A medical insurance settlement data risk screening and complaint material generation device and method

Abstract

This invention relates to a device and method for risk screening and appeal material generation of medical insurance settlement data, belonging to the field of medical informatization and medical insurance data processing technology. To address the problems of reliance on manual processes, inconsistent procedures, and easy omissions in evidence indexing in medical insurance settlement anomaly screening, appeal basis association, and appeal material generation, this invention reads and parses settlement details returned by the medical insurance bureau, calls medical insurance rules to screen high-risk cases, forms a question-and-answer path based on an appeal-guided decision tree, associates relevant medical insurance policy clauses, fragments of successful appeal cases, and relevant medical record evidence indexes, and generates an appeal explanation. This improves the completeness and standardization of appeal material generation and is applicable to fields such as hospital medical insurance settlement review, preparation of medical insurance refusal appeal materials, and review of suspected medical insurance violations.

Description

Technical Field

[0001] This invention belongs to the field of medical information technology and medical insurance data processing technology, specifically involving a technology for generating appeal materials based on risk screening of medical insurance settlement data, appeal guidance decision tree, and association of medical record evidence index. Background Technology

[0002] With the improvement of intelligent medical insurance review and hospital information management, the review of medical insurance settlement data is gradually evolving from manual verification to rule-based and systematic processing. After completing medical insurance settlement, hospitals typically need to review the settlement details, rejected items, or suspected violations provided by the medical insurance bureau, and prepare appeal materials in conjunction with the patient's medical records, treatment process, and medical insurance policies. This process involves multiple steps, including judging medical insurance rules, finding medical record evidence, organizing appeal basis, and document output, requiring high data processing efficiency and material standardization.

[0003] Existing technologies include systems capable of providing pre-emptive reminders, in-process audits, and post-event monitoring of medical insurance expenses. These systems utilize rule bases, audit engines, or anti-fraud modules to verify medical insurance expenses, medication duration, consumable usage, and treatment items, and alert staff to risks when anomalies are detected. Other solutions incorporate modules for appeals, submission of supporting documents, and feedback of audit results in prescription review, medical insurance violation monitoring, and insurance claim processing to assist in resolving audit disputes.

[0004] However, most of the above solutions focus on cost review, violation monitoring, or risk alerts, typically only addressing the issue of "detecting anomalies." They fail to establish a continuous processing chain from screening high-risk cases to generating appeal materials for the settlement details data returned by the medical insurance bureau. For cases that have already resulted in rejected or suspected violations, staff still need to manually determine the direction of the appeal, search for medical insurance policy clauses, retrieve similar appeal cases, and consult relevant medical record evidence indexes in the Hospital Information System (HIS). The appeal preparation process is easily influenced by personal experience, resulting in low processing efficiency, omission of key evidence, and inconsistent appeal explanation structures.

[0005] Therefore, it is necessary to propose a risk screening and appeal material generation scheme for medical insurance settlement data. This scheme can analyze and screen the settlement details data returned by the medical insurance bureau, identify high-risk cases, record the question-and-answer path through the appeal-guided decision tree, and link relevant medical insurance policy clauses, successful appeal case fragments, and relevant medical record evidence indexes. Finally, it generates and outputs the appeal statement and relevant medical record evidence index, thereby improving the standardization, completeness, and processing efficiency of medical insurance appeal material preparation. Summary of the Invention

[0006] To address the problems of existing medical insurance settlement anomaly screening, appeal basis association, and appeal material generation relying on manual processes, inconsistent procedures, and easy omissions in evidence indexing, this invention proposes the following solution: A device for risk screening and appeal material generation of medical insurance settlement data is disclosed. The device includes a medical insurance data parsing module, a rule base storage chip, a risk screening processor, an interactive interface, and an output module. The medical insurance data parsing module reads settlement detail data returned by the medical insurance bureau and parses the settlement detail data to obtain medical insurance settlement data fields. The rule base storage chip stores medical insurance rules. The risk screening processor is connected to the medical insurance data parsing module, the rule base storage chip, the interactive interface, and the output module, respectively, and is used to call the medical insurance rules to perform risk screening on the medical insurance settlement data fields and identify high-risk cases based on the screening results. The interactive interface includes a tilting touchscreen for displaying the high-risk cases and, after the user selects a high-risk case, displays an appeal guidance decision tree. The risk screening processor is also used to associate relevant medical insurance policy clauses, successful appeal case fragments, and relevant medical record evidence indexes based on the user's question-and-answer path in the appeal guidance decision tree, and generate an appeal description. The output module outputs the appeal description and the relevant medical record evidence index.

[0007] Furthermore, the medical insurance settlement data fields include at least one of the following: case identifier, settlement item, length of hospital stay, consumable usage data, rejected items, or suspected violation items.

[0008] Furthermore, the medical insurance rules include at least one of the rules for short hospital stays and rules for excessive consumables. The risk screening processor is used to mark the corresponding case as a high-risk case when the medical insurance settlement data field matches the medical insurance rules.

[0009] Furthermore, the tilting touchscreen includes a case list display area, an appeal guidance decision tree display area, a yes / no button touch area, and a sidebar display area; the case list display area is used to display the high-risk cases, the appeal guidance decision tree display area is used to display the appeal guidance decision tree, the yes / no button touch area is used to receive the user's selection results for the question and answer node, and the sidebar display area is used to simultaneously display the relevant medical insurance policy clauses and fragments of successful appeal cases.

[0010] Furthermore, the medical insurance data parsing module is also used to connect with the hospital information system and retrieve relevant medical record evidence indexes corresponding to the high-risk cases from the hospital information system according to the question-and-answer path.

[0011] Furthermore, the output module includes a high-speed document printing / packaging unit, which is used to print and bind the appeal statement and the relevant medical record evidence index into an appeal document bag.

[0012] Based on the same inventive concept, this invention also proposes a method for risk screening of medical insurance settlement data and generation of appeal materials. The method includes: S1, reading settlement detail data returned by the medical insurance bureau and parsing the settlement detail data to obtain medical insurance settlement data fields; S2, calling medical insurance rules to perform risk screening on the medical insurance settlement data fields and identifying high-risk cases based on the screening results; S3, displaying the high-risk cases, and after the user selects the high-risk case, displaying the appeal guidance decision tree corresponding to the high-risk case; S4, displaying question and answer nodes sequentially according to the appeal guidance decision tree. The system receives the user's selection results for the question-and-answer nodes, records the high-risk cases, the question-and-answer nodes, and the selection results to form a question-and-answer path; S5, based on the question-and-answer nodes and selection results in the question-and-answer path, it associates the relevant medical insurance policy clauses, successful appeal case fragments, and relevant medical record evidence indexes corresponding to the high-risk cases; S6, based on the high-risk cases, the question-and-answer path, the relevant medical insurance policy clauses, the successful appeal case fragments, and the relevant medical record evidence indexes, it generates an appeal explanation; S7, it outputs the appeal explanation and the relevant medical record evidence indexes.

[0013] Furthermore, the question-and-answer node in S4 includes a question-and-answer node for confirming the reason for the extension of the hospital stay and a question-and-answer node for confirming the record of admission.

[0014] Furthermore, the association of relevant medical insurance policy clauses, successful appeal case fragments, and relevant medical record evidence indexes with the high-risk cases described in S5 includes: determining the corresponding relevant medical insurance policy clauses and successful appeal case fragments based on the question-and-answer nodes in the question-and-answer path, and obtaining the corresponding relevant medical record evidence indexes from the hospital information system based on the high-risk cases.

[0015] Furthermore, the appeal description in S6 includes risk item content, appeal fact content, policy basis content, and evidence index content; the risk item content is determined based on the high-risk case, the appeal fact content is determined based on the question and answer path, the policy basis content is determined based on the relevant medical insurance policy clauses, and the evidence index content is determined based on the relevant medical record evidence index.

[0016] Compared with the prior art, the present invention has the following beneficial effects: The medical insurance data parsing module reads the settlement details data returned by the medical insurance bureau and parses the settlement details data to obtain the medical insurance settlement data fields, so that abnormal medical insurance settlement data can form a screenable data foundation, thereby reducing the omissions caused by manually checking the settlement details item by item.

[0017] By calling the medical insurance rules in the rule base storage chip through the risk screening processor, the medical insurance settlement data fields are screened for risks and high-risk cases are identified. This enables rejected items or suspected violations to be preliminarily located according to the medical insurance rules, thereby improving the accuracy and consistency of high-risk case screening.

[0018] High-risk cases are displayed on a tilting touchscreen, and an appeal guidance decision tree is displayed after the user selects a high-risk case. This allows the appeal processing to proceed according to preset question-and-answer nodes, thereby improving the problem of inconsistent appeal preparation processes.

[0019] By sequentially displaying question-and-answer nodes, receiving selection results, and forming a question-and-answer path according to the appeal guidance decision tree, high-risk cases, question-and-answer nodes, and selection results can be recorded accordingly, thereby providing clear data basis for subsequent appeal basis association and appeal explanation generation.

[0020] By linking relevant medical insurance policy clauses, successful appeal case fragments, and relevant medical record evidence indexes according to the question-and-answer path, the appeal basis and medical record evidence can be matched around high-risk cases, thereby reducing the omissions in manually searching for policy basis and medical record evidence indexes.

[0021] By generating appeal statements based on high-risk cases, Q&A pathways, relevant medical insurance policy clauses, successful appeal case excerpts, and relevant medical record evidence indexes, the appeal statements can include content on risk items, content on the facts of the appeal, content on policy basis, and content on evidence indexes, thereby improving the completeness and standardization of the appeal materials.

[0022] The output module outputs the appeal statement and relevant medical record evidence index, enabling the generated appeal materials to be directly submitted, thereby improving the efficiency of preparing and organizing medical insurance appeal materials.

[0023] This invention has the functions of risk screening of medical insurance settlement data, association of appeal basis and generation of appeal materials, which can improve the completeness, standardization and processing efficiency of medical insurance appeal materials preparation, and is applicable to the fields of hospital medical insurance settlement review, preparation of medical insurance refusal appeal materials, and review of suspected medical insurance violations. Attached Figure Description

[0024] Figure 1 This is a schematic diagram of the internal functional module connections of the device described in the embodiment; Figure 2 This is a flowchart of the method described in the implementation method; Figure 3 This is a schematic diagram showing the interactive interface of the device described in the embodiment. Detailed Implementation

[0025] The technical solutions in the embodiments of the present invention will now be clearly and completely described in conjunction with the accompanying drawings.

[0026] Implementation Method 1 like Figure 1 As shown, a medical insurance settlement data risk screening and appeal material generation device includes a medical insurance data parsing module 11, a rule base storage chip 12, a risk screening processor 13, an interactive interface 14, and an output module 15. The medical insurance data parsing module 11 is used to read the settlement details data returned by the medical insurance bureau and parse the settlement details data to obtain the medical insurance settlement data field; The rule base storage chip 12 is used to store medical insurance rules; The risk screening processor 13 is connected to the medical insurance data parsing module 11, the rule base storage chip 12, the interactive interface 14 and the output module 15 respectively, and is used to call the medical insurance rules to perform risk screening on the medical insurance settlement data fields, and identify high-risk cases based on the screening results. The interactive interface 14 includes a tilted touch screen 141, which is used to display the high-risk cases and display an appeal guidance decision tree after the user selects the high-risk cases. The risk screening processor 13 is also used to associate relevant medical insurance policy clauses, successful appeal case fragments and relevant medical record evidence indexes with the user's question and answer path in the appeal guidance decision tree, and generate an appeal description; The output module 15 is used to output the appeal statement and the relevant medical record evidence index.

[0027] Preferably, the medical insurance data parsing module 11, rule base storage chip 12, risk screening processor 13, interactive interface 14 and output module 15 form a continuous processing link from reading settlement details data, risk screening, appeal guidance to output of appeal materials.

[0028] Through the cooperation of the medical insurance data parsing module 11, rule base storage chip 12, risk screening processor 13, interactive interface 14 and output module 15, the settlement details data returned by the medical insurance bureau can be parsed, screened, guided, associated and output, thereby improving the continuity and standardization of the medical insurance settlement data risk screening and appeal material generation process.

[0029] Furthermore, the medical insurance settlement data fields include at least one of the following: case identifier, settlement item, length of hospital stay, consumable usage data, rejected items, or suspected violation items.

[0030] By parsing settlement details into at least one of the following: case identifier, settlement item, length of hospital stay, consumable usage data, rejected items, or suspected violation items, medical insurance settlement data can form a field basis suitable for risk screening, thereby improving the targeting of subsequent high-risk case identification.

[0031] Furthermore, the medical insurance rules include at least one of the rules for short hospital stays and rules for excessive consumables. The risk screening processor 13 is used to mark the corresponding case as a high-risk case when the medical insurance settlement data field matches the medical insurance rules.

[0032] By calling at least one of the rules for short hospital stays and excessive consumables to screen the medical insurance settlement data fields through the risk screening processor 13, the case identifiers of the medical insurance rules can be marked as high-risk cases, thereby improving the consistency of risk case screening results.

[0033] Furthermore, the tilting touchscreen 141 includes a case list display area 1411, an appeal guidance decision tree display area 1412, a yes / no button touch area 1413, and a sidebar display area 1414; the case list display area 1411 is used to display the high-risk cases, the appeal guidance decision tree display area 1412 is used to display the appeal guidance decision tree, the yes / no button touch area 1413 is used to receive the user's selection result for the question and answer node, and the sidebar display area 1414 is used to simultaneously display the relevant medical insurance policy clauses and fragments of successful appeal cases.

[0034] Preferably, the case list display area 1411, the appeal guidance decision tree display area 1412, the yes / no button touch area 1413, and the sidebar display area 1414 are located in the same tilted touch screen 141, so that high-risk case selection, question and answer node confirmation, and appeal basis viewing can be completed in the same interactive interface 14.

[0035] By partitioning the case list display area 1411, the appeal guidance decision tree display area 1412, the yes / no button touch area 1413, and the sidebar display area 1414, the display of high-risk cases, the display of the appeal guidance decision tree, the selection of question and answer nodes, and the display of relevant medical insurance policy clauses and successful appeal case fragments can all be completed in the same interactive interface 14, thereby improving the clarity of the appeal guidance process.

[0036] Furthermore, the medical insurance data parsing module 11 is also used to connect with the hospital information system and retrieve relevant medical record evidence indexes corresponding to the high-risk cases from the hospital information system according to the question-and-answer path.

[0037] By connecting the medical insurance data parsing module 11 with the hospital information system and retrieving relevant medical record evidence indexes corresponding to high-risk cases based on the question-and-answer path, the appeal explanation generation process can be linked to the medical record evidence indexes, thereby reducing the possibility of missing evidence indexes during the preparation of appeal materials.

[0038] Furthermore, the output module 15 includes a high-speed document printing / packaging unit 151, which is used to print and bind the appeal statement and the relevant medical record evidence index into an appeal document bag.

[0039] The high-speed document printing / packaging unit 151 prints and binds the appeal statement and related medical record evidence index into an appeal document bag, enabling the generated appeal materials to be physically output, thereby improving the efficiency of appeal material organization and output.

[0040] like Figure 2 As shown, based on the same inventive concept, this embodiment also proposes a method for risk screening of medical insurance settlement data and generation of appeal materials, the method comprising: S1. Read the settlement details data returned by the medical insurance bureau and parse the settlement details data to obtain the medical insurance settlement data field; S2. Call the medical insurance rules to perform risk screening on the medical insurance settlement data fields, and identify high-risk cases based on the screening results; S3. Display the high-risk cases, and after the user selects the high-risk cases, display the appeal guidance decision tree corresponding to the high-risk cases; S4. Display the question and answer nodes sequentially according to the appeal guidance decision tree, and receive the selection results input by the user for the question and answer nodes. Record the high-risk cases, the question and answer nodes and the selection results accordingly to form a question and answer path. S5. Based on the question-and-answer nodes and selection results in the question-and-answer path, associate the relevant medical insurance policy clauses, successful appeal case fragments, and relevant medical record evidence indexes corresponding to the high-risk cases; S6. Generate an appeal description based on the high-risk cases, the question-and-answer path, the relevant medical insurance policy clauses, the successful appeal case fragments, and the relevant medical record evidence index; S7. Output the appeal statement and the relevant medical record evidence index.

[0041] By reading settlement details, parsing medical insurance settlement data fields, screening high-risk cases, forming question-and-answer paths, associating relevant medical insurance policy clauses, fragments of successful appeal cases, and relevant medical record evidence indexes, and generating and outputting appeal explanations, the risk screening of medical insurance settlement data and the generation of appeal materials can be carried out in a continuous process, thereby improving the completeness of the appeal material generation process.

[0042] Furthermore, the question-and-answer node in S4 includes a question-and-answer node for confirming the reason for the extension of the hospital stay and a question-and-answer node for confirming the record of admission.

[0043] By setting up question-and-answer nodes to confirm the reasons for extended hospital stays and to confirm the details recorded in the admission records, the question-and-answer path can record selection results related to hospital stays and admission records, thereby providing a basis for generating factual content for subsequent appeals.

[0044] Furthermore, the association of relevant medical insurance policy clauses, successful appeal case fragments, and relevant medical record evidence indexes with the high-risk cases described in S5 includes: determining the corresponding relevant medical insurance policy clauses and successful appeal case fragments based on the question-and-answer nodes in the question-and-answer path, and obtaining the corresponding relevant medical record evidence indexes from the hospital information system based on the high-risk cases.

[0045] By identifying relevant medical insurance policy clauses and successful appeal case fragments based on the question-and-answer nodes in the question-and-answer path, and obtaining corresponding relevant medical record evidence indexes from the hospital information system based on high-risk cases, the policy basis, case fragments, and medical record evidence indexes can be linked around the same high-risk case, thereby improving the completeness of the appeal basis organization.

[0046] Furthermore, the appeal description in S6 includes risk item content, appeal fact content, policy basis content, and evidence index content; the risk item content is determined based on the high-risk case, the appeal fact content is determined based on the question and answer path, the policy basis content is determined based on the relevant medical insurance policy clauses, and the evidence index content is determined based on the relevant medical record evidence index.

[0047] By setting the appeal statement to include risk items, facts of the appeal, policy basis, and evidence index, the appeal statement can be generated corresponding to high-risk cases, Q&A paths, relevant medical insurance policy clauses, and relevant medical record evidence indexes, thereby improving the standardization of the appeal statement's content structure.

[0048] The method described in this embodiment can be executed by a processor calling a computer program, which can be stored in a computer storage medium. When the computer program is executed by the processor, the above-mentioned method for risk screening of medical insurance settlement data and generation of appeal materials can be implemented.

[0049] Implementation Method 2 In this embodiment, the medical insurance settlement data risk screening and appeal material generation device is used to read, parse, perform risk screening, provide appeal guidance, link medical record evidence indexes, and output appeal materials for the settlement details data returned by the medical insurance bureau. The device includes a medical insurance data parsing module 11, a rule base storage chip 12, a risk screening processor 13, an interactive interface 14, and an output module 15. The medical insurance data parsing module 11, rule base storage chip 12, interactive interface 14, and output module 15 are respectively connected to the risk screening processor 13, forming a processing chain from settlement details data parsing, medical insurance rule screening, appeal guidance decision tree display, appeal basis association, to appeal explanation output.

[0050] The medical insurance data parsing module 11 is used to read the settlement details data returned by the medical insurance bureau and parse the settlement details data to obtain medical insurance settlement data fields. The medical insurance settlement data fields include at least one of the following: case identifier, settlement item, length of hospital stay, consumable usage data, rejected items, or suspected violation items. By parsing the settlement details data returned by the medical insurance bureau, the original settlement details data can be converted into field data that can be called and compared by the risk screening processor 13.

[0051] The rule base storage chip 12 stores medical insurance rules, including at least one of the rules regarding short hospital stays and excessive consumables. The risk screening processor 13 calls the medical insurance rules in the rule base storage chip 12 to perform risk screening on the medical insurance settlement data fields parsed by the medical insurance data parsing module 11. When a medical insurance settlement data field matches either the short hospital stay rule or the excessive consumables rule, the risk screening processor 13 marks the corresponding case as a high-risk case. Through this process, the settlement details data returned by the medical insurance bureau can be marked as high-risk cases before entering the appeal preparation process.

[0052] The interactive interface 14 includes a tilted touchscreen 141. The tilted touchscreen 141 displays the high-risk cases and, after the user selects a high-risk case, displays an appeal guidance decision tree. The tilted touchscreen 141 includes a case list display area 1411, an appeal guidance decision tree display area 1412, a yes / no button touch area 1413, and a sidebar display area 1414. The case list display area 1411 displays high-risk cases; the appeal guidance decision tree display area 1412 displays the appeal guidance decision tree; the yes / no button touch area 1413 receives the user's selection result for the question-and-answer node; and the sidebar display area 1414 simultaneously displays relevant medical insurance policy clauses and excerpts of successful appeal cases. The display content and area distribution of the interactive interface 14 are as follows: Figure 3 As shown.

[0053] After a user selects a high-risk case, the tilting touchscreen 141 displays an appeal guidance decision tree corresponding to the high-risk case. The appeal guidance decision tree sequentially displays question-and-answer nodes, and receives the user's selection results for the question-and-answer nodes via the yes / no button touch area 1413. The question-and-answer nodes include those for confirming the reasons for prolonged hospital stay and those for confirming the information recorded in the admission record. The risk screening processor 13 records the high-risk case, the question-and-answer nodes, and the selection results to form a question-and-answer path.

[0054] The risk screening processor 13 associates relevant medical insurance policy clauses, successful appeal case fragments, and relevant medical record evidence indexes with the high-risk cases based on the question-and-answer nodes and selection results in the question-and-answer path. Specifically, it determines the corresponding relevant medical insurance policy clauses and successful appeal case fragments based on the question-and-answer nodes in the question-and-answer path, and retrieves the corresponding relevant medical record evidence indexes from the hospital information system based on the high-risk cases. The relevant medical insurance policy clauses and successful appeal case fragments can be simultaneously displayed in the sidebar display area 1414, and the relevant medical record evidence indexes are used to generate appeal explanations subsequently.

[0055] The risk screening processor 13 generates an appeal statement based on the high-risk cases, the question-and-answer path, the relevant medical insurance policy clauses, the successful appeal case fragments, and the relevant medical record evidence index. The appeal statement includes risk item content, appeal fact content, policy basis content, and evidence index content; the risk item content is determined based on the high-risk cases, the appeal fact content is determined based on the question-and-answer path, the policy basis content is determined based on the relevant medical insurance policy clauses, and the evidence index content is determined based on the relevant medical record evidence index.

[0056] Output module 15 is used to output the appeal statement and the relevant medical record evidence index. Output module 15 includes a high-speed document printing / packaging unit 151, which is used to print and bind the appeal statement and the relevant medical record evidence index into an appeal document bag. After being output through output module 15, the appeal statement and the relevant medical record evidence index can be organized as appeal materials.

[0057] In this embodiment, the method for risk screening of medical insurance settlement data and generation of appeal materials includes: S1, reading the settlement details data returned by the medical insurance bureau and parsing the settlement details data to obtain medical insurance settlement data fields; S2, calling medical insurance rules to perform risk screening on the medical insurance settlement data fields and identifying high-risk cases based on the screening results; S3, displaying the high-risk cases, and after the user selects the high-risk cases, displaying the appeal guidance decision tree corresponding to the high-risk cases; S4, displaying question and answer nodes sequentially according to the appeal guidance decision tree, receiving the selection results input by the user for the question and answer nodes, and recording the high-risk cases, the question and answer nodes, and the selection results accordingly to form a question and answer path; S5, associating the relevant medical insurance policy clauses, successful appeal case fragments, and relevant medical record evidence indexes corresponding to the high-risk cases based on the question and answer nodes and selection results in the question and answer path; S6, generating an appeal description based on the high-risk cases, the question and answer path, the relevant medical insurance policy clauses, the successful appeal case fragments, and the relevant medical record evidence indexes; S7, outputting the appeal description and the relevant medical record evidence indexes.

[0058] In this embodiment, the question-and-answer node in S4 includes a question-and-answer node for confirming the reason for the extended hospital stay and a question-and-answer node for confirming the admission record. The association of the relevant medical insurance policy clauses, successful appeal case fragments, and relevant medical record evidence indexes corresponding to the high-risk case in S5 includes: determining the corresponding relevant medical insurance policy clauses and successful appeal case fragments based on the question-and-answer nodes in the question-and-answer path, and obtaining the corresponding relevant medical record evidence indexes from the hospital information system based on the high-risk case. The appeal description in S6 includes risk item content, appeal fact content, policy basis content, and evidence index content; the risk item content is determined based on the high-risk case, the appeal fact content is determined based on the question-and-answer path, the policy basis content is determined based on the relevant medical insurance policy clauses, and the evidence index content is determined based on the relevant medical record evidence index.

[0059] The above description is merely a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. For those skilled in the art, reasonable modifications, equivalent substitutions, or improvements made to the above embodiments without departing from the technical concept of the present invention should all fall within the scope of protection of the present invention.

Claims

1. A device for risk screening of medical insurance settlement data and generation of appeal materials, characterized in that, The device includes a medical insurance data parsing module (11), a rule base storage chip (12), a risk screening processor (13), an interactive interface (14), and an output module (15). The medical insurance data parsing module (11) is used to read the settlement details data returned by the medical insurance bureau and parse the settlement details data to obtain the medical insurance settlement data field; The rule base storage chip (12) is used to store medical insurance rules; The risk screening processor (13) is connected to the medical insurance data parsing module (11), the rule base storage chip (12), the interactive interface (14) and the output module (15) respectively, and is used to call the medical insurance rules to perform risk screening on the medical insurance settlement data fields, and identify high-risk cases according to the screening results; The interactive interface (14) includes a tilted touch screen (141), which is used to display the high-risk cases and display an appeal guidance decision tree after the user selects the high-risk cases. The risk screening processor (13) is also used to associate relevant medical insurance policy clauses, successful appeal case fragments and relevant medical record evidence indexes with the user's question and answer path in the appeal guidance decision tree, and generate an appeal description; The output module (15) is used to output the appeal statement and the relevant medical record evidence index.

2. The apparatus according to claim 1, characterized in that, The medical insurance settlement data fields include at least one of the following: case identifier, settlement item, length of hospital stay, consumable usage data, rejected items, or suspected non-compliant items.

3. The apparatus according to claim 2, characterized in that, The medical insurance rules include at least one of the rules for short hospital stays and the rules for excessive consumables. The risk screening processor (13) is used to mark the corresponding case as a high-risk case when the medical insurance settlement data field matches the medical insurance rules.

4. The apparatus according to claim 1, characterized in that, The tilting touchscreen (141) includes a case list display area (1411), an appeal guidance decision tree display area (1412), a yes / no button touch area (1413), and a sidebar display area (1414). The case list display area (1411) is used to display the high-risk cases, the appeal guidance decision tree display area (1412) is used to display the appeal guidance decision tree, the yes / no button touch area (1413) is used to receive the user's selection result for the question and answer node, and the sidebar display area (1414) is used to simultaneously display the relevant medical insurance policy clauses and fragments of successful appeal cases.

5. The apparatus according to claim 1, characterized in that, The medical insurance data parsing module (11) is also used to connect with HIS and retrieve relevant medical record evidence indexes corresponding to the high-risk cases from HIS according to the question-and-answer path.

6. The apparatus according to claim 1, characterized in that, The output module (15) includes a high-speed document printing / packaging unit (151), which is used to print and bind the appeal statement and the relevant medical record evidence index into an appeal document bag.

7. A method for risk screening of medical insurance settlement data and generation of appeal materials, characterized in that, The method includes: S1. Read the settlement details data returned by the medical insurance bureau and parse the settlement details data to obtain the medical insurance settlement data field; S2. Call the medical insurance rules to perform risk screening on the medical insurance settlement data fields, and identify high-risk cases based on the screening results; S3. Display the high-risk cases, and after the user selects the high-risk cases, display the appeal guidance decision tree corresponding to the high-risk cases; S4. Display the question and answer nodes sequentially according to the appeal guidance decision tree, and receive the selection results input by the user for the question and answer nodes. Record the high-risk cases, the question and answer nodes and the selection results accordingly to form a question and answer path. S5. Based on the question-and-answer nodes and selection results in the question-and-answer path, associate the relevant medical insurance policy clauses, successful appeal case fragments, and relevant medical record evidence indexes corresponding to the high-risk cases; S6. Generate an appeal description based on the high-risk cases, the question-and-answer path, the relevant medical insurance policy clauses, the successful appeal case fragments, and the relevant medical record evidence index; S7. Output the appeal statement and the relevant medical record evidence index.

8. The method according to claim 7, characterized in that, The question-and-answer nodes mentioned in S4 include question-and-answer nodes for confirming the reasons for the extension of the hospital stay and question-and-answer nodes for confirming the information recorded in the admission record.

9. The method according to claim 7, characterized in that, S5, which associates the relevant medical insurance policy clauses, successful appeal case fragments, and relevant medical record evidence indexes with the high-risk cases, includes: determining the corresponding relevant medical insurance policy clauses and successful appeal case fragments based on the question and answer nodes in the question and answer path, and obtaining the corresponding relevant medical record evidence indexes from the HIS based on the high-risk cases.

10. The method according to claim 7, characterized in that, The appeal description in S6 includes risk item content, appeal fact content, policy basis content, and evidence index content; the risk item content is determined based on the high-risk case, the appeal fact content is determined based on the question and answer path, the policy basis content is determined based on the relevant medical insurance policy clauses, and the evidence index content is determined based on the relevant medical record evidence index.

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