Intelligent handwriting board-based clinical blood whole-process paperless management system and method

Abstract

The application belongs to the technical field of medical information, and discloses a clinical blood use whole-process paperless management system and method based on an intelligent handwriting board; through technical means such as structured form data acquisition, identity permission verification, handwriting integrity evaluation, signature image processing, document integrity check and safe archiving, comprehensive electronic management of the clinical blood use process is realized. The pressure sensing sampling technology is used to collect the signature trajectory and pressure value sequence, the handwriting integrity scoring mechanism is used to ensure the signature quality, the cryptography technology is used to generate the document fingerprint value to protect the document from being tampered, and the complete operation link record is constructed to realize the whole-process traceability. The application effectively improves the clinical blood use work efficiency, enhances the safety and standardization of the blood transfusion link, and optimizes the medical document storage and retrieval ability.

Description

Technical Field

[0001] This invention relates to the field of medical information technology, and more specifically, to a paperless management system and method for the entire clinical blood use process based on a smart handwriting tablet. Background Technology

[0002] Traditional clinical blood management faces several unresolved technical challenges. Frequent paper-based document transfers between hospital blood banks and clinical departments, especially during multi-departmental collaborations or emergency situations, often result in delayed delivery of blood products, directly impacting rescue efficiency. Paper signatures cannot be verified in real-time; in busy clinical environments, proxy signatures and retroactive signatures are common, severely weakening the legal validity of signatures and the effectiveness of clinical oversight. The boundaries of authority for medical staff are difficult to define precisely in traditional processes, allowing unqualified personnel to participate in key decision-making, creating potential medical safety risks. Furthermore, paper signatures lack objective quality assessment standards; careless and illegible signatures are widespread and difficult to standardize, reducing the professionalism and legibility of documents. In the event of medical disputes, paper-based processes fail to provide detailed timelines and evidence of responsibility chains; investigators often spend considerable time sifting through fragmented records, still struggling to reconstruct the full truth. In complex transfusion processes, documents often become stuck at certain stages for various reasons, lacking effective monitoring and reminder mechanisms, leading to process interruptions or delays. Furthermore, the widespread implementation of information technology in hospitals contrasts sharply with the paper-based blood transfusion process, making data exchange difficult. Medical staff are required to switch back and forth between electronic systems and paper documents, increasing their workload and introducing the risk of transcription errors.

[0003] In view of this, the present invention proposes a paperless management system and method for the entire clinical blood use process based on a smart handwriting tablet to solve the above problems. Summary of the Invention

[0004] To overcome the aforementioned shortcomings of existing technologies and achieve the above objectives, this invention provides the following technical solution: a paperless management method for the entire clinical blood use process based on a smart handwriting tablet, comprising: The system obtains structured form data of the current business node from the blood transfusion management system, parses the preset signature anchor point identifier in the document template, and calculates the absolute coordinate range and signature capacity size constraint of each signature area in the generated PDF document based on the signature anchor point identifier. When the signature area is activated, the operator's identity credential data is collected. The identity credential data is compared with the department personnel permission mapping table to extract the operator's role type label and authorized signature range identifier, and to determine whether the current operator has the business signing permission for the corresponding signature area. After the business signing permission verification is passed, the smart handwriting tablet is started, and the touch trajectory coordinate sequence and pressure value sequence are collected at a preset sampling frequency. The touch trajectory coordinate sequence is divided into several stroke segments according to the time interval between adjacent sampling points. The handwriting integrity score is calculated based on the number of effective sampling points and pressure value distribution characteristics of the stroke fragment. The handwriting integrity score is compared with the signature validity threshold. If it is lower than the threshold, a re-signing instruction is sent. If it reaches the threshold, the stroke fragment is vectorized and rendered to generate a signature image. After performing proportional scaling and coordinate offset transformation on the signature image according to the absolute coordinate range and signature capacity size constraint, it is written into the corresponding signature area of ​​the PDF document, and a signature traceability record containing the operator's employee number, signature timestamp, terminal device identifier and handwriting integrity score is embedded in the metadata area of ​​the PDF document. After the signature traceability record is written, the signature areas corresponding to all signature anchor identifiers in the PDF document are traversed to check whether each signature area has been associated with a valid signature traceability record. Based on the detection result, the signing completion status is determined and an archiving operation or a pending signature reminder notification is triggered. Upon completion of all signing, a hash digest calculation is performed on the PDF document to generate a document fingerprint value. The PDF document and the document fingerprint value are then uploaded to the electronic medical record archiving system. A complete operation chain record containing the document fingerprint value, traceability records of each signature, and business node identifiers is written into the audit log.

[0005] A paperless management system for the entire clinical blood use process based on a smart handwriting tablet is used to implement a paperless management method for the entire clinical blood use process based on a smart handwriting tablet, including: The document construction module is used to obtain structured form data of the current business node from the blood transfusion management system, parse the preset signature anchor point identifier in the document template, and calculate the absolute coordinate range and signature capacity size constraint of each signature area in the generated PDF document based on the signature anchor point identifier. The identity anchoring module is used to collect the operator's identity credential data when the signature area is activated, compare the identity credential data with the department personnel permission mapping table, extract the operator's role type label and authorized signature range identifier, and determine whether the current operator has the business signing permission for the corresponding signature area. The handwriting acquisition module is used to start the smart handwriting tablet after the business signing permission verification is passed, acquire the touch trajectory coordinate sequence and pressure value sequence at a preset sampling frequency, and divide the touch trajectory coordinate sequence into several stroke segments according to the time interval between adjacent sampling points. The handwriting quality assessment module is used to calculate the handwriting integrity score based on the number of effective sampling points and pressure value distribution characteristics of the stroke fragment, compare the handwriting integrity score with the signature validity threshold, send a re-signing instruction if it is lower than the threshold, and perform vectorized rendering on the stroke fragment to generate a signature image if it reaches the threshold. The signature fusion module is used to perform proportional scaling and coordinate offset transformation on the signature image according to the absolute coordinate range and signature capacity size constraint, and then write it into the corresponding signature area of ​​the PDF document. The module also embeds a signature traceability record containing the operator's employee number, signature timestamp, terminal device identifier and handwriting integrity score in the metadata area of ​​the PDF document. The process closed-loop determination module is used to traverse all signature areas corresponding to all signature anchor identifiers in the PDF document after the signature traceability record is written, detect whether each signature area has been associated with a valid signature traceability record, determine the signing completion status based on the detection result and trigger archiving operation or pending signature reminder notification. The archiving and auditing module is used to perform hash digest calculation on the PDF document to generate a document fingerprint value when all signing is completed, upload the PDF document and the document fingerprint value to the electronic medical record archiving system, and write a complete operation link record containing the document fingerprint value, each signature traceability record and business node identifier into the audit log.

[0006] The technical effects and advantages of the paperless management system and method for the entire clinical blood use process based on a smart handwriting tablet in this invention are as follows: This invention's precise identity and authorization verification mechanism constructs a robust operational protection network, ensuring that every step of the operation strictly complies with medical standards, thus improving the level of blood transfusion safety from a technical perspective. Handwriting analysis methods enable objective quantitative assessment of signature quality, eliminating the subjectivity of manual judgment and guaranteeing the standardization and consistency of document signing. A full-link data tracking mechanism enables complete traceability from application, review, blood dispensing, transfusion to archiving, providing precise location capabilities for medical quality control and incident investigation. Cryptographic security mechanisms solve the integrity verification problem in long-term storage. Real-time status monitoring and intelligent reminder functions eliminate the risk of process interruption, ensuring the continuity and timeliness of clinical blood use. Seamless integration between systems eliminates information silos, achieving integrated data flow and reducing the risk of transcription errors. Attached Figure Description

[0007] Figure 1 This is a schematic diagram of the paperless clinical blood use management system based on a smart handwriting tablet, as described in this invention. Figure 2 This is a schematic diagram of the paperless management method for the entire clinical blood use process based on a smart handwriting tablet, as described in this invention. Detailed Implementation

[0008] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0009] This invention provides a paperless management system and method for the entire clinical blood use process based on a smart handwriting tablet. Please refer to [link / reference]. Figure 1 In this embodiment of the invention, the paperless management system for the entire clinical blood use process based on a smart handwriting tablet includes: The document construction module is used to obtain structured form data of the current business node from the blood transfusion management system, parse the preset signature anchor identifiers in the document template, and calculate the absolute coordinate range and signature size constraints of each signature area in the generated PDF document based on the signature anchor identifiers. This method first connects to the blood transfusion management system database interface to obtain structured form data of the business node in real time, including core data elements such as patient basic information, requesting physician information, blood transfusion type and quantity, and blood product identification codes. The structured form data is obtained through a pre-configured secure interface protocol to ensure data integrity and real-time performance. The document template is defined in XML format, where the signature anchor identifier is embedded in a special markup form, recording the relative positioning information and size constraint parameters of the signature area. The PDF document is dynamically generated by the template engine based on the structured data, maintaining the standardization and consistency of the document format. The calculated absolute coordinate range ensures the accurate positioning of the signature area on different terminal devices, while the signature size constraints ensure the clarity and integrity of the signature image.

[0010] The identity anchoring module collects the operator's identity credentials when the signature area is activated. It compares this data with the departmental personnel permission mapping table to extract the operator's role type tag and authorized signature range identifier, determining whether the operator has the necessary business signing permissions for the corresponding signature area. When a user triggers the signature area, the system first initiates an identity verification process, collecting the operator's identity credentials through various authentication methods such as smart cards, fingerprint recognition, employee ID passwords, or biometrics. The departmental personnel permission mapping table is stored in a secure database and employs a role-based access control model, precisely defining the scope of business operations and authorization levels for each role. The comparison process first verifies the validity of the identity credentials and then checks the permission matching degree. Role type tags include key role categories such as blood dispensing personnel, blood collection nurses, and checking physicians, with each tag associated with a specific authorized signature range identifier. Authorization verification ensures that operators can only sign within their scope of responsibility, effectively preventing unauthorized operations and ensuring standardized management of clinical blood use.

[0011] The handwriting capture module is used to activate the smart handwriting tablet after successful business signing authorization verification. It collects touch trajectory coordinate sequences and pressure value sequences at a preset sampling frequency, and segments the touch trajectory coordinate sequence into several stroke segments based on the time interval between adjacent sampling points. After authorization verification, the system activates the pressure-sensitive sampling module of the smart handwriting tablet, enabling high-precision coordinate acquisition and pressure sensing channels. The sampling frequency is typically set to 100-200Hz to ensure the capture of subtle handwriting features during the signing process. The touch trajectory coordinate sequence records the two-dimensional positional changes of the pen tip on the handwriting tablet surface; each sampling point includes X-coordinate, Y-coordinate, and a timestamp. The pressure value sequence records the pressure changes during writing, reflecting the dynamic characteristics of writing force. By analyzing the time interval between adjacent sampling points, the system identifies the state transitions of pen placement and lifting. When the time interval exceeds a preset break threshold (usually 300-500 milliseconds), the system determines it as a stroke interruption and accordingly segments the continuous touch trajectory into independent stroke segments. Each stroke segment represents a natural writing unit in the signature, preserving the structural and writing habits of the signature, and providing a basic unit for subsequent integrity assessment.

[0012] The handwriting quality assessment module calculates a handwriting integrity score based on the number of valid sampling points and pressure value distribution characteristics of stroke segments. This score is compared to a signature validity threshold; if the score is below the threshold, a re-signing command is sent; if the score reaches the threshold, the stroke segment is vectorized and rendered to generate a signature image. The handwriting integrity score is a comprehensive indicator of signature quality, reflecting both clarity and writing quality. The calculation process first counts the number of sampling points in each stroke segment whose pressure values ​​exceed the minimum effective pressure threshold (typically 10% of the device's maximum pressure value), obtaining the number of valid sampling points. Then, the effective point coverage rate is calculated to measure the overall clarity of the signature. Simultaneously, the fluctuation characteristics of pressure values ​​within each segment are analyzed to assess writing stability. The formula for calculating the handwriting integrity score is: ; in, A score is given for handwriting integrity, with values ​​ranging from [0,1]. For the first The number of valid sampling points for each stroke segment This represents the total number of sampling points for this segment. This represents the standard deviation of the pressure values ​​for that segment. This represents the average pressure value of that segment. The total number of stroke segments. This is the weighting coefficient (usually set to 0.6-0.7).

[0013] The signature validity threshold is typically set between 0.75 and 0.85. When the handwriting integrity score falls below this threshold, the system determines that the current signature quality is insufficient and sends a re-signing instruction to the handwriting acquisition module, prompting the operator to re-sign. When the score reaches the threshold, the system vectorizes each stroke segment, converting the discrete sampling point sequence into a smooth Bézier curve, and adjusts the line thickness according to the pressure value, ultimately generating a high-quality signature image to ensure the visual effect and recognizability of the signature.

[0014] The signature fusion module performs proportional scaling and coordinate offset transformation on the signature image based on the absolute coordinate range and signature capacity constraints, then writes it into the corresponding signature area of ​​the PDF document. It also embeds a signature traceability record containing the operator's employee number, signature timestamp, terminal device identifier, and handwriting integrity score into the PDF document's metadata area. The signature image processing uses appropriate image transformations to perfectly fit the signature to the preset area. The process first obtains the original size of the signature image and compares it with the capacity size of the signature area; then, it calculates an appropriate scaling ratio to ensure the signature neither exceeds the area boundary nor becomes too small to affect readability; finally, it calculates a centering offset to center the signature within the area. Scaling follows a proportional principle to avoid signature distortion and maintain original morphological characteristics. The transformed signature image is written to a separate layer in the PDF document, ensuring it does not mix with the underlying text for easier later verification and management. Simultaneously, the system embeds a complete signature traceability record in the PDF document's metadata area (usually in XMP format), including the operator's employee number, a signature timestamp accurate to milliseconds, a unique identifier for the terminal device, and a handwriting integrity score. This metadata is stored in an encrypted manner to ensure it is not tampered with, providing a reliable technical basis for subsequent signature verification and auditing.

[0015] The process closure determination module, after the signature traceability record is written, iterates through all signature areas corresponding to signature anchor identifiers in the PDF document, checks whether each signature area is associated with a valid signature traceability record, determines the signing completion status based on the detection results, and triggers archiving operations or pending signature reminder notifications. The document integrity check systematically verifies whether all necessary signatures have been completed. The check process first extracts all predefined signature anchor identifiers from the document template to construct a complete signature requirement list; then it iterates through the metadata area in the document, retrieving the signature traceability record corresponding to each signature area; finally, it compares the actual signing status with the requirement list to determine the document's signing status. The signing completion status is divided into two types: "All Signatures Completed" and "Pending Signing". When all necessary signatures have been completed and the handwriting integrity score of each signature has reached the validity threshold, the system determines that "all signatures are completed" and triggers the subsequent document archiving process. If there are any incomplete necessary signatures, the system determines that the document is in a "pending signature" state. The system automatically generates a pending signature reminder notification, which includes a description of the unsigned area, the corresponding role type, and operation instructions. This notification is sent to relevant personnel through the hospital's internal messaging system to ensure that the process is not interrupted and to improve business processing efficiency.

[0016] The archiving and auditing module performs a hash digest calculation on the PDF document upon completion of all signing, generating a document fingerprint value. It then uploads the PDF document and its fingerprint value to the electronic medical record archiving system and writes a complete operation log containing the document fingerprint value, signature traceability records, and business node identifiers to the audit log. Document archiving is the final step in the clinical blood use management process, ensuring long-term data preservation and effective traceability through a secure and reliable archiving mechanism. The archiving process first performs a hash digest calculation on the complete PDF document, using cryptographically secure hash algorithms such as SHA-256 to generate a fixed-length document fingerprint value. The hash calculation formula is: ; in, For document fingerprint value, A complete binary data stream for a PDF document.

[0017] Document fingerprints serve as unique identifiers for document integrity, effectively verifying whether documents have been tampered with. The system appends the fingerprint value to the extended attributes of the PDF document, creating a self-verifying archive file. Simultaneously, the archive file and related index information are uploaded to the electronic medical record archiving system. The index information includes key retrieval fields such as the patient's unique identifier, blood transfusion event number, and document type code, facilitating later queries and retrieval. After upload, the system receives an archiving confirmation identifier from the archiving system, serving as proof of successful archiving. Simultaneously, a complete operation chain record is written to the system audit log, including the document fingerprint value, all signature traceability records, and business node identifiers, constructing a complete operation audit chain. This meets the requirements of medical regulations for data integrity and traceability, providing reliable technical support for subsequent auditing and quality control.

[0018] The modules are connected via wired and / or wireless means to enable data transmission between them.

[0019] In this embodiment of the invention, calculating the absolute coordinate range and signature capacity constraints of each signature region in the generated PDF document based on the signature anchor identifier includes: The relative positioning parameters of each signature anchor identifier in the document template are parsed. These parameters include the page number of the anchor, the horizontal offset ratio of the anchor relative to the top left corner of the page, and the vertical offset ratio. Signature area positioning is the fundamental step for accurately placing the signature; the precise location of the signature is determined by parsing the relative parameters in the template. The parsing process uses an XML parser to extract the positional information from the signature anchor identifiers. Each anchor contains three key positioning parameters: page number (an integer value indicating which page the anchor is located on), horizontal offset ratio (a floating-point value, ranging from 0 to 1, representing the relative distance of the anchor from the left edge of the page), and vertical offset ratio (a floating-point value, ranging from 0 to 1, representing the relative distance of the anchor from the top edge of the page). This relative positioning method ensures the consistency of the signature position across different page sizes, enhancing the template's versatility and adaptability. Anchor identifiers typically use a structured naming convention, such as the format "SIG_ROLE_PAGE_ID," where ROLE represents the signature role (e.g., DOCTOR, NURSE), PAGE represents the page number, and ID represents the sequence number within the same page, facilitating rapid system identification and processing.

[0020] Based on the actual page size and horizontal and vertical offset ratios of the PDF document, the relative positioning parameters are converted into absolute pixel coordinates to determine the top-left corner positioning point of each signature area. Converting relative coordinates to absolute coordinates is a crucial step in adapting to the actual document; it involves calculating and converting abstract proportional values ​​into specific pixel positions. The conversion process first obtains the actual pixel dimensions of each page of the PDF document, including the width (…). ) and height ( Then, the absolute coordinates are calculated using a proportional method. The conversion formula is: ; ; in, and The absolute pixel coordinates of the top-left corner of the signature area. and For the page's pixel width and height, and These represent the horizontal and vertical offset ratios, respectively.

[0021] The calculations use floating-point precision, and the final result is usually rounded to an integer pixel value to ensure accurate positioning at different resolutions. The top-left corner of the signature area serves as the reference point for subsequent calculations, determining the exact position of the signature area in the document and serving as the starting point for drawing the signature area.

[0022] Based on the aspect ratio constraint parameters of the signature frame carried in the signature anchor point identifier, the absolute coordinate range of each signature area is calculated by expanding downwards and to the right from the upper left corner positioning point. Determining the signature area size is a crucial step to meet different signature requirements; the signature space is reasonably defined through preset aspect ratio constraint parameters. The determination process first extracts the aspect ratio constraint parameters from the anchor point identifier (…). The width and height ratio represents the ideal width-to-height ratio of the signature area; then, based on the document type and role requirements, the standard width of the signature area is determined; finally, the corresponding height is calculated based on the width and aspect ratio to obtain the complete area range. This is represented as: ; ; in, The default standard width (usually 150-300 pixels). The aspect ratio constraint parameter (usually 2-3).

[0023] The absolute coordinate range of the signature area is determined by four values: the top-left X-coordinate, the top-left Y-coordinate, the bottom-right X-coordinate (equal to the top-left X-coordinate plus width), and the bottom-right Y-coordinate (equal to the top-left Y-coordinate plus height). These four coordinate values ​​completely define the position and size of the signature area, providing precise spatial constraints for the subsequent placement of the signature image.

[0024] Based on the area of ​​the absolute coordinate range and the output resolution of the PDF document, the maximum pixel width and maximum pixel height within the signature size constraint are calculated. The signature size constraint is a crucial parameter for ensuring signature clarity, and its calculation determines the ideal size range for the signature image. The calculation process first calculates the actual area (number of pixels) of the signature region based on the absolute coordinate range; then, considering the output resolution of the PDF document, the optimal signature image size is determined; finally, the maximum pixel width and height are derived as upper limits for signature image scaling. The calculation formula is: ; ; in, and The coordinates of the top left corner and The coordinates of the bottom right corner This is the resolution factor (usually 1-1.5). and These are the maximum pixel width and height, respectively.

[0025] Maximum pixel width and height control the rendering precision of the signature image, ensuring that the signature is neither too large and blurry, nor too small and difficult to recognize. These size constraints, together with the original size of the actual signature image, determine the scaling ratio of the final signature, guaranteeing the best display effect of the signature in the document.

[0026] In this embodiment of the invention, the role type tag and authorized signature range identifier of the operator are extracted by comparing the identity credential data with the department personnel permission mapping table, including: The process begins by extracting a unique identifier for each operator from the identity credential data. This identifier is then used to retrieve a matching personnel record from the departmental personnel access control table. Identity credential parsing is the first step in access control verification, confirming the operator's identity by extracting the identifier. Different extraction methods are used depending on the credential type: smart card credentials obtain the electronic serial number stored in the card through a card reader; biometric credentials generate a unique identifier using a feature matching algorithm; and employee ID password credentials directly use the employee ID as the identifier. The extracted unique identifier is then processed using a secure hash to ensure secure transmission and storage. The departmental personnel access control table is stored in a protected database using an efficient index structure, supporting fast and accurate queries. The retrieval process uses parameterized queries to prevent injection attacks, precisely matching personnel records using the unique identifier. If no match is found, the verification process is immediately terminated, and an abnormal access log is recorded. Personnel records contain complete identity information and access control configurations, forming the data foundation for subsequent access control decisions.

[0027] The system retrieves the role type tags of operators from personnel records. These tags include tags for blood dispensing personnel, blood collection nurses, and checking physicians. Role type acquisition is a crucial step in determining the scope of operational permissions, achieving separation of responsibilities and access control through role division. The acquisition process directly reads the role field from the matched personnel records. Each operator may be associated with one or more role type tags. The "blood dispensing personnel" tag represents blood bank staff responsible for dispensing and registering blood products; the "blood collection nurse" tag represents clinical nurses responsible for receiving blood products and performing transfusions; and the "checking physician" tag represents clinical physicians responsible for blood use review and issuing transfusion orders. Role type tags typically employ a hierarchical tree structure, supporting fine-grained permission inheritance and extension. For example, a senior nurse can inherit all the permissions of a regular nurse and possess additional special operational permissions. The system supports dynamic role allocation, allowing administrators to adjust role configurations in real time based on personnel changes, ensuring that permission allocation aligns with actual responsibilities.

[0028] The authorized signature scope identifier is retrieved based on the role type tag. This identifier indicates the set of signature anchor identifiers that the role is allowed to sign. Determining the authorized scope is a core step in refined access control, preventing unauthorized signing by clearly defining the operational boundaries of each role. The process begins by obtaining the role's basic authorization template, containing all signature anchors that the role can operate in standard procedures. Then, adjustments are made based on the operator's specific authorization level, potentially expanding or restricting some signature permissions. This ultimately forms the specific authorized signature scope for that operator. The authorized signature scope identifiers are stored as a set, with each element corresponding to a single, signable signature anchor identifier, such as "SIG_NURSE_1_1" representing the first nurse's signature area on the first page. Different roles have clearly defined boundaries for their authorized scopes: blood dispensing personnel can only sign on blood dispensing documents; blood collection nurses can sign on blood collection slips and transfusion records; and checking physicians can sign on medical orders and verification records. This role-based authorization mechanism ensures clear responsibilities and standardized procedures in clinical blood use, improving transfusion safety.

[0029] The system performs an inclusion check between the signature anchor identifier corresponding to the currently activated signature area and the set of signature anchor identifiers in the authorized signature range identifier. If the current signature anchor identifier belongs to the set, the system determines that the operator has the necessary business signing permissions. Permission matching is the final step in authorization verification, determining whether the current operation is permitted through precise comparison. The process first identifies the anchor identifier of the activated signature area; then checks whether the identifier is included in the operator's authorized signature range; finally, it determines the permissions based on the inclusion relationship. The inclusion check uses an efficient set operation algorithm, supporting fast lookup and comparison. If the current signature anchor identifier belongs to the authorized range, the system determines that the operator has the corresponding business signing permissions and allows the signing process to continue; if not, it is determined to be an unauthorized operation, the signing process is immediately interrupted, an unauthorized attempt log is recorded, and an insufficient permission prompt is displayed. For special circumstances, such as emergency blood use, the system supports a temporary authorization mechanism. After obtaining approval from a senior-authorized personnel, the authorization range can be temporarily expanded to ensure that business is not hindered in special circumstances, while recording the complete authorization chain to ensure traceability and auditability of the operation.

[0030] In this embodiment of the invention, the touch trajectory coordinate sequence is divided into several stroke segments according to the time interval between adjacent sampling points, including: Calculate the time interval between each pair of adjacent sampling points in the touch trajectory coordinate sequence. Time interval calculation is a fundamental step in detecting stroke continuity, identifying natural interruptions in the writing process by analyzing time series features. The calculation process traverses the complete touch trajectory coordinate sequence, performing time difference analysis on each pair of adjacent sampling points. Let the sampling point sequence be { }, where each point Includes coordinate values and timestamp The time interval between adjacent points The calculation is as follows: ; The calculations employ millisecond-level precision to ensure the capture of minute time variations. The system filters out outliers, such as non-physical time jumps caused by equipment malfunctions (e.g., negative or excessively large values), ensuring data validity. Time interval sequence { This reflects the dynamic changes in writing speed and is a key data source for analyzing the continuity of handwriting, providing a time dimension basis for subsequent stroke segmentation.

[0031] Each time interval value is compared one by one with a preset stroke break time threshold. If a time interval value exceeds the stroke break time threshold, a stroke segmentation marker is inserted between adjacent sampling points. Stroke break detection is a key step in recognizing natural writing structures, distinguishing between continuous writing and stroke interruptions through time threshold judgment. The detection process traverses the time interval sequence, comparing each interval value with a preset break time threshold (typically 300-500 milliseconds). A simple threshold judgment model is used for the comparison: ; in, Indicates whether or not at the point and Insert separator markers between them. This is the preset threshold for the time when strokes break off.

[0032] When an interval value exceeds a threshold, the system inserts a stroke segmentation marker at the corresponding position. This marker is typically represented by a special data structure containing a segmentation position index and segmentation confidence level. Inserting the segmentation marker does not alter the original sampled data; it only adds additional structural information to maintain data integrity. The system also considers multiple consecutive interval values ​​close to the threshold, using the cumulative effect to determine whether they represent a genuine stroke interruption. This avoids misjudgments caused by minor hand pauses, improving the accuracy and naturalness of the segmentation.

[0033] Based on the positions of the stroke segmentation markers, the touch trajectory coordinate sequence is divided into several continuous subsequences, each of which constitutes a stroke segment. Stroke sequence segmentation is a crucial step in constructing the signature structure model, transforming continuous trajectories into meaningful writing units through segmentation markers. The segmentation process first locates the position indices of all segmentation markers, forming an index sequence { },in The total number of segmentation markers; then, based on these indices, the original touch trajectory coordinate sequence is divided into... a continuous subsequence: { }, { }, ..., { Each subsequence contains the complete process from the beginning to the end of a stroke, forming a natural stroke segment. The segmentation follows a non-destructive principle, keeping the original data unchanged and establishing the stroke structure only through index relationships, facilitating subsequent processing and recovery. The system performs anomaly checks on the segmentation results, removing invalid segments that are too short (fewer than 3 sampling points) and merging related segments that are too close (time intervals close to a threshold), ensuring that the segmentation results conform to natural writing habits and accurately reflect the structural characteristics of the signature.

[0034] The system labels the sampling points in each stroke segment with the starting and ending points. The starting point is the first sampling point of each stroke segment, and the ending point is the last sampling point. Endpoint labeling is a necessary preparation for analyzing handwriting features, allowing for a deeper understanding of the signature writing process by identifying key points. The labeling process performs start and end point identification for each stroke segment: the first sampling point of the segment is labeled as the starting point, recording the precise location and time of the start of writing; the last sampling point of the segment is labeled as the ending point, recording the precise location and time of the end of writing. The starting point typically represents a phase of rapid pressure increase, while the ending point represents a phase of gradual pressure decrease. The system performs special processing on these key points to extract richer feature parameters, such as the starting angle, ending speed, and pressure change rate, forming a dynamic handwriting feature set. These features are of great value for understanding the personal style of a signature and verifying its authenticity. In addition, the system also analyzes the connection patterns between adjacent strokes, such as skip connections and smooth transitions, further enriching the description of the signature structure. Complete endpoint annotations provide a structured analytical basis for subsequent integrity assessments, supporting more accurate signature quality evaluations.

[0035] In this embodiment of the invention, the handwriting integrity score is calculated based on the number of effective sampling points and the pressure value distribution characteristics of the stroke fragment, including: The number of sampling points in each stroke segment whose pressure values ​​exceed a preset minimum effective pressure threshold is counted as the number of effective sampling points for each segment. Counting effective sampling points is a fundamental step in evaluating signature quality, using pressure thresholds to filter and identify valid writing areas. The statistical process first sets a minimum effective pressure threshold (typically 10-15% of the device's maximum pressure value). This threshold distinguishes between conscious writing pressure and unintentional light touches or hovering. Then, it iterates through all sampling points in each stroke segment, comparing the pressure value of each point with the threshold. Finally, the number of sampling points whose pressure values ​​exceed the threshold is counted as the number of effective sampling points for that segment. The statistical method uses cumulative counting, and for edge cases of pressure value fluctuations, a sliding window is used for smoothing to avoid misjudgments caused by single-point fluctuations. The number of effective sampling points directly reflects the substantial content of the signature, serving as a basic metric for evaluating signature integrity and providing the data basis for subsequent calculations of effective point coverage.

[0036] The effective point coverage rate is obtained by calculating the ratio of the sum of the effective sampling points of all stroke segments to the total number of sampling points. Calculating the effective point coverage rate is a crucial step in evaluating the overall quality of the signature, quantifying the proportion of valid content through ratio analysis. The calculation process first calculates the sum of the effective sampling points of all stroke segments, and simultaneously calculates the total number of sampling points in the original touch trajectory coordinate sequence; then, the ratio of the two is calculated to obtain the effective point coverage rate. The coverage rate calculation formula is: ; in, The effective point coverage rate has a value range of [0,1]. For the first The number of valid sampling points for each stroke segment This represents the total number of sampling points for this segment. This represents the total number of stroke segments.

[0037] High coverage indicates that most of the handwriting in the signature is supported by sufficient pressure and is clear and complete; low coverage indicates that there are many light touches or hovering areas in the signature, which may be a sign of incompleteness or hesitation. As a major component of handwriting completeness scoring, coverage directly affects the determination of signature validity.

[0038] The standard deviation of the pressure value sequence within each stroke segment is calculated. Based on this standard deviation, the stability of writing pressure is determined, generating a pressure stability score. Pressure stability analysis is a deeper step in assessing signature quality, quantifying the smoothness and confidence of the writing through statistical characteristics. The analysis process first calculates the standard deviation of the pressure value sequence within each stroke segment to quantify the degree of pressure fluctuation; then, the ratio of the standard deviation to the average pressure is used as a relative fluctuation index to eliminate the influence of differences in pressure baselines among individuals; finally, through nonlinear mapping, the relative fluctuation index is converted into a more easily understood pressure stability score. The formula for calculating the stability score is: ; in, This represents the pressure stability score, with a value ranging from [0,1]. For the first The standard deviation of pressure values ​​within a stroke segment This represents the average pressure value within that segment. This represents the total number of stroke segments.

[0039] The exponential transformation makes the stability score inversely proportional to the relative volatility index; the lower the volatility, the higher the stability. High stability indicates a smooth and confident signing process, while low stability may reflect hesitation or tension, affecting the reliability and consistency of the signature. The stability score, as an important supplement to the handwriting integrity score, provides another dimension for quality assessment.

[0040] The handwriting integrity score is obtained by weighted summation of the effective point coverage rate and pressure stability score. Feature fusion is the final step in generating the comprehensive score, integrating quality indicators from different dimensions through reasonable weight allocation. The fusion process first determines the weight coefficient of each indicator, reflecting its importance in the overall score; then, a weighted summation is performed to obtain the final handwriting integrity score. The weighted summation formula is as described above: ; in, Rate the completeness of the handwriting. For effective point coverage, The pressure stability score, This is the weighting coefficient (usually set to 0.6-0.7).

[0041] The weighting coefficients are set based on empirical data and user feedback optimization, typically favoring coverage metrics as they more directly reflect the completeness of the signature. The final handwriting integrity score is a normalized [0,1] value, with values ​​closer to 1 indicating higher signature quality. This score is compared with a preset signature validity threshold to determine whether to accept the current signature or request a re-signing, serving as a crucial mechanism for ensuring the quality and legal validity of electronic signatures.

[0042] In this embodiment of the invention, the signature image is scaled proportionally and its coordinates are shifted according to the absolute coordinate range and the signature size constraint before being written into the corresponding signature area of ​​the PDF document, including: The original pixel width and height of the signature image are obtained, and the width scaling ratio and height scaling ratio are calculated against the maximum pixel width and maximum pixel height in the signature size constraint. Signature size analysis is the first step in image adaptation, determining the necessary transformation parameters by comparing the original size with the target size. The analysis process first obtains the original size of the vectorized rendered signature image, including the pixel width. and pixel height Then obtain the previously calculated signature-containing size constraints, including the maximum pixel width. and maximum pixel height Finally, calculate the scaling ratio in both directions. The scaling ratio calculation formula is: ; ; in, This is the width scaling ratio. This is the height scaling ratio.

[0043] The scaling ratio intuitively reflects the size relationship between the original image and the target area; a ratio greater than 1 indicates that the image needs to be enlarged, while a ratio less than 1 indicates that the image needs to be reduced. The system checks for extreme cases, such as when the original size is zero or too small, and performs special processing to ensure the calculation results are valid. The calculation of the scaling ratio provides the basic parameters for subsequent proportional scaling and is a crucial step in correctly adapting the signature image to the signature area.

[0044] The smaller of the width scaling ratio and the height scaling ratio is used as the proportional scaling factor to scale the signature image, generating a suitable signature image. Proportional scaling is a crucial step in preserving the original form of the signature, avoiding image distortion through a single scaling factor. The process first compares the width and height scaling ratios, selecting the smaller value as the final proportional scaling factor to ensure the signature does not exceed the capacity constraints in either direction. Then, a high-quality image scaling algorithm, such as bicubic interpolation, is used to scale the original signature image as a whole, maintaining its original form and proportions. Finally, a suitable signature image that meets the size requirements is generated. The scaling factor selection follows the principle of "stricter constraints in the direction," ensuring the signature perfectly fits the target area and avoiding overflow in any direction. For extremely small scaling factors (e.g., less than 0.1), the system will issue a warning and indicate that it may affect signature clarity, suggesting the user re-sign a signature of a more suitable size. The generated suitable signature image retains all the details and features of the original signature, only adjusting the overall size, laying the foundation for subsequent precise positioning.

[0045] Based on the absolute coordinate range of the signature area and the size of the adapted signature image, the horizontal and vertical centering offsets are calculated. Centering calculation is a crucial step in achieving aesthetically pleasing signature placement; the offsets ensure the signature is visually centered within the area. The calculation process first obtains the absolute coordinate range of the signature area, including the coordinates of the top-left corner (…). ) and the coordinates of the lower right corner ( Then calculate the coordinates of the center point of the region; simultaneously obtain the actual size of the adapted signature image, including the scaled width. and height Finally, calculate the center offset in the horizontal and vertical directions. The formula for calculating the offset is: ; ; in, This is the horizontal center offset. This is the vertical center offset.

[0046] Offset ensures the signature image is centered relative to the signature area, enhancing visual appeal and professionalism. In special cases, such as when the signature area is too small or irregularly shaped, the system adjusts the centering strategy to ensure that key parts of the signature (such as the surname) are displayed first. Centering considers both user visual experience and signature validity, providing a precise positional reference for the final signature presentation.

[0047] A separate signature image layer is created within the PDF document. The adapted signature image is positioned using horizontal and vertical center offsets and then written into the layer. Layer writing is the final step in integrating the signature into the document, ensuring a clear separation between the signature and the document content through a separate layer structure. The writing process first creates a dedicated signature image layer within the PDF document, positioned above the content layer to ensure the signature is visible and not obscured by other elements. Then, based on the calculated horizontal and vertical center offsets, the precise placement of the signature image is determined. Finally, the adapted signature image is written into the layer, completing the visual presentation of the signature. The layer uses the standard PDF transparency overlay mode to ensure a clear distinction between the signature and the underlying content. The system creates a unique, independent layer for each signature, facilitating later management and verification. After writing is complete, the system performs an image quality check to verify the clarity and integrity of the signature, ensuring the final presentation meets expectations. This layer structure design not only improves document readability but also provides technical support for subsequent electronic signature verification, enhancing the document's legal validity and reliability.

[0048] In this embodiment of the invention, detecting whether each signature area has been associated with a valid signature traceability record, and determining the signing completion status based on the detection result, includes: Extract all written signature traceability records from the metadata area of ​​the PDF document and establish a mapping index between signature anchor identifiers and signature traceability records. Signature record extraction is a fundamental step in integrity verification, obtaining detailed information about completed signatures through metadata parsing. The extraction process first accesses the XMP metadata area of ​​the PDF document, which stores the document's extended attribute information in XML format; then it parses the signature traceability record section, where each record contains key information such as the operator's employee number, signature timestamp, device identifier, and handwriting integrity score; finally, it establishes a mapping index between signature anchor identifiers and signature traceability records for quick querying and matching. Parsing uses either a DOM or SAX parser, selecting the optimal method based on document size and complexity. The mapping index is typically implemented using a hash table, with the signature anchor identifier as the key and the corresponding signature traceability record as the value, supporting fast queries with O(1) complexity. This mapping index provides efficient data structure support for subsequent signature status checks and is the basis for determining the completion status of document signing.

[0049] The system iterates through all signature anchor identifiers defined in the document template, searching the mapping index one by one to check for the existence of a corresponding signature traceability record. Signature status checking is the core step in determining signature integrity, comprehensively comparing and confirming the completion status of all necessary signatures. The checking process first extracts all predefined signature anchor identifiers from the document template, constructing a complete list of signature requirements. Then, it iterates through this list, querying the previously established mapping index for each anchor identifier to check for the existence of a corresponding signature traceability record. Simultaneously, it verifies whether the handwriting integrity score in the found traceability record meets the validity threshold, ensuring that the signature not only exists but is also of acceptable quality. The system records the checking results for each anchor, including detailed information such as whether a corresponding record was found and whether the handwriting score meets the standard, providing a complete basis for the final status determination. The checking process supports parallel processing, significantly improving efficiency for large documents, and employs an exception handling mechanism to ensure that metadata corruption or formatting errors do not lead to checking failures.

[0050] If all signature anchor identifiers have corresponding signature traceability records and the handwriting integrity score in each record is not lower than the signature validity threshold, the signing completion status is determined to be "all signed." Completion status determination is a key decision point in document circulation, determining the current processing stage of the document through comprehensive analysis. The determination process is based on the aforementioned inspection results, comprehensively evaluating the document's signature integrity. When two conditions are met: all necessary signature anchors are associated with valid signature traceability records, and the handwriting integrity score of all signatures reaches or exceeds the preset validity threshold (usually 0.75-0.85), the system determines the document signing status to be "all signed." This status indicates that the document has met all signing requirements and can proceed to the next stage of archiving. The system will immediately trigger the archiving process after the determination, transferring the fully signed document to the electronic medical record archiving system, while simultaneously updating the business node status and marking the current blood use process stage as completed. Accurate determination of the completion status ensures the standardized execution and timely progress of the clinical blood use process, and is a key link in paperless management.

[0051] If any signature anchor identifier is not associated with a signature traceability record, the signing completion status is determined to be "pending signing," and the unassociated signature anchor identifier and its corresponding role type tag are encapsulated into a pending signing reminder notification. Incomplete processing is a mechanism to ensure process continuity, promoting the timely completion of incomplete signatures through reminders. The process first determines the signing status as "pending signing," indicating that the document has not yet met all signing requirements; then, it collects all anchor identifiers not associated with signature traceability records and parses the corresponding role type tags based on the identifiers to clarify the scope of responsibility; finally, it generates a structured pending signing reminder notification. The reminder notification uses a standard format, including key information such as document identifier, description of the unsigned area, required role type, and expected completion time, and is sent to relevant personnel through various methods such as system messages, emails, or mobile push notifications. The system supports a reminder escalation mechanism, automatically escalating the reminder frequency and scope for pending documents that have not been processed within the time limit, ensuring that important documents are not forgotten or delayed. This mechanism significantly improves the execution efficiency and integrity of the clinical blood use process, reduces process interruptions caused by signature omissions, and provides important protection for clinical blood use safety.

[0052] In this embodiment of the invention, performing hash digest calculation on the PDF document to generate a document fingerprint value, and uploading the PDF document and the document fingerprint value to the electronic medical record archiving system includes: The entire binary data stream of a PDF document is read, and a digest operation is performed on the binary data stream using a preset hash algorithm to generate a fixed-length document fingerprint. Fingerprint generation is a crucial step in ensuring document integrity, creating a unique identifier for the document through cryptographic methods. The generation process first reads the entire PDF document in binary mode to obtain the raw data stream without any transformation; then, a highly secure cryptographic hash algorithm, such as SHA-256 or SHA-3, is selected to perform a one-way hash operation on the entire data stream; finally, a fixed-length hash value is generated as the document's fingerprint. The choice of hash algorithm considers a balance between security, performance, and compatibility, ensuring resistance to collision attacks while efficiently processing large documents. The document fingerprint value is typically represented as a 64-character hexadecimal string, possessing extremely high uniqueness; even minor changes to the document content will result in significantly different fingerprint values. This characteristic makes fingerprint values ​​a reliable technical means of verifying document integrity and authenticity, providing important support for the legal validity of electronic medical records.

[0053] By attaching document fingerprint values ​​to the extended attribute fields of PDF documents, a self-verifying archive is created. Fingerprint embedding is a crucial step in achieving document self-verification, enabling documents to carry their own proof of integrity through metadata extension. The embedding process first creates a standardized fingerprint attribute structure, including information such as the fingerprint value, generation time, and hash algorithm used. This structure is then written into the extended attribute fields of the PDF document in XML format, becoming part of the document's metadata. The final result is a self-verifying archive containing the original content and proof of integrity. Fingerprint attributes use standard namespaces and architectures to ensure compatibility with different systems. The embedded fingerprint value can be viewed through the attribute panel of a standard PDF viewer, facilitating verification by administrators and auditors. This self-verification mechanism allows for future verification of document integrity even without support from the original system, extending the validity and credibility of electronic documents and providing a technological foundation for long-term archiving and legal evidence preservation.

[0054] Through a data interface with the electronic medical record (EMR) archiving system, self-verifying archived files and archiving index information containing patient unique identifiers, blood transfusion event numbers, and document type codes are uploaded synchronously. Archive upload is a crucial step for long-term preservation, securely transmitting documents to the archiving system via a standard interface. The upload process first prepares a complete upload data package, including the self-verifying archived file and structured archiving index information; then, an encrypted connection is established with the EMR archiving system through a pre-configured secure data interface, such as HTTPS, SFTP, or a dedicated API; finally, a synchronous upload operation is performed to ensure complete data package transmission and correct reception. The archiving index information is key metadata for retrieval and management, containing core fields such as patient unique identifiers (e.g., medical record number), blood transfusion event numbers (identifying specific blood transfusion procedures), and document type codes (distinguishing different document types). The upload process employs a transaction processing mechanism to ensure atomic upload of documents and indexes, avoiding data inconsistencies. The system supports breakpoint resume and upload confirmation, effectively handling network fluctuations and service interruptions, ensuring the reliability and integrity of data transmission, and providing technical assurance for the long-term preservation of electronic medical records.

[0055] The system receives an archiving confirmation identifier from the electronic medical record (EMR) archiving system and associates this identifier with the complete operation log. Archiving confirmation is the final step in closed-loop management, verifying successful archiving completion through a confirmation mechanism. The confirmation process first waits for the EMR archiving system to process the uploaded data packet. After receiving, verifying, and storing the data, the archiving system returns a unique archiving confirmation identifier. Then, the validity of the confirmation identifier is verified to ensure the archiving operation has been correctly executed and recorded. Finally, this confirmation identifier is associated with the operation record in the audit log, completing the archiving loop. The archiving confirmation identifier typically includes a timestamp, serial number, and digital signature, ensuring uniqueness and tamper-proofing. The confirmation process supports a timeout retry mechanism. For cases where confirmation is not returned in a timely manner, the system periodically checks the archiving status to ensure the operation is not lost or suspended. The complete record of archiving confirmation provides crucial evidence for subsequent auditing and traceability, proving that the document has been correctly archived and is acceptable for long-term preservation, meeting the stringent requirements of medical regulations for the integrity and traceability of electronic medical records. This is a crucial link in medical quality management and legal risk prevention.

[0056] In this embodiment of the invention, a complete operation chain record containing document fingerprint values, signature tracing records, and business node identifiers is written into the audit log, including: Based on the chronological order of the signature timestamps in each signature traceability record, all signature traceability records are organized into an ordered signature event chain. Event chain construction is a fundamental step in audit record organization, ensuring the integrity and continuity of the operational chain through chronological arrangement. The construction process first collects all signature traceability records in the document. Each record contains key information such as the operator's employee number, signature timestamp, device identifier, and handwriting integrity score. Then, it sorts the signature timestamps chronologically, constructing a complete event sequence from earliest to latest. This ultimately forms an ordered signature event chain, reflecting the complete timeline of the document signing process. A stable sorting algorithm is used to ensure that events with similar times maintain their original order. For timestamp anomalies, the system performs a rationality check, marking possible clock deviations or synchronization issues to ensure the accuracy of the event chain. The ordered signature event chain visually displays the entire signing activity from document creation to completion, providing a clear timeframe for auditing and traceability, and is an important tool for understanding the execution of business processes.

[0057] At the beginning of an ordered signature event chain, a business node identifier and a document generation timestamp are appended; at the end, a document fingerprint value and an archiving completion timestamp are appended, forming a complete operation chain record. Chain completion is a crucial step in building a comprehensive audit record, capturing the entire lifecycle of the business process through expansion at both ends. The completion process first adds a business node identifier (such as "blood application," "blood verification," etc.) and a precise document generation timestamp at the start of the event chain, marking the beginning of the process; then, a document fingerprint value and an archiving completion timestamp are added at the end of the event chain, marking the end of the process; ultimately forming a complete operation chain record covering creation to archiving. The business node identifier reflects the specific steps and functions of the document in the clinical blood use process; the document generation timestamp records the precise time point when the process started; the document fingerprint value provides cryptographic proof of content integrity; and the archiving timestamp confirms the time point when the process ended. These elements together constitute a complete chain of evidence for process execution, not only recording "what was done," but also clarifying "when it was done" and "whether it was done correctly," providing a comprehensive factual basis for subsequent auditing and evaluation.

[0058] A hash operation is performed on the entire complete operation link record to generate a link integrity check code, which is then appended to the end of the complete operation link record. Integrity protection is a crucial step in preventing record tampering, ensuring the authenticity of audit data through cryptographic methods. The protection process first serializes the complete operation link record into a standard format data stream to ensure structural consistency; then, a secure hash algorithm is selected to perform a hash operation on the entire data stream, generating a fixed-length check code; finally, this check code is appended to the end of the record, forming a self-verifying complete record. The check code generation uses the same hash algorithm as the document fingerprint, typically SHA-256, ensuring security and consistency. The integrity check code is highly sensitive; any minor change in the record will cause a significant change in the check code, thus being detected. The system periodically verifies the check codes of stored audit records to ensure that the records have not been tampered with, maintaining the credibility and legal validity of audit data, and providing reliable technical support for medical quality management and risk control.

[0059] The complete operation link record with attached link integrity check code is stored in the audit log in an append-only manner, and the audit log is configured to an append-only, non-modifiable storage mode. Secure storage is the fundamental guarantee of the audit system, and the immutability of the log is ensured through special storage strategies. The storage process adopts an append-only mode, where new records can only be added to the end of the log, and modification or deletion of existing records is prohibited, ensuring the integrity and continuity of the audit trail. Audit logs typically use dedicated log storage systems, such as WORM (Write-Once, Read-Many) storage devices or blockchain technology, to ensure data immutability at the hardware or architectural level. The system also implements strict access control and permission management; only authorized auditors can query the logs, and all query operations are themselves recorded, forming a meta-audit trail. Log data is backed up regularly and distributed for storage to prevent data loss due to single points of failure. This secure storage mechanism ensures the long-term availability and legal acceptability of the audit logs, meets the compliance requirements and risk management needs of medical institutions, and is an important security foundation for the paperless management of the entire clinical blood use process.

[0060] To further illustrate the practicality and effectiveness of the present invention, its application will be described in detail below in conjunction with actual clinical blood use scenarios.

[0061] For example, during a complex heart surgery, if blood loss exceeds expectations, an additional request for blood products may be needed. In the traditional procedure, the operating room nurse would have to leave the operating area to fill out a paper request form, which would then be manually passed to the blood bank – a time-consuming process that disrupts surgical coordination.

[0062] After applying the method of this invention, medical staff in the operating room can directly submit electronic blood requisition requests through the operating room workstation. The surgeon completes the electronic signature using a smart handwriting tablet, and the system immediately verifies the doctor's identity and surgical authority. The electronic request form is transmitted to the blood bank workstation in real time, shortening information transmission time. After confirming the blood preparation status, blood bank technicians confirm the issuance of blood products through electronic signature on the blood dispensing terminal.

[0063] When receiving blood, the circulating nurse verifies identity and confirms receipt of the blood through fingerprint recognition and electronic signature. Upon returning to the operating room, both the circulating nurse and the scrub nurse sign the electronic verification form, and the system automatically records the verification time and personnel information. After the transfusion is completed, the anesthesiologist provides final confirmation and signature on the transfusion record, completing the closed-loop electronic record of the entire temporary blood transfusion.

[0064] In this scenario, the method of this invention not only reduces the number of times nurses leave the operating room and improves operating room efficiency, but also ensures the safety and standardization of emergency blood transfusions through strict electronic authentication and automated process control. Electronic documents generated throughout the process are automatically archived into the patient's electronic medical record system for easy postoperative review and quality control analysis.

[0065] The foregoing described the paperless management system for the entire clinical blood use process based on a smart handwriting tablet in the embodiments of this application. The following describes the paperless management method for the entire clinical blood use process based on a smart handwriting tablet in the embodiments of this application. Please refer to [link to relevant documentation]. Figure 2 One embodiment of the paperless management method for the entire clinical blood use process based on a smart handwriting tablet in this application includes: The system obtains structured form data of the current business node from the blood transfusion management system, parses the preset signature anchor point identifier in the document template, and calculates the absolute coordinate range and signature capacity size constraint of each signature area in the generated PDF document based on the signature anchor point identifier. When the signature area is activated, the operator's identity credential data is collected. The identity credential data is compared with the department personnel permission mapping table to extract the operator's role type label and authorized signature range identifier, and to determine whether the current operator has the business signing permission for the corresponding signature area. After the business signing permission verification is passed, the smart handwriting tablet is started, and the touch trajectory coordinate sequence and pressure value sequence are collected at a preset sampling frequency. The touch trajectory coordinate sequence is divided into several stroke segments according to the time interval between adjacent sampling points. The handwriting integrity score is calculated based on the number of effective sampling points and pressure value distribution characteristics of the stroke fragment. The handwriting integrity score is compared with the signature validity threshold. If it is lower than the threshold, a re-signing instruction is sent. If it reaches the threshold, the stroke fragment is vectorized and rendered to generate a signature image. After performing proportional scaling and coordinate offset transformation on the signature image according to the absolute coordinate range and signature capacity size constraint, it is written into the corresponding signature area of ​​the PDF document, and a signature traceability record containing the operator's employee number, signature timestamp, terminal device identifier and handwriting integrity score is embedded in the metadata area of ​​the PDF document. After the signature traceability record is written, the signature areas corresponding to all signature anchor identifiers in the PDF document are traversed to check whether each signature area has been associated with a valid signature traceability record. Based on the detection result, the signing completion status is determined and an archiving operation or a pending signature reminder notification is triggered. Upon completion of all signing, a hash digest calculation is performed on the PDF document to generate a document fingerprint value. The PDF document and the document fingerprint value are then uploaded to the electronic medical record archiving system. A complete operation chain record containing the document fingerprint value, traceability records of each signature, and business node identifiers is written into the audit log.

[0066] This invention achieves paperless management of the entire clinical blood use process through intelligent handwriting tablet technology, identity and access verification, handwriting integrity assessment, secure archiving, and auditing. This fully electronic approach not only improves the efficiency of clinical blood use but also enhances transfusion safety and traceability through rigorous verification mechanisms and a complete data chain.

[0067] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

[0068] It should be noted that all formulas in this manual are calculated by removing dimensions and taking their numerical values. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters and thresholds in the formulas are set by those skilled in the art according to the actual situation.

[0069] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

Claims

1. A paperless management method for the entire clinical blood use process based on a smart handwriting tablet, characterized in that, include: The system obtains structured form data of the current business node from the blood transfusion management system, parses the preset signature anchor point identifier in the document template, and calculates the absolute coordinate range and signature capacity size constraint of each signature area in the generated PDF document based on the signature anchor point identifier. When the signature area is activated, the operator's identity credential data is collected. The identity credential data is compared with the department personnel permission mapping table to extract the operator's role type label and authorized signature range identifier, and to determine whether the current operator has the business signing permission for the corresponding signature area. After the business signing permission verification is passed, the smart handwriting tablet is started, and the touch trajectory coordinate sequence and pressure value sequence are collected at a preset sampling frequency. The touch trajectory coordinate sequence is divided into several stroke segments according to the time interval between adjacent sampling points. The handwriting integrity score is calculated based on the number of effective sampling points and pressure value distribution characteristics of the stroke fragment. The handwriting integrity score is compared with the signature validity threshold. If it is lower than the threshold, a re-signing instruction is sent. If it reaches the threshold, the stroke fragment is vectorized and rendered to generate a signature image. After performing proportional scaling and coordinate offset transformation on the signature image according to the absolute coordinate range and signature capacity size constraint, it is written into the corresponding signature area of ​​the PDF document, and a signature traceability record containing the operator's employee number, signature timestamp, terminal device identifier and handwriting integrity score is embedded in the metadata area of ​​the PDF document. After the signature traceability record is written, the signature areas corresponding to all signature anchor identifiers in the PDF document are traversed to check whether each signature area has been associated with a valid signature traceability record. Based on the detection result, the signing completion status is determined and an archiving operation or a pending signature reminder notification is triggered. Upon completion of all signing, a hash digest calculation is performed on the PDF document to generate a document fingerprint value. The PDF document and the document fingerprint value are then uploaded to the electronic medical record archiving system. A complete operation chain record containing the document fingerprint value, traceability records of each signature, and business node identifiers is written into the audit log.

2. The method according to claim 1, characterized in that, The calculation of the absolute coordinate range and signature capacity constraints of each signature region in the generated PDF document based on the signature anchor point identifier includes: The relative positioning parameters of each signature anchor point identifier in the document template are analyzed. The relative positioning parameters include the page number where the anchor point is located, the horizontal offset ratio and the vertical offset ratio of the anchor point relative to the upper left corner of the page. Based on the actual page size of the PDF document and the horizontal and vertical offset ratios, the relative positioning parameters are converted into absolute pixel coordinates to determine the upper left corner positioning point of each signature area. Based on the signature frame aspect ratio constraint parameters carried in the signature anchor point identifier, the absolute coordinate range of each signature area is calculated by expanding to the lower right from the upper left corner positioning point. Based on the area of ​​the absolute coordinate range and the output resolution of the PDF document, calculate the maximum pixel width and maximum pixel height in the signature containment size constraint.

3. The method according to claim 1, characterized in that, The step of comparing the identity credential data with the department personnel permission mapping table to extract the operator's role type tag and authorized signature range identifier includes: Extract the operator's unique identifier from the identity credential data, and retrieve the personnel record that matches the unique identifier from the department personnel permission mapping table; Read the role type tags of the operators from the personnel records. The role type tags include blood dispensing personnel tags, blood collection nurse tags, and checking physician tags. The authorized signature range identifier is queried according to the role type label. The authorized signature range identifier indicates the set of signature anchor identifiers that the role is allowed to sign. The signature anchor identifier corresponding to the currently activated signature area is compared with the set of signature anchor identifiers in the authorized signature range identifier. If the current signature anchor identifier belongs to the set, it is determined that the user has the business signing authority.

4. The method according to claim 1, characterized in that, The step of dividing the touch trajectory coordinate sequence into several stroke segments based on the time interval between adjacent sampling points includes: Calculate the time interval between each pair of adjacent sampling points in the touch trajectory coordinate sequence; Each of the time interval values ​​is compared with a preset stroke break time threshold. If a time interval value exceeds the stroke break time threshold, a stroke segmentation mark is inserted between the adjacent sampling points. Based on the position of the stroke segmentation mark, the touch trajectory coordinate sequence is divided into several continuous subsequences, and each continuous subsequence constitutes a stroke segment; The sampling points in each stroke segment are marked with the starting point and the ending point. The starting point is the first sampling point of each stroke segment, and the ending point is the last sampling point of each stroke segment.

5. The method according to claim 1, characterized in that, The calculation of handwriting integrity score based on the number of effective sampling points and pressure value distribution characteristics of the stroke fragment includes: The number of sampling points in each stroke segment whose pressure value is higher than the preset minimum effective pressure threshold is counted as the number of effective sampling points for each segment. The effective point coverage rate is obtained by calculating the ratio of the sum of the effective sampling points of all stroke segments to the total number of sampling points. Calculate the standard deviation of the pressure value sequence within each stroke segment, determine the stability of writing force based on the standard deviation, and generate a pressure stability score; The handwriting integrity score is obtained by weighted summing of the effective point coverage rate and the pressure stability score.

6. The method according to claim 1, characterized in that, The step of performing proportional scaling and coordinate offset transformation on the signature image according to the absolute coordinate range and signature capacity size constraint, and then writing it into the corresponding signature area of ​​the PDF document, includes: Obtain the original pixel width and original pixel height of the signature image, and calculate the width scaling ratio and height scaling ratio with the maximum pixel width and maximum pixel height in the signature containment size constraint, respectively; The smaller value between the width scaling ratio and the height scaling ratio is taken as the proportional scaling factor, and the signature image is scaled to generate an adapted signature image. Calculate the horizontal centering offset and the vertical centering offset based on the absolute coordinate range of the signature area and the size of the adapted signature image; Create a separate signature image layer in the PDF document, and then write the adapted signature image into the layer after positioning it according to the horizontal and vertical center offsets.

7. The method according to claim 1, characterized in that, The process of detecting whether each signature area is associated with a valid signature traceability record, and determining the signing completion status based on the detection results, includes: Extract all written signature traceability records from the metadata area of ​​the PDF document and establish a mapping index between signature anchor identifiers and signature traceability records; Iterate through all signature anchor identifiers defined in the document template and search the mapping index one by one to see if there is a corresponding signature tracing record. If all signature anchor identifiers have corresponding signature traceability records and the handwriting integrity score in each record is not lower than the signature validity threshold, then the signing completion status is determined to be all signing completed. If any signature anchor identifier is not associated with a signature tracing record, the signing completion status is determined to be pending signing, and the unassociated signature anchor identifier and its corresponding role type tag are encapsulated as a pending signing reminder notification.

8. The method according to claim 1, characterized in that, The step of performing hash digest calculation on the PDF document to generate a document fingerprint value, and uploading the PDF document and the document fingerprint value to the electronic medical record archiving system includes: Read the complete binary data stream of the PDF document, perform a digest operation on the binary data stream using a preset hash algorithm, and generate a fixed-length document fingerprint value; The document fingerprint value is appended to the extended attribute field of the PDF document to form a self-verified archive file; Through the data interface with the electronic medical record archiving system, the self-verified archive file and the archive index information containing the patient's unique identifier, blood use event number and document type code are uploaded synchronously. Receive the archiving confirmation identifier returned by the electronic medical record archiving system, and associate the archiving confirmation identifier with the complete operation link record in the audit log.

9. The method according to claim 1, characterized in that, The process of writing a complete operation chain record, including document fingerprint values, signature tracing records, and business node identifiers, into the audit log includes: Organize all signature traceability records into an ordered chain of signature events according to the chronological order of the signature timestamps in each signature traceability record; At the beginning of the ordered signature event chain, a business node identifier and a document generation timestamp are appended, and at the end, the document fingerprint value and an archiving completion timestamp are appended to form the complete operation chain record. Perform a hash operation on the entire complete operation link record to generate a link integrity check code, which is then appended to the end of the complete operation link record. The complete operation link record with the attached link integrity check code is stored in the audit log in an append-only manner, and the audit log is configured to an append-only, non-modifiable storage mode.

10. A paperless management system for the entire clinical blood use process based on a smart handwriting tablet, used to implement the method described in any one of claims 1 to 9, characterized in that, include: The document construction module is used to obtain structured form data of the current business node from the blood transfusion management system, parse the preset signature anchor point identifier in the document template, and calculate the absolute coordinate range and signature capacity size constraint of each signature area in the generated PDF document based on the signature anchor point identifier. The identity anchoring module is used to collect the operator's identity credential data when the signature area is activated, compare the identity credential data with the department personnel permission mapping table, extract the operator's role type label and authorized signature range identifier, and determine whether the current operator has the business signing permission for the corresponding signature area. The handwriting acquisition module is used to start the smart handwriting tablet after the business signing permission verification is passed, acquire the touch trajectory coordinate sequence and pressure value sequence at a preset sampling frequency, and divide the touch trajectory coordinate sequence into several stroke segments according to the time interval between adjacent sampling points. The handwriting quality assessment module is used to calculate the handwriting integrity score based on the number of effective sampling points and pressure value distribution characteristics of the stroke fragment, compare the handwriting integrity score with the signature validity threshold, send a re-signing instruction if it is lower than the threshold, and perform vectorized rendering on the stroke fragment to generate a signature image if it reaches the threshold. The signature fusion module is used to perform proportional scaling and coordinate offset transformation on the signature image according to the absolute coordinate range and signature capacity size constraint, and then write it into the corresponding signature area of ​​the PDF document. The module also embeds a signature traceability record containing the operator's employee number, signature timestamp, terminal device identifier and handwriting integrity score in the metadata area of ​​the PDF document. The process closed-loop determination module is used to traverse all signature areas corresponding to all signature anchor identifiers in the PDF document after the signature traceability record is written, detect whether each signature area has been associated with a valid signature traceability record, determine the signing completion status based on the detection result and trigger archiving operation or pending signature reminder notification. The archiving and auditing module is used to perform hash digest calculation on the PDF document to generate a document fingerprint value when all signing is completed, upload the PDF document and the document fingerprint value to the electronic medical record archiving system, and write a complete operation link record containing the document fingerprint value, each signature traceability record and business node identifier into the audit log.

Images