A medical insurance cost and curative effect combined evaluation method for surgical path optimization

Abstract

The application discloses a medical insurance cost and curative effect combined evaluation method for surgical path optimization, relates to the technical field of medical equipment data analysis, and comprises the following steps: S1, constructing a surgical path structure expression; S2, using a path node set and a node attribute set to construct path-level medical insurance cost mapping; S3, curative effect quantitative expression under the influence of medical support and transfer equipment; S4, using path cost distribution structure and path curative effect contribution structure for unified alignment processing; S5, using a standardized path evaluation benchmark to perform path-level medical insurance cost and curative effect combined evaluation. The application sets up a structured binding of cost and medical process, maps the cost to the path node, introduces the time proportion, makes the cost have the path stage distribution characteristics, provides the node-level cost input for subsequent curative effect modeling, and can convert the medical insurance cost from the traditional overall statistical result into the distribution structure along the surgical path node.

Description

Technical Field

[0001] This invention relates to the field of medical device data analysis technology, specifically a method for jointly evaluating medical insurance costs and efficacy for surgical pathway optimization. Background Technology

[0002] With the development of medical informatization and refined medical insurance management, medical institutions are gradually shifting from simple cost control to a synergistic evaluation of costs and treatment efficacy. During surgical treatment, different surgical pathways differ in their organizational methods, equipment configurations, and time distribution, leading to significant variations in medical insurance expenditure structures and patient efficacy outcomes. Current technologies often categorize medical costs by treatment cycle or cost items, while efficacy evaluation is primarily based on overall outcome indicators. The lack of a unified, structured expression and correlation analysis mechanism makes it difficult to support comprehensive evaluation at the surgical pathway level.

[0003] In existing technologies, medical insurance costs are usually statistically analyzed by item category or treatment cycle, and are mainly presented in the form of total cost or categorized summary cost. There is a lack of a structured processing mechanism to map costs to surgical path nodes, resulting in a lack of clear correspondence between costs and specific medical processes. At the same time, the lack of time proportion to express costs in the path stages makes it impossible to effectively align cost distribution with the changes in efficacy in the path. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a method for jointly evaluating medical insurance costs and treatment efficacy for surgical pathway optimization, thereby resolving the problems mentioned in the background section.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] In a first aspect, embodiments of the present invention provide a method for jointly evaluating medical insurance costs and efficacy for surgical pathway optimization, comprising the following steps:

[0007] S1. Construct the surgical path structure representation to obtain the path node set and node attribute set;

[0008] S2. Use the set of path nodes and the set of node attributes to construct a path-level medical insurance cost mapping to obtain the path cost distribution structure;

[0009] S3. Use the path node set and path cost distribution structure to quantify the efficacy under the influence of medical support and transportation equipment, and obtain the path efficacy contribution structure.

[0010] S4. Use the pathway cost distribution structure and pathway efficacy contribution structure to perform unified alignment processing to obtain a standardized pathway evaluation benchmark;

[0011] S5. Use standardized pathway evaluation benchmarks to conduct a joint evaluation of pathway-level medical insurance costs and efficacy, and obtain the joint evaluation results of surgical pathways.

[0012] To further optimize this technical solution, step S1 transforms the original medical process data into a standardized path node expression form using structured analysis methods. The expression is as follows:

[0013] ;

[0014] in,

[0015] : A complete set of surgical path nodes;

[0016] : No. There are path nodes, and ;

[0017] The total number of path nodes is determined by the path partitioning results;

[0018] Path nodes satisfy a strictly ordered relationship:

[0019] The expression for the node attribute set is:

[0020] ;

[0021] in, : No. The set of attributes corresponding to each path node;

[0022] At any node Its attribute set is:

[0023] ;

[0024] In the formula,

[0025] Indicates surgical classification attributes;

[0026] Indicates time characteristics, ,in The node start time; The node's end time; The duration of the node;

[0027] This indicates the type of medical behavior corresponding to the node;

[0028] Indicates the characteristics of medical device use. ,in The operating table is in use. Status of hospital bed occupancy; Status of transport equipment / stretcher in use; The bracket is in use. The environmental condition of the medical treatment room;

[0029] Indicates the correlation characteristics of medical insurance expenses. ,in This serves as the identifier for the cost type corresponding to the node. This serves as an identifier for medical insurance coverage.

[0030] To further optimize this technical solution, step S2 transforms the path node structure formed in step S1 into a cost structure expression, so that medical insurance costs are transformed from a traditional summary result into a distribution form unfolding along the path nodes.

[0031] Step S2, in constructing the path-level medical insurance cost mapping, includes the following steps:

[0032] Mapping medical procedures to expense items;

[0033] Cost data acquisition and standardization;

[0034] Detailed processing of medical insurance attribution determination;

[0035] Node fee summary processing;

[0036] Path location representation processing based on time features;

[0037] Path cost distribution structure construction.

[0038] To further optimize this technical solution, in step S2, when mapping medical behavior to expense items, the medical behavior characteristics of each node in step S1 are used as a basis. By using the mapping technology between medical behavior codes and fee item codes, the following mapping relationship is established: medical behavior identifiers are converted into corresponding sets of fee item codes, with each medical behavior corresponding to at least one fee item;

[0039] This yields the set of cost items corresponding to each node:

[0040] ;

[0041] Each of the fee items There is a specific fee item.

[0042] To further optimize this technical solution, in step S2, when acquiring and standardizing cost values, for each cost item... The data is obtained primarily through actual billing records in the hospital information system. When actual data is lacking, the data is assigned values ​​through item pricing in the standard billing database. To ensure consistency of data from different sources, a cost standardization process is adopted to convert costs to a uniform scale. After processing, each cost item has a definite cost value.

[0043] To further optimize this technical solution, in step S2, when refining the medical insurance attribution determination, the node-level medical insurance attribution identifier in step S1 is used. In conjunction with the expense item code, each expense item is evaluated item by item using the medical insurance catalog matching and rule-based judgment methods, and a medical insurance attribution function is set. Its value selection rules are as follows:

[0044] When the expense item is included in the medical insurance catalog, the value is 1;

[0045] When the expense item is not included in the medical insurance catalog, the value is 0;

[0046] Based on this, each expense item is divided into: expenses covered by medical insurance and out-of-pocket expenses.

[0047] To further optimize this technical solution, in step S2, when performing node cost aggregation processing, all cost items within a node are aggregated to obtain a node-level cost representation: ;

[0048] Simultaneously, we obtain:

[0049] ;

[0050] ;

[0051] in:

[0052] Total cost of the node;

[0053] Node medical insurance expenses;

[0054] Node self-payment fee.

[0055] To further optimize this technical solution, in step S2, when performing path location expression processing based on time features, the time features from step S1 are used as a basis. The time percentage normalization method is used to calculate the time percentage of a node in the overall path:

[0056] ;

[0057] Further construct time-weighted cost:

[0058] .

[0059] To further optimize this technical solution, in step S2, when constructing the path cost distribution structure, based on the above-mentioned node-level cost results, the path cost distribution structure is constructed according to the order of the path nodes to form an ordered sequence:

[0060] ;

[0061] Simultaneously construct a time-weighted cost series:

[0062] .

[0063] To further optimize this technical solution, step S3, based on the already defined path structure and cost distribution structure, incorporates medical support and transportation equipment factors and cost constraints into the efficacy analysis, resulting in a path efficacy contribution structure including a node efficacy contribution sequence. Overall therapeutic value of the pathway ;

[0064] Step S4 maps the path cost distribution structure from step S2 to the path efficacy contribution structure from step S3 using the same numerical scale and the same node indexing system, thus deriving a standardized path evaluation benchmark: ;

[0065] Step S5, based on the unified scale expression of cost and efficacy completed in Step S4, integrates the cost and efficacy calculations for each pathway node and forms a unified joint assessment result at the pathway level: ;

[0066] in:

[0067] : Comprehensive evaluation value of the route;

[0068] Average cost per route;

[0069] : Average efficacy level of the pathway.

[0070] In a second aspect, embodiments of the present invention provide a computer device, including a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program instructions are executed by the processor, they implement the steps of a method for jointly evaluating medical insurance costs and efficacy for surgical pathway optimization as described in the first aspect of the present invention.

[0071] Thirdly, embodiments of the present invention provide a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program instructions are executed by a processor, they implement the steps of a method for jointly evaluating medical insurance costs and efficacy for surgical pathway optimization as described in the first aspect of the present invention.

[0072] Compared with existing technologies, this invention provides a method for jointly evaluating medical insurance costs and efficacy for surgical pathway optimization, which has the following beneficial effects:

[0073] This method for jointly evaluating medical insurance costs and treatment efficacy in surgical pathway optimization maps costs to pathway nodes by establishing a structured binding between costs and the medical process. It also introduces time proportions to give costs a path-stage distribution characteristic, providing node-level cost input for subsequent efficacy modeling. This transforms medical insurance costs from traditional overall statistical results into a distribution structure unfolding along the surgical pathway nodes, making cost information consistent with medical behavior and the time evolution process. This achieves a structured correlation between costs and efficacy, improving the accuracy and interpretability of pathway-level joint evaluation. Attached Figure Description

[0074] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying 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.

[0075] Figure 1 This is a flowchart illustrating a method for jointly evaluating medical insurance costs and efficacy for surgical pathway optimization proposed in this invention.

[0076] Figure 2 This is a schematic diagram of the path-level medical insurance cost mapping construction process for a method for jointly evaluating medical insurance costs and efficacy in surgical pathway optimization proposed in this invention.

[0077] Figure 3 This is a schematic diagram illustrating the quantitative expression process of efficacy under the influence of medical support and transportation equipment in a method for jointly evaluating medical insurance costs and efficacy for surgical pathway optimization proposed in this invention.

[0078] Figure 4 This is a schematic diagram of the pathway-level medical insurance cost and efficacy joint evaluation process of the surgical pathway optimization method proposed in this invention. Detailed Implementation

[0079] 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.

[0080] 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.

[0081] Secondly, the term "an 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 throughout this specification does not necessarily refer to the same embodiment, nor is it a single embodiment or an embodiment selectively excluded from other embodiments.

[0082] Example 1:

[0083] Reference Figures 1-4 This is the first embodiment of the present invention, which provides a method for jointly evaluating medical insurance costs and efficacy for surgical pathway optimization, including the following steps:

[0084] S1. Construct the surgical path structure representation to obtain the path node set and node attribute set;

[0085] Step S1 transforms the original medical process data into a standardized path node representation using structured analysis methods, providing a unified input for subsequent steps.

[0086] Step S1, in constructing the surgical path structure representation, includes the following steps:

[0087] Determining the surgical classification-driven path template:

[0088] Based on surgical classification data (such as surgical codes and surgical names) in existing medical information systems, the target surgery is classified and identified using mature medical classification coding system matching technology (such as ICD coding system and surgical grading standards).

[0089] Based on this, the corresponding standard clinical pathway template library (such as the clinical pathway library in the hospital information system) is called to complete the following processing: the surgical category is mapped to the corresponding standard pathway template, and the stage division rules defined in the template (such as preoperative, intraoperative, postoperative, and transfer stages) are extracted; and a path structure framework that uniquely corresponds to the target surgical type is obtained.

[0090] Stage-based processing of raw medical process data:

[0091] After obtaining the path template, the original medical data (such as electronic medical records, surgical records, and nursing records) is analyzed; the medical process is divided into stages using mature time series segmentation technology and event tagging identification methods: medical behaviors are sorted according to timestamps; key events (such as entering the operating room, the start of anesthesia, the end of surgery, the start of transfer, etc.) are identified; and continuous medical behaviors are divided into corresponding path stages.

[0092] In this process, a combination of rule matching and event recognition is used, for example:

[0093] Identifying medical events using keyword matching;

[0094] Identify phase switching points using time interval thresholds;

[0095] This transforms the continuous medical process into a discrete structure divided into stages.

[0096] Path node generation and order determination:

[0097] Based on the phase division, a structured modeling method is further used to abstract each phase into a path node, generate a unique node identifier for each phase, and establish the connection relationship between nodes in chronological order to form an ordered sequence of path nodes.

[0098] This process employs mature process modeling methods (such as directed sequence modeling or flowchart modeling techniques) to ensure that the path has a clear order and logical relationship; it yields a complete set of path nodes and clarifies the order relationship between the nodes.

[0099] Node attribute extraction and standardization:

[0100] For each path node, a unified set of node attributes is extracted and constructed. The attribute extraction process is achieved through multi-source data fusion technology, including:

[0101] Medical behavior feature extraction: Identify the type of medical behavior corresponding to the node through electronic medical record structured parsing technology, and mark whether it involves surgical operation or auxiliary operation;

[0102] Time feature extraction: The duration of nodes and the order of occurrence of nodes are directly calculated through timestamp data, and the time at different scales is uniformly expressed (e.g., uniformly to minute or hour level) through standard time normalization method.

[0103] Medical equipment usage feature extraction: Through correlation analysis between equipment usage records and nursing records, rule matching methods are used to identify whether an operating table is used, whether bed support is involved, whether a transport tool or stretcher is used, whether a brace is used for fixation, and whether the environment is a specific medical treatment room. At the same time, the equipment usage status is uniformly identified so that it can be used for subsequent efficacy analysis.

[0104] Pre-labeling of medical insurance expense association features: By comparing the medical charge item codes with the medical insurance catalog, and using mature medical insurance code mapping technology, it is determined whether the relevant medical behavior of the node is within the scope of medical insurance reimbursement, and the expense type is marked (included or not included in the scope of medical insurance). This step only performs "attribution marking" and does not involve specific expense calculation, providing input conditions for subsequent S2.

[0105] Node attribute consistency verification and normalization:

[0106] To ensure the stability of subsequent steps, node attributes are standardized and uniformly named, attribute integrity is verified (to avoid missing key attributes in nodes), and abnormal data is corrected (such as time conflicts and missing device tags).

[0107] This process employs mature data cleaning and consistency verification methods.

[0108] The final output of step S1 includes a set of path nodes and a set of node attributes, where the expression for the set of path nodes is:

[0109] ;

[0110] in,

[0111] : A complete set of surgical path nodes;

[0112] : No. There are path nodes, and ;

[0113] The total number of path nodes is determined by the path partitioning results;

[0114] Path nodes satisfy a strictly ordered relationship:

[0115] This order is determined by the time series segmentation results, representing the execution order of the medical process, and: skipping is not allowed, and parallel nodes are not allowed.

[0116] The expression for the node attribute set is:

[0117] ;

[0118] in, : No. The set of attributes corresponding to each path node;

[0119] At any node Its attribute set is:

[0120] ;

[0121] In the formula,

[0122] This indicates that the surgical classification attribute remains constant throughout the entire path, i.e., for all... The same result is derived from the surgical classification and identification results in step S1, which is used to constrain the adaptation range of subsequent cost rules and efficacy models.

[0123] Indicates time characteristics, ,in The node start time; The node's end time; The duration of the node is calculated from the previous two values;

[0124] This indicates the type of medical behavior corresponding to the node, such as: preoperative preparation, anesthesia administration, surgical procedure, postoperative monitoring, and transport management, which is obtained by parsing medical records;

[0125] Indicates the characteristics of medical device use. ,in The operating table is in use. Status of hospital bed occupancy; Status of transport equipment / stretcher in use; The bracket is in use. This represents the environmental status of the medical treatment room; each item is a structured identifier used for subsequent efficacy contribution calculations.

[0126] Indicates the correlation characteristics of medical insurance expenses. ,in Identify the cost type corresponding to the node (e.g., surgery, examination, nursing). This is an identifier for medical insurance coverage (whether the item is covered by medical insurance).

[0127] The complete surgical pathway structure is expressed as follows: .

[0128] S2. Use the set of path nodes and the set of node attributes to construct a path-level medical insurance cost mapping to obtain the path cost distribution structure;

[0129] Step S2 transforms the path node structure formed in step S1 into a cost structure expression, changing the traditional summary result of medical insurance costs into a distributed form that unfolds along the path nodes.

[0130] Step S2, in constructing the path-level medical insurance cost mapping, includes the following steps:

[0131] Mapping medical procedures to expense items:

[0132] Based on the medical behavior characteristics of each node in step S1 By using mature medical behavior coding and fee item coding mapping technology (such as hospital fee item dictionary or medical insurance item coding reference table), the following mapping relationship is established: medical behavior identifiers are converted into corresponding fee item code sets, and each medical behavior corresponds to at least one fee item;

[0133] This yields the set of cost items corresponding to each node:

[0134] ;

[0135] Each of the fee items There is a specific fee item.

[0136] Cost data acquisition and standardization:

[0137] For each expense item Priority is given to obtaining actual billing records from the hospital information system. When actual data is lacking, values ​​are assigned using item pricing from the standard billing database. To ensure consistency of data from different sources, mature cost standardization methods are adopted to convert costs to a unified scale, such as using a unified currency and a unified billing unit. After processing, each cost item has a definite cost value.

[0138] Detailed processing of medical insurance attribution determination:

[0139] Based on the node-level medical insurance attribution identifier in step S1 In conjunction with expense item coding, and through mature medical insurance catalog matching and rule-based judgment methods, each expense item is judged item by item, and a medical insurance attribution function is set. Its value selection rules are as follows:

[0140] When the expense item is included in the medical insurance catalog, the value is 1;

[0141] When the expense item is not included in the medical insurance catalog, the value is 0;

[0142] Based on this, each expense item is divided into: expenses covered by medical insurance and out-of-pocket expenses.

[0143] Node fee summary processing:

[0144] By summing all cost items within a node, we obtain the node-level cost representation: ;

[0145] Simultaneously, we obtain:

[0146] ;

[0147] ;

[0148] in:

[0149] Total cost of the node;

[0150] Node medical insurance expenses;

[0151] Node self-paid fees;

[0152] This result reflects the node's contribution at the cost level.

[0153] Processing of path location representation based on time features:

[0154] To give the cost distribution path location significance, based on the time features in step S1 Using a mature time percentage normalization method, the time percentage of a node in the overall path is calculated:

[0155] ;

[0156] Further construct time-weighted cost:

[0157] ;

[0158] This processing is used to reflect the stage distribution characteristics of costs in the pathway, so that it can correspond to the subsequent evolution of treatment time.

[0159] Path cost distribution structure construction:

[0160] Based on the above node-level cost results, a path cost distribution structure is constructed according to the order of path nodes, forming an ordered sequence:

[0161] ;

[0162] Simultaneously construct a time-weighted cost series:

[0163] ;

[0164] This structure represents the path-level cost representation.

[0165] The final output path cost distribution structure of step S2 includes the node total cost distribution sequence. Medical insurance cost distribution sequence ; Self-paid expense distribution sequence Time-weighted cost distribution sequence .

[0166] Existing mature technologies typically summarize and statistically analyze medical insurance costs by item category or treatment cycle, with the output mainly consisting of total cost or category cost, lacking a correspondence with specific medical processes. In contrast, this step maps costs to surgical pathway nodes, creating a structured binding between costs and medical processes. It also introduces the distribution characteristics of pathway stages through time proportions, thereby achieving a refined expression of costs in the medical pathway and providing node-level input for subsequent efficacy modeling. The difference between the two is that the former focuses on result statistics, while the latter focuses on the structured distribution of processes.

[0167] S3. Use the path node set and path cost distribution structure to quantify the efficacy under the influence of medical support and transportation equipment, and obtain the path efficacy contribution structure.

[0168] Step S3, based on the established path structure and cost distribution structure, introduces medical support and transportation equipment factors and cost constraints into the efficacy analysis, thereby transforming the efficacy from an overall result to a path node contribution structure.

[0169] Step S3, in quantifying the therapeutic effect, includes the following steps:

[0170] Construction of basic therapeutic efficacy at nodes:

[0171] For each node Based on the medical behavior characteristics in step S1 and time characteristics By using mature clinical pathway scoring methods or historical case statistics methods, a mapping relationship between medical behavior and efficacy can be established.

[0172] In this process, based on clinical pathways or historical data, a "medical behavior-efficacy weight comparison table" is constructed to assign a basic efficacy weight to each type of medical behavior; the duration of each node is normalized and converted into a time-effect coefficient; the medical behavior weight and the time-effect coefficient are combined through linear weighting or rule-based lookup; thus, the basic efficacy quantity of each node is obtained.

[0173] ;

[0174] in:

[0175] This indicates the potential for therapeutic efficacy at the node without considering the impact of equipment and costs.

[0176] Quantifying the impact of medical support and transport equipment:

[0177] Based on the device usage characteristics in step S1 A mature multi-factor weighted evaluation method is used to quantify the impact of equipment; the impact weight and direction of action are preset for each type of equipment, including:

[0178] Operating table: Improves operational precision and has a positive impact on treatment efficacy;

[0179] Hospital beds: Improve recovery conditions and have a positive impact on treatment efficacy;

[0180] Transportation tools: may introduce shocks, negatively impacting the treatment efficacy;

[0181] Stents: Improve structural stability and have a positive impact on treatment efficacy;

[0182] Treatment room environment: affects infection risk and has a positive impact on treatment efficacy;

[0183] The weighting of influence is determined based on historical case data statistics using mature correlation or regression analysis methods. The greater the influence, the higher the weight, and vice versa.

[0184] Standardize the status values ​​of each device (such as whether it is in use or the intensity of use);

[0185] A weighted summation method is used to map the impact of multiple devices into a unified comprehensive impact factor. ,in: This represents the comprehensive impact factor of node equipment.

[0186] Construction of cost constraint factors:

[0187] Based on the node cost obtained in step S2 and time-weighted fees A cost constraint mechanism is constructed using mature cost-effectiveness analysis methods. This process first normalizes node costs to ensure they are on a uniform scale; then, based on the relationship between medical resource input and treatment efficacy, segmented mapping rules are established.

[0188] Low-cost range: limited efficacy;

[0189] Mid-range cost: Significant improvement in treatment efficacy;

[0190] High-cost range: Improvement in efficacy slows down;

[0191] Costs are mapped to constraint factors using piecewise functions or table lookups:

[0192] ;

[0193] in: This indicates the moderating effect of cost on treatment efficacy.

[0194] Calculation of the contribution of node efficacy:

[0195] Under the combined influence of basic efficacy, equipment limitations, and cost constraints, the contribution of each node to efficacy is constructed as follows:

[0196] ;

[0197] in:

[0198] It is the basic layer, reflecting the original therapeutic potential of the basic therapeutic effect reflection node;

[0199] This is the equipment layer, reflecting how equipment-related factors proportionally amplify or suppress the therapeutic effect. Amplify the therapeutic effect in time; This indicates no impact; Time-inhibiting therapeutic effect;

[0200] The resource layer reflects the limitations of resource input on therapeutic efficacy. This indicates that insufficient resources will limit the scope of treatment effectiveness;

[0201] The three factors act on different dimensions and are combined using a multiplicative approach to achieve a unified expression.

[0202] Construction of pathway efficacy contribution structure:

[0203] Arrange all node efficacy contributions in path order to construct a path efficacy structure:

[0204] ;

[0205] And calculate the overall therapeutic effect of the pathway:

[0206] ;

[0207] in:

[0208] This indicates the distribution of therapeutic effects along the pathway;

[0209] This indicates the overall level of therapeutic efficacy.

[0210] The final output of step S3, the path efficacy contribution structure, includes the node efficacy contribution sequence. Overall therapeutic value of the pathway .

[0211] Existing mature technologies typically evaluate efficacy as a holistic outcome, with the impact of medical equipment on efficacy often remaining at the level of empirical description, and efficacy analysis lacking a correspondence with the specific medical process structure. In contrast, this step decomposes efficacy to the surgical pathway node level, realizing a process-oriented expression of efficacy. At the same time, it quantifies the impact of medical support and transport equipment in a structured manner and introduces cost factors to form a constraint mechanism, thereby realizing the distribution expression of efficacy in the pathway structure and quantitative modeling of its influencing factors.

[0212] S4. Use the pathway cost distribution structure and pathway efficacy contribution structure to perform unified alignment processing to obtain a standardized pathway evaluation benchmark;

[0213] Step S4 maps the path cost distribution structure from step S2 and the path efficacy contribution structure from step S3 to the same numerical scale and the same node index system, thus constructing a comparable evaluation basis for costs and efficacy.

[0214] Step S4, during the uniform alignment process, includes the following steps:

[0215] Path node index consistency alignment:

[0216] Based on the output results of steps S2 and S3: Cost sequence and therapeutic sequence ;

[0217] First, consider the path nodes. Alignment is performed based on a unique index datum to ensure that each Unique Correspondence If missing data exists, the average of adjacent nodes is used to fill in the missing data, resulting in a node-level cost-treatment alignment sequence with consistent structure.

[0218] Global normalization processing (unified standardization):

[0219] To eliminate the dimensional differences between cost and efficacy, a unified minimum-maximum normalization method is adopted, and processing is performed based on the entire pathway node range, including:

[0220] Cost standardization: ;

[0221] Standardization of treatment efficacy: ;

[0222] Cost and efficacy are both mapped to the same numerical range. To maintain the relative size pattern between nodes, a unified standard is used to avoid scale deviation.

[0223] Node-level two-dimensional evaluation vector construction:

[0224] After standardization, a two-dimensional evaluation vector is constructed for each node:

[0225]

[0226] in:

[0227] : No. Standardized evaluation vectors for each path node;

[0228] Standardized cost characteristics;

[0229] Standardized therapeutic characteristics.

[0230] Path evaluation benchmark structure generation:

[0231] Arrange all node evaluation vectors in path order to form a path-level structure, indexed by node. By constructing the vector sequence sequentially, we obtain:

[0232] ;

[0233] This structure indicates that each node contains both cost and efficacy information, while maintaining consistency in the overall path sequence.

[0234] The final output of step S4 is the standardized path evaluation benchmark:

[0235] .

[0236] S5. Use standardized pathway evaluation benchmarks to conduct a joint evaluation of pathway-level medical insurance costs and efficacy to obtain the joint evaluation results of surgical pathways;

[0237] Step S5, based on the unified scale expression of cost and efficacy completed in step S4, integrates the cost and efficacy calculations of the pathway nodes and forms a unified joint evaluation result at the pathway level.

[0238] Step S5, when conducting a joint assessment of pathway-level medical insurance costs and efficacy, includes the following steps:

[0239] Calculation of node-level cost-efficacy combined evaluation value:

[0240] Based on the standardized path evaluation benchmark obtained in step S4 For each node, construct a joint evaluation value:

[0241]

[0242] in:

[0243] : Joint evaluation value of nodes;

[0244] Standardized efficacy values;

[0245] Standardized cost value;

[0246] Therapeutic efficacy weighting;

[0247] Cost weighting;

[0248] and The determination is based on historical surgical pathway data. A mature regression analysis method is used to calculate the contribution of efficacy and cost to the overall evaluation results. The obtained contribution values ​​are then normalized to obtain the final result, and the following conditions are met: .

[0249] Path-level joint evaluation value aggregation:

[0250] Path-level aggregation of joint evaluation values ​​of nodes:

[0251] ;

[0252] The node weights are based on the time features in step S1. calculate: And satisfy: This indicates that the longer the time of a node, the greater its impact on the overall path.

[0253] Calculation of average cost and efficacy of the pathway:

[0254] Based on the standardized data from step S4, calculate the path average index:

[0255] ;

[0256] ;

[0257] All calculations are based on standardized values ​​to ensure consistency with the output of step S4.

[0258] Construction of joint evaluation results:

[0259] The path-level evaluation values ​​and auxiliary indicators are structured and combined to form the final result:

[0260] ;

[0261] The result is a three-dimensional vector structure, where:

[0262] : Comprehensive evaluation value of the route;

[0263] Average cost per route;

[0264] : Average efficacy level of the pathway.

[0265] Existing mature technologies typically evaluate costs or efficacy separately or analyze them using simple ratios, lacking consideration for the surgical pathway structure. This step, however, performs hierarchical calculations based on the pathway node structure, achieving coupled expression of costs and efficacy at the node level, and forming a unified evaluation result through weighted aggregation at the pathway level. This enables unified quantification of costs and efficacy based on standardized data and joint assessment at the pathway level.

[0266] Example 2:

[0267] This embodiment provides a practical application scenario for a method for jointly evaluating medical insurance costs and treatment efficacy in surgical pathway optimization:

[0268] The path structure is constructed, corresponding to step S1. For total hip replacement surgery, the hospital divides the complete surgical process into multiple path nodes, for example:

[0269] Preoperative preparation stage The patient was transferred to the operating room. Surgical procedure stage Postoperative transport phase Ward recovery phase;

[0270] At the same time, for each node, the following are recorded: type of medical procedure (such as incision, implantation, fixation, etc.), duration, and equipment used (such as type of operating table, type of transport tool, type of hospital bed, etc.).

[0271] This results in a structured expression of the surgical path.

[0272] Cost distribution construction, corresponding to step S2, involves mapping the cost corresponding to each path node based on the hospital's medical insurance settlement system, for example:

[0273] Surgical stage costs (surgical consumables and equipment usage costs);

[0274] Transit costs (transit equipment and labor costs);

[0275] Ward-stage costs (bed fees, nursing fees);

[0276] By further incorporating time information, the costs are distributed and represented to form a cost structure sequence corresponding to each path node. This structure reflects the distribution of costs throughout the entire surgical path.

[0277] The efficacy contribution assessment, corresponding to step S3, involves the hospital evaluating the efficacy of each pathway node based on historical case data and clinical experience. For example:

[0278] Surgical stage: A high-precision operating table helps reduce errors and improve treatment outcomes;

[0279] During transport: Shock-absorbing transport tools can reduce the risk of postoperative complications;

[0280] Inpatient stage: Rehabilitation beds help accelerate recovery;

[0281] The impact of medical support and transportation equipment is quantified, and combined with cost constraints, the efficacy contribution of each path node is obtained, thus forming a path efficacy contribution structure.

[0282] The construction of a unified evaluation benchmark corresponds to step S4. Due to the different sources and inconsistent scales of cost and efficacy data, the hospital performs unified processing on the two types of data: mapping cost data and efficacy data to a unified range, and making one-to-one correspondences according to path nodes, ultimately forming a standardized evaluation structure in which each node contains two-dimensional information of "cost-efficacy". This structure provides a unified input for subsequent joint evaluation.

[0283] Joint evaluation of the paths, corresponding to step S5, involves a comprehensive evaluation of each path based on a standardized evaluation structure:

[0284] At the node level, a comprehensive evaluation is formed by combining costs and efficacy;

[0285] At the path level, a weighted summary is performed based on the duration of each node.

[0286] The final results obtained include the comprehensive evaluation of the pathway, the average cost level of the pathway, and the average efficacy level of the pathway.

[0287] In this implementation example, after evaluating path A and path B, the following conclusions are drawn:

[0288] Pathway A: Lower cost, but limited improvement in efficacy and longer recovery time;

[0289] Pathway B: Higher cost, but significantly improved efficacy, faster postoperative recovery, and lower complication rate;

[0290] The joint evaluation results revealed that:

[0291] Pathway B is superior in terms of "cost-efficacy balance" and is a high-investment but high-return path.

[0292] Example 3:

[0293] This embodiment also provides a computer device applicable to a method for jointly evaluating medical insurance costs and efficacy for surgical pathway optimization, including a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to realize the method for jointly evaluating medical insurance costs and efficacy for surgical pathway optimization as proposed in the above embodiment.

[0294] This embodiment also provides a storage medium storing a computer program that, when executed by a processor, implements a method for jointly evaluating medical insurance costs and efficacy for surgical pathway optimization as proposed in the above embodiments.

[0295] The computer device can be a terminal, comprising a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0296] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0297] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-including system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0298] More specific examples (a non-exhaustive list) of computer-readable media include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which programs can be printed, because programs can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0299] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0300] 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 jointly evaluating medical insurance costs and treatment efficacy for surgical pathway optimization, characterized in that, Includes the following steps: S1. Construct the surgical path structure representation to obtain the path node set and node attribute set; S2. Use the set of path nodes and the set of node attributes to construct a path-level medical insurance cost mapping to obtain the path cost distribution structure; S3. Use the path node set and path cost distribution structure to quantify the efficacy under the influence of medical support and transportation equipment, and obtain the path efficacy contribution structure. S4. Use the pathway cost distribution structure and pathway efficacy contribution structure to perform unified alignment processing to obtain a standardized pathway evaluation benchmark; S5. Use standardized pathway evaluation benchmarks to conduct a joint evaluation of pathway-level medical insurance costs and efficacy, and obtain the joint evaluation results of surgical pathways.

2. The method for jointly evaluating medical insurance costs and efficacy for surgical pathway optimization according to claim 1, characterized in that, Step S1 transforms the original medical process data into a standardized path node representation using structured analysis methods. The expression is as follows: ； in, : A complete set of surgical path nodes; : No. There are path nodes, and ; The total number of path nodes is determined by the path partitioning results; Path nodes satisfy a strictly ordered relationship: ; The expression for the node attribute set is: ； in, : No. The set of attributes corresponding to each path node; At any node Its attribute set is: ； In the formula, Indicates surgical classification attributes; Indicates time characteristics, ,in The node start time; The node's end time; The duration of the node; This indicates the type of medical behavior corresponding to the node; Indicates the characteristics of medical device use. ,in The operating table is in use. Status of hospital bed occupancy; Status of transport equipment / stretcher in use; The bracket is in use. The environmental condition of the medical treatment room; Indicates the correlation characteristics of medical insurance expenses. ,in This serves as the identifier for the cost type corresponding to the node. This serves as an identifier for medical insurance coverage.

3. The method for jointly evaluating medical insurance costs and efficacy for surgical pathway optimization according to claim 1, characterized in that, Step S2 transforms the path node structure formed in step S1 into a cost structure expression, changing the traditional summary result of medical insurance costs into a distribution form that unfolds along the path nodes. Step S2, in constructing the path-level medical insurance cost mapping, includes the following steps: Mapping medical procedures to expense items; Cost data acquisition and standardization; Detailed processing of medical insurance attribution determination; Node fee summary processing; Path location representation processing based on time features; Path cost distribution structure construction.

4. The method for jointly evaluating medical insurance costs and efficacy for surgical pathway optimization according to claim 3, characterized in that, In step S2, when mapping medical behaviors to expense items, the medical behavior characteristics of each node in step S1 are used as a basis. By using the mapping technology between medical behavior codes and fee item codes, the following mapping relationship is established: medical behavior identifiers are converted into corresponding sets of fee item codes, with each medical behavior corresponding to at least one fee item; This yields the set of cost items corresponding to each node: ； Each of the fee items There is a specific fee item.

5. The method for joint evaluation of medical insurance costs and efficacy for surgical pathway optimization according to claim 3, characterized in that, In step S2, when acquiring and standardizing cost values, each cost item is processed... The data is obtained primarily through actual billing records in the hospital information system. When actual data is lacking, the data is assigned values ​​through item pricing in the standard billing database. To ensure consistency of data from different sources, a cost standardization process is adopted to convert costs to a uniform scale. After processing, each cost item has a definite cost value.

6. The method for jointly evaluating medical insurance costs and efficacy for surgical pathway optimization according to claim 3, characterized in that, In step S2, when refining the medical insurance attribution determination, the node-level medical insurance attribution identifier in step S1 is used as the basis. In conjunction with the expense item code, each expense item is evaluated item by item using the medical insurance catalog matching and rule-based judgment methods, and a medical insurance attribution function is set. Its value selection rules are as follows: When the expense item is included in the medical insurance catalog, the value is 1; When the expense item is not included in the medical insurance catalog, the value is 0; Based on this, each expense item is divided into: expenses covered by medical insurance and out-of-pocket expenses.

7. The method for joint evaluation of medical insurance costs and efficacy for surgical pathway optimization according to claim 3, characterized in that, In step S2, when performing node cost aggregation, all cost items within a node are aggregated to obtain a node-level cost representation: ; Simultaneously, we obtain: ； ； in: Total cost of the node; Node medical insurance expenses; Node self-payment fee.

8. The method for joint evaluation of medical insurance costs and efficacy for surgical pathway optimization according to claim 3, characterized in that, In step S2, when performing path location representation processing based on time features, the time features from step S1 are used as a basis. The time percentage normalization method is used to calculate the time percentage of a node in the overall path: ； Further construct time-weighted cost: 。 9. A method for jointly evaluating medical insurance costs and treatment efficacy for surgical pathway optimization according to claim 3, characterized in that, In step S2, when constructing the path cost distribution structure, the path cost distribution structure is built based on the above node-level cost results, according to the order of the path nodes, forming an ordered sequence: ； Simultaneously construct a time-weighted cost series: 。 10. A method for jointly evaluating medical insurance costs and treatment efficacy for surgical pathway optimization according to claim 1, characterized in that, Step S3, based on the established path structure and cost distribution structure, incorporates medical support and transportation equipment factors, as well as cost constraints, into the efficacy analysis to derive the path efficacy contribution structure, including the node efficacy contribution sequence. Overall therapeutic value of the pathway ; Step S4 maps the path cost distribution structure from step S2 to the path efficacy contribution structure from step S3 using the same numerical scale and the same node indexing system, thus deriving a standardized path evaluation benchmark: ; Step S5, based on the unified scale expression of cost and efficacy completed in Step S4, integrates the cost and efficacy calculations for each pathway node and forms a unified joint assessment result at the pathway level: ; in: : Comprehensive evaluation value of the route; Average cost per route; : Average efficacy level of the pathway.

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