logs are recorded as invalid logs, and the consumables are counted one by one. The number of invalid logs on the traceback node is obtained Invalid call value;

[0151] Will The valid call values ​​are respectively After adding the invalid call values, we get Get the total value and The valid call values ​​are respectively Compare the total values ​​of the calls and get The percentage value is retrieved;

[0152] The expression for retrieving the percentage value is:

[0153] ;

[0154] In the formula, For the The call ratio of the traceability nodes, For the The effective call value of the traceability node, For the Invalid call value for a traceback node.

[0155] After obtaining the in-and-out consumption values, the inventory time ratio and the retrieval ratio, the node abnormality coefficient can be calculated based on the in-and-out consumption values, the inventory time ratio and the retrieval ratio. The node abnormality coefficient can numerically represent the abnormal degree of retrieval and use of consumables at each traceability node and serve as the basis for subsequent traceability management.

[0156] The expression of node abnormality coefficient is:

[0157] ;

[0158] In the formula, For the The node anomaly coefficient of the traceable node, , , is a weight factor greater than 0;

[0159] in, ,For example, is 0.36, is 0.34, is 0.30; , , The setting is to balance the proportion of in-and-out consumption value, in-stock time ratio and call-out ratio in the node abnormality coefficient, so as to adjust the influence of the balanced in-and-out consumption value, in-stock time ratio and call-out ratio on the node abnormality coefficient.

[0160] S4: Compare the node abnormality coefficient with the preset node abnormality threshold, determine whether to issue an early warning and traceability prompt, and mark the abnormal node;

[0161] After calculating the node abnormality coefficient, the node abnormality coefficient can be compared, and according to the comparison result of the node abnormality coefficient, it can be determined whether there is any abnormality in the retrieval and use of consumables at the traceability node, so as to issue an early warning to the traceability node where the retrieval and use is abnormal, and provide early warning information for subsequent traceability management;

[0162] Whether to issue an early warning traceability prompt is used to indicate whether there is any abnormality in the retrieval and use of the traceability node, so as to accurately indicate the retrieval and use of consumables;

[0163] An abnormal node refers to a node whose node abnormality coefficient of the traceability node is too large, and serves as the target node for subsequent traceability management of the consumables retrieval and use on the traceability node;

[0164] The determination methods for whether to issue an early warning traceability prompt include:

[0165] Will Node abnormality coefficient The preset node abnormality threshold Comparison; The preset node abnormality threshold is used to represent the minimum value of the node abnormality coefficient that needs to be traced when abnormal phenomena occur in the retrieval and use of consumables on the traceability node. It can provide a numerical basis for distinguishing the size of the node abnormality coefficient and serve as a basis for judging and comparing the consumables and each traceability node;

[0166] when Greater than or equal to When the consumables are The node anomaly coefficient on the traceability node is greater than or equal to the preset node anomaly threshold. The probability of abnormality in the process of using the traceability node is high, so the If the usage of the traceability node is traced, a warning traceability prompt will be issued and the The traceability nodes are recorded as abnormal nodes, and n abnormal nodes are obtained;

[0167] when Less than , explain The node anomaly coefficient on the traceability node is less than the preset node anomaly threshold. The probability of abnormality in the process of using the traceability node is small, and there is no need to If the retrieval and use of each traceability node is used for traceability management, it is determined that no warning traceability prompt will be issued and there will be no abnormal nodes.

[0168] S5: Develop a traceability management model based on the number of abnormal nodes, mark abnormal parameters from the comprehensive retrieved data, and perform traceability management of abnormal parameters under the traceability management model;

[0169] The traceability management mode refers to the way of traceability management of abnormal parameters according to the specific distribution of abnormal nodes on the traceability path, and provides guidance for subsequent traceability management of abnormal parameters;

[0170] The traceability management mode includes the combined traceability mode and the independent traceability mode; the combined traceability mode refers to the overall combined traceability management operation of all abnormal parameters on abnormal nodes, and the independent traceability mode refers to the individual independent traceability management operation of all abnormal parameters on abnormal nodes;

[0171] The methods for developing combined traceability models and independent traceability models include:

[0172] According to the order of the traceability node marking, all traceability nodes are numbered in ascending order, and the numbers of the n abnormal nodes are recorded as abnormal numbers;

[0173] Count the number of abnormal nodes whose abnormal numbers are in adjacent order to obtain adjacent values;

[0174] When the adjacent value is greater than the traceability calibration value, the number of abnormal nodes in the adjacent position is large, and the abnormal nodes need to be traced as a whole, and a combined traceability mode is formulated; the traceability calibration value is a value used to limit the size of the adjacent value, and serves as a basis for distinguishing the combined traceability mode from the independent traceability mode; the traceability calibration value is set according to the actual number of abnormal nodes, as long as it meets the use requirements; for example, the traceability calibration value is one-third of the number of abnormal nodes;

[0175] When the adjacent value is less than or equal to the traceability calibration value, the number of abnormal nodes in the adjacent position is small, and the abnormal nodes need to be traced separately and independently, so an independent tracing mode is developed.

[0176] Abnormal parameters refer to specific data that is too large or too small in the comprehensive retrieved data marked as abnormal nodes, and serve as the target data for subsequent traceability management, thereby providing a basis for the execution of subsequent traceability management;

[0177] The marking methods for abnormal parameters include:

[0178] Compare the in-and-out consumption values, in-stock time ratios, and retrieval proportions in the comprehensive retrieval data of n abnormal nodes with the consumption safety value, time safety value, and retrieval safety value one by one; the consumption safety value and retrieval safety value refer to the maximum values ​​of the in-and-out consumption values ​​and the retrieval proportions of the consumables under normal retrieval and use, thereby limiting the upper limits of the in-and-out consumption values ​​and the retrieval proportions; the time safety value refers to the minimum value of the in-stock time ratio of the consumables under normal retrieval and use, thereby limiting the lower limit of the in-stock time ratio; the consumption safety value, time safety value, and retrieval safety value are obtained by collecting the maximum values ​​of the in-and-out consumption values, the minimum values ​​of the in-stock time ratios, and the maximum values ​​of the retrieval proportions of a large number of consumables on the nodes that have not been identified as abnormal in history when they are normally retrieved and used, and then calculating their average values;

[0179] When the in-and-out consumption value is greater than the consumption safety value, it means that the in-and-out consumption value exceeds the maximum value of the corresponding in-and-out consumption value under normal retrieval and use, and the in-and-out consumption value is recorded as an abnormal parameter;

[0180] When the in-library time ratio is less than the time safety value, it means that the in-library time ratio is lower than the minimum value of the in-library time ratio corresponding to normal retrieval and use, and the in-library time ratio is recorded as an abnormal parameter;

[0181] When the call ratio is greater than the call safety value, it means that the call ratio exceeds the maximum value of the call ratio corresponding to the normal call usage, and the call ratio is recorded as an abnormal parameter.

[0182] After developing different traceability management modes, the abnormal parameters on abnormal nodes can be traced according to different traceability management modes, so as to identify and trace the starting position of abnormal phenomena in the process of retrieval and use of consumables;

[0183] The methods for traceability management of abnormal parameters include:

[0184] When the combined tracing mode is formulated, the abnormal parameters of n abnormal nodes are summarized in turn to generate n abnormal data packets;

[0185] At the same time, the original positions of the abnormal parameters in n abnormal data packets are traced through the SPD platform, and the traced original positions are bound to the corresponding abnormal data packets one by one to obtain n combined traceability sources;

[0186] When an independent tracing mode is developed, the abnormal parameters of n abnormal nodes are arranged in sequence to generate n abnormal data rows;

[0187] According to the order in which the abnormal data rows are arranged, the original positions of the abnormal parameters in the n abnormal data rows are traced through the SPD platform, and the traced original positions are bound to the corresponding abnormal parameters one by one to obtain n independent traceability sources.

[0188] In this embodiment, by screening out the retrieval events of consumables from the database, identifying the event status of the retrieval events, and determining whether to enter the traceability management state, the traceability features are extracted from the retrieval events, and a traceability path is planned according to the traceability features, and the traceability nodes are marked in the traceability path, and the comprehensive retrieval data of the traceability nodes are obtained, and the node abnormality coefficient is calculated according to the comprehensive retrieval data, and the node abnormality coefficient is compared with the preset node abnormality threshold to determine whether to issue an early warning traceability prompt, and mark the abnormal nodes, mark the abnormal parameters of the abnormal nodes, formulate a traceability management mode according to the abnormal nodes, and perform traceability management of the abnormal parameters under the traceability management mode; compared with the prior art, by extracting the traceability features of medical consumables during the retrieval and use process, the influencing data of the consumables during the retrieval and use process can be represented. , and construct a traceability path through traceability features, conduct an overall simulation display of the retrieval and use process of consumables, and serve as the data collection object for subsequent safety monitoring of consumable scheduling and use, thereby clarifying the data collection scope in the retrieval and use of consumables and improving the accuracy of data collection. At the same time, by calculating the node abnormality coefficient through comprehensive retrieval data, the abnormal points of consumables in the process of retrieval and use can be accurately identified. At the same time, a traceability management model that conforms to the abnormal retrieval and use of consumables is formulated, and the original position of the abnormal situation of consumables in retrieval and use can be accurately traced, ensuring that the medical consumables in the operating room can be fully and accurately monitored and traced, preventing the loss and management confusion of medical consumables in the process of retrieval and use, thereby improving the management efficiency of medical consumables.

[0189] Example 2: Please refer to Figure 2 As shown, the part not described in detail in this embodiment is described in the first embodiment, which provides an operating room SPD medical consumables intelligent monitoring and tracing management system, which is applied to the SPD platform and is used to implement an operating room SPD medical consumables intelligent monitoring and tracing management method, including a state determination module, a path planning module, a coefficient calculation module, an early warning determination module and a tracing management module, wherein each module is connected via a wired or wireless network;

[0190] A status determination module is used to identify the event status of the retrieved event, which includes a retrieved state and a non-retrieved state, and determine whether to enter the traceability management state according to the ratio of the number of retrieved events whose event status is the non-retrieved state to the total number of retrieved events;

[0191] The path planning module is used to extract the traceability features from the retrieved events, plan the traceability path according to the traceability features, and mark the traceability nodes in the traceability path if the traceability management state is entered;

[0192] The coefficient calculation module is used to obtain the comprehensive retrieval data of the traceability node. The comprehensive retrieval data includes the in-and-out consumption value, the in-stock time ratio and the retrieval ratio value, and calculate the node abnormality coefficient based on the comprehensive retrieval data;

[0193] The early warning judgment module is used to compare the node abnormality coefficient with the preset node abnormality threshold, and determine whether to issue an early warning traceability prompt based on the comparison result;

[0194] The traceability management module is used to formulate a traceability management mode according to the number of abnormal nodes if an early warning traceability prompt is issued, mark the abnormal parameters from the comprehensive retrieved data, and perform traceability management of the abnormal parameters under the traceability management mode.

[0195] Example 3: Please refer to Figure 3 As shown, this embodiment discloses an electronic device, including a processor and a memory;

[0196] Wherein, the memory stores a computer program that can be called by the processor;

[0197] The processor executes the method for intelligent monitoring and tracing management of SPD medical consumables in an operating room by calling the computer program stored in the memory.

[0198] Since the electronic device introduced in this embodiment is an electronic device used to implement an operating room SPD medical consumables intelligent monitoring and tracing management method in Example 1 of this application, based on the operating room SPD medical consumables intelligent monitoring and tracing management method introduced in the embodiment of this application, the technical personnel of this field can understand the specific implementation of the electronic device of this embodiment and its various variations, so how the electronic device implements the method in the embodiment of this application is not described in detail here. As long as the technical personnel of this field implement the electronic device used in the operating room SPD medical consumables intelligent monitoring and tracing management method in the embodiment of this application, it belongs to the scope of protection of this application.

[0199] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. An intelligent monitoring and tracing management method for SPD medical consumables in operating rooms, applied to the SPD platform, characterized in that: include: S1: Identify the event status of the retrieved event, which includes the retrieved state and the unretrieved state, and determine whether to enter the traceability management state according to the ratio of the number of retrieved events with the unretrieved state to the total number of retrieved events; S2: If the traceability management state is entered, the traceability features are extracted from the retrieved events, the traceability path is planned according to the traceability features, and the traceability nodes are marked in the traceability path; The traceability features include time features, location features and authority features. The extraction methods of time features, location features and authority features include: Query the database one by one A data frame of retrieved events, marked The record phrases of the data frame are obtained Record phrases; Through natural language processing technology, we can identify The semantics of the recorded phrases are arranged in sequence to generate semantic line groups, and the keywords in the semantic line groups are identified one by one; The semantics with the keywords of time, moment and timeliness are recorded as time features, and k time features are obtained; The semantics with the keywords of place, location and space are recorded as place features, and k place features are obtained; The semantics with the keywords of authority, identity and level are recorded as authority features, and k authority features are obtained; The marking methods of traceability nodes include: Combine and aggregate the time features, location features, and authority features belonging to the same retrieval event to obtain k feature combinations; Marking k location points corresponding to the location features on the electronic map in sequence to obtain k initial points, and constructing interpretation frames having a first interpretation unit and a second interpretation unit on the k initial points respectively; Import the time feature and the authority feature in the same feature combination as the k location features into the first interpretation unit and the second interpretation unit of the initial point respectively, and obtain k path points; According to the order of the time features in the path points, the k path points are numbered in sequence, and a connecting line is established between two adjacent numbered path points to generate a tracing path; Identify the attribute states of time features, location features, and authority features corresponding to k path points one by one, and record the path points whose attribute states are all qualified attributes as traceability nodes, and obtain traceability nodes; S3: Obtain the comprehensive retrieval data of the traceability node, which includes the in-and-out consumption value, the ratio of the in-stock time and the retrieval ratio, and calculate the node abnormality coefficient based on the comprehensive retrieval data; The expression of the in-and-out consumption value is: ； In the formula, For the The inbound and outbound consumption value of each traceability node, For the The expenditure value of the traceability node, For the The entry value of the traceability node; The expression of the in-stock time ratio is: ； In the formula, For the The ratio of the in-stock time of the traceability nodes, is the inventory cycle, For the The expenditure duration of each traceability node; The expression for retrieving the percentage value is: ； In the formula, For the The call ratio of the traceability nodes, For the The effective call value of the traceability node, For the Invalid call value of the traceability node; The expression of node abnormality coefficient is: ； In the formula, For the The node anomaly coefficient of the traceable node, , , is a weight factor greater than 0; The determination methods for whether to issue an early warning traceability prompt include: Will Node abnormality coefficient The preset node abnormality threshold Compare; when Greater than or equal to When the warning is issued, the The traceability nodes are recorded as abnormal nodes, and n abnormal nodes are obtained; when Less than When it is determined that no early warning retrospective prompt will be issued; S4: Compare the node abnormality coefficient with the preset node abnormality threshold, and determine whether to issue an early warning traceability prompt based on the comparison result; S5: If an early warning traceability prompt is issued, a traceability management mode is formulated according to the number of abnormal nodes, abnormal parameters are marked from the comprehensive retrieved data, and traceability management of abnormal parameters is performed under the traceability management mode; The traceability management mode includes the combined traceability mode and the independent traceability mode. The formulation methods of the combined traceability mode and the independent traceability mode include: According to the order of the traceability node marking, all traceability nodes are numbered in ascending order, and the numbers of the n abnormal nodes are recorded as abnormal numbers; Count the number of abnormal nodes whose abnormal numbers are in adjacent order to obtain adjacent values; When the adjacent value is greater than the traceability calibration value, a combined traceability mode is developed; When the adjacent value is less than or equal to the traceability calibration value, an independent traceability mode is formulated; The marking methods for abnormal parameters include: Compare the in-and-out consumption values, in-stock time ratios, and retrieval ratios in the comprehensive retrieval data of n abnormal nodes with the consumption safety value, time safety value, and retrieval safety value one by one; When the in-and-out consumption value is greater than the consumption safety value, the in-and-out consumption value is recorded as an abnormal parameter; When the in-stock time ratio is less than the time safety value, the in-stock time ratio is recorded as an abnormal parameter; When the call ratio is greater than the call safety value, the call ratio is recorded as an abnormal parameter; The methods for traceability management of abnormal parameters include: When the combined tracing mode is formulated, the abnormal parameters of n abnormal nodes are summarized in turn to generate n abnormal data packets; At the same time, the original positions of the abnormal parameters in n abnormal data packets are traced through the SPD platform, and the traced original positions are bound to the corresponding abnormal data packets one by one to obtain n combined traceability sources; When an independent tracing mode is developed, the abnormal parameters of n abnormal nodes are arranged in sequence to generate n abnormal data rows; According to the order in which the abnormal data rows are arranged, the original positions of the abnormal parameters in the n abnormal data rows are traced through the SPD platform, and the traced original positions are bound to the corresponding abnormal parameters one by one to obtain n independent traceability sources.

2. According to claim 1, a method for intelligent monitoring and tracing management of SPD medical consumables in an operating room is characterized in that: The method for identifying the called state and the uncalled state includes: Mark all consumables record events in the database one by one, and query the remark words of all consumables record events through the attribute management system to obtain i remark words; The keywords of i remark words are identified one by one through natural language processing technology, and the remark words with keywords such as borrowing, retrieval, expenditure and use are recorded as valid words, and the consumables record events corresponding to the valid words are recorded as retrieval events. A call event; Through the status management system, query one by one A status box for the call event is marked a first state value and a second state value of a state box; Identify the event state of the calling event corresponding to the state box in which the first state value and the second state value are both 1 as the called state; When the first state value and the second state value are not both 1, the event state of the calling event corresponding to the state box is identified as a not called state.

3. According to claim 2, a method for intelligent monitoring and tracing management of SPD medical consumables in an operating room is characterized in that: The method for determining whether to enter the traceability management state includes: The number of call events whose event status is the called state is counted, recorded as the call quantity value, and the call quantity value is compared with the total number of call events to obtain the effective proportion value; The expression of effective proportion is: ； In the formula, is the effective proportion value, To retrieve the value; When the effective ratio Greater than or equal to the preset effective ratio threshold When the system enters the traceability management state; When the effective ratio Less than the preset effective ratio threshold When the traceability management state is not entered.

4. According to claim 3, a method for intelligent monitoring and tracing management of SPD medical consumables in an operating room is characterized in that: The method for obtaining the in-and-out consumption value includes: Through the warehouse management system, we can check the consumables one by one. The in-and-out logs of each tracing node can be tracked, and the in-and-out status of the in-and-out logs can be identified; Record the in-and-out logs with the status of expenditure and entry as expenditure logs and entry logs respectively, and obtain Expenditure logs and Enter the log; Through the database to query the consumables one by one Expenditure logs and The number of entries in the log is obtained Expenditure value and Enter the value The expenditure value and After subtracting the input values ​​one by one, we get The consumption value of inbound and outbound storage.

5. The method for intelligent monitoring and tracing management of SPD medical consumables in operating rooms according to claim 4 is characterized in that: The method for obtaining the in-stock time ratio includes: Query one by one by timestamp Expenditure logs and The first time that consumables are spent and consumables are entered into the log, respectively. The spending time and An entry moment; Will Expenditure time to The time between the entry moments is recorded as the expenditure time, and the Length of expenditure; Query one by one by timestamp The time corresponding to the time feature in the traceability node is obtained to obtain u candidate moments. After arranging the u candidate moments in chronological order, the candidate moment in the middle is selected and recorded as the node moment to obtain Node moments; The duration between two adjacent node moments is counted one by one, recorded as the node duration, and the maximum value of the node duration is recorded as the inventory cycle; In the library cycle, After subtracting the expenditure time, we get The length of time in the library and The in-stock time is compared with the in-stock cycle to obtain The ratio of time in stock.

6. The method for intelligent monitoring and tracing management of SPD medical consumables in operating rooms according to claim 5 is characterized in that: The method for obtaining the ratio value includes: Through the warehouse management system, all the in-and-out logs are queried, and the in-and-out logs with both expenditure logs and entry logs are recorded as valid logs, and the consumables are counted one by one. The number of valid logs on the traceability node is obtained Valid call values; The in-and-out logs that do not have both expenditure logs and entry logs are recorded as invalid logs, and the consumables are counted one by one. The number of invalid logs on the traceback node is obtained Invalid call value; Will The valid call values ​​are respectively After adding the invalid call values, we get Get the total value and The valid call values ​​are respectively Compare the total values ​​and get The percentage value is retrieved.

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