Method and system for selecting and confirming patient informing object, and storage medium

Abstract

The invention relates to a method and a system for selecting and confirming informed objects of patients and a storage medium. The method comprises the following steps of: establishing an informed rule base containing a patient classification group and a corresponding informed object permission sorting system; receiving relation information between the informed notification object and the patient and a certification material, and verifying the consistency of the declared patient information and the existing patient information of the medical and health institution at the same time; verifying the correctness and effectiveness of the relationship between the informed object and the patient by adopting a relative relationship verification mode based on credibility; based on the informed informing rule base and the patient diagnosis and treatment information, generating an informed informing object suitable sorting table of the patient; and providing a data service based on the informed object suitable sorting table, wherein the data service comprises a relationship query service and an informed object verification service. The problem that in the prior art, it is difficult for medical staff to efficiently select an appropriate informing object is solved.

Description

Technical Field

[0001] This invention belongs to the field of medical information management technology, specifically relating to a method, system, and storage medium for selecting and confirming the recipients of informed consent for patients. Background Technology

[0002] Informed consent is a core principle of medical services. Medical staff often need to inform legal guardians, close relatives, etc., due to the patient's condition, restrictions, or protective treatment needs. However, the accurate identification and verification of the informed consent recipients is the key to the implementation of the informed consent system, but there are currently multiple challenges.

[0003] First, there is no standard for selecting the informed consent recipients: patients have different civil capacity and different conditions, and the legally required informed consent recipients and priorities vary. Medical staff often rely on experience to make judgments, which can easily lead to confusion about priorities and render the informed consent process invalid. Second, existing kinship confirmation technologies have poor adaptability: although there are solutions based on knowledge graphs, image features, and population data, they can only determine whether someone is a relative, but cannot determine whether someone is a legally entitled to be notified or the priority of notification, thus failing to meet the needs of medical scenarios. Third, there is an imbalance between verification efficiency and accuracy: manual verification of paper materials is inefficient and prone to misjudgment, and some technical verifications lack credibility grading and cross-verification mechanisms, resulting in insufficient legal recognition of the results. Fourth, there is a lack of real-time data services: In some emergency scenarios, medical staff have difficulty quickly identifying high-priority individuals to be notified, and information sharing among multiple departments is difficult, affecting medical decision-making.

[0004] Therefore, it is necessary to develop a new method, system, and storage medium for selecting and confirming the recipients of informed consent for patients. Summary of the Invention

[0005] The purpose of this invention is to provide a method, system, and storage medium for selecting and confirming the recipients of informed consent for patients, in order to solve the problem that medical personnel in the prior art find it difficult to efficiently select appropriate recipients of informed consent.

[0006] In a first aspect, the method for selecting and confirming the recipients of informed consent for patients according to the present invention includes the following steps: Establish an informed consent rule base that includes patient classification groups and corresponding informed consent ordering systems; Receive information and supporting documents from informed consent recipients regarding their relationship with patients, and verify the consistency between the declared patient information and existing patient information in medical and health institutions. A credibility-based kinship verification method was used to verify the correctness and effectiveness of the relationship between the informed consent recipient and the patient. Based on the informed consent rule base and patient medical information, a suitable sorting table for informed consent recipients is generated. Provide data services based on the appropriate ranking table of the informed consent recipients, the data services including relationship query services and informed consent recipient verification services.

[0007] Optionally, an informed consent rule base may be established, specifically as follows: Based on multiple factors including patient age, civil capacity, illness, treatment items, and level of protective treatment, a patient grouping device was constructed to classify patients into groups with full civil capacity, minors without civil capacity, minors with limited civil capacity, patients who cannot recognize their own actions or consequences, patients who are unable to exercise their right to informed choice due to illness, and patients whose situation should not be directly explained to them when implementing protective medical measures. For each patient classification group, a corresponding informed consent target group and its order are defined, forming an informed consent target system table; By combining the patient grouper and the informed consent recipient system table, the informed consent rule base is generated. The patient grouper is constructed using multiple dimensions (age, civil capacity, etc.) to achieve precise patient classification, covering patients with full civil capacity, minors, and those in a state of unconsciousness. Simultaneously, a customized informed consent recipient ranking is assigned to each patient category, clearly defining who is prioritized for notification (e.g., parents are prioritized for minor patients), avoiding confusion regarding priorities. Furthermore, the grouper and ranking system are combined into a rule base, forming standardized selection criteria to ensure consistent informed consent recipient selection for the same patient category by different medical personnel and institutions, improving the standardization of medical services. In summary, this solves the problem of unclear scope and priority of informed consent recipients for different patients.

[0008] Optionally, the information and supporting documents regarding the relationship between the recipient of the informed consent and the patient specifically include: Configure an information declaration template, which includes fields for entering applicant information, entering information about the informed consent recipient, entering patient information, entering information about the relationship with the patient, and uploading supporting documents for proof of the relationship. The information submission template collects various information from applicants, including: applicant information (institutional applicants: name, organization code, responsible person, and contact information; individual applicants: name, ID card information, contact information, and address); informed consent recipient information (name, ID card type and number, contact information, and level of civil capacity); patient information (name, medical record number, ID card type and number); and relationship information (relationship type, relationship status, start and end dates). By configuring a structured submission template, the required information items (applicant, informed consent recipient, patient, relationship information, and supporting documents) are clearly defined, preventing omissions. The template also details the content of each information item (e.g., organizational code for institutional applicants, ID card for individual applicants), ensuring complete and traceable information. Furthermore, the requirement to upload relationship proof provides a basis for subsequent relationship verification, reducing the risk of missing documents or falsified information, and improving the effectiveness of the submitted information. In summary, this addresses the problems of disorganized and incomplete informed consent recipient information.

[0009] Optionally, the consistency between the patient information submitted for verification and the existing patient information of the medical and health institution is specifically as follows: The patient information submitted by the applicant will be compared with the existing patient information of the medical and health institutions. If the comparison results match, the patient information verification is deemed successful, and the relationship declaration process can continue. If the comparison results are inconsistent, the applicant is prompted to verify the patient information and resubmit. By comparing with existing patient information at medical institutions, it ensures that the applicant corresponds to the correct patient; it also clarifies the judgment logic of passing if consistent and prompting resubmission if inconsistent, quickly filtering out erroneous patient information and reducing subsequent invalid verification processes; it also reduces the workload of medical staff manually verifying patient information, improves information verification efficiency, and removes obstacles for subsequent relationship verification stages. In summary, this solves the problem of mismatch between the applicant's patient information and the actual patient information at medical institutions.

[0010] Optionally, a trust-based kinship verification method may be adopted, specifically as follows: Preset credibility values ​​for different trusted channels; If the obtained verification data comes from a channel with a credibility value ≥ the preset credibility threshold, the relationship verification is deemed qualified when the verification of a single channel passes. If the obtained verification data comes from channels with a credibility value lower than a preset credibility threshold, the relationship verification is considered successful if at least two such channels pass the verification. By setting a preset credibility value for trusted channels, the reliability of verification data is differentiated (e.g., police data is more reliable than self-verification by relatives). Simultaneously, the logic of single-channel verification for high-credibility data and cross-verification through multiple channels for low-credibility data ensures the efficiency of high-credibility data while avoiding the risk of misjudgment from low-credibility data. Furthermore, it ensures that the kinship verification results are based on evidence and are trustworthy, enhancing the legal validity of informing the recipient of their identity and reducing medical disputes caused by incorrect relationship confirmation. In summary, this addresses the problems of existing verification methods lacking credibility grading and having low result acceptance.

[0011] Optionally, a suitable sorting table for informed consent recipients is generated, specifically as follows: Extracting patient medical information from a medical and health diagnosis and treatment information system, the medical information including basic personal information, diagnostic information, and treatment information; The patient's medical information is input into the patient grouper, which automatically determines the patient's classification group. Based on the informed consent system table corresponding to the patient's classification group, and combined with the verified informed consent information, the informed consent recipients are sorted according to priority rules, generating an appropriate sorting table for informed consent recipients that includes the priority value, recipient's name, ID information, contact information, level of civil capacity, and relationship to the patient. By extracting patient information from the medical system, the basis for patient classification (such as condition and treatment items) is ensured to be accurate and avoids classification bias. Simultaneously, it automatically matches the patient's classification group with the corresponding sorting system without manual intervention, automating the generation of the appropriate sorting table for informed consent recipients. Furthermore, the appropriate sorting table includes key information such as priority value and contact information, which medical staff can directly access without secondary queries, improving notification efficiency, especially suitable for time-sensitive scenarios such as emergency rescues. In summary, this solves the problem of determining the optimal order from verified informed consent recipients.

[0012] Optionally, a relationship query service can be provided, specifically: Receive externally inputted patient information, informed consent information, and relationship information; The input information is matched with the patient information and verified informed consent information stored in the system. If a match is found, the system outputs a result indicating a correct relationship; if a match is not found, the system outputs a result indicating an incorrect relationship, along with possible reasons for the error. By matching the received input information with the system's stored information, the system quickly determines whether a relationship is correct; if a mismatch is found, it can also indicate the reason for the error, helping medical staff quickly locate the problem. Furthermore, it eliminates the need for manual review of medical records and verification of materials, enabling real-time relationship queries and improving the efficiency of multi-departmental collaboration. In summary, this system solves the problem of medical staff being unable to quickly confirm whether a particular individual is a legitimate relative.

[0013] Optionally, a verification service for those who have been informed can be provided, specifically: Receives externally inputted patient information, informed consent recipient information, and informed consent order value information; The system queries the appropriate sorting table of informed consent recipients for the patient and determines whether the input informed consent recipient and order value exist in the appropriate sorting table of informed consent recipients. If the information does not exist, output a message indicating that the informed consent recipient or the order value does not exist. If the information exists, verify whether the input order value matches the priority value in the sorting table. If they match, output that the order is correct; otherwise, output that the order is incorrect and the correct priority value. By querying the appropriate sorting table for informed consent recipients, the validity of the informed consent recipients and their order values ​​can be quickly verified. It also clarifies the feedback logic of prompting if the information does not exist and informing the correct value if the order is incorrect, directly guiding medical staff to adjust the informed consent recipients and avoiding errors such as recipients not being on the list or the order being reversed. Furthermore, it provides a final check for the informed consent process, ensuring that the actual informed consent recipients match the sorting table, further guaranteeing the correctness of the informed consent procedure. In summary, this solves the problem of medical staff being unsure whether a recipient is in the informed consent sorting and whether the order is correct.

[0014] Secondly, the patient informed consent selection and confirmation system of the present invention includes a processor and a memory, wherein the memory stores a computer program, and when the computer program is executed by the processor, it implements the steps of the patient informed consent selection and confirmation method of the present invention.

[0015] Thirdly, the present invention provides a storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the method for selecting and confirming the recipients of informed consent as described in the present invention.

[0016] The beneficial effects of this invention are: (1) This invention solves the problem of lack of standardized criteria for selecting informed consent recipients in the prior art by establishing an informed consent rule base that includes patient classification groups and corresponding informed consent recipient ranking system. By classifying patients according to age, civil capacity, etc., and matching each type of patient with a clear ranking of informed consent recipients, this invention breaks the traditional model of medical staff selecting recipients based on experience and forms a unified and reusable selection standard.

[0017] (2) By setting up a step to receive the relationship information and supporting materials submitted by the recipient and verify the consistency between the patient information and the medical institution information, the present invention solves the problems of messy application information and mismatched patient information.

[0018] (3) This invention adopts a credibility-based kinship verification method, which solves the problems of existing kinship verification lacking grading and unreliable results. Compared with traditional single-material verification or general kinship determination, by setting a credibility value for a credible channel (such as the credibility of public security data being higher than that of self-verification by relatives) and formulating a judgment logic of single verification for high credibility and multiple verification for low credibility, it not only ensures the verification efficiency of high credibility data (such as public security household registration data directly confirming spousal relationship), but also avoids the risk of misjudgment of low credibility data through cross-verification, making the kinship verification results based on evidence and traceable, improving the legal recognition of the identity of the informed party, and reducing medical disputes caused by incorrect relationships.

[0019] (4) This invention generates a suitable ordering table for notification recipients based on a rule base and patient medical information, solving the problem of not knowing who to notify first after verification. By linking patient medical information (such as condition and treatment items) with the rule base, the invention automatically matches the patient's classification group and the corresponding ordering of notification recipients, eliminating the need for manual sorting and achieving automated transformation from verified recipients to the optimal order. The ordering table contains key information such as priority values ​​and contact information, allowing medical staff to directly obtain information on who to notify first and how to contact them without secondary queries. This is particularly suitable for scenarios requiring rapid notification, such as emergency rescue, improving notification efficiency.

[0020] (5) This invention provides data services including relationship query and object verification, which solves the problem of lack of real-time verification methods during the notification process. The relationship query service allows medical staff to quickly confirm whether an object is a legitimate relative of the patient, avoiding the mistaken inclusion of non-relatives as notification recipients; the object verification service can verify whether an object is in the sort and whether the order is correct, avoiding the reversal of the notification order.

[0021] In summary, this invention, through a five-step process of rule base establishment, information reception and verification, relationship verification, sorting table generation, and data service, fundamentally solves the shortcomings of existing technologies that can only confirm kinship relationships and cannot adapt to medical informed consent scenarios. Attached Figure Description

[0022] Figure 1 This is a flowchart illustrating the method for selecting and confirming the recipients of informed consent as described in the embodiments of this application; Figure 2 This is a schematic diagram of the patient informed consent selection and confirmation system described in this application embodiment. Detailed Implementation

[0023] The following description, with reference to the accompanying drawings and preferred embodiments, illustrates the implementation of the technical solution of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be understood that the preferred embodiments are only for illustrating the present invention and not for limiting the scope of protection of the present invention.

[0024] like Figure 1 As shown in the embodiments of this application, a method for selecting and confirming the recipients of informed consent for patients includes the following steps: Establish an informed consent rule base that includes patient classification groups and corresponding informed consent ordering systems.

[0025] Receive information and supporting documents from informed consent recipients regarding their relationship with patients, and verify the consistency between the declared patient information and existing patient information in medical and health institutions.

[0026] A credibility-based kinship verification method was used to verify the correctness and effectiveness of the relationship between the informed consent recipient and the patient.

[0027] Based on the informed consent rule base and patient medical information, a suitable ranking table for informed consent recipients is generated.

[0028] Provide data services based on the appropriate ranking table of the informed consent recipients, the data services including relationship query services and informed consent recipient verification services.

[0029] In one possible embodiment, an informed consent rule base is established in accordance with relevant laws, regulations, and medical and health management systems, specifically as follows: The informed consent rule base mainly consists of a patient grouper and an informed consent recipient system table.

[0030] Patient grouping system: The patient grouping system is constructed based on multiple factors including patient age, civil capacity, illness, treatment items, and level of protective treatment. Patients are divided into groups such as those with full civil capacity, minors without civil capacity, minors with limited civil capacity, patients unable to recognize their own actions or consequences, patients unable to exercise their right to informed choice due to illness, and patients for whom it is not appropriate to directly explain the situation to them when implementing protective medical measures.

[0031] The group with full civil capacity mainly includes natural persons aged 18 and above, as well as minors aged 16 and above but under 18, who rely on their own labor income as their main source of livelihood.

[0032] The group of minors without civil capacity mainly includes minors who are 10 years of age or older and have no civil capacity.

[0033] The group of minors with limited civil capacity mainly includes minors aged 10 to under 18 who are mentally sound and have limited civil capacity (excluding those aged 16 to under 18 who rely on their own labor income as their main source of livelihood).

[0034] Patients who cannot recognize the consequences of their actions: This group mainly includes patients with specific conditions such as mental illness and dementia. This group of diseases is usually provided in a disease classification dictionary.

[0035] Patients who are unable to exercise their right to informed choice due to illness: This group mainly includes patients who are 18 years of age or older and are in a state of unconsciousness such as coma, shock, or anesthesia.

[0036] Patients for whom protective medical measures should not be directly explained to them: This group mainly consists of patients who have been marked by medical staff as not suitable for protective medical measures to be directly explained to them.

[0037] Informed Consent Recipient System Table: For each patient classification group, a corresponding informed consent recipient population and its order are defined, forming an informed consent recipient system table; specifically: Group with full civil capacity: The informed consent recipients are the patient or their authorized representative.

[0038] For minors without civil capacity: the informed consent recipients are, in order, parents, grandparents, maternal grandparents, adult siblings, and other close relatives.

[0039] The group of minors with limited civil capacity: The people who are informed are, in order, parents, grandparents, maternal grandparents, adult brothers and sisters, and other close relatives.

[0040] For patients who cannot recognize their own actions or consequences: the informed consent recipients are, in order, their spouses, parents, adult children, and other close relatives.

[0041] Patients who are unable to exercise their right to informed consent due to illness: The informed consent recipients are close relatives with full civil capacity.

[0042] For patients in whom protective medical measures should not be directly explained: the group to whom the information should be provided consists of close relatives with full civil capacity.

[0043] The informed consent rule base is generated by combining the patient grouper and the informed consent subject system table.

[0044] This method constructs a patient grouper based on multiple dimensions (age, civil capacity, etc.) to achieve precise patient classification, covering patients with full civil capacity, minors, and those with impaired consciousness across all scenarios. Simultaneously, it customizes the notification recipient ranking for each patient category, clearly defining who should be informed first (e.g., prioritizing parents for minor patients) to avoid confusion regarding priorities. Furthermore, the grouper and ranking system are combined into a rule base, forming standardized selection criteria to ensure consistent notification recipient selection for the same patient category by different medical personnel and institutions, thereby improving the standardization of medical services. In summary, this method solves the problem of unclear scope and priority of notification recipients for different patients.

[0045] In one possible embodiment, receiving information and supporting documentation from the informed consent recipient regarding their relationship with the patient, specifically: Configure the information declaration template, which includes fields for entering the applicant's information, the identity information of the informed consent recipient, the patient's information, the relationship information with the patient, and the uploading of supporting documents for proof of relationship.

[0046] Information submitted by applicants is collected through an information declaration template. This includes: applicant information (for institutional applications, the organization name, organization code, responsible person, and contact information); or individual information (for individual applications, the name, ID card information, contact information, and address). Information on the informed consent recipients includes name, ID card type and number, contact information, and level of civil capacity. Patient information includes name, medical record number, ID card type and number; and relationship information includes relationship type, relationship status, and start and end dates. The relationship type is defined according to the "GB / T4761-2008 Family Relationship Code".

[0047] For example, the family relationship code is as follows: In one possible embodiment, proof of relationship typically includes household registration book, marriage certificate, birth certificate, and certificates from relevant authoritative institutions.

[0048] This method uses a structured application template to clearly define the required information items (applicant, recipient, patient, relationship information, and supporting documents), preventing omissions. It also details the content of each information item (e.g., organizations must submit an organization code, individuals must submit an ID card), ensuring completeness and traceability. Furthermore, it requires the uploading of relationship verification documents, providing a basis for subsequent relationship verification, reducing the risk of missing documents or falsified information, and improving the effectiveness of the application. In summary, this method solves the problems of disorganized and incomplete information in the recipient's application.

[0049] In one possible implementation, the consistency between the declared patient information and the existing patient information of the medical and health institution is verified, specifically as follows: The patient information submitted by the applicant will be compared with the existing patient information of the medical and health institutions. If the comparison results match, the patient information verification is deemed successful, and the relationship application process can continue. If the comparison results do not match, the applicant will be prompted to verify the patient information and resubmit it.

[0050] This method ensures that the reported patients correspond to the correct patients by comparing their information with existing patient information at medical institutions. It also clarifies the logic for approving submissions based on consistency and prompting for resubmissions based on inconsistencies, quickly filtering out erroneous patient information and reducing subsequent invalid verification processes. Furthermore, it reduces the workload of medical staff manually verifying patient information, improves information verification efficiency, and removes obstacles for subsequent relationship verification. In summary, this method solves the problem of mismatch between reported patients and actual patient information at medical institutions.

[0051] In one possible embodiment, a trust-based kinship verification method is employed, specifically as follows: The system presets credibility values ​​for different trusted channels. If the obtained verification data comes from a channel with a credibility value greater than or equal to the preset credibility threshold, the relationship verification is considered successful if verification is passed by a single channel. If the obtained verification data comes from a channel with a credibility value less than the preset credibility threshold, the relationship verification is considered successful if verification is passed by at least two channels of that type.

[0052] For example: For channels with a credibility of 99% or higher, verification through a single channel is sufficient; for channels with a credibility of less than 99%, verification through at least two channels is required.

[0053] This method differentiates the reliability of verification data by pre-setting credibility values ​​for trusted channels (e.g., police data is more reliable than self-verification by relatives). It also employs a logic of single-channel verification for high-credibility data and cross-verification through multiple channels for low-credibility data, ensuring the efficiency of high-credibility data while avoiding the risk of misjudgment from low-credibility data. Furthermore, it ensures that kinship verification results are based on evidence and are trustworthy, enhancing the legal validity of informing the recipient of their identity and reducing medical disputes caused by incorrect relationship confirmation. In summary, this method solves the problems of existing verification methods lacking credibility grading and having low result acceptance.

[0054] In one possible embodiment, a suitable ranking table for informed consent recipients is generated, specifically as follows: The patient's medical information, including basic personal information, diagnosis, and treatment, is extracted from the healthcare information system. This information is then input into the patient grouper, automatically determining the patient's classification group. Based on the informed consent recipient list corresponding to the patient's classification group, and combined with verified informed consent recipient information, the recipients are sorted according to priority rules, generating a suitable ranking table that includes a priority value, recipient's name, ID information, contact information, level of civil capacity, and relationship to the patient. The priority values ​​are numbered sequentially from 1 to 3, with earlier numbers indicating higher priority for notification.

[0055] This method extracts patient information from the diagnostic and treatment system, ensuring the accuracy of patient classification criteria (such as condition and treatment items) and avoiding classification bias. It also automatically matches the patient's classification group with the corresponding ranking system without manual intervention, automating the generation of an appropriate ranking table for informed consent recipients. Furthermore, the appropriate ranking table includes key information such as priority values ​​and contact information, which medical staff can directly access without secondary queries, improving notification efficiency, especially suitable for time-sensitive scenarios such as emergency rescues. In summary, this method solves the problem of determining the optimal order from verified informed consent recipients.

[0056] In one possible embodiment, a relationship query service is provided, specifically as follows: It receives externally input patient information, informed consent recipient information, and relationship information. It matches the input information with the patient information and verified informed consent recipient relationship information stored in the system. If a match is found, it outputs a result indicating a correct relationship; otherwise, it outputs a result indicating an incorrect relationship and suggests possible reasons for the error.

[0057] This method quickly determines the correctness of a relationship by matching input information with information stored in the system. If discrepancies are found, it can also indicate the reason for the error, helping medical staff quickly locate the problem. Furthermore, it eliminates the need for manual review of medical records and verification of materials, enabling real-time relationship queries and improving the efficiency of multi-departmental collaboration. In summary, it solves the problem of medical staff being unable to quickly confirm whether a particular individual is a legitimate relative.

[0058] In one possible embodiment, an informed consent verification service is provided, specifically as follows: The system receives externally input patient information, informed consent recipient information, and informed consent order value information. It queries the appropriate ordering table for informed consent recipients corresponding to the patient in the system, determining whether the input informed consent recipient and order value exist in the appropriate ordering table. If not, it outputs a message indicating that the informed consent recipient or order value does not exist; if it exists, it verifies whether the input order value matches the priority order value in the ordering table. If they match, it outputs that the order is correct; otherwise, it outputs that the order is incorrect and the correct priority order value.

[0059] This method, by querying a suitable sorting table of informed consent recipients, can quickly verify the validity of the recipients and their order values. It also clarifies the feedback logic of prompting if a recipient is not listed and informing them of the correct value if the order is incorrect, directly guiding medical staff to adjust the informed consent recipients and avoiding errors such as recipients not being on the list or being in the wrong order. Furthermore, it provides a final check for the informed consent process, ensuring that the actual recipients match the sorting table, further guaranteeing the correctness of the informed consent procedure. In summary, this method solves the problem of medical staff being unsure whether a recipient is in the informed consent sorting table and whether the order is correct.

[0060] like Figure 2 As shown in the embodiments of this application, a system for selecting and confirming the recipients of informed consent for patients includes a processor and a memory. The memory stores a computer program, and when the computer program is executed by the processor, it implements the steps of the method for selecting and confirming the recipients of informed consent for patients as described in the embodiments of this application.

[0061] In one possible embodiment, a storage medium stores a computer program that, when executed by a processor, implements the steps of the method for selecting and confirming the recipients of informed consent as described in this application.

[0062] The program code used to implement the methods of this application may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing device, such that when executed by the processor or controller, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0063] In the context of this application's embodiments, a storage medium can be a tangible storage medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. The storage medium can be a machine-readable signal storage medium or a machine-readable storage medium. Storage media can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0064] The above embodiments are preferred embodiments of the present invention, but the embodiments of the present invention are not limited to the above embodiments. Any changes, modifications, substitutions, combinations, or simplifications made without departing from the spirit and principle of the present invention shall be considered equivalent substitutions and shall be included within the protection scope of the present invention.

Claims

1. A method for selecting and confirming the recipients of informed consent for patients, characterized in that, Includes the following steps: Establish an informed consent rule base that includes patient classification groups and corresponding informed consent ordering systems; Receive information and supporting documents from informed consent recipients regarding their relationship with patients, and verify the consistency between the declared patient information and existing patient information in medical and health institutions. A credibility-based kinship verification method was used to verify the correctness and effectiveness of the relationship between the informed consent recipient and the patient. Based on the informed consent rule base and patient medical information, a suitable sorting table for informed consent recipients is generated. Provide data services based on the appropriate ranking table of the informed consent recipients, the data services including relationship query services and informed consent recipient verification services.

2. The method for selecting and confirming the recipients of informed consent for patients according to claim 1, characterized in that, Establish an informed consent rule base, specifically as follows: Based on multiple factors including patient age, civil capacity, illness, treatment items, and level of protective treatment, a patient grouping device was constructed to classify patients into groups with full civil capacity, minors without civil capacity, minors with limited civil capacity, patients who cannot recognize their own actions or consequences, patients who are unable to exercise their right to informed choice due to illness, and patients whose situation should not be directly explained to them when implementing protective medical measures. For each patient classification group, a corresponding informed consent target group and its order are defined, forming an informed consent target system table; The informed consent rule base is generated by combining the patient grouper and the informed consent subject system table.

3. The method for selecting and confirming the recipients of informed consent for patients according to claim 1, characterized in that, The information and supporting documents regarding the relationship between the informed consent recipient and the patient, as reported by the informed consent recipient, specifically include: Configure an information declaration template, which includes fields for entering applicant information, entering information about the informed consent recipient, entering patient information, entering information about the relationship with the patient, and uploading supporting documents for proof of the relationship. The information submitted by the applicant is collected through the information declaration template. The information includes: the applicant's information, such as the name of the institution, organization code, person in charge and contact information when the institution applies, or the name, ID information, contact information and address when the individual applies; the identity information of the informed consent recipient includes the name, ID type and number, contact information and level of civil capacity; the patient's information includes the name, medical record number, ID type and number; and the relationship information with the patient includes the relationship type, relationship status and start and end time.

4. The method for selecting and confirming the recipients of informed consent for patients according to claim 3, characterized in that, The consistency between the patient information submitted for verification and the existing patient information of the medical and health institutions is specifically as follows: The patient information submitted by the applicant will be compared with the existing patient information of the medical and health institutions. If the comparison results match, the patient information verification is deemed successful, and the relationship declaration process can continue. If the comparison results are inconsistent, the applicant will be prompted to verify the patient information and resubmit.

5. The method for selecting and confirming the recipients of informed consent for patients according to claim 1, characterized in that, A credibility-based kinship verification method is adopted, specifically as follows: Preset credibility values ​​for different trusted channels; If the obtained verification data comes from a channel with a credibility value ≥ the preset credibility threshold, the relationship verification is deemed qualified when the verification of a single channel passes. If the obtained verification data comes from channels with a credibility value less than the preset credibility threshold, the relationship verification is deemed qualified when at least two such channels pass the verification.

6. The method for selecting and confirming the recipients of informed consent for patients according to claim 2, characterized in that, Generate a suitable sorting table for those to be informed, as follows: Extracting patient medical information from a medical and health diagnosis and treatment information system, the medical information including basic personal information, diagnostic information, and treatment information; The patient's medical information is input into the patient grouper, which automatically determines the patient's classification group. Based on the informed consent recipient system table corresponding to the patient's classification group, and combined with the verified informed consent recipient information, the informed consent recipients are sorted according to the priority order rules to generate an appropriate sorting table for informed consent recipients, which includes the informed consent priority value, recipient's name, ID information, contact information, civil capacity level, and relationship with the patient.

7. The method for selecting and confirming the recipients of informed consent for patients according to claim 1, characterized in that, Provide relationship query service, specifically: Receive externally inputted patient information, informed consent information, and relationship information; The input information is matched with the patient information and verified informed consent information stored in the system. If a match is found, output the result indicating the correct relationship. If the match is inconsistent, output the result indicating an incorrect relationship, and indicate the possible reasons for the error.

8. The method for selecting and confirming the recipients of informed consent for patients according to claim 1, characterized in that, Provide informed consent verification services, specifically: Receives externally inputted patient information, informed consent recipient information, and informed consent order value information; The system queries the appropriate sorting table of informed consent recipients for the patient and determines whether the input informed consent recipient and order value exist in the appropriate sorting table of informed consent recipients. If it does not exist, output the message that the informed object or the order value does not exist; If it exists, verify whether the input order value is consistent with the priority value in the sorting table. If they are consistent, output the correct order. If they are inconsistent, output the incorrect order and the correct priority value.

9. A system for selecting and confirming recipients of informed consent for patients, characterized in that, It includes a processor and a memory, wherein the memory stores a computer program, and when the computer program is executed by the processor, it implements the steps of the method for selecting and confirming the recipient of informed consent as described in any one of claims 1-8.

10. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the method for selecting and confirming the recipients of informed consent as described in any one of claims 1-8.

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