Electronic health record-based nursing data collaborative sharing method

Abstract

The present application relates to the nursing data collaborative sharing method based on electronic health records, relate to data management technical field, including the record feature extraction to the nursing data package, the present application carries out the verification to the nursing data package, with the trusted level of nursing data as the direct execution sharing transmission constraint, improves the data quality baseline of entering the shared channel, and according to the failure type dynamic matching operable repair suggestion, so that the sending end can accurately locate the problem, according to the failure type dynamic selection diagnosis depth, so that the nursing data transmission reaches the best transmission efficiency and reliability under different scenarios, through the self-healing strategy of state query and differential retransmission, without reinitiating complete sharing, automatically complete the supplement of missing data, so as to improve the accuracy after data transmission, through the quality evaluation report collection transmission success rate, end-to-end delay, retransmission number key index, dynamic update the comprehensive quality score of each candidate sharing method and adjust the priority order.

Description

Technical Field

[0001] This invention relates to the field of data management technology, and in particular to a method for collaborative sharing of nursing data based on electronic health records. Background Technology

[0002] As a core infrastructure for regional health information platforms and smart hospital construction, electronic health records directly affect the effectiveness of hierarchical medical treatment, the continuity of nursing services, and patient safety through cross-institutional and cross-system collaborative sharing of nursing data. Nursing data, as an important component of medical and health information, is fundamentally supported by cross-institutional and cross-system sharing and exchange to achieve continuous nursing, regional medical collaboration, and clinical research. With the deepening development of nursing informatization, the demand for nursing data sharing is increasing, involving multiple application scenarios such as the transmission of nursing information for patient referrals between hospitals, the synchronization of home nursing data between communities and hospitals, and the collection of nursing research data. However, existing methods for sharing nursing data suffer from the following three interconnected but unresolved technical shortcomings in practical applications: Existing electronic health record sharing systems generally follow the default principle that data can be shared as long as it exists in the database. When nursing data sharing fails, existing systems usually only return general prompts such as transmission failure or parsing error. The sending nurse cannot know the specific reason for the failure, whether it is a problem with the data itself, a transmission problem, or a problem with the receiving end. When the sender discovers errors in the original nursing data that has been successfully shared and corrects the local records, the receiving system still retains the erroneous data. Nurses continue to make nursing decisions, compile statistical reports, and conduct clinical research based on the erroneous data without their knowledge, resulting in the inability to reverse-correct the shared erroneous data and the continued existence of security risks.

[0003] To address the aforementioned technical shortcomings, a solution is proposed. Summary of the Invention

[0004] This invention adopts the following technical solution: a method for collaborative sharing of nursing data based on electronic health records, comprising the following steps: Step 1: Based on the data monitoring nodes, the nursing data package will be subjected to archive feature extraction to generate a health care data distribution set. According to the data time update node of the nursing data repository, the nursing data package detection result will be generated. Step 2: Based on the nursing data packet detection results, the shared transmission constraints are directly executed according to the trust level of the nursing data. If the transmission fails, a dynamic sequence is generated. Repair suggestions are matched from the preset diagnostic knowledge base according to the dynamic sequence, and the diagnostic depth is dynamically selected according to the failure type. The diagnostic results and repair suggestions are then output to the sending end. Step 3: Establish a temporary feedback channel between the transmitting and sending ends according to the sharing method. Use the preset transmission duration as the receiving time window and wait for the receiving end to return the business entry confirmation. Then, close the temporary feedback channel and trigger the status query request. Determine whether the result is a true success or a false success based on the result returned by the receiving end, and execute the corresponding self-healing strategy. Step 4: When the sending end detects an error in the successfully shared original nursing data and performs local correction, it sends correction notification packets to all direct and secondary receivers based on the pre-built shared consumption graph. Step 5: Construct a quality assessment report for the shared methods, and use it as a feedback sample to update the overall quality score of each candidate shared method.

[0005] Furthermore, based on the time update nodes of the nursing data repository, nursing data package detection results are generated. The specific process is as follows: Monitoring nodes are deployed at the data exit of the nursing information system to capture nursing data packets to be shared in real time and extract core record feature fields, including patient unique identifier, nursing record generation time, nursing assessment items, performing nurse identifier, and data version number; Multi-dimensional statistical analysis was performed on the captured archival features to construct a health care data distribution set based on a sliding time window, which includes four dimensions: integrity distribution, time distribution, numerical distribution, and source distribution. Label nursing data packages with information on urgency, non-urgency, sensitive data, capacity, and shared attributes across institutions; Based on the data time update nodes in the nursing data repository, the last modification timestamp and the modifier are recorded. Version consistency checks are performed on the data packets to be shared, comparing the data version number with the latest record in the repository to determine the latest version. If they are inconsistent, conflict types of data are further identified. When a conflict occurs, sharing is prevented and the corresponding processing flow is triggered. Generate detection results that include integrity score, consistency score, timeliness score, version status, attributes, and comprehensive credibility index.

[0006] Furthermore, based on the nursing data packet detection results, the shared transmission constraints are directly executed according to the trust level of the nursing data. If transmission fails, a dynamic sequence containing the failed step, the reason for failure, and the failed object is generated. The specific process is as follows: Based on the nursing data packet detection results, a comprehensive credibility index is extracted, and data credibility level matching is performed to obtain the corresponding credibility level matching results. The nursing data is divided into three credibility levels, and three credibility index ranges are set. Shared transmission constraints based on credibility levels are executed, including direct transmission level, transmission quality warning level, and transmission stop level. When transmission is prohibited, the failed nursing data packets are parsed to generate a dynamic sequence including the failure point, the reason for failure, and the failure object. Failure events include sender version verification failure, semantic parsing failure, and transmission failure; The reasons for failure include encoding mismatch, network timeout, and insufficient permissions. The object of failure is the file data version.

[0007] Furthermore, repair suggestions are matched from a preset diagnostic knowledge base based on the dynamic sequence, and the diagnostic depth is dynamically selected according to the failure type. The diagnostic results and repair suggestions are then output to the sending end. The specific process is as follows: The generated dynamic sequence is used as the query target and matched against a preset diagnostic knowledge base. This knowledge base has three levels, each corresponding to a confidence level. Upon successful matching, the diagnostic depth is automatically selected based on the failed step and its cause. The selection of diagnostic depth is dynamically adjusted based on the historical repair success rate of the failed cause, including: This is a shallow diagnostic tool applicable to network timeout and insufficient permissions environments. It only outputs the failure status code and error description, without providing specific repair steps. Mid-level diagnostics, applicable to single-field errors such as missing data and out-of-bounds values, adds root cause analysis, outputs specific error field locations and repair operation instructions. Deep diagnostics, applicable scenarios: errors that require systematic correction such as encoding mismatch and semantic conflict, increase the encoding comparison supported by the receiver, generate mapping schemes and estimate the reliability after repair, generate diagnostic results and transmit them to the sender; After the diagnosis is completed, the confidence weight of the corresponding matching item in the diagnostic knowledge base is updated based on whether the sending nurse adopted the repair suggestion and whether the sharing was successful after the repair.

[0008] Furthermore, a temporary feedback channel is established between the transmitting and sending ends, with a preset transmission duration as the receiving time window, to wait for the receiving end to return confirmation of business entry into the database. The specific process is as follows: The sharing method is selected based on the attributes of the nursing data package, and the sharing method is determined based on the data sensitivity level and cross-institutional identifier. Then, the comprehensive suitability of each candidate method is calculated based on the data size, network conditions, and historical success rate. The method with the highest suitability is selected for transmission. The sharing methods include real-time push, batch push, encrypted direct transmission, compressed fragmentation, and breakpoint resume transmission. The sending end negotiates with the receiving end to establish a dedicated temporary feedback channel according to the selected sharing method. After the channel is successfully established, the sending end starts transmitting nursing data packets. A preset receiving time window is set. Within the receiving time window, the sending end waits for the receiving end to return business entry confirmation, including transport layer confirmation and business entry confirmation.

[0009] Furthermore, by executing the closure of the temporary feedback channel and triggering a status query request, the system determines whether the success is genuine or false based on the result returned by the receiving end, and executes the corresponding self-healing strategy. The specific process is as follows: When a business entry confirmation is received, the temporary channel is closed. When a confirmation is received from the transport layer, it is considered a false success, triggering a status query request. The sending end initiates a status query to the receiving end to obtain the sequence number bitmap of the data packets that have been entered into the database. After parsing the bitmap, the sending end calculates the data segments that have not been entered into the database and only resends these missing data segments. It does not resend the data that has already been entered into the database. After the differential retransmission is completed, it retransmits and enters the waiting confirmation state. If the business database entry confirmation is received, the transmission is considered successful.

[0010] Furthermore, when the sending end detects an error in the successfully shared original nursing data and performs local correction, it sends correction notification packets to all direct and secondary receivers based on the pre-built shared consumption graph. The specific process is as follows: For each successfully shared nursing data, maintain a shared consumption graph. When the sending nurse performs corrections on the local original nursing data, obtain the correction behavior and extract the data snapshots before and after the correction, the reason for the correction, and generate the corresponding correction notification package, which includes the unique identifier of the original data, the fingerprint of the original version, the full text of the corrected data, the reason for the correction, the basis for the correction, and the correction time. Generate a corresponding correction notification package, which includes the original data's unique identifier, the original version's fingerprint, the full text of the corrected data, the reason for the correction, the basis for the correction, the correction level, and the correction time. After receiving the correction notification, the receiving end first verifies the version fingerprint to confirm that there is data to be corrected locally, then marks the old data as obsolete, stores the corrected data, and forces it to be displayed.

[0011] Furthermore, a quality assessment report of the shared methods is constructed as a feedback sample to update the overall quality score of each candidate shared method. The specific process is as follows: After sharing is completed, key indicators are collected, including the success rate of business entry confirmation, the total time from initiation to receipt of confirmation, the number of retransmissions, and the delivery rate of correction notifications, and then normalized. Based on the normalized key indicators, a comprehensive quality score is calculated. An independent quality score record is maintained for each sharing method. The score is then updated using an exponentially weighted moving average method. The updated comprehensive quality scores are reordered from high to low and used as the basis for selecting the next sharing method.

[0012] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are: This collaborative sharing method for nursing data based on electronic health records verifies nursing data packets. Based on the detection results, it directly enforces shared transmission constraints according to the trust level of the nursing data. If transmission fails, a dynamic sequence containing the failed step, cause, and object is generated, improving the baseline quality of data entering the sharing channel. Version conflict detection effectively solves the inconsistency problem caused by multiple people simultaneously editing the same nursing record, ensuring the final consistency of shared data. It dynamically matches actionable repair suggestions based on the failure type, enabling the sending end to accurately locate problems and quickly complete corrections. The method dynamically selects the diagnostic depth based on the failure type, responding quickly to simple errors and conducting in-depth analysis for complex errors, achieving both diagnostic efficiency and accuracy. The optimal balance ensures that nursing data transmission achieves the best transmission efficiency and reliability in different scenarios. By distinguishing between transmission layer confirmation and business entry confirmation, false successes are identified. Through status query and differentiated retransmission self-healing strategies, missing data can be automatically retransmitted without nurses having to re-initiate a complete sharing process, reducing manual retransmission costs. When the source sender corrects erroneous data, all direct and secondary receivers receive a forced correction notification, thereby improving the accuracy of data transmission. The quality assessment report collects key indicators such as transmission success rate, end-to-end latency, and retransmission count, dynamically updates the comprehensive quality score of each candidate sharing method, and adjusts the priority ranking, upgrading method selection from static configuration to data-driven adaptive optimization. Attached Figure Description

[0013] Figure 1 A schematic diagram of the overall steps of the method of the present invention is shown. Detailed Implementation

[0014] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided below.

[0015] Example: like Figure 1 As shown, the method for collaborative sharing of nursing data based on electronic health records includes the following steps: Step 1: Based on the data monitoring nodes, the nursing data package will be subjected to archive feature extraction to generate a health care data distribution set. According to the data time update node of the nursing data repository, the nursing data package detection result will be generated. Step 2: Based on the nursing data packet detection results, the shared transmission constraints are directly executed according to the trust level of the nursing data. If the transmission fails, a dynamic sequence is generated. Repair suggestions are matched from the preset diagnostic knowledge base according to the dynamic sequence, and the diagnostic depth is dynamically selected according to the failure type. The diagnostic results and repair suggestions are then output to the sending end. Step 3: Establish a temporary feedback channel between the transmitting and sending ends according to the sharing method. Use the preset transmission duration as the receiving time window and wait for the receiving end to return the business entry confirmation. Then, close the temporary feedback channel and trigger the status query request. Determine whether the result is a true success or a false success based on the result returned by the receiving end, and execute the corresponding self-healing strategy. Step 4: When the sending end detects an error in the successfully shared original nursing data and performs local correction, it sends correction notification packets to all direct and secondary receivers based on the pre-built shared consumption graph. Step 5: Construct a quality assessment report for the shared methods, and use it as a feedback sample to update the overall quality score of each candidate shared method.

[0016] Based on the time update nodes of the nursing data repository, nursing data package detection results are generated. The specific process is as follows: Monitoring nodes are deployed at the data exit of the nursing information system to capture nursing data packets to be shared in real time and extract core record feature fields, including patient unique identifier, nursing record generation time, nursing assessment items, performing nurse identifier, and data version number; Multi-dimensional statistical analysis was performed on the captured archival features to construct a health care data distribution set based on a sliding time window, which includes four dimensions: integrity distribution, time distribution, numerical distribution, and source distribution. Label nursing data packages with information on urgency, non-urgency, sensitive data, capacity, and shared attributes across institutions; Based on the data time update nodes in the nursing data repository, the last modification timestamp and the modifier are recorded. Version consistency checks are performed on the data packets to be shared, comparing the data version number with the latest record in the repository to determine the latest version. If they are inconsistent, conflict types of data are further identified. When a conflict occurs, sharing is prevented and the corresponding processing flow is triggered. Generate detection results that include integrity score, consistency score, timeliness score, version status, attributes, and comprehensive credibility index.

[0017] In this solution, when constructing the health care data distribution set, completeness is defined by the missing rate of required fields and the proportion of null values ​​in key numerical fields; time distribution is defined by the regularity of the time when nursing data is generated; numerical distribution is defined by the numerical range, mean, standard deviation, and frequency of outliers for each nursing assessment item; and source distribution is defined by the data generation volume and historical data quality records of each department and nurse. A sliding time window is used, with the window width set to the number of days, and is dynamically updated. Expired data is removed and newly generated data is included each time the window slides, ensuring that the distribution set reflects the actual situation of current nursing work. Based on the data time update node field in the nursing data repository, the timestamp of the last modification and the modifier's identifier for each piece of nursing data are recorded, and version consistency checks are performed on the nursing data package to be shared. First, extract the patient identifier, nursing record time, and data version number from the data package to be shared, and perform a triplet comparison with the latest record of the same patient and the same nursing time point in the repository: If the version numbers are the same, and the last modification time of the repository is not later than the generation time of the data package to be shared, then it is determined to be the latest version; If the version numbers are inconsistent or there are updated modification records in the repository, it is determined to be a version conflict. Further determination of the conflict type is required, including whether it has been updated by others and whether it has been modified concurrently.

[0018] Based on the nursing data packet detection results, shared transmission constraints are directly executed according to the trust level of the nursing data. If transmission fails, a dynamic sequence is generated. The specific process is as follows: Based on the nursing data packet detection results, a comprehensive credibility index is extracted, and data credibility level matching is performed to obtain the corresponding credibility level matching results. The nursing data is divided into three credibility levels, and three credibility index ranges are set. Shared transmission constraints based on credibility levels are executed, including direct transmission level, transmission quality warning level, and transmission stop level. When transmission is prohibited, the failed nursing data packets are parsed to generate a dynamic sequence including the failure point, the reason for failure, and the failure object. Failure events include sender version verification failure, semantic parsing failure, and transmission failure; The reasons for failure include encoding mismatch, network timeout, and insufficient permissions. The object of failure is the file data version.

[0019] Based on the dynamic sequence, repair suggestions are matched from the preset diagnostic knowledge base, and the diagnostic depth is dynamically selected according to the failure type. The diagnostic results and repair suggestions are then output to the sending end. The specific process is as follows: Obtain the generated dynamic sequence as the query target and match it in the preset diagnostic knowledge base. The diagnostic knowledge base has three hierarchical levels, and the three hierarchical levels correspond to three trust levels. After successful matching, according to the failure link and failure reason, automatically select the diagnostic depth, and the selection of the diagnostic depth is dynamically adjusted according to the historical repair success rate of the failure reason, including: Shallow diagnosis, applicable to environment - related errors such as network timeout and insufficient permissions. Only the failure status code and error description are output, and no specific repair steps are output; Medium - level diagnosis, applicable to single - field errors such as data missing and value out - of - bounds. Root - cause analysis is added, and the specific position of the error field and repair operation guidelines are output; Deep diagnosis, applicable to scenarios: errors that require systematic correction such as coding mismatch and semantic conflict. Comparison of the encoding supported by the receiving end, generation of mapping schemes, and estimation of the credibility after repair are added, and the diagnostic results are generated and transmitted to the sending end; After diagnosis, according to whether the nurse at the sending end adopts the repair suggestion and whether the sharing after repair is successful, update the confidence weight of the corresponding matching item in the diagnostic knowledge base.

[0020] In this solution, extract the comprehensive credibility index Z and version status from the nursing data packet detection results, and execute differential transmission constraints according to the preset trust - level division criteria, including the preset first - level threshold X and second - level threshold Y. When the comprehensive credibility index is greater than the preset first - level threshold X, the version status is the latest, and automatic sharing transmission is performed without manual intervention. The transmission process uses the default real - time synchronous push method. When Y ≤ Z < X and the version is in doubt, conduct a check and verification of the nursing data packet. When Z < Y, the version is untrusted, and the nursing data packet is rebuilt. When transmission is prohibited, generate a unit dynamic sequence, and use the dynamic sequence as the query key to match the repair suggestion in the diagnostic knowledge base. Select the diagnostic depth according to the failure type.

[0021] Establish a feedback temporary channel between the transmission end and the sending end, and use the preset transmission duration as the receiving time window to wait for the receiving end to return the business warehousing confirmation. The specific process is as follows: Select the sharing method according to the nursing data packet attributes, determine the sharing method according to the data sensitivity level and cross - institutional identification, and then calculate the comprehensive adaptability of each candidate method according to the data size, network condition, and historical success rate, and select the method with the highest adaptability to execute the transmission. The sharing methods include real - time push, batch push, encrypted direct transmission, compressed sharding, and resume - interrupted transfer; The sending end negotiates with the receiving end to establish a dedicated feedback temporary channel according to the selected sharing method. After the channel is successfully established, the sending end starts to transmit the nursing data packet. Set the preset receiving time window, and within the receiving time window, the sending end waits for the receiving end to return the business warehousing confirmation, including transport - layer confirmation and business warehousing confirmation.

[0022] The process involves closing the temporary feedback channel and triggering a status query request. Based on the result returned by the receiving end, it is determined whether the success is genuine or false, and the corresponding self-healing strategy is executed. The specific process is as follows: When a business entry confirmation is received, the temporary channel is closed. When a confirmation is received from the transport layer, it is considered a false success, triggering a status query request. The sending end initiates a status query to the receiving end to obtain the sequence number bitmap of the data packets that have been entered into the database. After parsing the bitmap, the sending end calculates the data segments that have not been entered into the database and only resends these missing data segments. It does not resend the data that has already been entered into the database. After the differential retransmission is completed, it retransmits and enters the waiting confirmation state. If the business database entry confirmation is received, the transmission is considered successful.

[0023] In this scheme, before transmission, a comprehensive selection is made from six candidate methods: real-time synchronous push of high-priority urgent data, asynchronous batch synchronization for non-urgent general data, encrypted direct transmission for sensitive data, proxy relay for cross-organizational sharing, compressed fragmented transmission for large-capacity data, and breakpoint resume transmission for weak network environments. The selection is based on data sensitivity level, data size, and network conditions. The sending and receiving ends negotiate to establish a dedicated temporary feedback channel. The channel has a limited lifespan, is valid within the current transmission cycle, has a two-way confirmation mechanism, and automatically releases upon timeout. The receiving time window is dynamically calculated. Wait for the receiving end to return a business entry confirmation, distinguish between transport layer confirmation and business entry confirmation. When successful, close the channel and clear the confirmation queue. If it is a false success, keep the channel open and trigger a status query. If it fails, re-execute the sending steps.

[0024] When the sending end detects an error in the successfully shared original nursing data and performs local correction, it sends correction notification packets to all direct and secondary receivers based on the pre-built shared consumption graph. The specific process is as follows: For each successfully shared nursing data, maintain a shared consumption graph. When the sending nurse performs corrections on the local original nursing data, obtain the correction behavior and extract the data snapshots before and after the correction, the reason for the correction, and generate the corresponding correction notification package, which includes the unique identifier of the original data, the fingerprint of the original version, the full text of the corrected data, the reason for the correction, the basis for the correction, and the correction time. Generate a corresponding correction notification package, which includes the original data's unique identifier, the original version's fingerprint, the full text of the corrected data, the reason for the correction, the basis for the correction, the correction level, and the correction time. After receiving the correction notification, the receiving end first verifies the version fingerprint to confirm that there is data to be corrected locally, then marks the old data as obsolete, stores the corrected data, and forces it to be displayed.

[0025] In this scheme, a shared consumption graph is maintained for each successfully shared nursing data. The initial edge between the original sender and direct receiver is recorded, as well as the secondary propagation edges when the receiver further shares the data. The graph is stored in a consortium blockchain as a directed acyclic graph. Each edge includes a source node, a target node, a sharing timestamp, a data version fingerprint, and a description of the sharing scope. When a nurse performs corrections on local nursing data (numerical correction, assessment adjustment, diagnosis change, record deletion), a correction notification packet is generated. This packet contains the original data identifier, original version fingerprint, the full text of the corrected data, the reason for the correction, the basis for the correction, the correction timestamp, and the impact assessment request. This packet is digitally signed and sent to all direct receivers and secondary receivers. Critical corrections are sent via a high-priority channel, and the receiver verifies the version. After consistency is achieved, the local old data is marked as obsolete, and the corrected data is stored. During critical corrections, a pop-up window is forced to display the correction content every time a nurse accesses the patient record. For critical corrections, all nursing operation records performed by the nurse based on the old data are retrieved to generate an impact list. Nurses are required to assess whether each operation needs to be reviewed and adjusted. The assessment results are recorded in the audit log. The receiving end returns a confirmation receipt containing the processing status and an impact assessment summary. The sending end can view the complete transmission status. If no confirmation is received within the time limit, an automatic upgrade reminder is issued. If the receiving end itself also acts as a sender and shares the old data with downstream devices, its new sharing behavior of the old data is automatically suspended. The correction must be completed before a new version is generated. If the correction is not completed within the specified time, the system will forcibly add a warning label when it initiates sharing.

[0026] A quality assessment report of the shared methods is constructed as a feedback sample to update the overall quality score of each candidate shared method. The specific process is as follows: After sharing is completed, key indicators are collected, including the success rate of business entry confirmation, the total time from initiation to receipt of confirmation, the number of retransmissions, and the delivery rate of correction notifications, and then normalized. In this solution, after each sharing session is completed, the system automatically collects the following key metrics from the entire sharing process: The transmission success rate is the number of successful business entry confirmations / the total number of sent requests; the total time is the total time from the sending end initiating the sharing to receiving the business entry confirmation; the number of retransmissions is the total number of application layer retransmissions that occurred in this sharing; and the correction notification delivery rate is the number of actual recipients / the total number of recipients that should be delivered if correction propagation is triggered after this sharing. After normalizing the original indicators, a weighted comprehensive quality score is calculated. An exponentially weighted moving average is used to update the comprehensive quality score of each candidate method. The candidate methods are then reordered from high to low according to the updated scores. The updated quality score matrix and priority sorting are stored in the strategy configuration center.

[0027] The size of the interval and threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by those skilled in the art for each set of sample data; as long as it does not affect the ratio between the parameter and the quantized value.

[0028] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation. In the two embodiments provided in this application, it should be understood that the disclosed methods can be implemented in other ways; for example, the method embodiments described above are merely illustrative. For example, the division of modules is merely a logical functional division, and there may be other division methods in actual implementation. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection between the shown or discussed components may be indirect coupling or communication connection through some interfaces, devices or modules, and may be electrical, mechanical or other forms. The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A method for collaborative sharing of nursing data based on electronic health records, characterized in that, Includes the following steps: Step 1: Based on the data monitoring nodes, the nursing data package will be subjected to archive feature extraction to generate a health care data distribution set. The nursing data package will be subjected to version detection to generate nursing data package detection results. Step 2: Based on the nursing data packet detection results, the shared transmission constraints are directly executed according to the trust level of the nursing data. If the transmission fails, a dynamic sequence is generated. Based on the dynamic sequence, repair suggestions are matched from the preset diagnostic knowledge base, and the diagnostic depth is dynamically selected according to the failure type. The diagnostic results and repair suggestions are then output to the sending end. Step 3: Establish a temporary feedback channel between the transmitting and sending ends according to the sharing method. Use the preset transmission duration as the receiving time window and wait for the receiving end to return the business entry confirmation. Then, close the temporary feedback channel and trigger the status query request. Determine whether the result is a true success or a false success based on the result returned by the receiving end, and execute the corresponding self-healing strategy. Step 4: When the sending end detects an error in the successfully shared original nursing data and performs local correction, it sends correction notification packets to all direct and secondary receivers based on the pre-built shared consumption graph. Step 5: Construct a quality assessment report for the shared methods, and use it as a feedback sample to update the overall quality score of each candidate shared method.

2. The method for collaborative sharing of nursing data based on electronic health records according to claim 1, characterized in that, Based on the time update nodes of the nursing data repository, nursing data package detection results are generated. The specific process is as follows: Monitoring nodes are deployed at the data exit of the nursing information system to capture nursing data packets to be shared in real time and extract core record feature fields, including patient unique identifier, nursing record generation time, nursing assessment items, performing nurse identifier, and data version number; Multi-dimensional statistical analysis was performed on the captured archival features to construct a health care data distribution set based on a sliding time window, which includes four dimensions: integrity distribution, time distribution, numerical distribution, and source distribution. Label the nursing data package with information on urgency, non-urgency, sensitive data, size, and shared attributes across institutions; Based on the data time update nodes in the nursing data repository, the last modification timestamp and the modifier are recorded. Version consistency checks are performed on the data packets to be shared, comparing the data version number with the latest record in the repository to determine the latest version. If they are inconsistent, conflict types of data are further identified. When a conflict occurs, sharing is prevented and the corresponding processing flow is triggered. Generate detection results that include integrity score, consistency score, timeliness score, version status, attributes, and comprehensive credibility index.

3. The method for collaborative sharing of nursing data based on electronic health records according to claim 1, characterized in that, Based on the nursing data packet detection results, shared transmission constraints are directly executed according to the trust level of the nursing data. If transmission fails, a dynamic sequence is generated. The specific process is as follows: Based on the nursing data packet detection results, a comprehensive credibility index is extracted, and data credibility level matching is performed to obtain the corresponding credibility level matching results. The nursing data is divided into three credibility levels, and three credibility index ranges are set. Shared transmission constraints based on credibility levels are executed, including direct transmission level, transmission quality warning level, and transmission stop level. When transmission is prohibited, the failed nursing data packets are parsed to generate a dynamic sequence including the failure link, the failure reason, and the failure object; Failure events include sender version verification failure, semantic parsing failure, and transmission failure; The reasons for failure include encoding mismatch, network timeout, and insufficient permissions. The object of failure is the file data version.

4. The method for collaborative sharing of nursing data based on electronic health records according to claim 1, characterized in that, Based on the dynamic sequence, repair suggestions are matched from the preset diagnostic knowledge base, and the diagnostic depth is dynamically selected according to the failure type. The diagnostic results and repair suggestions are then output to the sending end. The specific process is as follows: The generated dynamic sequence is used as the query target and matched against a preset diagnostic knowledge base. This knowledge base has three levels, each corresponding to a confidence level. Upon successful matching, the diagnostic depth is automatically selected based on the failed step and its cause. The selection of diagnostic depth is dynamically adjusted based on the historical repair success rate of the failed cause, including: This is a shallow diagnostic tool applicable to network timeout and insufficient permissions environments. It only outputs the failure status code and error description, without providing specific repair steps. Mid-level diagnostics, applicable to single-field errors such as missing data and out-of-bounds values, adds root cause analysis, outputs specific error field locations and repair operation instructions. Deep diagnostics, applicable scenarios: errors that require systematic correction such as encoding mismatch and semantic conflict, increase the encoding comparison supported by the receiver, generate mapping schemes and estimate the reliability after repair, generate diagnostic results and transmit them to the sender; After the diagnosis is completed, the confidence weight of the corresponding matching item in the diagnostic knowledge base is updated based on whether the sending nurse adopted the repair suggestion and whether the sharing was successful after the repair.

5. The method for collaborative sharing of nursing data based on electronic health records according to claim 1, characterized in that, A temporary feedback channel is established between the transmitting and sending ends, with a preset transmission duration serving as the receiving time window. The process involves waiting for the receiving end to return confirmation of business entry into the database. The specific process is as follows: The sharing method is selected based on the attributes of the nursing data package, and the sharing method is determined based on the data sensitivity level and cross-institutional identifier. Then, the comprehensive suitability of each candidate method is calculated based on the data size, network conditions, and historical success rate. The method with the highest suitability is selected for transmission. The sharing methods include real-time push, batch push, encrypted direct transmission, compressed fragmentation, and breakpoint resume transmission. The sending end negotiates with the receiving end to establish a dedicated temporary feedback channel according to the selected sharing method. After the channel is successfully established, the sending end starts transmitting nursing data packets. A preset receiving time window is set. Within the receiving time window, the sending end waits for the receiving end to return business entry confirmation, including transport layer confirmation and business entry confirmation.

6. The method for collaborative sharing of nursing data based on electronic health records according to claim 1, characterized in that, The process involves closing the temporary feedback channel and triggering a status query request. Based on the result returned by the receiving end, it is determined whether the success is genuine or false, and the corresponding self-healing strategy is executed. The specific process is as follows: When a business entry confirmation is received, the temporary channel is closed. When a confirmation is received from the transport layer, it is considered a false success, triggering a status query request. The sending end initiates a status query to the receiving end to obtain the sequence number bitmap of the data packets that have been entered into the database. After parsing the bitmap, the sending end calculates the data segments that have not been entered into the database and only resends these missing data segments. It does not resend the data that has already been entered into the database. After the differential retransmission is completed, it retransmits and enters the waiting confirmation state. If the business database entry confirmation is received, the transmission is considered successful.

7. The method for collaborative sharing of nursing data based on electronic health records according to claim 1, characterized in that, When the sending end detects an error in the successfully shared original nursing data and performs local correction, it sends correction notification packets to all direct and secondary receivers based on the pre-built shared consumption graph. The specific process is as follows: For each successfully shared nursing data, maintain a shared consumption graph. When the sending nurse performs corrections on the local original nursing data, obtain the correction behavior and extract the data snapshots before and after the correction, the reason for the correction, and generate the corresponding correction notification package, which includes the unique identifier of the original data, the fingerprint of the original version, the full text of the corrected data, the reason for the correction, the basis for the correction, and the correction time. Generate a corresponding correction notification package, which includes the original data's unique identifier, the original version's fingerprint, the full text of the corrected data, the reason for the correction, the basis for the correction, the correction level, and the correction time. After receiving the correction notification, the receiving end first verifies the version fingerprint to confirm that there is data to be corrected locally, then marks the old data as obsolete, stores the corrected data, and forces it to be displayed.

8. The method for collaborative sharing of nursing data based on electronic health records according to claim 1, characterized in that, A quality assessment report of the shared methods is constructed as a feedback sample to update the overall quality score of each candidate shared method. The specific process is as follows: After sharing is completed, key indicators are collected, including the success rate of business entry confirmation, the total time from initiation to receipt of confirmation, the number of retransmissions, and the delivery rate of correction notifications, and then normalized. Based on the normalized key indicators, a comprehensive quality score is calculated. An independent quality score record is maintained for each sharing method. The score is then updated using an exponentially weighted moving average method. The updated comprehensive quality scores are reordered from high to low and used as the basis for selecting the next sharing method.

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