A method and system for disaster recovery of a pharmaceutical system based on data backup

Abstract

This invention relates to the field of disaster recovery technology for pharmaceutical information systems, and discloses a disaster recovery method and system for pharmaceutical systems based on data backup. The method includes: screening cold chain drug-related records in active medical orders; calculating a temperature compliance status summary containing a joint sensitivity value and embedding it into the active medical order mirror status table; incorporating the temperature compliance status summary into incremental differential backup synchronization; identifying temperature-controlled risk batches based on the temperature compliance status summary and performing temperature control compliance judgment during disaster recovery switchover; estimating the temperature change curve during the disaster based on a temperature decay model and recalculating the remaining effective shelf life; comparing the preliminary judgment results with the complete assessment results and performing corrections. This invention eliminates the blind spot period for cold chain drug temperature control compliance information during disaster recovery switchover.

Description

Technical Field

[0001] This invention relates to the field of disaster recovery technology for medical information systems, and more specifically, to a method and system for disaster recovery of medical systems based on data backup. Background Technology

[0002] In emergency and intensive care settings within the medical system, active medical order data is synchronized in real-time to the backup and recovery node via dual-channel parallel transmission using incremental differential packets to ensure business continuity in the event of a disaster. The active medical order mirror status table records the execution parameters of the medical orders, including medication dosage and infusion rate. When a disaster occurs in the main system, the backup and recovery node completes the business switchover based on differential packet supplementation for uncertain intervals and verification of the rationality of the medication plan, restoring the medical order execution process.

[0003] In existing disaster recovery backup solutions, the temperature control compliance status data of cold chain medicines is stored and managed as a separate temperature control time-series dataset, and is not included in the real-time incremental backup synchronization scope of the active medical order mirror status table. When a disaster event also causes a power outage in the cold storage, the cold chain medicines may actually fail due to excessive temperature. However, after completing the millisecond-level disaster recovery switch, the backup and recovery node will immediately resume executing the emergency medical orders containing these medicines.

[0004] Although the temperature-controlled time-series dataset is considered jointly sensitive data and can be prioritized for recovery, its complete recovery time is much longer than the millisecond-level time window for backup switching. This creates a blind spot of missing temperature control compliance information between the completion of the disaster recovery switch and the complete recovery of the temperature-controlled time-series dataset. During this blind spot, the system cannot determine whether cold-chain medicines are still effective, posing a risk of continuing to dispense expired medicines for emergency treatment and creating medication safety hazards. Summary of the Invention

[0005] This invention provides a disaster recovery method and system for pharmaceutical systems based on data backup, which solves the technical problem in related technologies that when a pharmaceutical system experiences a catastrophic failure and undergoes disaster recovery switching, the temperature control compliance data of cold chain drugs cannot be effectively preserved and continuously evaluated, resulting in the inability to guarantee drug safety after disaster recovery.

[0006] This invention discloses a disaster recovery method for a pharmaceutical system based on data backup, comprising: acquiring medical order records in an active execution state, matching the drug batch identifiers involved in the medical order records with a cold chain drug batch association mapping table, filtering out active medical order records using cold chain drugs, and generating a set of active medical order records for cold chain drugs; For each batch of cold chain medicine associated with the temperature control monitoring device in the active medical order record set of cold chain medicines, the latest temperature sampling value is obtained at micro-period intervals, the temperature compliance status summary within the sliding time window is calculated, and the temperature compliance status summary is embedded as an additional field into the data structure of the corresponding medical order record in the active medical order mirror status table; The temperature compliance status summary field is included in the micro-incremental differential detection range, and the micro-incremental differential packet containing the temperature compliance status summary change data is sent to the backup and recovery node through dual-channel parallel transmission. When a disaster event in the main system triggers a disaster recovery switch, the backup recovery node reads the temperature compliance status summary from the locally maintained active medical order image status table and identifies temperature control risk batches based on the cumulative duration of exceeding the standard and the highest temperature value within the window. For the active medical order records associated with the aforementioned temperature control risk batches, a temperature control compliance determination is performed during the medication regimen rationality verification process, and the medical order execution status is marked based on the determination result; After the backup and recovery node takes over the operation, it estimates the temperature change curve during the disaster based on the temperature decay model, recalculates the remaining effective shelf life of each batch of cold chain medicines, compares the complete assessment results with the preliminary judgment results, and performs corrections. The temperature compliance status summary includes the current temperature value, the highest temperature value within the window, the cumulative duration of exceeding the standard, and a joint sensitivity value. The joint sensitivity value is obtained by weighted fusion calculation based on temperature control risk factors and expiration date urgency.

[0007] Furthermore, the calculation method of the joint sensitivity value is as follows: the value obtained by multiplying the temperature control risk factor by the temperature control risk weight coefficient is added to the value obtained by multiplying the expiration date urgency by the expiration date urgency weight coefficient, and the sum of the temperature control risk weight coefficient and the expiration date urgency weight coefficient is equal to 1; the temperature control risk factor and the expiration date urgency are both dimensionless normalized values ​​in the range of 0 to 1, and the value range of the joint sensitivity value is in the range of 0 to 1.

[0008] Furthermore, the temperature control risk factor is calculated as follows: subtract the negative exponent of the natural constant from 1, where the exponent of the negative exponent is the negative value of the product of the sensitivity coefficient and the weighted cumulative temperature deviation; the sensitivity coefficient is a positive real number pre-calibrated by the temperature sensitivity level corresponding to the drug type; the weighted cumulative temperature deviation is calculated as follows: for each sampling moment within the sliding time window, if the temperature sampling value at that moment exceeds the upper limit of the compliant temperature range, the excess temperature at that moment is multiplied by the time interval between adjacent sampling moments and then accumulated; if the temperature sampling value at that moment does not exceed the compliant temperature range, the contribution at that moment is zero.

[0009] Furthermore, the calculation method for the expiration date urgency is as follows: subtract 1 from the ratio of the remaining expiration date of the drug batch to the standard expiration date of the drug type; the remaining expiration date is calculated from the time the drug batch enters the warehouse, and the remaining expiration date at the time of entry into the warehouse is equal to the standard expiration date. As time goes by, the remaining expiration date continuously decreases, and the expiration date urgency increases monotonically; when the remaining expiration date exceeds the range of 0 to the standard expiration date, the expiration date urgency is truncated to the boundary value of the interval between 0 and 1.

[0010] Furthermore, incorporating the temperature compliance status summary field into the micro-incremental differential detection range includes: setting change detection thresholds for each indicator value in the temperature compliance status summary; determining a change when the change in the current temperature value exceeds the temperature change detection threshold; determining a change when the increment of the cumulative exceedance duration exceeds the duration change detection threshold; and determining a change when the change in the combined sensitivity value exceeds the sensitivity change detection threshold; each change detection threshold is a pre-configured fixed constant. The differential transmission of the temperature compliance status summary adopts a hierarchical transmission strategy: when the joint sensitivity value is less than or equal to the warning lower limit, the temperature compliance status summary is included in the differential packet with a long transmission interval period; when the joint sensitivity value is greater than the warning lower limit but less than the failure upper limit, the transmission interval period is shortened to the same micro-cycle interval as the medical order execution parameter; when the joint sensitivity value is greater than or equal to the failure upper limit, the temperature compliance status summary is included in the differential packet for transmission in each micro-cycle; the warning lower limit and the failure upper limit are both pre-configured dimensionless constants and the warning lower limit is less than the failure upper limit.

[0011] Furthermore, identifying temperature-controlled risk batches based on cumulative exceedance duration and the highest temperature value within the window includes: after the backup and recovery node executes the uncertain interval differential package supplementary application, it reads the temperature compliance status summary of all medical order records containing cold chain drug batch identifiers in the active medical order mirror status table; for each temperature compliance status summary, it compares the cumulative exceedance duration with the preset allowable offset threshold for that drug type, and compares the highest temperature value within the window with the storage temperature limit for that drug type; when the cumulative exceedance duration exceeds the allowable offset threshold or the highest temperature value within the window exceeds the storage temperature limit, the corresponding cold chain drug batch is marked as a temperature-controlled risk batch.

[0012] Furthermore, the temperature control compliance determination includes: obtaining the cumulative duration of temperature control risk batches exceeding the standard and comparing it with the failure determination standard corresponding to the drug type; when the cumulative duration of exceeding the standard reaches the failure determination standard, marking the execution status of the corresponding medical order record as cold chain suspension, generating a cold chain early warning event and pushing it to the emergency terminal; when the cumulative duration of exceeding the standard does not reach the failure determination standard and the joint sensitivity value is greater than the lower limit of the early warning and less than the upper limit of failure, adding a temperature control risk warning mark to the corresponding medical order record and activating the medical order record as a state that can continue to be executed; the failure determination standard is stricter than the allowable offset threshold.

[0013] Furthermore, estimating the temperature change curve during a disaster based on the temperature decay model includes: identifying the start and end times of the temperature acquisition interruption gap caused by the disaster; obtaining the last valid temperature sample value before the start time of the interruption gap as the initial temperature; and obtaining the reference temperature of the environment where the cold storage is located. The temperature decay model is calculated as follows: the estimated temperature value is equal to the environmental reference temperature plus the difference between the initial temperature and the environmental reference temperature multiplied by the negative exponent of the natural constant. The exponent of the negative exponent is the negative value of the product of the thermal decay coefficient and the elapsed time since the start time of the interruption gap. The thermal decay coefficient is pre-calibrated based on the insulation performance parameters of the cold storage and historical temperature decay records.

[0014] Furthermore, with access to cold storage door opening and closing records, the temperature decay model is segmented and corrected: the interruption gap is divided into several consecutive sub-periods based on the switching time between the cold storage door opening and closing states; when the cold storage door is open, the heat decay coefficient is increased to the original heat decay coefficient multiplied by a dimensionless door opening correction factor greater than 1 to obtain the corrected heat decay coefficient; when the cold storage door is closed, the original heat decay coefficient is used; for each sub-period, the estimated temperature value at the beginning of the sub-period is used as the initial temperature and substituted into the temperature decay model for calculation; between adjacent sub-periods, the estimated temperature value at the end of the previous sub-period is used as the initial temperature of the next sub-period; and the estimated temperature values ​​of each sub-period are spliced ​​together in chronological order to form a complete temperature change curve for the interruption gap. The actual cumulative duration of exceeding the standard during the disaster is recalculated using the estimated temperature change curve. This is then added to the cumulative duration of exceeding the standard before the interruption to obtain the updated total cumulative duration of exceeding the standard. Based on the updated total cumulative duration of exceeding the standard, the remaining effective shelf life of each batch of cold chain medicines is calculated.

[0015] This invention provides a disaster recovery system for a medical system based on data backup, comprising: The cold chain medical order screening module is used to obtain medical order records that are in an active execution state, match the drug batch identifiers involved in the medical order records with the cold chain drug batch association mapping table, filter out active medical order records that use cold chain drugs, and generate a set of active medical order records for cold chain drugs. The temperature compliance status summary calculation and embedding module is used to obtain the latest temperature sampling value of each batch of cold chain medicine associated with the temperature control monitoring device in the active medical order record set of cold chain medicine at micro-period intervals, calculate the temperature compliance status summary within the sliding time window, and embed the temperature compliance status summary as an additional field into the data structure of the corresponding medical order record in the active medical order mirror status table; The differential synchronization module is used to include the temperature compliance status summary field into the micro-incremental differential detection range, and sends the micro-incremental differential packet containing the temperature compliance status summary change data to the backup and recovery node through dual-channel parallel transmission. The temperature control risk batch identification module is used to read the temperature compliance status summary from the active medical order image status table maintained locally by the backup recovery node when a disaster event triggers a disaster recovery switch in the main system, and to identify temperature control risk batches based on the cumulative duration of exceeding the standard and the highest temperature value within the window. The temperature control compliance determination module is used to perform temperature control compliance determination on active medical order records associated with temperature control risk batches during the medication regimen rationality verification process, and mark the medical order execution status based on the determination result; The temperature estimation and correction module is used to estimate the temperature change curve during the disaster based on the temperature decay model after the backup and recovery node takes over the operation, recalculate the remaining effective shelf life of each batch of cold chain medicines, compare the complete assessment results with the preliminary judgment results, and perform corrections.

[0016] This invention embeds the temperature compliance status summary of cold chain pharmaceuticals as an additional field into the active medical order mirror status table and incorporates it into the micro-incremental differential backup synchronization range. This allows backup and recovery nodes to directly read the temperature compliance status summary of each batch of cold chain pharmaceuticals and perform temperature control compliance determination without waiting for the complete recovery of the temperature control time-series dataset after completing millisecond-level disaster recovery switchover. This solves the technical problem of blind spots in the temperature control compliance information of cold chain pharmaceuticals during disaster recovery switchover, achieving the technical effect of identifying temperature control risk batches and preventing the dispensing of substandard pharmaceuticals within the immediate time window of disaster recovery switchover. Furthermore, the temperature compliance status summary adopts a compact encoding format and a hierarchical transmission strategy based on joint sensitivity values, achieving the technical effect of continuous synchronization of temperature control status under limited bandwidth conditions. Further, by comparing and correcting the precise reassessment after the complete recovery of the temperature control time-series dataset with the preliminary judgment results, the technical effect of correcting the deviation of the preliminary judgment and forming a two-stage disaster recovery verification process is achieved. Attached Figure Description

[0017] Figure 1 This is a flowchart of a disaster recovery method for a medical system based on data backup, provided in an embodiment of the present invention. Figure 2This is a schematic diagram comparing the batch temperature control risk indicators of cold chain pharmaceuticals provided in the embodiments of the present invention; Figure 3 This is a schematic diagram of the temperature estimation curve during a disaster provided by the BCH-AV042 antivenom serum in an embodiment of the present invention; Figure 4 This is a schematic diagram comparing the cumulative duration of exceeding the standard for each batch with the failure judgment criteria provided in the embodiments of the present invention; Figure 5 This is a schematic diagram comparing the highest temperature within each batch window with the upper limit of the storage temperature provided in the embodiments of the present invention; Figure 6 This is a schematic diagram of the joint sensitivity value S and the threshold distribution of the hierarchical transmission strategy provided in the embodiments of the present invention; Figure 7 This is a schematic diagram showing the distribution of the deviation of the excessive temperature and the duration of the BCH-AV042 provided in the embodiments of the present invention; Figure 8 This is a schematic diagram comparing the estimated highest temperature during the interruption intervals of each batch, provided in an embodiment of the present invention. Figure 9 This is a schematic diagram of the medical order screening process provided in this embodiment of the invention: active medical order batch matching results. Detailed Implementation

[0018] In emergency and intensive care settings within the medical system, active medical order data is synchronized in real-time to the backup and recovery node via dual-channel parallel transmission using incremental differential packets to ensure business continuity in the event of a disaster. The active medical order mirror status table records the execution parameters of the medical orders, including medication dosage and infusion rate. When a disaster occurs in the main system, the backup and recovery node completes the business switchover based on differential packet supplementation for uncertain intervals and verification of the rationality of the medication plan, restoring the medical order execution process.

[0019] However, the effectiveness of cold chain medicines (such as antivenom, emergency insulin, and biological agents) depends on the continuous compliance of cold storage temperature control monitoring data. In existing disaster recovery backup solutions, the temperature control compliance status data of cold chain medicines is stored and managed as an independent temperature control time-series dataset, which is not within the scope of real-time incremental backup synchronization of the active medical order mirror status table. When a disaster event simultaneously causes a power outage in the cold storage, the cold chain medicines may actually become ineffective due to excessive temperature. However, after the backup recovery node completes the millisecond-level disaster recovery switch, it will immediately resume executing emergency medical orders containing these medicines. Although the temperature control time-series dataset is joint sensitive data and can be prioritized for recovery, the complete recovery time of the temperature control time-series dataset is much longer than the millisecond-level time window of the backup switch. This creates a blind spot period of missing temperature control compliance information between the completion of the disaster recovery switch and the complete recovery of the temperature control time-series dataset. During the blind spot period, the system cannot determine whether the cold chain medicines are still effective and may continue to allocate ineffective medicines for emergency rescue, posing a medication safety risk.

[0020] Therefore, a data backup and recovery method is needed that can determine the temperature control compliance of cold chain pharmaceuticals within a millisecond-level disaster recovery switchover time window, in order to eliminate the blind spot of temperature control compliance during the disaster recovery switchover process.

[0021] According to an embodiment of this invention, a disaster recovery method for a pharmaceutical system based on data backup is provided. It should be understood that before implementing the method of this embodiment, the pharmaceutical system has deployed a micro-incremental differential backup synchronization mechanism for an active medical order mirror status table. This mechanism generates differential packets at millisecond-level micro-period intervals and transmits them to the backup and recovery node in parallel through dual channels. The pharmaceutical system maintains a batch association mapping table for cold chain pharmaceuticals, which records the association between cold chain pharmaceutical batch identifiers and corresponding temperature control monitoring device identifiers. The temperature control monitoring device for cold chain pharmaceuticals continuously collects cold storage temperature data at a preset sampling frequency, forming a temperature control time-series dataset.

[0022] At least one embodiment of the present invention discloses a disaster recovery method for a medical system based on data backup, such as... Figure 1 As shown, it includes the following steps: Step 1: Filter the cold chain drug association records in active medical orders; The system retrieves all active medical order records from the pharmaceutical system, extracts the batch identifier of the medication associated with each record, matches the extracted batch identifier with a cold chain medication batch association mapping table, filters out active medical order records using cold chain medications, and generates a set of active cold chain medication medical order records. For each record in the set of active cold chain medication medical order records, the associated cold chain medication batch identifier and temperature control monitoring device identifier are appended based on the cold chain medication batch association mapping table.

[0023] It should be noted that the above-mentioned active execution status refers to the current state of the medical order being executed or awaiting the next execution, including long-term medical orders that are continuously infused and temporary medical orders that have been issued but have not yet completed all doses, but does not include medical orders that have been completed or have been stopped by the physician.

[0024] It should be noted that the above matching process refers to using the batch identifier of the medication in the medical order record as the query key to search for a corresponding entry in the cold chain medication batch association mapping table. When a matching entry is found, the medical order record is determined to be associated with cold chain medications; when no matching entry is found, the medical order record is determined not to involve cold chain medications and is excluded from subsequent processing.

[0025] Step 2: Calculate the temperature compliance status summary and embed it into the active medical order mirror status table; For each batch of cold chain medicines associated with a temperature control monitoring device in the active medical order record set, the latest temperature sampling value is acquired at a preset micro-period interval. Based on the latest temperature sampling value and historical sampling values, a temperature compliance status summary within the most recent sliding time window is calculated. The temperature compliance status summary is then embedded as an additional field into the data structure of the corresponding medical order record in the active medical order mirror status table.

[0026] The above temperature compliance status summary includes the following indicators: current temperature value, highest temperature value within the window, cumulative duration of exceeding the standard, and combined sensitivity value.

[0027] The joint sensitivity value is calculated based on a weighted fusion of temperature control risk factors and expiration date urgency. The calculation formula is as follows: in, For the joint sensitivity value, As a risk factor for temperature control, Due to the urgency of the expiration date, and These are the weighting coefficients corresponding to the temperature control risk factor and the urgency of the expiration date, respectively. .

[0028] because and All values ​​are within the range of The dimensionless normalized values ​​within the interval can be directly weighted and summed to obtain the joint sensitivity value. Also in Within the range.

[0029] It should be noted that the above-mentioned temperature control risk factors This refers to a normalized value calculated based on the degree and duration of temperature deviation from the compliance range within the sliding time window. The calculation formula is: in, Represents the natural constant. As a risk factor for temperature control, This represents the weighted cumulative temperature deviation within the sliding time window, expressed in degrees Celsius per minute (°C·min). To control Follow The positive real sensitivity coefficient of the growth rate, in units of The temperature sensitivity level is pre-defined according to the type of drug. and The product of these is a dimensionless value, thus ensuring that For the range of values ​​within Dimensionless normalized values ​​within the interval. The calculation method is as follows: For each sampling moment within the sliding time window, if the temperature sample value at that moment exceeds the upper limit of the compliant temperature range, the excess amount (i.e., the difference between the temperature sample value and the upper limit of the compliant temperature range, in °C) is multiplied by the time interval between adjacent sampling moments (in minutes) and then accumulated. If the temperature sample value at that moment does not exceed the compliant temperature range, then at that moment... The contribution is zero. This applies when the temperature within the window remains within the compliant range. ,thereby ;when When it increases Approaching .

[0030] It should be noted that the above-mentioned urgency of expiration date This refers to the decreasing function value of the ratio of the remaining shelf life of a drug batch to the standard shelf life of that type of drug. The calculation formula is: in, Due to the urgency of the expiration date, This refers to the remaining expiration date of the drug batch. The standard shelf life of this type of drug is defined by both, using the same time unit, and the ratio is... It is a dimensionless value, thus ensuring For the range of values ​​within The dimensionless normalized value within the interval. When near hour Approaching ,when Approaching zero Approaching .

[0031] Furthermore, the aforementioned urgency of the expiration date The formula is based on the time of drug batch entry into the warehouse. The starting point for calculation, i.e., the new batch of goods entering the warehouse. equal ,at this time As time goes by Continuously decreasing Monotonically increasing, until Approaching zero time Approaching Urgency of expiration date The implicit constraint of the formula is ,when When it exceeds this range (e.g., due to data anomalies) ), should be Cut off to Interval boundary value handling.

[0032] It should be noted that the length of the sliding time window mentioned above is preset according to the temperature sensitivity level corresponding to the type of cold chain drug. For highly temperature sensitive drugs (such as biological agents), the sliding time window is set to a shorter duration; for moderately temperature sensitive drugs, the sliding time window is set to a longer duration.

[0033] In this embodiment of the application, in order to complete the embedding of the temperature compliance status summary without significantly increasing the amount of data recorded in the active medical order mirror status form, the temperature compliance status summary adopts a compact encoding format, which encodes the current temperature value, the highest temperature value within the window, the cumulative duration of exceeding the standard, and the joint sensitivity value into a fixed-length byte sequence and appends it to the reserved extended field area of ​​the medical order record data structure.

[0034] Step 3: Incorporate the temperature compliance status summary into the incremental differential backup synchronization; When performing incremental differential calculations on the active medical order mirror status table, the temperature compliance status summary field is included in the differential detection scope. For each medical order record in the active medical order mirror status table that contains a temperature compliance status summary, the values ​​of each indicator in the temperature compliance status summary of the current micro-cycle and the previous micro-cycle are compared. When any indicator value in the temperature compliance status summary changes, the changed field value is included in the incremental differential packet. The incremental differential packet containing the temperature compliance status summary change data is sent to the backup and recovery node through dual-channel parallel transmission. After receiving the incremental differential packet, the backup and recovery node parses the temperature compliance status summary change data in the incremental differential packet and synchronously updates the temperature compliance status summary field of the corresponding medical order record in the locally maintained active medical order mirror status table.

[0035] It should be noted that the differential detection described above sets change detection thresholds for each indicator value when determining whether the temperature compliance status summary has changed. A change is determined to have occurred when the magnitude of the change in the current temperature value exceeds the temperature change detection threshold, and a change is also determined to have occurred when the increment of the cumulative duration of exceeding the limit exceeds the duration change detection threshold, combined with the sensitivity value. A change is considered to have occurred when the magnitude of the change exceeds the sensitivity change detection threshold. All of the above change detection thresholds are pre-configured fixed constants. The unit for the temperature change detection threshold is °C, the unit for the time change detection threshold is min, and the sensitivity change detection threshold is a dimensionless value with a range of [value missing]. Within the range. By setting a change detection threshold, frequent differential packet generation is avoided due to minor fluctuations in temperature sampling values.

[0036] In this embodiment, to further control the bandwidth usage of the real-time backup channel by the temperature compliance status summary synchronization, a hierarchical transmission strategy is adopted for the differential transmission of the temperature compliance status summary. When the joint sensitivity value is in the low-risk range, the temperature compliance status summary is included in the differential packet with a longer transmission interval; when the joint sensitivity value enters the warning range, the transmission interval is shortened to the same micro-cycle interval as the medical order execution parameter; when the joint sensitivity value enters the high-risk range, the temperature compliance status summary is included in the differential packet for transmission in every micro-cycle.

[0037] Furthermore, the division of low-risk, early warning, and high-risk zones in the aforementioned tiered transmission strategy is based on the pre-set early warning lower limit in step 5. and failure limit Confirmed: When When the time corresponds to the low-risk range, when The corresponding warning interval is when The three intervals correspond to the high-risk intervals, and are consistent with the compliance, early warning, and failure determination intervals in step 5 to ensure the consistency between transmission priority and risk determination logic.

[0038] Step 4: Identify temperature control risk batches based on temperature compliance status summary during disaster recovery switchover; When a disaster recovery switch is triggered by a primary system disaster, the backup and recovery node executes an indeterminate interval differential package supplementary application. After the indeterminate interval differential package supplementary application is completed, it reads the temperature compliance status summary of all medical order records containing cold chain drug batch identifiers from the active medical order mirror status table. For each temperature compliance status summary, it obtains the cumulative exceedance duration and the highest temperature value within the window, and compares them with the preset allowable offset threshold and storage temperature limit for that drug type, respectively. When the cumulative exceedance duration exceeds the allowable offset threshold, or the highest temperature value within the window exceeds the storage temperature limit, the corresponding cold chain drug batch is marked as a temperature control risk batch.

[0039] It should be noted that the aforementioned permissible deviation thresholds refer to the maximum allowable cumulative duration of deviations for different types of cold chain pharmaceuticals, based on their pharmacological characteristics and stability test data. Different types of pharmaceuticals have different permissible deviation thresholds; for example, the permissible deviation threshold for highly sensitive biological agents is shorter than that for general refrigerated pharmaceuticals.

[0040] It should be noted that the above-mentioned upper limit of storage temperature refers to the highest temperature value within the storage temperature range specified in the instructions or pharmacopoeia of cold chain drugs.

[0041] Step 5: Perform a temperature control compliance check during the medication regimen rationality verification process; For active medical order records associated with batches at risk of temperature control issues, add a temperature control compliance check to the medication regimen rationality verification process. Obtain the cumulative duration of exceeding the limit for batches at risk of temperature control issues and compare it with the expiration criteria corresponding to that drug type.

[0042] When the cumulative duration of exceeding the standard reaches the drug expiration determination standard, the execution status of the corresponding medical order record will be marked as cold chain suspension, a cold chain early warning event will be generated, and the cold chain early warning event will be pushed to the emergency terminal.

[0043] When the cumulative duration of exceeding the standard does not reach the failure judgment standard, and the combined sensitivity value is within the warning range, a temperature control risk warning mark is added to the corresponding medical order record, and the medical order record is activated as a state that can continue to be executed.

[0044] It should be noted that the aforementioned failure determination criteria refer to the cumulative time required for the active ingredient of a drug to degrade to an unacceptable level under specific temperature deviation conditions, as determined based on drug stability data. The failure determination criteria are stricter than the allowable deviation threshold; that is, the allowable deviation threshold serves as a preliminary risk screening condition, while the failure determination criteria serve as the final failure confirmation condition.

[0045] It should be noted that the above warning range refers to the joint sensitivity value. Greater than the lower limit of the warning And less than the failure limit The range of values ​​for , i.e. .when It is determined to be invalid when It was determined to be compliant at that time. and All are pre-configured dimensionless constants, with values ​​ranging from... Within the interval, and satisfying .

[0046] In this embodiment, to ensure timely processing of medical orders in a cold chain suspension state on the backup and recovery node, the cold chain early warning event includes the following information fields: medical order record identifier, drug batch identifier, drug generic name, values ​​of each indicator in the most recently synchronized temperature compliance status summary, corresponding patient identifier, and department identifier. After receiving the cold chain early warning event, the emergency terminal displays the medical order record in a cold chain suspension state with visual distinction markers on the medical order execution interface, and simultaneously generates drug batch replacement suggestions for medical staff reference.

[0047] Step 6: Estimate the temperature change curve during the disaster based on the temperature decay model; After the backup and recovery node takes over the operation, it initiates a complete recovery process for the temperature control time-series dataset associated with cold chain pharmaceuticals. During the recovery process, the start and end times of the temperature acquisition interruption caused by the disaster are identified. The last valid temperature sample value before the start time of the interruption is obtained as the initial temperature, and the reference temperature of the cold storage environment is acquired. Based on a temperature decay model, the temperature values ​​at each time point within the interruption are estimated using the initial and reference temperatures, generating a temperature change curve during the disaster.

[0048] The calculation formula for the above temperature decay model is as follows: in, The duration of time elapsed since the start of the interruption within the interruption interval. The estimated temperature value at the location, in °C; This refers to the reference temperature of the environment where the cold storage is located, in °C. This is the last valid temperature sample value before the start time of the interruption gap, in °C. Represents the natural constant; The heat decay coefficient of the cold storage, in units of ; This represents the elapsed time since the start of the interruption interval, in minutes. and The product is a dimensionless value, thus ensuring the dimensionality consistency of the exponent term and the overall formula. Units and and They are the same, both at ℃.

[0049] Furthermore, in the above temperature decay model, the thermal decay coefficient The physical meaning is: after the power is cut off, the temperature in the cold storage room will decrease to the ambient temperature. Approaching rate parameter A higher value indicates poorer cold storage insulation performance and a faster temperature rise. A smaller value indicates better cold storage insulation performance and a slower temperature recovery. As it approaches infinity, Approaching zero, Approaching This is consistent with the physical process by which the temperature of a cold storage facility eventually approaches ambient temperature after a power outage.

[0050] Using the estimated temperature change curves, the actual cumulative duration of exceeding the limit during the disaster was recalculated for each batch of cold chain medicines. The actual cumulative duration of exceeding the limit during the disaster was then added to the cumulative duration of exceeding the limit prior to the interruption, yielding the updated total cumulative duration of exceeding the limit. Based on the updated total cumulative duration of exceeding the limit and the medicine's shelf-life decay rules, the remaining effective shelf life of each batch of cold chain medicines was calculated.

[0051] It should be noted that the above thermal attenuation coefficient The coefficient of thermal decay is a constant value pre-calibrated based on the insulation performance parameters and historical temperature decay records of the cold storage. Different cold storage facilities have different thermal decay coefficients due to differences in insulation materials, volume, and sealing conditions.

[0052] It should be noted that the above reference temperature This refers to the ambient temperature that the cold storage room will eventually approach after a power outage. When some environmental monitoring data has been restored after a disaster, the actual measured ambient temperature value is used; when environmental monitoring data is unavailable, the typical indoor temperature value for the corresponding season in the region is used as a substitute.

[0053] In this embodiment, to improve the accuracy of the temperature decay model estimation, a segmented correction is performed on the model when cold storage door opening and closing records are available. When the cold storage door is open during a disaster, the heat decay coefficient is increased to a correction factor. ,in The corrected heat decay coefficient is given when the door is open. The original thermal decay coefficient, greater than The dimensionless door opening correction factor; when the cold storage door is closed, the original thermal decay coefficient is used. By calculating and stitching together the estimated temperature values ​​for each time period in segments, a temperature change curve that more closely reflects the actual situation can be obtained.

[0054] Furthermore, the specific implementation method of the above-mentioned segmented correction is as follows: the interruption gap is divided into several continuous sub-periods according to the switching time point between the cold storage door opening and closing states. For each sub-period, the estimated temperature value at the beginning of the sub-period is used as the initial temperature of the sub-period. This initial temperature is then substituted into the temperature decay model formula, and the corresponding heat decay coefficient is used (for the open state). Use when the door is closed Calculate the estimated temperature value at each time point within the sub-period; between adjacent sub-periods, the estimated temperature value at the end of the previous sub-period is used as the initial temperature of the next sub-period to ensure that the estimated temperature values ​​of each sub-period are continuously connected at the switching time point. Finally, the sequence of estimated temperature values ​​of each sub-period is spliced ​​together in chronological order to form a complete temperature change curve between interruptions.

[0055] Step 7: Compare the preliminary judgment results with the complete evaluation results and make corrections accordingly; The remaining effective service life, recalculated based on the complete temperature control time series dataset, will be compared with the preliminary judgment result made in step 5 during disaster recovery switching based on the temperature compliance status summary.

[0056] For drug batches initially determined to be executable but with a remaining effective shelf life of zero or less after a full assessment, these batches are classified as expired. A medication termination instruction is sent to the restored medical system, updating the execution status of the corresponding prescription record from executable to cold chain suspended. Simultaneously, a batch replacement suggestion is generated, instructing that the drug batch associated with the corresponding prescription be replaced with a compliant batch of the same drug, and updating the drug batch association information in the corresponding prescription record.

[0057] For drug batches initially deemed to have their cold chain suspended but still have a remaining effective shelf life greater than zero after a complete assessment, the initial assessment is considered conservative. The temperature control risk warning label for these batches will be updated to a corrected label containing complete assessment data, allowing healthcare professionals to reassess whether to resume use.

[0058] It should be noted that the aforementioned medication termination instruction refers to a control instruction sent by the system to the medical order execution module to forcibly stop the dispensing and administration of a specified batch of drugs in a particular medical order record. The execution priority of the medication termination instruction is higher than that of the regular medical order scheduling instruction.

[0059] In this embodiment, to ensure complete traceability and auditing of the correction process, a correction audit record is generated for each comparison and correction operation. The correction audit record includes: the drug batch identifier, a summary of temperature compliance status and values ​​for each indicator at the time of preliminary determination, the total cumulative duration of exceeding standards and the remaining effective shelf life after complete evaluation, the execution status of the medical orders before and after correction, and the timestamp of the correction operation. The correction audit record is written to the operation log of the backup and recovery node for subsequent quality traceability and compliance auditing.

[0060] This implementation embeds a summary of the temperature compliance status of cold chain medicines as an additional field into the data structure of the active medical order mirror status table, and includes this summary field in the synchronization range of incremental differential backup. This allows backup and recovery nodes to continuously receive temperature control compliance information for cold chain medicines during regular incremental differential synchronization. Therefore, when a disaster event triggers a disaster recovery switchover, the backup and recovery nodes, after completing the millisecond-level switchover and supplementing the uncertain interval differential package, can directly read the temperature compliance status summary of each batch of cold chain medicines from the locally maintained active medical order mirror status table without waiting for the complete recovery of the temperature control time-series dataset. Based on this, they can perform temperature control risk batch identification and temperature control compliance determination for cold chain medicines. This eliminates the blind spot period of temperature control compliance information between the completion of the disaster recovery switchover and the complete recovery of the temperature control time-series dataset, providing the ability to prevent the continued dispensing of medicines that have exceeded the standards within the immediate time window of the disaster recovery switchover.

[0061] Furthermore, the temperature compliance status summary is embedded in the reserved extended field of the medical order record in a compact encoding format, and the differential transmission adopts a hierarchical transmission strategy based on the joint sensitivity value. Therefore, the synchronization of the temperature compliance status summary has a limited bandwidth occupation on the real-time backup channel and does not change the overall transmission architecture of the existing micro-incremental differential backup synchronization mechanism.

[0062] Furthermore, after the backup and recovery node takes over the operation, the actual cumulative duration of exceeding the standard and the remaining effective shelf life of each batch of cold chain medicines are recalculated through the complete recovery of the temperature control time-series dataset and the temperature estimation during the disaster based on the temperature decay model. This recalculation is then compared and corrected with the initial judgment results during the disaster recovery switchover. Therefore, any judgment bias that may exist in the initial judgment stage due to the limited granularity of information can be corrected by the accurate data in the complete assessment stage. This forms a two-stage disaster recovery verification process that connects rapid initial screening with accurate reassessment, ensuring the immediate security of the disaster recovery switchover while improving the accuracy of the final medication decision.

[0063] The following is an example of an application of the present invention, such as Figure 2-9 As shown, the implementation process is as follows: A major system disaster occurred in the medical system of the Emergency Intensive Care Unit (ICU) of a tertiary hospital in the early morning of a certain day in 20XX. The ICU uses three types of cold-chain medications: antivenom serum (batch number BCH-AV042), emergency insulin (batch number BCH-IN087), and recombinant human erythropoietin injection (batch number BCH-EP031). Temperature data is continuously collected by temperature monitoring devices DEV-C01, DEV-C02, and DEV-C03 in the cold storage. The disaster caused the main system to crash and simultaneously triggered a power outage in the cold storage, interrupting the temperature monitoring data collection. Backup and recovery nodes completed the disaster recovery switchover within milliseconds, but the complete recovery of the temperature monitoring time-series dataset was expected to take tens of minutes. The following demonstrates the specific execution process of each step in this scenario.

[0064] In the ICU's medical system, there are currently 7 active medical orders. The system extracts the batch identifier of each active order and matches it against a cold chain drug batch association mapping table. Batch numbers BCH-AV042, BCH-IN087, and BCH-EP031 all found corresponding entries in the mapping table, while the remaining batch numbers (such as the ordinary intravenous injection batch PNS-L201 and the antibiotic batch ABT-K103) did not find any matching entries and were excluded from further processing. The final set of active cold chain drug medical order records contains 5 medical order records, each with its associated temperature monitoring device identifier.

[0065] Table 1. Collection of active medical order records for cold chain medications (Results of Step 1 screening): The system acquires the latest temperature sampling values ​​of DEV-C01, DEV-C02, and DEV-C03 at preset micro-period intervals (500 milliseconds in this scenario), and calculates a temperature compliance status summary within their respective sliding time windows. Specifically, the sliding time window for antivenom serum (biological agent, high temperature sensitivity) is 30 minutes, while the sliding time window for emergency insulin (moderate temperature sensitivity) and recombinant human erythropoietin injection (moderate temperature sensitivity) is 60 minutes. The upper limit of the compliant storage temperature range for each batch is 8°C.

[0066] Taking batch BCH-AV042 (antive venom serum) as an example, the calculation process of the combined sensitivity value S is explained.

[0067] Calculation of temperature control risk factor Rtc: Within a 30-minute sliding window, DEV-C01 recorded three instances of exceeding the standard sampling rate: 9.4℃ at minute 8 (exceeding the compliance limit by 1.4℃, lasting 2 minutes), 10.1℃ at minute 15 (exceeding the compliance limit by 2.1℃, lasting 1 minute), and 9.7℃ at minute 22 (exceeding the compliance limit by 1.7℃, lasting 2 minutes). The cumulative temperature deviation is: Sensitivity coefficient of antivenom serum ,but: Calculation of the urgency of expiry date (Uexp): BCH-AV042 batch has a remaining shelf life of 4 months, and the standard shelf life for this type of drug is 18 months. Therefore: Calculation of the joint sensitivity value S: taking the weighting coefficients , ,but: The temperature compliance status summary calculation results for the three batches are shown in the table below, and are appended to the reserved extended field of the corresponding record in the active medical order mirror status table in a compact encoding format.

[0068] Table 2 Summary of Temperature Compliance Status of Each Cold Chain Drug Batch (Calculation Results from Step 2): During each micro-cycle, when performing incremental differential calculations, the system incorporates each field of the temperature compliance status summary in the table above into the differential detection range. The preset change detection thresholds are: temperature change detection threshold 0.2℃, duration change detection threshold 1 minute, and sensitivity change detection threshold 0.05.

[0069] Based on the comparison of the combined sensitivity value S of each batch with the preset thresholds (S_low threshold = 0.30, S_high threshold = 0.65), the tiered transmission strategy is implemented as follows: BCH-AV042, with S = 0.602, satisfies S_low threshold < S_high threshold, placing it in the warning range. Its temperature compliance status summary is included in the differential packet at the same micro-period interval (500 milliseconds) as the medical order execution parameters. BCH-IN087, with S = 0.261, and BCH-EP031, with S = 0.257, both satisfy S ≤ S_low threshold, placing them in the low-risk range. They are included in the differential packet at a longer transmission interval (set to 30 seconds in this scenario). The micro-incremental differential packets containing the temperature compliance status summary change data are sent to the backup and recovery node through dual-channel parallel transmission. After parsing, the backup and recovery node synchronously updates the extended fields of the corresponding records in the local active medical order mirror status table.

[0070] When a disaster occurs in the main system, the backup and recovery node completes the millisecond-level disaster recovery switch and executes the uncertain interval differential package supplementary application. It then immediately reads the temperature compliance status summary of all 5 cold chain drug-related medical order records in the active medical order image status table, compares the cumulative time exceeding the standard with the preset allowable offset threshold for each batch, and compares the highest temperature value within the window with the upper limit of the storage temperature for each batch (all 8°C) to identify batches with temperature control risks.

[0071] Table 3. Batch Identification and Judgment for Temperature Control Risks (Step 4): The highest temperature values ​​within the window of all three batches exceeded the upper limit of storage temperature by 8°C, so they were all marked as temperature control risk batches and entered the temperature control compliance determination process in step 5.

[0072] For all five active medical order records associated with the three batches at risk of temperature control issues, a temperature control compliance check was added to the medication regimen rationality verification process. The cumulative duration of exceeding the limit for each batch was compared with the failure judgment standard, and the combined sensitivity value S was compared with the warning interval (S low threshold = 0.30, S high threshold = 0.65) to determine the handling result of each medical order record.

[0073] BCH-AV042's S=0.602 falls within the warning range (0.30 < 0.602 < 0.65), and the cumulative time exceeding the limit is 5 minutes, which does not meet the failure criterion (the failure criterion for antivenom serum is a cumulative time exceeding the limit for 8 minutes). Therefore, associated medical orders ORD-E0041 and ORD-E0042 have a temperature control risk warning tag added and are activated as executable. BCH-IN087 and BCH-EP031 both have S values ​​below the low threshold, and the cumulative time exceeding the limit does not meet the failure criterion (the failure criterion for insulin is 30 minutes, and for erythropoietin it is 25 minutes). The associated medical orders also have a temperature control risk warning tag added and are activated as executable.

[0074] Table 4 Temperature control compliance judgment results (step 5): After the backup and recovery node took over the operation, it identified a 20-minute interval in temperature data acquisition during the disaster (using the cold storage where BCH-AV042 is located as an example). At the start of the interval, the last valid sample value of DEV-C01 was 9.7℃, the ambient reference temperature of the cold storage was 26.0℃, and the thermal decay coefficient of the cold storage was k=0.035min⁻¹ (pre-calibrated based on the historical temperature decay records of the cold storage). The cold storage door records during the disaster showed that the cold storage door was open from the 5th to the 9th minute of the interval (door opening correction factor γ=1.8, corrected thermal decay coefficient k'=0.035×1.8=0.063min⁻¹), and the cold storage door was closed during the rest of the time.

[0075] Temperature estimates were calculated in three segments: First segment (door closed, time from 0 to 5 minutes): Second segment (with the door open, starting at 12.32℃, t from 0 to 4 minutes): Third segment (door closed, starting at 15.37℃, t from 0 to 11 minutes): Since the maximum compliant storage temperature for BCH-AV042 is 8°C, the estimated temperature exceeded 8°C throughout the 20-minute interruption interval, resulting in a cumulative excess time of 20 minutes during the disaster. Adding this to the 5 minutes of cumulative excess time before the interruption, the total cumulative excess time after the BCH-AV042 update was 25 minutes, far exceeding the failure threshold of 8 minutes. Therefore, the remaining usable lifespan of this batch is determined to be zero.

[0076] Table 5. Temperature estimates and cumulative duration of exceeding limits for each batch of cold chain pharmaceuticals during the disaster (Step 6): The complete evaluation results from step 6 were compared batch by batch with the preliminary judgment results from step 5. BCH-AV042, after the update, had a total cumulative exceedance time of 25 minutes, exceeding its failure judgment standard by 8 minutes, and was therefore deemed invalid. BCH-IN087, after the update, had a total cumulative exceedance time of 23 minutes, not exceeding its failure judgment standard of 30 minutes, and remained valid. BCH-EP031, after the update, had a total cumulative exceedance time of 21 minutes, not exceeding its failure judgment standard of 25 minutes, with approximately 2 days of remaining effective usage period, and was preliminarily determined to require no correction.

[0077] Table 6 Comparison and correction of preliminary judgment results with complete assessment results (Step 7): For ORD-E0041 and ORD-E0042 associated with BCH-AV042, the system sends a medication termination instruction to the medical order execution module, updates the execution status from "can continue" to "cold chain suspended", generates a batch replacement suggestion, instructs that it should be replaced with a compliant batch of the same product, and generates a correction audit record and writes it to the operation log.

[0078] The data flow throughout the entire implementation process demonstrates a clear logical chain: Step 1 selects 5 cold chain drug-related records from all active medical orders, carrying batch and equipment identifiers, and flows into Step 2; Step 2 calculates a temperature compliance status summary (including a joint sensitivity value S) for each batch based on real-time temperature sampling, embeds the summary into the extended field of the active medical order mirror status table, and Step 3 continuously synchronizes it to the backup and recovery node according to the S value; After a disaster event is triggered, Step 4 directly reads the summary data from the local table of the backup and recovery node, identifies 3 temperature control risk batches based on both over-temperature and timeout conditions, and the data flows into... Step 5; Step 5 combines the failure judgment criteria and warning interval to complete the initial judgment, and all 5 medical orders enter the state of being able to continue execution; Step 6 uses the temperature decay model to estimate the 20-minute interruption interval in segments, recalculates the total cumulative time exceeding the standard, and the data flows into Step 7; Step 7 corrects the initial judgment with complete evaluation data, BCH-AV042 is judged to be invalid and triggers the medication termination instruction and batch replacement recommendation, while BCH-IN087 and BCH-EP031 remain in the state of being able to continue execution, forming a complete and coherent data flow process from the initial active medical order data to the final medication safety decision.

[0079] The embodiments of the present invention have been described above. However, the embodiments are not limited to the specific implementation methods described above. The specific implementation methods described above are merely illustrative and not restrictive. Those skilled in the art can make more equivalent embodiments under the guidance of the present embodiments, and all of them are within the protection scope of the present embodiments.

Claims

1. A disaster recovery method for a medical system based on data backup, characterized in that, Includes the following steps: Obtain medical order records that are in active execution status, match the drug batch identifiers involved in the medical order records with the cold chain drug batch association mapping table, filter out active medical order records that use cold chain drugs, and generate a set of active medical order records for cold chain drugs. For each batch of cold chain medicine associated with the temperature control monitoring device in the active medical order record set of cold chain medicines, the latest temperature sampling value is obtained at micro-period intervals, the temperature compliance status summary within the sliding time window is calculated, and the temperature compliance status summary is embedded as an additional field into the data structure of the corresponding medical order record in the active medical order mirror status table; The temperature compliance status summary field is included in the micro-incremental differential detection range, and the micro-incremental differential packet containing the temperature compliance status summary change data is sent to the backup and recovery node through dual-channel parallel transmission. When a disaster event in the main system triggers a disaster recovery switch, the backup recovery node reads the temperature compliance status summary from the locally maintained active medical order image status table and identifies temperature control risk batches based on the cumulative duration of exceeding the standard and the highest temperature value within the window. For the active medical order records associated with the aforementioned temperature control risk batches, a temperature control compliance determination is performed during the medication regimen rationality verification process, and the medical order execution status is marked based on the determination result; After the backup and recovery node takes over the operation, it estimates the temperature change curve during the disaster based on the temperature decay model, recalculates the remaining effective shelf life of each batch of cold chain medicines, compares the complete assessment results with the preliminary judgment results, and performs corrections. The temperature compliance status summary includes the current temperature value, the highest temperature value within the window, the cumulative duration of exceeding the standard, and a joint sensitivity value. The joint sensitivity value is obtained by weighted fusion calculation based on temperature control risk factors and expiration date urgency.

2. The disaster recovery method for a medical system based on data backup according to claim 1, characterized in that, The calculation method of the joint sensitivity value is as follows: the value obtained by multiplying the temperature control risk factor by the temperature control risk weight coefficient is added to the value obtained by multiplying the expiration date urgency by the expiration date urgency weight coefficient, and the sum of the temperature control risk weight coefficient and the expiration date urgency weight coefficient is equal to 1; The temperature control risk factor and the expiration date urgency are both dimensionless normalized values ​​ranging from 0 to 1, and the joint sensitivity value also ranges from 0 to 1.

3. The disaster recovery method for a medical system based on data backup according to claim 2, characterized in that, The temperature control risk factor is calculated as follows: subtract the negative exponent of the natural constant from 1, where the exponent of the negative exponent is the negative value of the product of the sensitivity coefficient and the weighted cumulative temperature deviation. The sensitivity coefficient is a positive real number pre-calibrated by the temperature sensitivity level corresponding to the drug type. The weighted cumulative temperature deviation is calculated as follows: for each sampling moment within the sliding time window, if the temperature sampling value at that moment exceeds the upper limit of the compliant temperature range, the excess temperature at that moment is multiplied by the time interval between adjacent sampling moments and then accumulated. If the temperature sampling value at that moment does not exceed the compliant temperature range, the contribution at that moment is zero.

4. The disaster recovery method for a medical system based on data backup according to claim 2, characterized in that, The method for calculating the urgency of the expiration date is as follows: subtract 1 from the ratio of the remaining expiration date of the drug batch to the standard expiration date of the drug type; the remaining expiration date is calculated from the time the drug batch enters the warehouse, and the remaining expiration date at the time of entry into the warehouse is equal to the standard expiration date. As time goes by, the remaining expiration date continuously decreases, and the urgency of the expiration date increases monotonically; when the remaining expiration date exceeds the range of 0 to the standard expiration date, the urgency of the expiration date is truncated to the boundary value of the interval between 0 and 1.

5. The disaster recovery method for a medical system based on data backup according to claim 1, characterized in that, Including the temperature compliance status summary field in the micro-incremental differential detection range includes: setting change detection thresholds for each indicator value in the temperature compliance status summary; determining a change when the change in the current temperature value exceeds the temperature change detection threshold; determining a change when the increment of the cumulative exceedance time exceeds the duration change detection threshold; and determining a change when the change in the joint sensitivity value exceeds the sensitivity change detection threshold; each change detection threshold is a pre-configured fixed constant. The differential transmission of the temperature compliance status summary adopts a hierarchical transmission strategy: when the joint sensitivity value is less than or equal to the warning lower limit, the temperature compliance status summary is included in the differential packet with a long transmission interval period; when the joint sensitivity value is greater than the warning lower limit but less than the failure upper limit, the transmission interval period is shortened to the same micro-cycle interval as the medical order execution parameter; when the joint sensitivity value is greater than or equal to the failure upper limit, the temperature compliance status summary is included in the differential packet for transmission in each micro-cycle; the warning lower limit and the failure upper limit are both pre-configured dimensionless constants and the warning lower limit is less than the failure upper limit.

6. The disaster recovery method for a medical system based on data backup according to claim 1, characterized in that, Identifying temperature-controlled risk batches based on cumulative exceedance duration and highest temperature value within a window includes: After the backup and recovery node executes the uncertain interval differential package supplementary application, it reads the temperature compliance status summary of all medical order records containing cold chain drug batch identifiers in the active medical order mirror status table; for each temperature compliance status summary, it compares the cumulative exceedance duration with the preset allowable offset threshold for that drug type, and compares the highest temperature value within the window with the storage temperature limit for that drug type; when the cumulative exceedance duration exceeds the allowable offset threshold or the highest temperature value within the window exceeds the storage temperature limit, the corresponding cold chain drug batch is marked as a temperature-controlled risk batch.

7. The disaster recovery method for a medical system based on data backup according to claim 6, characterized in that, The temperature control compliance determination includes: obtaining the cumulative duration of temperature control risk batches exceeding the standard and comparing it with the failure determination standard corresponding to the drug type; when the cumulative duration of exceeding the standard reaches the failure determination standard, marking the execution status of the corresponding medical order record as cold chain suspension, generating a cold chain early warning event and pushing it to the emergency terminal; when the cumulative duration of exceeding the standard does not reach the failure determination standard and the joint sensitivity value is greater than the lower limit of the early warning and less than the upper limit of failure, adding a temperature control risk warning mark to the corresponding medical order record and activating the medical order record as a state that can continue to be executed; the failure determination standard is stricter than the allowable offset threshold.

8. The disaster recovery method for a medical system based on data backup according to claim 1, characterized in that, Estimating the temperature change curve during a disaster based on a temperature decay model includes: identifying the start and end times of the temperature acquisition interruption caused by the disaster; obtaining the last valid temperature sample value before the start time of the interruption as the initial temperature; and obtaining the reference temperature of the environment where the cold storage is located. The temperature decay model is calculated as follows: the estimated temperature value is equal to the environmental reference temperature plus the difference between the initial temperature and the environmental reference temperature multiplied by the negative exponent of the natural constant. The exponent of the negative exponent is the negative value of the product of the thermal decay coefficient and the elapsed time since the start time of the interruption. The thermal decay coefficient is pre-calibrated based on the insulation performance parameters of the cold storage and historical temperature decay records.

9. The disaster recovery method for a medical system based on data backup according to claim 8, characterized in that, With access to cold storage door opening and closing records, the temperature decay model is modified in segments: the interruption gap is divided into several consecutive sub-periods based on the switching time between the cold storage door opening and closing states; when the cold storage door is open, the heat decay coefficient is increased to the original heat decay coefficient multiplied by a dimensionless door opening correction factor greater than 1 to obtain the modified heat decay coefficient; when the cold storage door is closed, the original heat decay coefficient is used; for each sub-period, the estimated temperature value at the beginning of the sub-period is used as the initial temperature and substituted into the temperature decay model for calculation; between adjacent sub-periods, the estimated temperature value at the end of the previous sub-period is used as the initial temperature of the next sub-period; the estimated temperature values ​​of each sub-period are spliced ​​together in chronological order to form a complete temperature change curve for the interruption gap. The actual cumulative duration of exceeding the standard during the disaster is recalculated using the estimated temperature change curve. This is then added to the cumulative duration of exceeding the standard before the interruption to obtain the updated total cumulative duration of exceeding the standard. Based on the updated total cumulative duration of exceeding the standard, the remaining effective shelf life of each batch of cold chain medicines is calculated.

10. A disaster recovery system for a medical system based on data backup, used to execute the disaster recovery method for a medical system based on data backup as described in any one of claims 1 to 9, characterized in that, include: The cold chain medical order screening module is used to obtain medical order records that are in an active execution state, match the drug batch identifiers involved in the medical order records with the cold chain drug batch association mapping table, filter out active medical order records that use cold chain drugs, and generate a set of active medical order records for cold chain drugs. The temperature compliance status summary calculation and embedding module is used to obtain the latest temperature sampling value of each batch of cold chain medicine associated with the temperature control monitoring device in the active medical order record set of cold chain medicine at micro-period intervals, calculate the temperature compliance status summary within the sliding time window, and embed the temperature compliance status summary as an additional field into the data structure of the corresponding medical order record in the active medical order mirror status table; The differential synchronization module is used to include the temperature compliance status summary field into the micro-incremental differential detection range, and sends the micro-incremental differential packet containing the temperature compliance status summary change data to the backup and recovery node through dual-channel parallel transmission. The temperature control risk batch identification module is used to read the temperature compliance status summary from the active medical order image status table maintained locally by the backup recovery node when a disaster event triggers a disaster recovery switch in the main system, and to identify temperature control risk batches based on the cumulative duration of exceeding the standard and the highest temperature value within the window. The temperature control compliance determination module is used to perform temperature control compliance determination on active medical order records associated with temperature control risk batches during the medication regimen rationality verification process, and mark the medical order execution status based on the determination result; The temperature estimation and correction module is used to estimate the temperature change curve during the disaster based on the temperature decay model after the backup and recovery node takes over the operation, recalculate the remaining effective shelf life of each batch of cold chain medicines, compare the complete assessment results with the preliminary judgment results, and perform corrections.

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