Medical big data traceability system and method based on block chain

Abstract

The invention relates to the technical field of medical data management, and discloses a medical big data traceability system and method based on a block chain. A main chain is constructed to record a medical data life cycle key event, a sub-chain records an operation history, a sub-chain root hash is embedded into a main chain node, and a tree-shaped association structure of the main chain and the sub-chain is formed; and in combination with an incremental hash tree structure, a block chain, distributed file storage and a cross-layer hash verification mechanism between local or cloud storage, efficient traceability and integrity verification of the medical data are realized, and the method is suitable for a multi-mechanism medical data sharing and compliance auditing scene.

Description

Blockchain-based Medical Big Data Traceability System and Method Technical Field

[0001] This invention relates to the field of medical information and data management technology, specifically to a medical big data traceability system and method based on blockchain technology, used for reliable traceability, integrity verification and lifecycle management of multi-source heterogeneous medical data. Background Technology

[0002] With the widespread deployment of medical information systems (HIS, EMR, PACS, LIS, etc.), a large amount of medical data is generated and used within institutions and across institutions. In existing technologies, medical data is typically stored and logged, which presents the following technical problems: 1. The traceability chain structure is simple, making efficient querying difficult: Most systems only record operation logs in a linear time sequence, lacking hierarchical management of "critical lifecycle events" and "detailed operation history." Traceability queries usually require traversing a large number of log records, resulting in high time complexity and making it difficult to support efficient retrieval in large-scale data scenarios.

[0003] 2. Conflict between on-chain storage overhead and the need for complete traceability: Some blockchain solutions attempt to write complete medical records or all traceability information directly to the blockchain, resulting in excessive on-chain storage pressure; if only a single hash digest is written to the chain, it is difficult to achieve fine-grained traceability and integrity verification while ensuring privacy.

[0004] 3. Lack of a unified traceability mechanism for multi-source heterogeneous medical data: Medical data types include HL7 FHIR structured medical records, DICOM medical images, HL7 v2 / v3 test results, and real-time vital sign monitoring data, etc. Existing solutions are often designed for a single format and do not have unified parsing and traceability capabilities.

[0005] 4. Incomplete data lifecycle management: Existing technologies focus more on data creation and partial access records, and lack sufficient records of the entire lifecycle of data, including major modifications, cross-organizational sharing, archiving and deletion, making it difficult to meet regulatory audit and compliance requirements.

[0006] Therefore, there is a need for a medical big data traceability system and method that is geared towards medical scenarios, supports multi-source heterogeneous data, and enables efficient querying and integrity verification while ensuring privacy. Summary of the Invention

[0007] (I) Technical problems to be solved The purpose of this invention is to provide a blockchain-based medical big data traceability system and method to solve at least the following problems in the prior art: 1. The traceability chain structure is simple and the query efficiency is low; 2. The on-chain storage overhead is difficult to balance with the complete traceability requirements; 3. The lack of a unified traceability mechanism for multi-source heterogeneous medical data; 4. The incomplete recording of the medical data life cycle.

[0008] By designing the traceability chain structure and storage architecture in a targeted manner, we can achieve reliable traceability, efficient querying, and cross-storage layer integrity verification of medical data.

[0009] To address the aforementioned technical issues, this invention provides a blockchain-based medical big data traceability system, comprising: 1. A multi-source data acquisition module: used to collect medical data conforming to standards such as HL7FHIR, DICOM, and HL7 v2 / v3 from heterogeneous medical information systems (HIS, EMR, PACS, LIS, real-time monitoring systems, etc.), automatically identify key attributes such as data type, acquisition time, and institution identifier, perform irreversible desensitization processing on patient identifiers, and generate corresponding data fingerprints and structured metadata based on data content, structure, and time information.

[0010] 2. Layered Traceability Chain Construction Module: This module is used to construct a two-layer traceability chain structure, including a main chain and sub-chains, based on the data fingerprint and structured metadata. Specifically: - The main chain records key events in the medical data lifecycle, including at least one of data creation, major modification, cross-institutional sharing, archiving, and deletion; - Sub-chains record the specific operation history of the medical data, including at least one of data modification, access records, permission changes, and compliance verification; - Each main chain node stores the sub-chain root hash calculated from the set of sub-chain nodes associated with it, thus forming a tree-like association structure between the main chain nodes and the sub-chains.

[0011] 3. Traceability Chain Hash Calculation Unit: Connected to the hierarchical traceability chain construction module, it internally stores incremental hash tree structure calculation functions suitable for medical data traceability. When a new node is added to the traceability chain, it only updates the hash values ​​of intermediate nodes on the path from the new node to the corresponding root node to calculate the main chain root hash and the child chain root hash, and generates the final traceability chain root hash based on this. When performing traceability verification, it supports partial verification only for the part of the path related to the medical data to be verified, without having to traverse and verify the entire traceability chain.

[0012] 4. Hybrid Storage Module: This module is used to write the root hash of the traceability chain and its corresponding data digest to the blockchain, write the large file corresponding to the medical data content to the distributed file storage system, and write the complete traceability chain data and the encrypted medical data text to the local or cloud storage system. It stores association fields for hash verification between the blockchain layer, the distributed file storage layer, and the local or cloud storage layer. When performing a traceability query, it compares the root hash of the traceability chain stored in the blockchain layer, the hash verification value stored in the local or cloud storage layer, and the content identifier stored in the distributed file storage layer to verify the integrity and consistency of the medical data across different storage layers.

[0013] 5. Traceability Query and Verification Module: Based on the data fingerprint or patient identifier, institution identifier, time range, and other conditions carried in the query request, this module uses a pre-established index to quickly locate the corresponding traceability chain root hash on the blockchain. Combining data from local or cloud storage and distributed file storage systems, it performs main chain and sub-chain hash chain verification and cross-storage layer hash comparison to generate traceability results that include data source, flow path, integrity, and compliance status.

[0014] The present invention also provides a blockchain-based medical big data traceability method, including: 1. Step S1: Multi-source data collection and preprocessing. Collect medical data from at least one medical information system, extract patient identifiers, data types, time information and institution identifiers, perform desensitization processing and standardization conversion, and generate corresponding data fingerprints and structured metadata.

[0015] 2. Step S2: The hierarchical traceability chain is constructed based on the data fingerprint and structured metadata. A two-layer traceability chain structure including a main chain and sub-chains is constructed. Key events in the life cycle of medical data are recorded on the main chain, specific operation history is recorded on the sub-chains, and the corresponding sub-chain root hash is stored in the main chain nodes.

[0016] 3. Step S3: Incremental hash calculation and root hash generation adopt an incremental hash tree structure calculation function to calculate the main chain root hash, the sub-chain root hash and the final trace chain root hash for the trace nodes in the main chain and sub-chain. When adding a new trace node, only the hash value of the intermediate node on the path from the new node to the corresponding root node is updated, and local path verification is supported during trace verification.

[0017] 4. Step S4: Hybrid storage and cross-layer association: Write the root hash of the traceability chain and its corresponding data digest into the blockchain, write the large file corresponding to the medical data content into the distributed file storage system, write the complete traceability chain data and the encrypted medical data text into the local or cloud storage system, and establish associations between different storage layers through preset hash verification fields.

[0018] 5. Step S5: Source Tracing and Integrity Verification. Upon receiving a source tracing query request, the corresponding source chain root hash is obtained from the blockchain layer and combined with data from local or cloud storage / distributed file storage systems. Main chain and sub-chain hash chain verification and cross-storage layer hash comparison are performed, returning a structured source tracing report containing basic data information, the source tracing path, and integrity results. Beneficial Effects

[0019] Compared with the prior art, the present invention has at least the following beneficial effects: 1. Improve the efficiency of traceability query: Through the main chain-sub-chain two-layer traceability structure, the key events and operation details of the life cycle are managed in layers. When querying, an overview can be obtained first based on the main chain, and then drill down to the sub-chain as needed to obtain detailed records, so that traceability query still has good time complexity and response performance in large-scale data scenarios.

[0020] 2. Balancing on-chain storage overhead with complete traceability capabilities: Through a hybrid storage architecture, only the root hash of the traceability chain and necessary digest information are stored on the blockchain, while the complete traceability chain data and large medical data are stored off-chain. At the same time, cross-layer associations are established through hash verification fields, which reduces on-chain storage overhead while still enabling consistency verification of the complete traceability path and original data content.

[0021] 3. Adaptation to multi-source heterogeneous medical data: The multi-source data acquisition module and unified data fingerprint generation mechanism provide unified abstraction for multiple standards such as HL7 FHIR, DICOM, and HL7 v2 / v3, and offer consistent traceability and verification methods for different data types, simplifying the unified management of multi-source heterogeneous medical data.

[0022] 4. Supports traceability throughout the entire data lifecycle: By recording key events such as data creation, major modifications, cross-institutional sharing, archiving, and deletion in the main chain, and recording operations such as access and permission changes in the sub-chain, this invention can technically track the entire lifecycle of medical data, facilitating auditing and compliance checks. Attached Figure Description

[0023] The accompanying drawings in this specification are provided to help understand the technical solutions of this invention and do not constitute a limitation on the scope of protection of this invention.

[0024] - Figure 1 is a schematic diagram of the overall architecture of the blockchain-based medical big data traceability system of the present invention; - Figure 2 is a schematic diagram of the medical data traceability chain structure of the present invention; - Figure 3 shows the hash embedding method. Detailed Implementation

[0025] The following detailed embodiments are used to further illustrate the present invention, but do not constitute a limitation on the scope of protection of the present invention.

[0026] Example 1: Blockchain-based Medical Big Data Traceability System. Referring to Figure 1, the medical big data traceability system in this example can be deployed in a medical institution consortium blockchain environment, including a multi-source data acquisition module, a hierarchical traceability chain construction module, a traceability chain hash calculation unit, a hybrid storage module, and a traceability query and verification module, etc.

[0027] The multi-source data acquisition module interfaces with various medical information systems. According to the preset data access specifications, it performs format recognition, field extraction, and sensitive field desensitization on the medical data entering the system. It also generates data fingerprints based on data content, structure, and time information to uniformly identify medical data from different sources.

[0028] The hierarchical traceability chain construction module establishes at least one main chain node representing the creation of each piece of medical data in the main chain based on data fingerprints and structured metadata. When significant changes occur in the data or critical events such as cross-institutional sharing, corresponding nodes are added to the main chain. For routine access, permission changes, and other operations, sub-chain nodes are added to the sub-chain, and the sub-chain root hash is maintained in the corresponding main chain node, thus forming the main chain-sub-chain tree-like traceability structure shown in Figure 2.

[0029] In one specific implementation, the data structure of the main chain node may include the following fields: | Field Name | Example Content | Description | |---------------------|----------------------|------------------------| | `data_fingerprint` | `sha256(fhir_record)` | Medical data fingerprint | | `prev_main_hash` | `0xabc123...` | Previous main chain node hash | | `subchain_root_hash` | `0xdef456...` | Subchain root hash (embedded in the main chain node) | | `event_type` | `CREATE` / `UPDATE` etc. | Lifecycle event type | | `timestamp` | `2025-01-01T10:00:00Z` | Event occurrence time | By setting `subchain_root_hash` in the main chain node The main chain not only records the lifecycle events of medical data, but also establishes an immutable association with the sub-chains through this field; any addition, deletion or modification of a sub-chain node will be reflected in the main chain node through the change of the sub-chain root hash, so that the tampering of the sub-chain historical records can be detected in time during traceability verification.

[0030] The traceability chain hash calculation unit is based on an incremental hash tree structure, performing hierarchical hash calculations on nodes of the main chain and sub-chains: when adding a new traceability node, only the hash values ​​of intermediate nodes are updated along the path from the new node to the root node, thus maintaining the integrity of the traceability chain while avoiding a full recalculation of the entire hash tree. When performing traceability verification, only local paths related to the data to be verified are loaded and verified based on the fingerprint of the data to be verified, avoiding traversal of the entire traceability chain.

[0031] The hybrid storage module stores the traceability chain root hash, timestamp, and necessary data digests at the blockchain layer; large-file medical data in the distributed file storage layer; and complete traceability chain node data and encrypted medical data text in the local or cloud storage layer. By setting interrelated hash verification fields between the three storage layers, data from different storage layers can be compared during traceability queries and integrity verification to detect potential tampering risks.

[0032] The traceability query and verification module provides a query interface. When the search conditions such as data fingerprint, patient identifier, institution identifier and time range are entered, the corresponding traceability chain root hash is first located on the blockchain through indexing. Then, the relevant main chain and sub-chain nodes are loaded from local or cloud storage. Large file data is loaded from the distributed file storage system as needed to verify the integrity of the hash chain and the consistency of data across storage layers. The module outputs a traceability report that includes the data source, key event timeline and integrity status.

[0033] Example 2: Blockchain-based medical big data traceability method. This example corresponds to the functional flow of the aforementioned system and can be applied to scenarios within a single medical institution or an alliance of multiple medical institutions.

[0034] In step S1, the system receives newly generated or updated medical data from systems such as EMR, PACS, and LIS, converts it into an internal standard format, extracts key information such as patient identification (and desensitizes it), data type, collection time, and institution identification, and generates data fingerprints and structured metadata based on a preset algorithm.

[0035] In step S2, the system generates a data creation node in the main chain based on the data fingerprint, and adds the corresponding node in the main chain when there are major changes in the data or key events such as cross-organizational sharing; at the same time, the daily access operations, permission adjustments and compliance verification processes are recorded in the sub-chain, forming a two-layer traceability structure that links the main chain and the sub-chain.

[0036] In step S3, the system uses an incremental hash tree function to perform hash updates on the path where the newly added traceability node is located, thereby obtaining the new main chain root hash, sub-chain root hash and final traceability chain root hash; when it is necessary to verify the traceability information of a certain data in the future, only the relevant path is loaded for local hash verification based on the data fingerprint.

[0037] In an example implementation, the update process of an incremental hash tree may include: 1) attaching the new source node as a leaf node to the bottom layer of the hash tree; 2) calculating the hash value of its parent node from the leaf node upwards, where the parent node hash is calculated from the hashes of its left and right child nodes in a preset connection order; 3) repeating step 2 until the root node hash is updated, without recalculating other branch nodes unrelated to the new node during this process; 4) writing the updated root hash as the current root hash of the corresponding main chain or sub-chain to storage.

[0038] The above update method ensures that each change to the traceability record only affects a limited number of path nodes, reducing unnecessary redundant calculations and facilitating good system response performance in high-concurrency scenarios.

[0039] To further illustrate the technical effects of this invention, comparative tests were conducted in a simulated scenario containing a large number of medical records. Under the same hardware and data scale, traditional linear log-based tracing methods require traversing all records to reconstruct the data lifecycle. In contrast, this invention, through a main-chain-sub-chain two-layer structure and an incremental hash tree, only needs to load the main chain nodes and local paths related to the target data to complete the verification. With millions of records, the two-layer structure significantly shortens the time required for querying and verification in the experimental environment, and reduces unnecessary redundant records in terms of on-chain storage, demonstrating significant optimization effects in query efficiency and storage overhead from an engineering implementation perspective.

[0040] Infringement Determination Guidelines (Examples) To facilitate subsequent technical comparison of systems that may implement the present invention, the present invention provides the following reference points for infringement determination, which do not constitute a limitation on the claims: 1. By publicly or on-site testing of the blockchain ledger, confirm whether at least one main chain record representing a key life cycle event is recorded on the chain for each piece of medical data, and whether there is a sub-chain root hash field that corresponds one-to-one with the main chain record.

[0041] 2. Conduct technical analysis on the suspected system-generated traceability data to check whether it adopts a tree-like association structure in which the main chain records key lifecycle events, the sub-chain records operation history, and the sub-chain root hash is embedded into the main chain node.

[0042] 3. Without disrupting the normal operation of the system, capture the traceability records of newly added or modified medical data and analyze whether, when adding a new traceability node, only the hash value on the path from the new node to the root node is updated, without recalculating the hash value for unrelated nodes.

[0043] 4. Perform hash comparisons on the same medical data across blockchain layers, local or cloud storage layers, and distributed file storage layers to verify the existence of a cross-layer hash verification field with the traceability chain root hash as its core and its consistency verification logic.

[0044] If the system being compared simultaneously possesses the above-mentioned structural features and processing methods, it can be preliminarily determined from a technical perspective that its implementation scheme falls within the protection scope defined by the claims of this invention.

[0045] In step S4, the system writes the latest traceability chain root hash and summary information into the blockchain, stores the corresponding large-file medical data in a distributed file storage system, stores the complete traceability chain node and encrypted medical data text in a local or cloud storage system, and maintains comparable hash verification values ​​between different storage layers.

[0046] In step S5, the system automatically retrieves and reconstructs the traceability chain of the corresponding medical data based on the query conditions submitted by the user, performs integrity verification on the main chain, sub-chains and cross-storage layer data, and returns the verification results and data flow path in a structured manner.

[0047] Those skilled in the art can make various equivalent modifications or substitutions to the above embodiments without departing from the spirit and essence of the present invention, and all such modifications or substitutions should fall within the protection scope of the claims of the present invention.

[0048] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are 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.

Claims

1. A blockchain-based medical data traceability system, characterized in that, include: The hierarchical traceability chain construction module is configured as follows: the main chain is built based on the data fingerprint of medical data, and the main chain nodes record key events in the life cycle of medical data; A subchain is constructed based on the operation records of medical data, and the subchain nodes record the operation history of medical data; the root hash of the subchain is embedded into the corresponding main chain node to form a tree-like association structure between the main chain and the subchain; wherein, the main chain and the subchain together constitute a two-layer traceability chain structure to support the source tracing and integrity verification of medical data.

2. A blockchain-based method for tracing medical data, characterized in that, include: Build a main chain to record key events in the lifecycle of medical data; A sub-chain is constructed to record the operation history of medical data; the root hash of the sub-chain is embedded into the main chain node to form a tree-like association structure between the main chain and the sub-chain; based on the two-layer traceability chain structure, the source of medical data is traced and its integrity is verified.

3. The system or method according to claim 1 or 2, characterized in that, In the aforementioned two-layer traceability chain structure: the main chain node includes at least the current data fingerprint, the hash value of the previous main chain node, and a marker field used to characterize the lifecycle stage of medical data. The events corresponding to the main chain node include at least one of data creation, major modification, cross-institutional sharing, data archiving, and data deletion. The sub-chain node includes at least the current data fingerprint, the hash value of the previous sub-chain node, and a field used to characterize the specific operation type. The operation type includes at least one of data modification, access record, permission change, and compliance verification.

4. The system or method according to claim 1 or 2, characterized in that, The traceability chain hash calculation unit includes: an incremental hash tree structure, whose nodes correspond one-to-one with the traceability data records in the two-layer traceability chain; a local update module, configured to update only the hash values ​​of intermediate nodes on the path from the new node to the corresponding root node when a new node is added to the traceability chain; and a local verification module, configured to load only the local path related to the medical data to be verified for hash comparison when performing traceability verification, without having to traverse and verify the entire traceability chain.

5. The system or method according to claim 1 or 2, characterized in that, The hybrid storage module includes a blockchain storage submodule, which is configured to store traceability chain root hash, timestamp, and data digest information related to medical data traceability on the blockchain, and use the traceability chain root hash as the traceability identifier of the blockchain layer.

6. The system or method according to claim 1 or 2, characterized in that, The hybrid storage module includes a distributed file storage submodule, which is configured to write large files corresponding to medical data content into the distributed file storage system and obtain content identifiers, and then write the content identifiers as reference fields into the blockchain storage submodule and the local or cloud storage submodule.

7. The system or method according to claim 1 or 2, characterized in that, The hybrid storage module includes a local or cloud storage sub-module. The local or cloud storage sub-module is configured to store complete traceability chain node data and encrypted medical data text according to a preset data model, and to store hash verification fields corresponding to the blockchain storage sub-module and the distributed file storage sub-module, so as to confirm the consistency of data in different storage layers through hash comparison when performing traceability queries and integrity verification.

8. The system or method according to claim 1 or 2, characterized in that, The multi-source data acquisition module is configured to support at least one medical data standard such as HL7 FHIR, DICOM, and HL7 v2 / v3. It automatically identifies different data formats and structures through an adaptive data parsing engine, extracts key attributes such as patient identification, data type, time information, and institution identification from the medical data, and performs irreversible desensitization processing on the patient identification.

9. The system or method according to claim 1 or 2, characterized in that, The hybrid storage module is also configured to calculate hash verification values ​​for large medical data stored in the distributed file storage system and the main body of medical data stored in the local or cloud storage system, and to compare the traceability chain root hash stored in the blockchain layer, the hash verification value stored in the local or cloud storage layer, and the content identifier stored in the distributed file storage layer when performing traceability queries, so as to verify the integrity and consistency of medical data in different storage layers.

Images