A data processing management method, system and intelligent chip for electronic medical records

Abstract

This invention provides a data processing and management method, system, and smart chip for electronic medical records, belonging to the field of data processing technology. Specifically, it includes: identifying electronic medical records within a doctor's electronic medical record that require real-time data processing based on similar situations and related examination data, and using these as target electronic medical records; determining the data processing methods for other electronic medical records based on the composition data of the target electronic medical record; and determining the update processing results of the target electronic medical record based on the data processing results of the target electronic medical record and the electronic medical records using various data processing methods. This further improves the reliability and timeliness of electronic medical record quality inspection processing.

Description

Technical Field

[0001] This invention belongs to the field of data processing technology, and in particular relates to a data processing and management method, system and smart chip for electronic medical records. Background Technology

[0002] To achieve quality inspection of electronic medical records, data processing of patient electronic medical records is often required. Specifically, the invention patent application CN202410314102.4, "Representative Text Sampling Method, System, Terminal and Medium," proposes clustering of target texts based on similarity calculation results, and then extracting multiple target texts as representative texts for quality inspection based on the clustering results. This can greatly reduce the workload of manual quality inspection and improve efficiency. However, the above technical solution has the following drawbacks: When processing electronic medical records (EMR) data, it is often necessary to verify the EMRs in conjunction with examination data. However, examinations often involve a certain delay. Therefore, determining the EMR data processing method based on the delay of examinations, and improving the efficiency of EMR data processing while ensuring its real-time performance, has become an urgent technical problem to be solved.

[0003] To address the aforementioned technical problems, this application provides a data processing and management method, system, and smart chip for electronic medical records. Summary of the Invention

[0004] To achieve the objectives of this invention, the following technical solution is adopted: Specifically, this application provides a data processing and management method for electronic medical records, which includes: S1 uses the updated data of electronic medical records as a basis to determine the associated examination items of electronic medical records. Based on the report issuance time of the associated examination items, if the data processing delay of the department's electronic medical records does not meet the requirements, the identification results of the doctor's electronic medical records are used to determine the similarity of the doctor's diagnosed patient's electronic medical records. Based on the similarity and the associated examination item data, the electronic medical records of the doctor's electronic medical records that are undergoing real-time data processing are determined and used as the target electronic medical records. S2 determines the data processing method for the doctor in other electronic medical records based on the composition data of the target electronic medical record in the doctor's records, and determines the update processing result of the doctor's target electronic medical record based on the data processing results of the target electronic medical record and the electronic medical records of various data processing methods.

[0005] Furthermore, the updated data of the electronic medical records is determined based on the update status of the electronic medical records of patients diagnosed by doctors in the department.

[0006] Furthermore, the associated examination items of the electronic medical record are the examination items of the patient corresponding to the electronic medical record.

[0007] Furthermore, it was determined that the data processing delay of the department's electronic medical records did not meet the requirements, specifically including: Based on the data of related examination items in the electronic medical records of the department, determine the report issuance time of the related examination items in the electronic medical records of the department; Based on the report issuance time, update delay check items are performed in the associated check items; Based on the electronic medical record data associated with the update delay check item, determine whether the data processing delay of the electronic medical records in the department meets the requirements.

[0008] Furthermore, the method for determining the update processing result of the doctor's target electronic medical record is as follows: Based on the data processing results of the target electronic medical record and electronic medical records using various data processing methods, identify electronic medical records with abnormal quality inspection results and classify them as abnormal quality inspection medical records. Based on the composition data of the doctor's target electronic medical record, the proportion of newly added target electronic medical records in different time periods among all newly added electronic medical records is determined, and this proportion is used as the target electronic medical record proportion. Based on the composition data of the abnormal medical records and the proportion of target electronic medical records, the update processing result of the doctor's target electronic medical records is determined.

[0009] In a second aspect, the present invention provides a computer system comprising: a memory and a processor connected in communication, and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the aforementioned data processing and management method for electronic medical records when running the computer program.

[0010] Thirdly, this application provides a smart chip, including a method executed by the smart chip when the processor in the computer system runs the computer program.

[0011] The beneficial effects of this invention are as follows: Based on the aforementioned similarities and related examination data, the electronic medical records of the doctor that undergo real-time data processing are identified. This enables the identification of electronic medical records that undergo real-time data processing from the perspective of the report issuance time of related examination items and the frequency of diagnosis and treatment of electronic medical records of the same disease type. This ensures the efficiency and reliability of quality control processing for electronic medical records of disease types with long report issuance times and low treatment rates.

[0012] Based on the data processing results of the target electronic medical record and various data processing methods, the update processing results of the doctor's target electronic medical record are determined. This avoids the technical problem of low reliability of quality inspection processing caused by not updating the target electronic medical record when the number of target electronic medical records is small and the number of abnormal quality inspection results in the electronic medical record is large. This further improves the reliability of electronic medical record data processing.

[0013] Other features and advantages will be set forth in the following description, and the objects and other advantages of the invention are realized and obtained through the structures particularly pointed out in the description and the drawings.

[0014] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0015] The above and other features and advantages of the present invention will become more apparent from a detailed description of exemplary embodiments thereof with reference to the accompanying drawings.

[0016] Figure 1 This is a flowchart of a data processing and management method for electronic medical records; Figure 2 This is a flowchart to determine if the data processing delay of the department's electronic medical records does not meet the requirements; Figure 3 This is a flowchart illustrating the method for determining the target electronic medical record; Figure 4 It is a flowchart of the method for determining the data processing methods of doctors in other electronic medical records; Figure 5 It is a framework diagram of a computer system. Detailed Implementation

[0017] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this specification, and not all embodiments. Based on the embodiments of this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this specification.

[0018] In this application, based on the report issuance duration of the examination items associated with the electronic medical record and the frequency of historical diagnoses of the disease type corresponding to the electronic medical record, a differentiated quality inspection strategy is determined for electronic medical records with low frequency and long report issuance duration. That is, as long as a new report appears, the electronic medical record is subjected to quality inspection processing, thereby ensuring the efficiency and reliability of the quality inspection processing.

[0019] Example 1 like Figure 1 As shown, this application provides a data processing and management method for electronic medical records, specifically including: S1 uses the updated data of electronic medical records as a basis to determine the associated examination items of electronic medical records. Based on the report issuance time of the associated examination items, if the data processing delay of the department's electronic medical records does not meet the requirements, the identification results of the doctor's electronic medical records are used to determine the similarity of the doctor's diagnosed patient's electronic medical records. Based on the similarity and the associated examination item data, the electronic medical records of the doctor's electronic medical records that are undergoing real-time data processing are determined and used as the target electronic medical records. Furthermore, the updated data of the electronic medical records is determined based on the update status of the electronic medical records of patients diagnosed by doctors in the department.

[0020] Furthermore, the associated examination items of the electronic medical record are the examination items of the patient corresponding to the electronic medical record.

[0021] Specifically, such as Figure 2 As shown, the data processing delay of the department's electronic medical records does not meet the requirements, specifically including: In this embodiment, the associated examination items of electronic medical records are statistically analyzed by department. Data processing delays are identified based on the report issuance time of each associated examination item (the time interval between the issuance of the examination item and the generation of the examination report). When the data processing delay of an electronic medical record in a certain department does not meet the requirements, the similarity analysis of the disease type of the patient's electronic medical record is further combined with the doctor's diagnosis to screen out the target electronic medical records that require real-time data processing. This enables the accurate positioning and priority processing of electronic medical records with high delay risk, improving the timeliness of electronic medical record data processing and laying the foundation for subsequent data processing method optimization.

[0022] S11 determines the report issuance time for the related examination items in the electronic medical records of the department based on the related examination item data of the department's electronic medical records.

[0023] The associated examination items refer to the various examination items that the patient underwent according to the electronic medical record, such as blood routine, urine routine, and imaging examinations; the report issuance time refers to the time interval from the issuance of the examination item to the generation of the examination report.

[0024] Suppose that a department has multiple doctors who have each seen a number of patients in the past month. Each patient corresponds to an electronic medical record. The system extracts the examination items associated with each electronic medical record, counts the time from the order of the examination to the generation of the report, and calculates the report issuance time for each associated examination item.

[0025] This step provides a data foundation for the identification of subsequent update delay inspection items. Its significance lies in enabling the system to quantitatively assess the degree of data processing delay by accurately calculating the report issuance time of each inspection item.

[0026] S12 performs the update delay check item in the associated check items based on the report issuance time.

[0027] The update delay check items refer to the related check items where the report issuance time does not meet the requirements, that is, check items where the report generation time exceeds the preset report issuance time threshold.

[0028] Assuming the system sets the report issuance time threshold to 2 days, it will determine whether the report issuance time of each related inspection item exceeds 2 days, and mark the inspection items that exceed the threshold as update delayed inspection items.

[0029] The significance of this step lies in filtering out inspection items with data processing delays from all related inspection items by using a threshold for report issuance duration, forming an updated set of delayed inspection items, and providing a focused range of indicators for the overall assessment of data processing delays in subsequent departments.

[0030] S13 determines whether the data processing delay of the electronic medical records in the department meets the requirements based on the electronic medical record data associated with the update delay check item.

[0031] It should be noted that the electronic medical record data associated with the update delay inspection items refers to electronic medical records that have update delay inspection items in the associated inspection items within the most recent preset time period, that is, there are at least one electronic medical record whose report issuance time exceeds the threshold; whether the data processing delay of the department's electronic medical records meets the requirements refers to judging whether the timeliness of the overall electronic medical record data processing of the department meets the preset standard by comprehensively considering the distribution of update delay inspection items in each electronic medical record.

[0032] Suppose a department has 200 electronic medical records in the past month. The system counts the number and distribution of electronic medical records with delayed update items for related examinations. Based on this, it calculates the data processing delay assessment index at the department level to determine whether the department needs to trigger the screening process for the target electronic medical records.

[0033] This step provides an entry point for determining the delay in departmental data processing. Its significance lies in using quantitative indicators to determine whether the data on the distribution of delayed inspection items needs to be included in the target electronic medical record screening process at the doctor level, based on the summary and update of the data on the distribution of delayed inspection items, thereby achieving precise positioning from department to doctor.

[0034] It should be noted that, based on the electronic medical record data associated with the aforementioned update delay check item, determining whether the data processing delay of the department's electronic medical records meets the requirements specifically includes the following: S131 Based on the electronic medical record data associated with the update delay check item, determine that the electronic medical record data of the update delay check item exists in the associated check items.

[0035] The electronic medical record data with delayed update items in the associated examination items refers to electronic medical records that meet the following conditions: within the most recent preset time period, at least one of the examination items associated with the electronic medical record has a report issuance time exceeding a preset report issuance time threshold.

[0036] Suppose that in the past month, among 200 electronic medical records in a certain department, some electronic medical records are associated with multiple examination items such as blood routine and imaging examinations. Among them, report A is issued within 2 days while examination report B is issued within 3 days (exceeding the threshold). The system will mark the electronic medical records with delayed update of examination items in these associated examination items.

[0037] The significance of this step lies in using electronic medical records as the basic unit to screen out medical records with delayed examination items, providing a statistical basis for subsequent calculation and updating of delay weight values.

[0038] S132 determines the update delay weight value of the update delay inspection item based on the electronic medical record containing the update delay inspection item in the associated inspection items.

[0039] The update delay weight value refers to the proportion of electronic medical records with update delay check items in the associated check items within the most recent preset time period among all electronic medical records. This proportion reflects the contribution of the update delay check item to the overall data processing delay.

[0040] Suppose a department has 200 electronic medical records in the past month. Among them, a certain test B is a test with a delayed update time. In 40 electronic medical records, there are cases where the report issuance time exceeds 2 days. Then the update delay weight value of this test with a delayed update time is 40÷200=0.20.

[0041] The significance of this step is to quantify the delay level of each update delay check item into a weight value, which facilitates a comprehensive evaluation of the department's overall data processing delay situation.

[0042] S133 determines whether the data processing delay of the electronic medical records of the department meets the requirements based on the sum of the update delay weight values ​​of each update delay check item.

[0043] When the sum of the update delay weight values ​​of each update delay check item is greater than the preset weight threshold, it is determined that the data processing delay of the department's electronic medical records does not meet the requirements, and the target electronic medical record screening process at the doctor level needs to be triggered.

[0044] Suppose a department has three update delay check items in the past month, with update delay weight values ​​of 0.15, 0.12 and 0.18 respectively in 200 electronic medical records. The sum of the update delay weight values ​​is 0.45. If the preset weight threshold is 0.40, then 0.45 > 0.40, and the judgment result is "yes". It is determined that the data processing delay of the department's electronic medical records does not meet the requirements.

[0045] This step assesses the overall data processing delay of the department by summarizing the weight values ​​of all update delay check items. Its significance lies in using quantitative indicators as a basis to avoid subjective judgment and ensure the objectivity and consistency of departmental delay identification.

[0046] Furthermore, the similarity of the doctor's diagnosis of the patient's electronic medical record is determined based on the type of disease diagnosed in the doctor's diagnosis of the patient's electronic medical record.

[0047] Specifically, such as Figure 3 As shown, the method for determining the target electronic medical record is as follows: S21 categorizes the doctor's electronic medical records in history into different groups based on the aforementioned similar circumstances; The similarity refers to the similarity between the disease types diagnosed in the patient's electronic medical record by the doctor; the different combinations refer to dividing the doctor's historical electronic medical record into several groups according to the similarity of disease types, with each group representing a type of similar disease or similar treatment scenario.

[0048] Suppose a doctor has treated multiple patients in the past, and each patient corresponds to an electronic medical record. The system calculates the similarity of the diagnosed disease types (such as pneumonia, gastritis, coronary heart disease, etc.) in each electronic medical record, and groups electronic medical records with the same or similar disease types into the same group to form the doctor's electronic medical record set.

[0049] The significance of this step lies in structuring and grouping doctors' historical electronic medical records according to disease similarity, providing an organizational basis for subsequent analysis of strongly correlated examination items and determination of target electronic medical records in groups.

[0050] S22 uses the examination item data of the electronic medical record in the combination as a basis to determine the correlation between the electronic medical record and the examination items, and determines the examination items with a correlation coefficient greater than a preset correlation coefficient as strongly correlated examination items.

[0051] The correlation coefficient refers to the frequency with which a certain examination item is associated in the electronic medical record combination, that is, the proportion of the examination item appearing in all electronic medical records in the combination; the strongly correlated examination item refers to the examination item with a correlation coefficient greater than a preset correlation coefficient threshold, reflecting that there is a strong diagnostic association between the examination item and the combination of disease types.

[0052] Suppose a doctor has a set of 20 electronic medical records related to coronary heart disease, of which 15 are associated with electrocardiogram (ECG) examinations. The correlation coefficient of ECG in this set is 15 ÷ 20 = 0.75. If the preset correlation coefficient threshold is 0.60, then ECG is included in the subsequent analysis as a strongly associated examination item.

[0053] The significance of this step lies in quantifying the strength of the association between examination items and disease type combinations through correlation coefficients, screening out strongly correlated examination items, and providing key indicators for the subsequent determination of target electronic medical records.

[0054] S23 determines whether the electronic medical record in the combination is the target electronic medical record based on the report issuance duration of the strongly correlated inspection items and the electronic medical record data in the combination.

[0055] It should be noted that when the electronic medical record data in the combination does not meet the requirements, that is, the number of electronic medical records in the combination is small, the diagnostic experience in the relevant disease types is limited due to the small number of electronic medical records in the combination. In order to ensure the real-time and reliability of the quality inspection process, the electronic medical records in the combination are determined to belong to the target electronic medical records.

[0056] The statement that the electronic medical record data in the combination does not meet the requirements means that the number of electronic medical records in the combination is lower than the preset combination number threshold, reflecting that the doctor's diagnostic experience in this type of disease is insufficient.

[0057] Suppose a doctor has only 5 electronic medical records for a rare disease, which is far below the preset threshold of 10 records for a combination. The system will then determine that the combination of electronic medical records does not meet the requirements and will directly include the 5 electronic medical records in the target electronic medical record range.

[0058] The significance of this step (Case 1) is that combinations with insufficient experience accumulation are directly included in the target monitoring scope, avoiding the problem of insufficient quality inspection reliability due to insufficient sample size.

[0059] Furthermore, when the electronic medical record data in the combination meets the requirements, if there are no strongly correlated examination items in the electronic medical records in the combination, then it is determined that the electronic medical records in the combination do not belong to the target electronic medical record.

[0060] When the number of combined electronic medical records meets the standard but there are no strongly related examination items, it indicates that the electronic medical records in the combination lack significant characteristics at the examination item level, and potential data processing risks cannot be identified by abnormal report issuance duration. Therefore, they are not included in the target electronic medical records.

[0061] Suppose a doctor has 30 electronic medical records related to a certain type of disease, which meets the combination requirement. However, after calculating the correlation coefficient, no examination item has a correlation coefficient exceeding the preset correlation coefficient threshold of 0.60. The system determines that there are no strongly correlated examination items in this combination and will not include it in the target electronic medical records.

[0062] The significance of this step (Scenario 2) is to exclude combinations without significant correlation characteristics between the checked items, provided that there is sufficient experience in combining them, so as to avoid unnecessary interference with the normal data processing flow.

[0063] It should also be noted that if there are strongly correlated examination items in the electronic medical records in the combination, and if the average report issuance time of the strongly correlated examination items is greater than a preset time threshold, then the electronic medical records in the combination are determined to belong to the target electronic medical records.

[0064] When a strongly correlated examination item exists and its average report issuance time exceeds the preset time threshold, it indicates that the data processing delay problem of this type of examination item in the combination is relatively prominent, and it needs to be included in the target electronic medical record for real-time monitoring.

[0065] Suppose a doctor has 25 electronic medical records for a certain type of disease, which meets the combination quantity requirement, and the correlation coefficient of a certain examination item (such as B monitoring) is 0.72 (exceeding the threshold of 0.60), and the average report issuance time of this strongly correlated examination item is 35 hours (exceeding the preset time threshold of 30 hours), the system determines that this combination belongs to the target electronic medical record.

[0066] The significance of this step (Scenario 3) lies in using the report issuance time of strongly correlated examination items as a key indicator to identify combinations with prominent data processing delay risks, thereby achieving accurate positioning of the target electronic medical record.

[0067] It should also be noted that if the electronic medical records in the combination contain strongly correlated examination items and the average report issuance time of the strongly correlated examination items is not greater than a preset time threshold, then the electronic medical records in the combination are determined not to belong to the target electronic medical records.

[0068] When a strongly correlated inspection item exists but its average report issuance time is controllable (within the threshold), it indicates that the data processing delay risk of the combination is within an acceptable range and there is no need to include it in the target electronic medical record for additional monitoring.

[0069] Suppose a doctor has 25 electronic medical records for a certain type of disease. There is a strongly correlated examination item (correlation coefficient 0.60), but its average report issuance time is 22 hours, which does not exceed the preset time threshold of 30 hours. The system determines that this combination does not belong to the target electronic medical record.

[0070] The significance of this step (case 4, a supplement to L01) is that, under the premise of strong correlation of inspection items, we can further use the report issuance time as a screening criterion to exclude combinations where the delay risk is already at a controllable level, and avoid excessively expanding the scope of the target electronic medical record.

[0071] This embodiment achieves precise identification of data processing delay risks through a four-layer progressive structure: departmental delay assessment → physician electronic medical record grouping → identification of strongly correlated examination items → target electronic medical record determination. Its core value lies in three aspects: First, the aggregation of departmental update delay weight values ​​ensures the objectivity of delay identification; second, grouping physicians by disease type similarity guarantees the homogeneity of electronic medical records within the group; and third, through a comprehensive judgment based on three dimensions—sufficient grouping experience, existence of strong correlation features, and controllable report issuance time—precise screening of target electronic medical records requiring real-time data processing is achieved, laying a reliable foundation for the optimization of subsequent data processing methods.

[0072] S2 determines the data processing method for the doctor in other electronic medical records based on the composition data of the target electronic medical record in the doctor's records, and determines the update processing result of the doctor's target electronic medical record based on the data processing results of the target electronic medical record and the electronic medical records of various data processing methods.

[0073] Specifically, such as Figure 4 As shown, the method for determining the data processing method for doctors in other electronic medical records is as follows: In this embodiment, based on the proportion of the doctor's target electronic medical record in all electronic medical records, and combined with the distribution of associated examination items and report issuance time of each electronic medical record, differentiated data processing methods are assigned to the doctor, including real-time detection method, batch waiting method, periodic polling method, etc., so as to optimize the efficiency of medical resource utilization while ensuring the timeliness of electronic medical record data processing.

[0074] S31 uses the constituent data of the target electronic medical records in the doctor as a basis to determine the proportion of the target electronic medical records in the doctor's electronic medical records in the doctor's electronic medical records in which the doctor has not yet processed the data according to all the associated examination items, and uses it as the proportion of target electronic medical records.

[0075] The electronic medical records that have not yet been processed according to all related examination items refer to the remaining electronic medical records among all the doctor's electronic medical records, excluding those that have been processed according to all related examination items. This reflects the scale of electronic medical records that the doctor is currently processing or waiting to process. The target electronic medical record ratio refers to the proportion of target electronic medical records among the electronic medical records waiting to be processed. This is used to measure the urgency and priority of the doctor's current data processing tasks.

[0076] Suppose that Doctor A has a total of 100 electronic medical records, of which 40 have completed data processing based on all related examination items, 60 are still pending processing, and there are 25 target electronic medical records. Then the proportion of target electronic medical records is 25÷60≈41.7%.

[0077] The significance of this step lies in quantifying the proportion of target electronic medical records in the doctor's pending tasks by using the target electronic medical record ratio, thus providing a quantitative basis for the subsequent allocation of differentiated data processing methods.

[0078] S32 determines the data processing method for the doctor in other electronic medical records based on the target electronic medical record ratio, the associated examination items of the other electronic medical records, and the association between the examination items and the examination items.

[0079] It should be noted that, in Case 1, when the target electronic medical record ratio is not less than a preset ratio threshold, if the other electronic medical records have multiple related examination items and there are related examination items whose report issuance time does not meet the requirements, then the data processing method for the other electronic medical records is determined to be that when any related examination item issues an examination result, the data processing of the other electronic medical records is performed. However, if the other electronic medical records do not have multiple related examination items or do not have related examination items whose report issuance time does not meet the requirements, then the data processing method for the other electronic medical records is determined to be that the data processing of the other electronic medical records is performed after all related examination items have issued examination results.

[0080] Specifically, the associated inspection items are the inspection items that the electronic medical record needs to check.

[0081] When the proportion of target electronic medical records is high (indicating that the doctor's current data processing and updates are in good real-time) and other electronic medical records have multiple related examination items and related examination items whose report issuance time does not meet the requirements, in order to improve the reliability of quality inspection processing, a real-time detection method is adopted—data processing is triggered as soon as any examination is completed; when other electronic medical records have few examination items or no delayed items, a batch waiting method is adopted—processing is carried out uniformly after all examinations are completed.

[0082] Assuming Doctor A's target electronic medical record ratio is 41.7%, and the preset ratio threshold is 0.30, 41.7% > 30%, which meets the condition. Some other electronic medical records are associated with two tests: a complete blood count and a complete biochemistry panel. The biochemistry panel report takes 3 days to be issued (which does not meet the requirement), while the complete blood count report takes 0.5 days (which meets the requirement). Therefore, a real-time detection method is adopted, and data processing is triggered as soon as any test is completed.

[0083] Furthermore, in scenario 2, when the target electronic medical record ratio is less than a preset ratio threshold, if other electronic medical records have related examination items whose report issuance time does not meet the requirements, then the data processing method for the other electronic medical records is determined to be to determine whether there are new related examination items for issuing examination results in the other electronic medical records according to a preset time period. If there are new related examination items for issuing examination results in the other electronic medical records, then the data processing of the other electronic medical records is performed.

[0084] When the target electronic medical record accounts for a low percentage (indicating poor real-time performance of the overall quality inspection and processing by doctors), if other electronic medical records have report issuance delays, a periodic polling method is used—regularly checking other electronic medical records at preset time intervals to see if any new examination reports have been issued, and triggering data processing if so.

[0085] Assuming that Doctor A's target electronic medical record ratio is 15%, which is lower than the preset ratio threshold of 0.30; and that some of the other electronic medical records have imaging examination reports issued within 3 days (more than 1 day), the system polls the examination report status of these electronic medical records every 2 hours. When a new examination report is issued for an electronic medical record within the current examination cycle, the data processing of that electronic medical record is immediately triggered.

[0086] The significance of this step (Scenario 2) is that when the target electronic medical record is under low pressure, the periodic polling method can ensure the timely processing of other electronic medical records with an appropriate polling frequency, thereby avoiding excessively frequent examinations that consume medical resources.

[0087] Additionally, it should be noted that in scenario 3, if the other electronic medical records do not have any related examination items whose report issuance duration does not meet the requirements, and if the other electronic medical records have examination items with a correlation coefficient greater than the preset correlation coefficient and a report issuance duration greater than the preset issuance duration, then the data processing method for the other electronic medical records is determined to be to determine whether there are any new related examination items for issuing examination results according to a preset time period. When there are new related examination items for issuing examination results, quality inspection processing is performed.

[0088] When other electronic medical records do not have overall delay issues, but there are some examination items with high delay levels that are strongly related to electronic medical records, the periodic polling method is still used for key monitoring.

[0089] Suppose that in Doctor A's other electronic medical records there are no related examination items whose report issuance time does not meet the 2-day threshold, but there is a certain special examination item whose correlation coefficient with the electronic medical records in the same combination is 0.7 (greater than the threshold of 0.60) and the report issuance time of this examination item is 15 hours (greater than the threshold of 12 hours). The system will conduct key round-robin queries on this electronic medical record according to a preset cycle to ensure the timeliness of quality inspection processing.

[0090] It also includes the following: Case 4: If the other electronic medical records do not have any examination items with a correlation coefficient greater than the preset correlation coefficient and a report issuance duration greater than the preset issuance duration, then the data processing method for the other electronic medical records is determined to be to wait until all related examination items have issued their examination results before performing data processing on the other electronic medical records.

[0091] When other electronic medical records have neither overall delay issues nor strongly related delay items, a batch waiting method is adopted—processing is carried out uniformly after all related examination items are issued to ensure data integrity.

[0092] If, in other examination reports associated with Doctor A's electronic medical record, there are no examination reports that are strongly correlated (correlation coefficient > 0.60) with the combination in which the electronic medical record is located and whose report issuance time is more than 12 hours, the system adopts a batch waiting method, waiting for all associated examination reports to be issued before triggering data processing.

[0093] The significance of this step (Scenario 4) lies in adopting the simplest processing method in the scenario with the lowest data processing risk, reducing unnecessary triggers and saving medical resources.

[0094] This embodiment achieves refined management of doctors' electronic medical record processing tasks by driving differentiated data processing method allocation through a target electronic medical record ratio. Its core value lies in three aspects: First, by using the target electronic medical record ratio as a core diversion indicator, the real-time nature of doctors' current processing tasks is divided, laying the foundation for differentiated method allocation; second, through a three-tiered method system of real-time detection, periodic polling, and batch waiting, it covers processing needs across all scenarios, from "multi-item delays" to "periodic key monitoring" and "full-scale waiting"; third, through a combination of real-time monitoring and periodic polling of examination report issuance time, it improves the timeliness of quality inspection processing and achieves balanced control over the timeliness of quality inspection processing for different doctors.

[0095] Specifically, the method for determining the update processing result of the doctor's target electronic medical record is as follows: S41, based on the data processing results of the target electronic medical record and electronic medical records using various data processing methods, identify electronic medical records with abnormal quality inspection results and designate them as abnormal quality inspection medical records.

[0096] The term "abnormal medical records" refers to electronic medical records that, during the data processing process, are found to have logical errors or other problems during quality checks.

[0097] Suppose that after processing the data of 25 target electronic medical records of doctor A, 15 other electronic medical records using the real-time detection method, and 45 other electronic medical records using the batch waiting method, the system performs a quality check on them, identifies several electronic medical records with data anomalies, and marks them as quality inspection abnormal medical records.

[0098] The significance of this step lies in accurately identifying electronic medical records with quality problems from the data processing results, providing a basis for subsequent evaluation of doctors' target electronic medical record update strategies.

[0099] S42 determines the proportion of newly added target electronic medical records in all newly added electronic medical records in different time periods based on the composition data of the doctor's target electronic medical records, and uses it as the proportion of target electronic medical records.

[0100] The different time periods refer to several preset statistical periods, such as statistical windows divided by month or week; the newly added target electronic medical records ratio refers to the proportion of newly added electronic medical records that belong to the target electronic medical records within a certain statistical period, which is used to measure the dynamic change trend of the target electronic medical records.

[0101] Assuming the system uses the previous month as the statistical period, it counts the number of new electronic medical records added by Doctor A in the past three months and the number of target electronic medical records among them, calculates the proportion of new target electronic medical records in each month, and observes the trend of this proportion in different months.

[0102] The significance of this step lies in assessing the effectiveness of the current target electronic medical record management strategy by analyzing the changing trend of the proportion of newly added target electronic medical records in different time periods, and providing a dynamic reference for determining the update processing results.

[0103] S43. Based on the composition data of the abnormal medical records and the proportion of target electronic medical records, determine the update processing result of the doctor's target electronic medical records.

[0104] It should be noted that, in case 1, when the proportion of the target electronic medical records in different time periods is greater than the preset proportion threshold, the update result of the doctor's target electronic medical records is determined to be that no update processing is required.

[0105] If the proportion of newly added target electronic medical records in each time period exceeds the preset proportion threshold, it indicates that the real-time quality inspection and processing of doctors' electronic medical records is high, and there is no need to adjust the current management strategy.

[0106] Assuming that Doctor A's newly added target electronic medical records in the past three months are 38%, 35%, and 40% respectively, and the preset threshold for the proportion is 0.30, if the proportions in all three periods are greater than 0.30, the judgment result is "yes", and the update processing result is determined to be that no update processing is required.

[0107] Furthermore, in scenario 2, when the proportion of target electronic medical records in different time periods is not greater than the preset proportion threshold, and when the number of combinations of the constituent data of the quality inspection abnormality proportion that do not meet the requirements is greater than the preset combination number threshold, then the abnormality of electronic medical records may frequently occur due to the doctor's lack of experience. Therefore, the update processing result of the doctor's target electronic medical records is determined to be that all electronic medical records are used as target electronic medical records.

[0108] When the proportion of target electronic medical records decreases (indicating a reduction in recent cases of delayed risk), but at the same time there are a large number of abnormal combinations in quality inspections that exceed the threshold, it indicates that the doctor's accumulated diagnostic experience is still insufficient to support stable electronic medical record quality, and the scope of monitoring needs to be expanded.

[0109] Assuming that the proportion of new target electronic medical records added by doctor A in the past three months is 20%, 18%, and 22% respectively, all of which are lower than the preset proportion threshold of 0.30; the system further analyzes the abnormal medical records and finds that there are 5 combinations of electronic medical records whose abnormality rate exceeds the preset abnormality rate threshold. The preset combination number threshold is 3, and 5>3, so the judgment result is "yes". Therefore, the update processing result is determined to treat all electronic medical records of doctor A as target electronic medical records and implement comprehensive monitoring.

[0110] The significance of this step (Scenario 2) is that when the scope of the target electronic medical records shrinks, i.e. when the real-time performance of quality inspection is poor, by monitoring the number of abnormal combinations of quality inspection, the quality problems of electronic medical records caused by insufficient doctor experience can be detected in a timely manner, and the monitoring scope can be expanded from some targets to all electronic medical records to ensure the quality of data processing.

[0111] Additionally, in scenario 3, when the number of combinations whose constituent data of the quality inspection anomaly ratio does not meet the requirements is not greater than the preset combination number threshold, the electronic medical records of the combinations whose constituent data of the quality inspection anomaly ratio does not meet the requirements are determined to be combinations belonging to the target electronic medical record and are regarded as reliable combinations for quality inspection. When the number of combinations whose constituent data of the quality inspection anomaly ratio does not meet the requirements, excluding the reliable combinations for quality inspection, is less than the preset number threshold, the update processing result of the doctor's target electronic medical record is determined to be that no update processing is required.

[0112] When the number of abnormal combinations in quality inspection does not exceed the threshold, further analysis is conducted on how many of these abnormal combinations belong to the target electronic medical record (reliable combination in quality inspection). After excluding the reliable part, if the number of remaining abnormal combinations is still lower than the preset number threshold, it indicates that the abnormality mainly comes from the target electronic medical record. At this time, the real-time performance of quality inspection is high, and no strategy adjustment is required.

[0113] Assuming there are 2 abnormal combinations in total (not exceeding the threshold of 3), after verification, one of the abnormal combinations belongs to the target electronic medical record (a reliable combination for quality inspection). After removing this combination, there is 1 abnormal combination remaining. The preset quantity threshold is 2, 1<2, the judgment result is "yes", and the update processing result is determined to be no update processing required.

[0114] It should also be noted that, in case 4, when the number of reliable quality inspection combinations removed from the combination of components whose quality inspection abnormality ratio does not meet the requirements is not less than the preset number threshold, the update processing result of the doctor's target electronic medical record is determined to be the electronic medical record of the combination of examination items with multiple report issuance durations that do not meet the requirements and whose correlation coefficients are greater than the preset correlation coefficients.

[0115] If the number of remaining abnormal combinations still exceeds the threshold after removing reliable combinations from the quality inspection, it indicates that the existing target electronic medical record positioning strategy has a deviation. The target screening conditions need to be adjusted to include combinations with multiple strongly correlated long-delay inspection items in the target range in order to improve the coverage accuracy of the target electronic medical records.

[0116] Assuming there are 5 abnormal combinations in the quality inspection (more than the threshold of 3), one of which is a reliable combination (target electronic medical record), after removing it, there are 4 abnormal combinations remaining. The preset number threshold is 2, 4≥2, and the judgment result is "yes". The system further analyzes the related inspection items of all combinations and finds that electronic medical records with two or more inspection items with a correlation coefficient greater than 0.60 and a report issuance time of more than 1 day are newly included in the target electronic medical record scope.

[0117] Example 2 Secondly, such as Figure 5 As shown, the present invention provides a computer system comprising: a memory and a processor connected in communication, and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the above-described data processing and management method for electronic medical records when running the computer program.

[0118] Example 3 Thirdly, this application provides a smart chip, including a method executed by the smart chip when the processor in the computer system runs the computer program.

[0119] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on its differences from other embodiments. In particular, the embodiments of apparatus, devices, and non-volatile computer storage media are basically similar to the method embodiments, so the descriptions are relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0120] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0121] The above description is merely one or more embodiments of this specification and is not intended to limit this specification. Various modifications and variations can be made to the one or more embodiments of this specification by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of one or more embodiments of this specification should be included within the scope of the claims of this specification.

Claims

1. A data processing and management method for electronic medical records, characterized in that, Specifically, it includes: Based on the updated data of electronic medical records, the associated examination items of electronic medical records are determined. Based on the report issuance time of the associated examination items, when the data processing delay of the department's electronic medical records does not meet the requirements, the identification results of the doctor's electronic medical records are used to determine the similarity of the doctor's diagnosed patient's electronic medical records. Based on the similarity and the associated examination item data, the electronic medical records of the doctor's electronic medical records that are processed in real time are determined and used as the target electronic medical records. Based on the constituent data of the target electronic medical record in the doctor's data, the data processing method of the doctor in other electronic medical records is determined. Based on the data processing results of the target electronic medical record and electronic medical records using various data processing methods, the update processing result of the doctor's target electronic medical record is determined.

2. The data processing and management method for electronic medical records as described in claim 1, characterized in that, The update data of the electronic medical records is determined based on the update status of the electronic medical records of patients diagnosed by doctors in the department.

3. The data processing and management method for electronic medical records as described in claim 1, characterized in that, The associated examination items of the electronic medical record are the examination items of the patient corresponding to the electronic medical record.

4. The data processing and management method for electronic medical records as described in claim 1, characterized in that, The data processing delay of the department's electronic medical records did not meet the requirements, specifically including: Based on the data of related examination items in the electronic medical records of the department, determine the report issuance time of the related examination items in the electronic medical records of the department; Based on the report issuance time, update delay check items are performed in the associated check items; Based on the electronic medical record data associated with the update delay check item, determine whether the data processing delay of the electronic medical records in the department meets the requirements.

5. The data processing and management method for electronic medical records as described in claim 4, characterized in that, The update delay check item is an associated check item where the report issuance time does not meet the requirements.

6. The data processing and management method for electronic medical records as described in claim 4, characterized in that, Based on the electronic medical record data associated with the update delay check item, determine whether the data processing delay of the department's electronic medical records meets the requirements, specifically including: Based on the electronic medical record data associated with the update delay inspection item, it is determined that the electronic medical record data of the update delay inspection item exists in the associated inspection items; Based on the electronic medical records containing the update delay inspection item in the associated inspection items, determine the update delay weight value of the update delay inspection item; Based on the sum of the update delay weight values ​​of each update delay check item, determine whether the data processing delay of the electronic medical records in the department meets the requirements.

7. The data processing and management method for electronic medical records as described in claim 1, characterized in that, The similarity of the doctor's diagnosis of the patient's electronic medical record is determined based on the type of disease diagnosed in the doctor's diagnosis of the patient's electronic medical record.

8. The data processing and management method for electronic medical records as described in claim 1, characterized in that, The method for determining the update result of the doctor's target electronic medical record is as follows: Based on the data processing results of the target electronic medical record and electronic medical records using various data processing methods, identify electronic medical records with abnormal quality inspection results and classify them as abnormal quality inspection medical records. Based on the composition data of the abnormal medical records, determine the composition data of abnormal medical records in different combinations. Based on the constituent data of the doctor's target electronic medical record and the constituent data of medical records with quality inspection abnormalities in different combinations, the update processing result of the doctor's target electronic medical record is determined.

9. A computer system, comprising: A memory and processor connected in communication, and a computer program stored in the memory and capable of running on the processor, characterized in that, when the processor runs the computer program, it executes a data processing and management method for electronic medical records as described in any one of claims 1-8.

10. A smart chip, characterized in that, This includes the smart chip being used to execute the method performed by the processor in the computer system of claim 9 when running the computer program.

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