A medical labor point calculation method and system based on RBRVS and DRGDIP fusion
Patent Information
- Application Number
- CN202611182416.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-08-05
- Publication Date
- 2026-10-30
Smart Images
Figure CN123017395A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of medical data processing technology, and in particular to a method and system for calculating medical labor points based on the integration of RBRVS and DRGDIP. Background Technology
[0002] With the continuous advancement of performance management in public hospitals, the construction of medical informatization, and the reform of DRG / DIP medical insurance payment methods, the evaluation of medical labor value has gradually evolved from the traditional revenue and expenditure surplus accounting model to a refined management model that relies on medical records, medical insurance settlement lists, and treatment item execution records to measure workload. Especially against the backdrop of increasingly detailed medical service items, a continuous increase in difficult and severe cases, and the collaborative participation of multiple professional families such as physicians, nurses, medical technicians, and pharmacists in diagnosis and treatment, the medical labor point calculation system no longer only undertakes the function of statistically counting the number of items, but has gradually evolved into a comprehensive evaluation tool that integrates item value standardization, professional family labor breakdown, medical record workload collection, and disease value correction. Existing related technologies usually use the RBRVS work relative value unit to evaluate the labor intensity, technical difficulty, and risk level of treatment items, or use DRG relative weights, CMI, and DIP disease scores to measure the difficulty of case combinations and the level of disease resource consumption. Some solutions also introduce CCHI operation point values to localize RBRVS items to assist medical institutions in carrying out departmental and professional family workload accounting. Overall, healthcare labor point calculation technology is evolving from simple item counting and income-related accounting to a holistic evaluation that integrates item value, disease value, and multi-career labor contribution. However, existing technologies still have shortcomings when integrating RBRVS and DRG / DIP for healthcare labor point calculation. Most schemes directly multiply or sum the RBRVS item points with the relative weights of DRG or the disease scores of DIP without unifying the hierarchical role and numerical scale of the two evaluation systems. This can easily lead to double-counting of disease weights and uncontrolled total points over the calculation period. At the same time, item points lack conservation and splitting mechanisms and case-level aggregation mechanisms among physician, nurse, medical technology, and pharmacy career lines, making it difficult to accurately reflect the actual labor contribution of different career lines within a single medical record. Summary of the Invention
[0003] In view of the aforementioned existing problems, the present invention is proposed.
[0004] Therefore, this invention provides a method and system for calculating medical labor points based on the integration of RBRVS and DRG / DIP, which solves the problems in existing medical labor point calculations such as inconsistent levels of the value of RBRVS projects and the value of DRG / DIP diseases, inconsistent numerical scales of different evaluation systems, inaccurate division of occupational labor contributions, and loss of control over the total number of points after disease correction.
[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution:
[0006] In a first aspect, the present invention provides a method for calculating medical service points based on the fusion of RBRVS and DRGDIP, which includes,
[0007] Collect multi-source medical data to form a unified project execution dataset;
[0008] Based on multi-source medical data, a mapping between in-hospital projects and RBRVS and CCHI standard projects is established, and RBRVS and CCHI parameters are integrated to generate standard workload scores.
[0009] Set the weight of project categories, calculate the basic points of job series based on the standard workload score, collect the basic labor points of job series, calculate the total basic labor points of medical records and the contribution ratio of each job series;
[0010] Based on DRG / DIP disease value calculations using multi-source medical data, disease correction factors are calculated, and the final disease correction coefficient is further calculated. Combined with the basic labor points of each occupational series, the final labor points of each occupational series are calculated and the total amount is calibrated.
[0011] As a preferred embodiment of the medical labor point calculation method based on the fusion of RBRVS and DRGDIP described in this invention, wherein: the collection of multi-source medical data to form a unified project execution dataset refers to obtaining the basic data for medical labor point calculation;
[0012] Screen formally settled medical records and establish a unique identifier for each record;
[0013] For the The first case in the medical record Each project has a count of completed items. Number of cancellations and the amount of refund And determine the effective execution quantity. ;
[0014] Merge records of the same medical case and the same project, and output a unified project execution dataset.
[0015] As a preferred embodiment of the medical labor points calculation method based on the fusion of RBRVS and DRGDIP described in this invention, the step of establishing the mapping between in-hospital items and RBRVS and CCHI standard items based on multi-source medical data refers to constructing an RBRVS candidate set and a CCHI candidate set, and forming a candidate standard item set.
[0016] The names and connotations of projects within the institute in the unified project execution dataset, as well as the names and connotations of projects in the candidate standard project set, are segmented and semantically encoded to obtain name semantic vectors and connotation semantic vectors.
[0017] Computer Institute Projects With candidate standard projects Overall similarity ;
[0018] First and second candidate projects are selected from the RBRVS candidate set and CCHI candidate set according to the comprehensive similarity from high to low. The corresponding comprehensive similarity is recorded. Then, the candidate projects that meet the requirements are screened to establish a mapping with the projects within the institute, and the working RVU of the RBRVS project is output. Operation point values in CCHI projects Human resource consumption value Technical difficulty value and risk level value .
[0019] As a preferred embodiment of the medical labor points calculation method based on the fusion of RBRVS and DRGDIP described in this invention, the fusion of RBRVS and CCHI parameters refers to calculating the median RBRVS working RVU for each item category in the basic data using the established mapping relationship. Median of CCHI operation point values Median CCHI labor consumption value Median technical difficulty value of CCHI Median CCHI risk level value ;
[0020] For the For each project within the institute, calculate the relative value of the CCHI operation point. Relative value of human resource consumption Relative value of technical difficulty Relative value of risk level ;
[0021] Based on the relative value of CCHI operation point Relative value of human resource consumption Relative value of technical difficulty Relative value of risk level Calculate the first CCHI Localization Value Index of Each Project .
[0022] As a preferred embodiment of the medical labor points calculation method based on the fusion of RBRVS and DRGDIP described in this invention, wherein: the generated standard workload score refers to the work RVU of the RBRVS project. Calculate the first and corresponding median. RBRVS relative value of each project ;
[0023] According to the CCHI Localization Value Index of Each Project Relative value of RBRVS Calculate the standard workload score .
[0024] As a preferred embodiment of the medical labor points calculation method based on the fusion of RBRVS and DRGDIP described in this invention, wherein: setting the weight of item category and calculating the basic points of the job series in combination with the standard workload score refers to setting the weight of item category a to the performing job series k. ;
[0025] For each project category a, perform a job family weight check. Calculate the base points for projects that meet the conditions; otherwise, stop the calculation for that project category.
[0026] Based on the project's standard workload score, the number of effective executions, and the weight assigned to the execution job series k. Calculate the first The first case The project was assigned to the first Project career base points for each career family .
[0027] As a preferred embodiment of the medical labor point calculation method based on the fusion of RBRVS and DRGDIP described in this invention, the following steps are taken: The collection of basic labor points by job category, the calculation of the total basic labor points for medical records, and the contribution ratio of each job category refer to designing an effective set of treatment items based on the basic labor points of each job category. ;
[0028] According to the collection of effective medical procedures And the calculation of basic points of the job series The first case Basic labor points for each job category ;
[0029] Based on basic labor points Calculate the first Basic total labor points for each medical record ;
[0030] Based on basic labor points and basic total labor points Calculate the first The first case Contribution ratio of each job series .
[0031] As a preferred embodiment of the medical service point calculation method based on the fusion of RBRVS and DRGDIP described in this invention, the disease correction factor for calculating the DRG / DIP disease value based on multi-source medical data refers to establishing DRG and DIP disease benchmark values respectively according to the payment patterns in the basic data. ;
[0032] Based on disease-specific benchmarks Calculate the first Relative disease value of medical records ;
[0033] Set upper and lower limits for disease-specific adjustments and a disease-specific value compression coefficient, and calculate the first disease based on the relative disease-specific value of the medical records. Initial disease correction factor for the medical records .
[0034] As a preferred embodiment of the medical labor point calculation method based on the fusion of RBRVS and DRGDIP described in this invention, the further calculation of the final disease type correction coefficient and the calculation of the final labor point for each occupational category in conjunction with the occupational category basic labor point, and the total amount conservation calibration, refers to constructing an effective medical record set for the payment model within the current calculation period. ;
[0035] Calculate the total amount conservation calibration coefficient corresponding to the payment mode. ;
[0036] Based on the initial disease correction factor and total amount conservation calibration coefficient Calculate the first Final disease correction coefficient for each medical record ;
[0037] Further combine the calculation of the basic labor points of the job series to determine the first The first case Final medical labor points for each job category ;
[0038] The total amount of the final verification and calculation cycle is conserved.
[0039] Secondly, this invention provides a medical staff labor point calculation system based on the integration of RBRVS and DRGDIP, comprising:
[0040] The data acquisition module is used to collect medical records, medical insurance settlements, treatment items and occupational data, screen formally settled medical records and calculate the number of effective executions of items to form a unified project execution dataset;
[0041] The project mapping module is used to construct the RBRVS candidate set and the CCHI candidate set, calculate the comprehensive similarity between in-house projects and candidate standard projects, and establish the mapping relationship between in-house projects and RBRVS projects and CCHI projects.
[0042] The point value standardization module is used to calculate the median of the RBRVS and CCHI parameters for each project category, and generate the standard workload score for the project based on the relative value of RBRVS and the CCHI localization value index.
[0043] The job family breakdown module is used to set the weights of physician, nurse, medical technology and pharmacy job families according to project category, and calculate the basic points of the project job family by combining the standard workload score and the number of effective executions.
[0044] The medical record collection module is used to construct a set of effective diagnosis and treatment items by medical record number, collect the basic points of each job category, and calculate the total basic labor points of medical records and the contribution ratio of each job category.
[0045] The point correction module is used to establish DRG and DIP disease baseline values respectively, calculate the relative disease value of medical records, the initial disease correction factor and the total conservation calibration coefficient, generate the final medical labor points for each job series and perform total conservation verification.
[0046] The beneficial effects of this invention are as follows: By collecting multi-source medical data and forming a unified project execution dataset, this invention achieves unified association of medical records, treatment items, job series, and medical insurance settlement data; by establishing a mapping relationship between in-hospital projects and RBRVS and CCHI standard projects, it realizes the localization and standardization of project labor value; by splitting job series basic points according to project category weights and performing case-level aggregation, it realizes the structured expression of labor contribution of different job series; by calculating DRG / DIP disease correction factors and total amount conservation calibration coefficients, it reflects the differences in disease value while maintaining the stability of job series contribution ratio and total points in the calculation cycle, ultimately improving the accuracy, comparability, and traceability of medical labor point calculation. Attached Figure Description
[0047] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0048] Figure 1 This is a flowchart of the medical labor points calculation method based on the fusion of RBRVS and DRGDIP in Example 1.
[0049] Figure 2This is a structural diagram of the medical labor point calculation system based on the fusion of RBRVS and DRGDIP in Example 1. Detailed Implementation
[0050] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
[0051] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.
[0052] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.
[0053] Example 1, referring to Figure 1 and Figure 2 This is the first embodiment of the present invention, which provides a method for calculating medical service points based on the fusion of RBRVS and DRGDIP, including the following steps:
[0054] S1. Collect multi-source medical data to form a unified project execution dataset;
[0055] Obtain basic data for calculating medical labor points, including medical record number, discharge date, and discharge department; obtain payment mode, DRG disease group code, DRG relative weight (RW), DIP disease code, DIP disease score, and formal settlement indicator from the medical insurance settlement list; obtain project codes, project names, project categories, project content, execution quantity, execution status, business serial number, executing department, and executing job series from HIS, electronic medical records, nursing, LIS, PACS, and manual anesthesia systems; department codes, job codes, and job series categories from the human resources system; project codes, project names, and work RVUs from the RBRVS benchmark table; and project codes, project names, operation point values, manpower consumption values, technical difficulty values, and risk level values from the CCHI benchmark table.
[0056] To screen formally settled medical records, first read all discharged medical records within the current calculation period, and only retain medical records marked as "settled". For DRG model medical records, they must have both DRG disease group code and a relative weight RW greater than 0; for DIP model medical records, they must have both DIP disease code and a disease score greater than 0.
[0057] A unique identifier is established for each medical record, using the medical record number as the unique identifier. This identifier links project execution records, medical insurance settlement results, and discharge information to the same medical record. It should be noted that the discharge information record consists of the medical record number, discharge date, and discharge department obtained from the medical record management system; the medical insurance settlement result consists of the medical record number, payment mode, DRG disease group code, DRG relative weight (RW), DIP disease code, DIP disease score, and formal settlement flag obtained from the medical insurance settlement list; and the project execution record consists of the medical record number, project code, project name, project category, execution quantity, execution status, business serial number, executing department, and executing job series obtained from HIS, electronic medical records, nursing, LIS, PACS, and manual anesthesia systems.
[0058] For the The first case in the medical record Each project has a count of completed items. Number of cancellations and the amount of refund And determine the effective execution quantity. :
[0059]
[0060] in, The effective execution quantity used for subsequent point calculations; when When, delete the record for that project; when At that time, retain the project and its effective execution count;
[0061] Merging records of the same medical case and the same project: For multiple valid records of the same medical case, the same project code, the same project category, and the same performing job series, the number of valid executions will be added together to form a single medical case project summary record. For example, if there are 4 Level II nursing completion records for the same medical case, a single Level II nursing summary record with 4 valid executions will be formed, instead of repeatedly saving 4 sets of basic project data.
[0062] Output a unified project execution dataset. Each data entry should include at least: medical record number, payment method, DRG disease group code and RW, or DIP disease code and disease score, in-hospital project code, project name, project category, project content, and number of valid executions. , Execution Department, Execution Job Series.
[0063] S2. Establish a mapping between in-house projects and RBRVS and CCHI standard projects;
[0064] Construct the RBRVS candidate set and the CCHI candidate set, and form a candidate standard project set; specifically, select standard projects with the same project category as the institute's projects from the RBRVS benchmark table and the CCHI benchmark table, form the RBRVS candidate set from the standard projects selected from the RBRVS benchmark table, form the CCHI candidate set from the standard projects selected from the CCHI benchmark table, merge the two candidate sets to form a candidate standard project set, and read the project name and project content of each candidate standard project.
[0065] The names and connotations of projects within the institute and those in the candidate standard project set from the unified project execution dataset are segmented and semantically encoded to obtain name semantic vectors and connotation semantic vectors, respectively. Specifically, after terminology unification and WordPiece segmentation of the text in the names, connotations, and candidate standard project sets, the text is input into the BERT model for semantic encoding to obtain context hidden vectors, which are then averaged and normalized to obtain name semantic vectors and connotation semantic vectors for projects within the institute and for candidate standard projects. It should be noted that terminology unification involves converting full-width characters in project names and connotations to half-width characters, unifying English letters to lowercase, and removing extra spaces. Repeated punctuation marks are removed, and the longest term priority principle is used to replace abbreviations and synonyms with standard terms. The WordPiece vocabulary that BERT comes with is used to perform longest matching starting from the beginning of the text, splitting the text into words that the model can recognize. The words are then labeled with beginning and end tags to form word sequences that are input into the BERT model. The BERT model mainly consists of an input embedding layer and a multi-layer bidirectional Transformer encoder. The input embedding layer converts word numbers, text positions, and text segment types into vectors. Subsequently, the 12-layer Transformer encoder processes the bidirectional contextual relationships between words through a 12-head self-attention mechanism, a feedforward neural network, residual connections, and layer normalization, and finally outputs a contextual hidden vector for each word.
[0066] Computer Institute Projects With candidate standard projects Overall similarity :
[0067]
[0068] in, For comprehensive similarity; and These are the semantic vectors of the names of projects within the institute and candidate projects, respectively. and These are the semantic vectors of the project connotations of the two entities, respectively. Indicates cosine similarity; This is a category consistency indicator; it is set to 1 if the categories match, and 0 otherwise. Indicates the first Project categories for projects within the hospital, Indicates the first The project categories of the candidate standard projects; , and The weights are respectively based on name, connotation, and category, with the preferred option being... This approach balances name accuracy and project content differences. The name weight is set at 0.55 because the project name is the most stable field in actual project mapping. The project content weight is set at 0.35 to distinguish projects with similar names but different operational content. The project category weight is set at 0.10 to further eliminate cross-category erroneous mappings.
[0069] First and second candidate projects are selected from the RBRVS candidate set and CCHI candidate set according to the comprehensive similarity from high to low. The corresponding comprehensive similarity is recorded. Then, the candidate projects that meet the requirements are screened to establish a mapping with the projects within the institute, and the working RVU of the RBRVS project is output. Operation point values in CCHI projects Human resource consumption value Technical difficulty value and risk level value In the RBRVS candidate set, candidate items are ranked from highest to lowest based on their overall similarity, and the item with the highest similarity is designated as the first RBRVS candidate item. Their similarity is denoted as The item with the second highest similarity was designated as the second RBRVS candidate item. Their similarity is denoted as Following the same method, the first CCHI candidate project was determined from the CCHI candidate set. Second CCHI candidate project and their similarity , When the first candidate project of RBRVS simultaneously meets the following conditions: At that time, the projects within the hospital With the first RBRVS candidate project Establish mapping relationship; when CCHI first candidate item simultaneously meets the following conditions... At that time, the projects within the hospital With the first CCHI candidate project A mapping relationship is established, where 0.90 is the minimum automatic mapping similarity to ensure that the two projects are highly consistent in name and content, and 0.05 is the candidate advantage threshold to ensure that the first candidate project has a clear advantage over the second candidate project. Only when both the RBRVS mapping conditions and the CCHI mapping conditions are met is the project within the institute determined to be successfully automatically mapped, and the working RVU is read from the corresponding RBRVS project. Read the operation point value from the corresponding CCHI project. Human resource consumption value Technical difficulty value and risk level value ;
[0070] It should be noted that establishing a mapping relationship means permanently associating the in-hospital item code with the successfully matched RBRVS item code and CCHI item code. For example, the in-hospital item code for "laparoscopic cholecystectomy" is... The matched RBRVS project code is The CCHI project code is This will create a record: This indicates that you will be able to access projects within the hospital in the future. At that time, directly query the RBRVS project based on the mapping relationship. RVU work And search for CCHI projects Operation point value Human resource consumption value Technical difficulty value and risk level value .
[0071] S3. Integrate RBRVS and CCHI parameters to generate standard workload scores;
[0072] In the basic data, item category a is fixed and includes surgical procedures, diagnostic examinations, comprehensive treatment, basic nursing care, and pharmaceutical services;
[0073] For each item category in the base data, the median RVU of the RBRVS working data is calculated using the established mapping relationship. Median of CCHI operation point values Median CCHI labor consumption value Median technical difficulty value of CCHI Median CCHI risk level value ;
[0074] For the For each project within the institute, calculate the relative value of the CCHI operation point. Relative value of human resource consumption Relative value of technical difficulty Relative value of risk level :
[0075] It should be noted that, This represents the project category of the j-th project within the institute;
[0076] Based on the relative value of CCHI operation point Relative value of human resource consumption Relative value of technical difficulty Relative value of risk level Calculate the first CCHI Localization Value Index of Each Project :
[0077]
[0078] in, , , and The weights for CCHI operation point value, manpower consumption, technical difficulty, and risk level are respectively selected, with the following being the preferred values: CCHI operation point value is a comprehensive evaluation result of the labor value of medical projects, which can reflect the service intensity of the project as a whole, and therefore it is given the highest weight. The human resource consumption value directly reflects the number of personnel, operation time and labor input required for project implementation, and is directly related to the purpose of medical labor points calculation; The technical difficulty value reflects the project's requirements for professional knowledge, operational skills, and clinical judgment, and is used to enhance the value of complex medical projects, but it cannot replace actual labor input. The risk level value reflects the medical risks borne by medical staff during the implementation of the project. It is an additional correction factor and therefore has the lowest weight to prevent high-risk projects from receiving excessive points simply because of their high risk.
[0079] According to the work of the RBRVS project, RVU Calculate the first and corresponding median. RBRVS relative value of each project :
[0080]
[0081] in, This indicates that the RBRVS labor value of this project is equal to the average level of standard projects in the same category;
[0082] According to the CCHI Localization Value Index of Each Project Relative value of RBRVS Calculate the standard workload score :
[0083]
[0084] in, This is the standard scaling factor, preferably set to 100. It is only used to make the standard item points easier to read and does not change the relative relationship between items. The RBRVS contribution coefficient is selected by preference. At this point, the relative value of RBRVS and the CCHI localization value index have the same effect. Increasing the value makes the calculation results closer to the original RBRVS system. The calculation results are more dependent on CCHI localized parameters. Using the same weights can simultaneously retain the horizontal comparison capability between RBRVS projects and the domestic adaptability of CCHI.
[0085] S4. Set the weight of project categories and calculate the basic points of job families in combination with the standard workload score;
[0086] Assign a weight to project category 'a' to the executive job family 'k'. ;Specifically, Representing the physician, nurse, medical technician, and pharmacist job categories, the preferred weighting for surgical procedures is: Physician 0.60, Nursing 0.30, Medical Technician 0.10, Pharmacist 0. Physicians, responsible for surgical procedure selection, key operations, and intraoperative decisions, receive the highest weighting. Nurses, responsible for preoperative preparation, instrument coordination, and intraoperative nursing, have a higher workload and receive 0.30. Medical technicians primarily provide equipment operation or monitoring support and receive 0.10. Pharmacists typically do not directly participate in surgical procedures and receive 0. For diagnostic examinations, the preferred weighting is: Physician 0.20, Nursing 0.10, Medical Technician 0.70, Pharmacist 0. Medical technicians, primarily responsible for sample testing, image acquisition, equipment operation, and quality control, are the main implementers of this category and receive 0.70. Physicians, responsible for examination requests, indication assessment, and result interpretation, receive 0.20. Nurses, responsible for patient preparation, cooperation, and observation, receive 0.10. Pharmacists do not directly participate in general diagnostic examinations and receive 0. For comprehensive treatment, the preferred weighting is: Physician 0.50, Nursing 0.50. 0. Both medical technology and pharmacy are 0. These projects are typically handled by physicians who develop treatment plans and make technical judgments, while nurses continuously implement treatment, observe responses, and record results. Direct labor input from both job categories is indispensable, therefore, they are allocated equally. Basic nursing care is preferably assigned as follows: Physicians 0.15, Nurses 0.85, Medical technology and pharmacy 0. Nurses directly and continuously perform basic nursing procedures, hence 0.85. Physicians are responsible for issuing prescriptions, determining nursing levels, and handling abnormal situations, hence 0.15. Medical technology and pharmacy personnel typically do not directly implement basic nursing care, hence 0. Pharmaceutical services are preferably assigned as follows: Physicians 0.20, Nurses 0.05, Medical technology 0, Pharmacy 0.75. Pharmacy personnel are responsible for prescription review, medication dispensing, medication evaluation, and pharmaceutical monitoring, making them the primary implementing job category, hence 0.75. Physicians are responsible for developing and adjusting medication plans, hence 0.20. Nurses handle a small amount of medication verification or execution, hence 0.05. Medical technology personnel typically do not directly participate in pharmaceutical services, hence 0.
[0087] For each project category 'a', perform a job family weight check. Calculate the base points for projects that meet the criteria; otherwise, stop calculating the weights for that project category. Specifically, for each project category... Test assigned to the first The weight of each job category is calculated. For project categories whose sum of weights equals 1, the basic points of the job category are calculated. Otherwise, the calculation of the project category is stopped.
[0088] Based on the project's standard workload score, the number of effective executions, and the weight assigned to the execution job series k. Calculate the first The first case The project was assigned to the first Project career base points for each career family :
[0089]
[0090] in, This represents the standard workload score for the project. For the effective execution quantity; Assign the category to which this project belongs to the first The weight of each job family; for example, the standard workload score for a certain surgical procedure. Valid execution count Then, the physician, nurse and medical technician professions will receive 72 points, 36 points and 12 points respectively, and their sum will still be 120 points.
[0091] S5. Collect the basic labor points for each job series, calculate the total basic labor points for medical records and the contribution ratio of each job series;
[0092] Design an effective set of diagnostic and treatment items based on occupational family base points. Specifically, they are grouped according to medical record number, starting from the first... Extract unique in-hospital item codes from all records corresponding to each medical record. Items with at least one occupational family base point greater than 0 are grouped into a valid set of diagnostic and treatment items for that medical record. ;
[0093] According to the collection of effective medical procedures And the calculation of basic points of the job series The first case Basic labor points for each job category :
[0094]
[0095] in, The number of basic labor points for the medical record job series; This refers to the base points for the project's job family;
[0096] Based on basic labor points Calculate the first Basic total labor points for each medical record :
[0097]
[0098] in, This indicates the total basic labor volume after localization, standardization, and job series breakdown of all valid treatment items in the medical record; if This indicates that the medical record has no calculable valid items, and the medical record will be added to the abnormal list;
[0099] Based on basic labor points and basic total labor points Calculate the first The first case Contribution ratio of each job series :
[0100]
[0101] in, Indicates the first The proportion of basic labor contribution of each occupational family in this case, due to The sum of the base points for all job categories is equal to 1, therefore the sum of the contribution ratios of each job category for the same case is equal to 1.
[0102] S6. Calculate the disease correction factor based on the DRG / DIP disease value of multi-source medical data, further calculate the final disease correction coefficient, and combine it with the basic labor points of the occupational series to calculate the final labor points of each occupational series and perform total conservation calibration.
[0103] Based on the payment patterns in the basic data, establish DRG and DIP disease benchmarks respectively. Specifically, let the payment mode be... ,in or For DRG mode, the relative weight (RW) of each medical record is read; for DIP mode, the disease score of each medical record is read. The median disease value of medical records under the same payment mode is recorded as... ,in, It is the median of the historical DRG case recovery time (RW). It is the median of the disease category scores in historical DIP medical records; it should be noted that DRG and DIP are calculated separately because the numerical scales of RW and DIP disease category scores are different and cannot be directly put into the same benchmark system.
[0104] Based on disease-specific benchmarks Calculate the first Relative disease value of medical records :
[0105]
[0106] in, For the first The original disease value of the medical records; when hour, Take the medical record RW, when hour, Take the DIP disease score from this medical record; The median for the same payment pattern; when At that time, it indicated that the disease value of the case was consistent with the historical average. This indicates that the value of the disease is higher than the historical average. This indicates a level below the historical average.
[0107] Set upper and lower limits for disease-specific adjustments and a disease-specific value compression coefficient, and calculate the first disease based on the relative disease-specific value of the medical records. Initial disease correction factor for the medical records :
[0108]
[0109] in, To correct the lower limit, a value of 0.60 is preferred to prevent the actual medical labor of common low-weight diseases from being excessively suppressed; To correct the upper limit, a value of 1.80 is preferred to prevent extremely high-weight diseases from excessively consuming points in the current period; The disease value compression coefficient is preferably set to 0.50. At that time, the difference in disease value will be linearly transmitted to the points, which can easily lead to cases with high RW or high DIP scores receiving excessively high points. When the value is close to 0, the difference between diseases has almost no effect, therefore the preferred method is to select... That is, taking the square root of the relative disease value, while compressing extreme differences while preserving the order of disease values;
[0110] Construct a set of valid medical records for the current calculation period based on the payment model. Specifically, retain the basic total labor points for medical records. It has effective disease value. The medical records were then grouped according to the payment method, with the payment method being... All medical records constitute a medical record collection. ;when DRG case collection ,when DIP case collection obtained at that time ;
[0111] Calculate the total amount conservation calibration coefficient corresponding to the payment mode. :
[0112]
[0113] Where 'e' is the index, the numerator is the total base labor points for all medical records under this payment model before correction, and the denominator is the total points for all medical records after initial correction according to the initial disease type correction factor; the calculation is based on a weighted average of the total base labor points. This ensures that the total points after disease type correction are strictly equal to the total points before correction; DRG and DIP records are calculated separately. and To prevent the transfer of points between the two payment methods;
[0114] Based on the initial disease correction factor and total amount conservation calibration coefficient Calculate the first Final disease correction coefficient for each medical record :
[0115]
[0116] in, This serves as the total amount conservation calibration coefficient for the payment model to which this medical case belongs. This serves as the initial disease type correction factor for this case.
[0117] Further calculation of the first The first case Final medical labor points for each job category :
[0118]
[0119] in, For medical records, the basic labor points for the occupational family are... This is the final disease correction factor;
[0120] Based on the final medical labor points and basic total labor points The total amount of verification and calculation is conserved; specifically, for payment models... After revision, the final labor points for all medical records meet the following requirements:
[0121]
[0122] The left side of the equation represents the final labor points after correction for all medical records under this payment model, while the right side represents the total base labor points before correction. A calculation error threshold is set. If the difference between the left and right sides of the equation exceeds the threshold, no formal result will be output, and the case set, base points, and disease correction factor will be re-examined.
[0123] Output the standard workload score for each project. Basic points for each job family The number of basic labor points for each job category in each medical record Basic total labor points per medical record The relative value of each medical record to the disease Initial disease correction factor for each medical record Total amount conservation calibration coefficient for DRG or DIP payment modes Final disease correction coefficient for each medical record The final number of medical labor points for each job category in each medical record. .
[0124] This embodiment also provides a medical staff labor point calculation system based on the integration of RBRVS and DRGDIP, including:
[0125] The data acquisition module is used to collect medical records, medical insurance settlements, treatment items and occupational data, screen formally settled medical records and calculate the number of effective executions of items to form a unified project execution dataset;
[0126] The project mapping module is used to construct the RBRVS candidate set and the CCHI candidate set, calculate the comprehensive similarity between in-house projects and candidate standard projects, and establish the mapping relationship between in-house projects and RBRVS projects and CCHI projects.
[0127] The point value standardization module is used to calculate the median of the RBRVS and CCHI parameters for each project category, and generate the standard workload score for the project based on the relative value of RBRVS and the CCHI localization value index.
[0128] The job family breakdown module is used to set the weights of physician, nurse, medical technology and pharmacy job families according to project category, and calculate the basic points of the project job family by combining the standard workload score and the number of effective executions.
[0129] The medical record collection module is used to construct a set of effective diagnosis and treatment items by medical record number, collect the basic points of each job category, and calculate the total basic labor points of medical records and the contribution ratio of each job category.
[0130] The point correction module is used to establish DRG and DIP disease baseline values respectively, calculate the relative disease value of medical records, the initial disease correction factor and the total conservation calibration coefficient, generate the final medical labor points for each job series and perform total conservation verification.
[0131] In summary, this invention achieves unified association of medical records, treatment items, job series, and medical insurance settlement data by collecting multi-source medical data and forming a unified project execution dataset; it realizes the localization and standardization of project labor value by establishing a mapping relationship between in-hospital projects and RBRVS and CCHI standard projects; it achieves a structured expression of labor contribution of different job series by splitting job series basic points according to project category weights and performing case-level aggregation; and it reflects the differences in disease value while maintaining the stability of job series contribution ratio and total points in the calculation cycle by calculating DRG / DIP disease correction factors and total conservation calibration coefficients, ultimately improving the accuracy, comparability, and traceability of medical labor point calculation.
[0132] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.
Claims
1. A method for calculating medical service points based on the integration of RBRVS and DRGDIP, characterized in that, include: Collect multi-source medical data to form a unified project execution dataset; Based on multi-source medical data, a mapping between in-hospital projects and RBRVS and CCHI standard projects is established, and RBRVS and CCHI parameters are integrated to generate standard workload scores. Set the weight of project categories, calculate the basic points of job series based on the standard workload score, collect the basic labor points of job series, calculate the total basic labor points of medical records and the contribution ratio of each job series; Based on DRG / DIP disease value calculations using multi-source medical data, disease correction factors are calculated, and the final disease correction coefficient is further calculated. Combined with the basic labor points of each occupational series, the final labor points of each occupational series are calculated and the total amount is calibrated.
2. The method for calculating medical service points based on the fusion of RBRVS and DRGDIP as described in claim 1, characterized in that: The collection of multi-source medical data to form a unified project execution dataset refers to obtaining the basic data for calculating medical labor points. Screen formally settled medical records and establish a unique identifier for each record; For the The first case in the medical record Each project has a count of completed items. Number of cancellations and the amount of refund And determine the effective execution quantity. ; Merge records of the same medical case and the same project, and output a unified project execution dataset.
3. The method for calculating medical service points based on the fusion of RBRVS and DRGDIP as described in claim 2, characterized in that: The establishment of a mapping between in-hospital items and RBRVS and CCHI standard items based on multi-source medical data refers to constructing an RBRVS candidate set and a CCHI candidate set, and forming a candidate standard item set. The names and connotations of projects within the institute in the unified project execution dataset, as well as the names and connotations of projects in the candidate standard project set, are segmented and semantically encoded to obtain name semantic vectors and connotation semantic vectors. Computer Institute Projects With candidate standard projects Overall similarity ; First and second candidate projects are selected from the RBRVS candidate set and CCHI candidate set according to the comprehensive similarity from high to low. The corresponding comprehensive similarity is recorded. Then, the candidate projects that meet the requirements are screened to establish a mapping with the projects within the institute, and the working RVU of the RBRVS project is output. Operation point values in CCHI projects Human resource consumption value Technical difficulty value and risk level value .
4. The method for calculating medical service points based on the fusion of RBRVS and DRGDIP as described in claim 3, characterized in that: The fusion of RBRVS and CCHI parameters refers to calculating the median of the RBRVS working RVU for each item category in the basic data, using the established mapping relationship. Median of CCHI operation point values Median CCHI labor consumption value Median technical difficulty value of CCHI Median CCHI risk level value ; For the For each project within the institute, calculate the relative value of the CCHI operation point. Relative value of human resource consumption Relative value of technical difficulty Relative value of risk level ; Based on the relative value of CCHI operation point Relative value of human resource consumption Relative value of technical difficulty Relative value of risk level Calculate the first CCHI Localization Value Index of Each Project .
5. The method for calculating medical service points based on the fusion of RBRVS and DRGDIP as described in claim 4, characterized in that: The generated standard workload score refers to the workload RVU of the RBRVS project. Calculate the first and corresponding median. RBRVS relative value of each project ; According to the CCHI Localization Value Index of Each Project Relative value of RBRVS Calculate the standard workload score .
6. The method for calculating medical service points based on the fusion of RBRVS and DRGDIP as described in claim 5, characterized in that: The setting of project category weights, and the calculation of job family base points based on standard workload scores, refers to setting the weight of project category a to the performing job family k. ; For each project category a, perform a job family weight check. Calculate the base points for projects that meet the conditions; otherwise, stop the calculation for that project category. Based on the project's standard workload score, the number of effective executions, and the weight assigned to the execution job series k. Calculate the first The first case The project was assigned to the first Project career base points for each career family .
7. The method for calculating medical service points based on the fusion of RBRVS and DRGDIP as described in claim 6, characterized in that: The collection of basic labor points by job category, the calculation of the total basic labor points for medical records and the contribution ratio of each job category refer to the design of an effective set of diagnostic and treatment items based on the basic labor points of job categories. ; According to the collection of effective medical procedures And the calculation of basic points of the job series The first case Basic labor points for each job category ; Based on basic labor points Calculate the first Basic total labor points for each medical record ; Based on basic labor points and basic total labor points Calculate the first The first case Contribution ratio of each job series .
8. The method for calculating medical service points based on the fusion of RBRVS and DRGDIP as described in claim 7, characterized in that: The disease correction factor for calculating the DRG / DIP disease value based on multi-source medical data refers to establishing DRG and DIP disease benchmark values respectively based on the payment patterns in the basic data. ; Based on disease-specific benchmarks Calculate the first Relative disease value of medical records ; Set upper and lower limits for disease-specific adjustments and a disease-specific value compression coefficient, and calculate the first disease based on the relative disease-specific value of the medical records. Initial disease correction factor for the medical records .
9. The method for calculating medical service points based on the fusion of RBRVS and DRGDIP as described in claim 8, characterized in that: The further calculation of the final disease type correction coefficient, combined with the basic labor points of each occupational category, to calculate the final labor points of each occupational category and perform total conservation calibration, refers to constructing a valid set of medical records for the payment model within the current calculation period. ; Calculate the total amount conservation calibration coefficient corresponding to the payment mode. ; Based on the initial disease correction factor and total amount conservation calibration coefficient Calculate the first Final disease correction coefficient for each medical record ; Further combine the calculation of the basic labor points of the job series to determine the first The first case Final medical labor points for each job category ; The total amount of the final verification and calculation cycle is conserved.
10. A medical service point calculation system based on the fusion of RBRVS and DRGDIP, based on the medical service point calculation method based on the fusion of RBRVS and DRGDIP as described in any one of claims 1 to 9, characterized in that, include: The data acquisition module is used to collect medical records, medical insurance settlements, treatment items and occupational data, screen formally settled medical records and calculate the number of effective executions of items to form a unified project execution dataset; The project mapping module is used to construct the RBRVS candidate set and the CCHI candidate set, calculate the comprehensive similarity between in-house projects and candidate standard projects, and establish the mapping relationship between in-house projects and RBRVS projects and CCHI projects. The point value standardization module is used to calculate the median of the RBRVS and CCHI parameters for each project category, and generate the standard workload score for the project based on the relative value of RBRVS and the CCHI localization value index. The job family breakdown module is used to set the weights of physician, nurse, medical technology and pharmacy job families according to project category, and calculate the basic points of the project job family by combining the standard workload score and the number of effective executions. The medical record collection module is used to construct a set of effective diagnosis and treatment items by medical record number, collect the basic points of each job category, and calculate the total basic labor points of medical records and the contribution ratio of each job category. The point correction module is used to establish DRG and DIP disease baseline values respectively, calculate the relative disease value of medical records, the initial disease correction factor and the total conservation calibration coefficient, generate the final medical labor points for each job series and perform total conservation verification.