CN-122000003-A - Assessment method for cost control of hospital management

CN122000003ACN 122000003 ACN122000003 ACN 122000003ACN-122000003-A

Abstract

The invention relates to the technical field of hospital management and discloses a method for evaluating cost control of hospital management, which comprises the steps of slicing a process state data stream in a multi-granularity behavior mode, and performing context-aware analysis on sliced data to obtain microscopic cost causes; the method comprises the steps of carrying out time-based analysis on a result data stream to construct a dynamic mapping relation, analyzing a conduction relation between microscopic cost dynamic factors according to the dynamic mapping relation, taking the conduction relation as a side, taking the microscopic cost dynamic factors as nodes, constructing a cost dynamic conduction map, carrying out strategy inverse facts deduction on management intervention measures based on the cost dynamic conduction map to obtain cost-effect panoramic simulation, analyzing deviation between the whole-network equilibrium state change and a historical normal state interval, evaluating cost structure robustness by combining external market pressure test data, and formulating a composite cost control strategy according to the cost-effect panoramic simulation and the cost structure robustness.

Inventors

WANG ZHEN

Assignees

常州市第二人民医院
医顺通信息科技(江苏)有限公司

Dates

Publication Date: 20260508
Application Date: 20260130

Claims (10)

1. A method of assessing cost control for hospital management, the method comprising: s1, performing multi-granularity behavior slicing on a process state data stream of a target hospital, and performing context sensing analysis on sliced data to obtain a microscopic cost cause of the target hospital; S2, carrying out time-based analysis on the result state data stream of the target hospital based on the microscopic cost trend, so as to construct a dynamic mapping relation between the microscopic cost trend and the result state data stream; S3, analyzing the conduction relation between the microscopic cost trends according to the dynamic mapping relation, taking the conduction relation as an edge, taking the microscopic cost trends as nodes, and constructing a cost dynamic conduction map of the target hospital; S4, carrying out strategy counterfactual deduction on the management intervention measures of the target hospital based on the cost dynamic conduction map to obtain the cost influence panoramic simulation of the target hospital; S5, analyzing deviation between the whole network equilibrium state change caused by the management intervention measures and a historical normal state interval in the target hospital, and evaluating the cost structure robustness of the target hospital under the management intervention measures by combining external market pressure test data of the target hospital; and S6, formulating a composite cost control strategy of the target hospital according to the cost-affected panoramic simulation and the cost structure robustness.
2. The method for evaluating cost control of hospital management according to claim 1, wherein the step of performing multi-granularity behavioral slicing on a process state data stream of a target hospital and performing context-aware analysis on the sliced data to obtain microscopic cost trends of the target hospital comprises: acquiring a doctor's advice execution track, a device use log and a personnel line record of a target hospital to obtain a process state data stream of the target hospital; carrying out unified space-time reference alignment on the process state data stream to obtain synchronous process state data of the target hospital; according to the time window of business occurrence in the target hospital, initially dividing the synchronous process state data to obtain a primary data slice of the target hospital; Carrying out refined decomposition on the primary data slice to obtain a secondary data slice of the target hospital; And performing pattern matching on the secondary data slices, and performing causal reasoning on the matched patterns to obtain microscopic cost causes of the target hospital.
3. The method of assessing cost control for hospital management of claim 1, wherein said performing a temporal resolution of a result state data stream of said target hospital based on said microscopic cost trends to construct a dynamic mapping between said microscopic cost trends and said result state data stream comprises: acquiring a financial settlement record and a material consumption list of the target hospital to obtain a result state data stream of the target hospital; Time alignment is carried out on the result state data stream and the microscopic cost dynamic factor, so as to obtain a dual data set of the target hospital; Performing collaborative fluctuation mode analysis on the dual data set to obtain hysteresis correlation and mode matching degree of the dual data set; determining the influence intensity of the microscopic cost factor according to the hysteresis correlation and the pattern matching degree; carrying out time-based tracking on the influence intensity to obtain a change rule of the influence intensity; and carrying out association analysis on the microscopic cost dynamic cause and the result state data stream based on the influence intensity and the change rule to obtain a dynamic mapping relation between the microscopic cost dynamic cause and the result state data stream.
4. The method for evaluating cost control of hospital management according to claim 1, wherein said analyzing a conduction relation between said microscopic cost trends based on said dynamic mapping relation and constructing a cost dynamic conduction map of said target hospital with said conduction relation as a side and said microscopic cost trends as nodes comprises: screening out the microcosmic cost dynamic factors with the same time sequence according to the dynamic mapping relation to obtain a to-be-analyzed dynamic factor pair of the target hospital; carrying out collaborative fluctuation analysis on the to-be-analyzed dynamic factor pairs, and identifying potential conduction links of the microscopic cost dynamic factors; Performing global networking verification on the potential conduction links, and performing reverse constraint on the verified conduction links according to the dynamic mapping relation to obtain a conduction relation between the micro cost causes; Taking the conduction relation as a directed edge and taking the microscopic cost factor as a node; and connecting the directed edge and the node according to the business logic of the target hospital, and constructing a cost dynamic conduction map of the target hospital.
5. The method of assessing a hospital managed cost control of claim 4 wherein said collaborative wave analysis of said pair of trends to be analyzed identifies potential conductive links of said microscopic cost trends comprising: counting the frequency of the to-be-analyzed dynamic factor pairs to obtain a frequency index sequence of the microscopic cost dynamic factor; carrying out trend term decomposition on the frequency index sequence to obtain a fluctuation component of the microscopic cost dynamic factor; Performing time lag estimation on the fluctuation component to obtain a leading-lagging relation and a time difference of the microscopic cost dynamic factor; Based on the leading and lagging relation, carrying out state transition analysis on the to-be-analyzed dynamic factor pair to obtain a fluctuation mode conversion rule of the microscopic cost dynamic factor; And synthesizing the lead-lag relation, the time difference and the fluctuation mode conversion rule, and quantitatively evaluating the causal influence direction and the strength of the moving factor pair to be analyzed to obtain the potential conduction link of the microscopic cost moving factor.
6. The method for evaluating cost control of hospital management according to claim 1, wherein the performing policy counterfactual deduction on the management intervention of the target hospital based on the cost dynamic conduction map to obtain a cost-impact panoramic simulation of the target hospital comprises: Encoding management intervention measures of the target hospital into intervention instructions of the target hospital; Mapping the intervention instruction into an initial state adjustment quantity of a target node in the cost dynamic conduction map; Traversing the directed edge of the cost dynamic conduction map from the target node, and determining a conduction path and a conduction time sequence of the initial state adjustment quantity to obtain a state change conduction sequence of the target hospital; based on the state change conduction sequence, carrying out iterative updating on a downstream node of the target node, and tracking a loop feedback path generated in the iterative updating process in real time; According to the circulating feedback path, adjusting the state value of the relevant node in the cost dynamic conduction map until the state change of the relevant node tends to be stable; and integrating time sequence evolution records of the related nodes and steady-state distribution of the stabilized nodes to obtain the cost-effect panoramic simulation of the target hospital.
7. The method for evaluating cost control of hospital management according to claim 1, wherein said analyzing deviations of said management intervention induced global equilibrium state changes from historical normalcy intervals in said target hospital, in combination with external market pressure test data of said target hospital, evaluates cost structure robustness of said target hospital under said management intervention, comprises: extracting node stable values of a cost dynamic conduction map in the target hospital from the cost-affected panoramic simulation of the target hospital to obtain a current equilibrium state vector of the target hospital; comparing and analyzing the state value of the current equilibrium state vector with the historical normal interval of the target hospital to obtain the state deviation degree and the deviation direction of the target hospital; Based on the cost dynamic conduction map, panoramic mapping is carried out on the state deviation degree and the deviation direction, and a multidimensional deviation spectrum of the target hospital is obtained; analyzing external market pressure test data of the target hospital, and mapping the external market pressure test data to the cost dynamic conduction map to obtain a standardized pressure impact scene of the target hospital; applying the standardized pressure impact scene to the current equilibrium state vector to obtain a multi-scenario pressure test response sequence of the target hospital; and determining the cost structure robustness of the target hospital according to the multidimensional deviation spectrum and the multi-scenario pressure test response sequence.
8. The method of assessing a cost control of hospital management of claim 7 wherein said determining a cost structural robustness of said target hospital from said multidimensional deviation spectrum and said sequence of multi-scenario stress test responses comprises: scalar convergence is carried out on the multidimensional deviation spectrum, and a standard deviation value of the multidimensional deviation spectrum is obtained; Carrying out toughness parameter quantification on the pressure scenes in the multi-scene pressure test response sequence to obtain scene elasticity ratio of the multi-scene pressure test response sequence; Calculating initial cost structure robustness of the target hospital according to the standard deviation value and the scene elasticity ratio; And carrying out consistency check on the initial cost structure robustness to obtain the cost structure robustness of the target hospital.
9. The method of assessing a hospital managed cost control of claim 8 wherein the initial cost structure robustness is calculated as: ; Wherein, the Representing the initial cost structure robustness of the described, A total number of nodes representing the multi-dimensional deviation spectrum, Represent the first The standard deviation values of the individual nodes, Representing the total number of pressure scenarios in question, Represent the first The scene elasticity ratio of each of the pressure scenes, Represents a natural constant of the natural product, Representing a natural logarithmic function.
10. The method of assessing cost control of hospital management of claim 1, wherein said formulating a composite cost control strategy for said target hospital based on said cost-effective panoramic simulation and said cost structure robustness comprises: Performing strategy influence reverse analysis on the cost influence panoramic simulation to obtain a core regulation node of the target hospital; Combining the cost structure robustness assessment result and the core regulation node to obtain a candidate action node set of the target hospital; performing critical deconstructment on the candidate action node set to obtain a basic strategy atom of the target hospital; based on the cost dynamic conduction map of the target hospital, combining and splicing the basic strategy atoms to obtain a composite strategy scheme of the target hospital; and carrying out multi-target strategy optimization on the composite strategy scheme to obtain the composite cost control strategy of the target hospital.

Description

Assessment method for cost control of hospital management Technical Field The invention relates to the technical field of hospital management, in particular to a cost control evaluation method for hospital management. Background The existing cost control evaluation method for hospital management has a remarkable short board on the data processing level, lacks the normal multi-granularity splitting and deep context perception analysis on process state data streams generated in the operation process of the hospital, is difficult to accurately position microcosmic cost causes distributed in various business links, and the coarseness of the data processing leads to the identification of cost influencing factors to have one-sided performance and hysteresis, so that the basic data support of the cost control evaluation is insufficient, and the overall efficiency and the accuracy of the evaluation work are directly restricted. The traditional cost control evaluation method fails to construct a dynamic association mechanism between microscopic cost causes and result state data streams, and lacks systematic analysis on the conduction relation between the cost causes, so that complete logic of cost formation and conduction cannot be comprehensively presented, the traditional method does not develop effective panoramic simulation and robustness verification aiming at management intervention measures, the formulated cost control strategy is difficult to adapt to complex business processes and external market fluctuation, the pertinence and the adaptability of the strategy are insufficient, the refinement and sustainable management and control of hospital cost are difficult to realize, and therefore, how to improve the refinement degree of hospital management cost control becomes a problem to be solved urgently. Disclosure of Invention The present invention provides a method for evaluating cost control of hospital management to solve the problems set forth in the background art. To achieve the above object, the present invention provides a method for evaluating cost control of hospital management, comprising: s1, performing multi-granularity behavior slicing on a process state data stream of a target hospital, and performing context sensing analysis on sliced data to obtain a microscopic cost cause of the target hospital; S2, carrying out time-based analysis on the result state data stream of the target hospital based on the microscopic cost trend, so as to construct a dynamic mapping relation between the microscopic cost trend and the result state data stream; S3, analyzing the conduction relation between the microscopic cost trends according to the dynamic mapping relation, taking the conduction relation as an edge, taking the microscopic cost trends as nodes, and constructing a cost dynamic conduction map of the target hospital; S4, carrying out strategy counterfactual deduction on the management intervention measures of the target hospital based on the cost dynamic conduction map to obtain the cost influence panoramic simulation of the target hospital; S5, analyzing deviation between the whole network equilibrium state change caused by the management intervention measures and a historical normal state interval in the target hospital, and evaluating the cost structure robustness of the target hospital under the management intervention measures by combining external market pressure test data of the target hospital; and S6, formulating a composite cost control strategy of the target hospital according to the cost-affected panoramic simulation and the cost structure robustness. In a preferred embodiment, the slicing the process state data stream of the target hospital with multi-granularity behavior and performing context-aware analysis on the sliced data to obtain the microscopic cost factor of the target hospital includes: acquiring a doctor's advice execution track, a device use log and a personnel line record of a target hospital to obtain a process state data stream of the target hospital; carrying out unified space-time reference alignment on the process state data stream to obtain synchronous process state data of the target hospital; according to the time window of business occurrence in the target hospital, initially dividing the synchronous process state data to obtain a primary data slice of the target hospital; Carrying out refined decomposition on the primary data slice to obtain a secondary data slice of the target hospital; And performing pattern matching on the secondary data slices, and performing causal reasoning on the matched patterns to obtain microscopic cost causes of the target hospital. In a preferred embodiment, the performing, based on the microscopic cost trend, temporal analysis on the result state data stream of the target hospital to construct a dynamic mapping relationship between the microscopic cost trend and the result state data stream includes: acquiring a financial settlement record