CN-122025059-A - Medical care joint follow-up outpatient method and related equipment for chronic patients of children

CN122025059ACN 122025059 ACN122025059 ACN 122025059ACN-122025059-A

Abstract

The invention discloses a medical care joint follow-up visit method and related equipment for children chronic patients, which are characterized in that multi-source follow-up visit data formed by children in outpatient service, nursing follow-up visit and home monitoring scenes are obtained, a set of follow-up states characterizing the disease state, the care execution state, and the home care state simultaneously is constructed. Generating a follow-up execution strategy comprising the cooperative relationship of doctor diagnosis and treatment actions, nursing intervention actions and home cooperation actions, continuously receiving new follow-up data in the execution process, and dynamically updating a follow-up state set. When the new follow-up state meets the preset state transition condition, automatically triggering the reconstruction of the follow-up execution strategy, and synchronously applying the reconstructed strategy to the medical care end and the home end. The method realizes the cooperative consistency and dynamic adjustment of the follow-up actions of the medical, nursing and home parties, and solves the problems of insufficient cooperation, data fragmentation and intervention lag in the follow-up of the traditional chronic diseases of children.

Inventors

WANG CHENGSHUANG
ZHU ZHENYUN

Assignees

华中科技大学同济医学院附属同济医院

Dates

Publication Date: 20260512
Application Date: 20260214

Claims (10)

1. A method for medical care joint follow-up clinic for a child chronic patient, which is characterized by comprising the following steps: Acquiring multi-source follow-up data formed by the child in an outpatient scene, a nursing follow-up scene and a home monitoring scene; constructing a follow-up state set for representing the disease state, the nursing execution state and the family care state of the child patient based on the multi-source follow-up data; generating a follow-up execution strategy corresponding to the current follow-up state based on the follow-up state set, wherein the follow-up execution strategy at least comprises a cooperative relationship among doctor diagnosis and treatment actions, nursing intervention actions and family cooperation actions; Continuously receiving new follow-up data in the implementation process of the follow-up execution strategy, and updating the follow-up state set based on the new follow-up data to form a new follow-up state; When the new follow-up state meets the preset state transition condition, automatically triggering the reconstruction of the follow-up execution strategy, and synchronously applying the reconstructed follow-up execution strategy to the medical care end and the home end.
2. The method of claim 1, wherein constructing a set of follow-up states for characterizing a child patient disease state, a care execution state, and a home care state based on the multi-source follow-up data comprises: Carrying out data type identification and semantic classification on the multi-source follow-up data, and dividing the multi-source follow-up data into disease related data, nursing related data and household care related data; based on the disease-related data, extracting disease state parameters for reflecting the change trend of the infant illness state, and mapping the disease state parameters into disease state identifiers; based on the nursing related data, extracting nursing execution parameters for reflecting the implementation degree of nursing measures, and mapping the nursing execution parameters into nursing execution state identifiers; Based on the home care related data, extracting home care parameters for reflecting the home care capability and the compliance, and mapping the home care parameters into home care state identifiers; and carrying out association combination on the disease state identifier, the nursing execution state identifier and the family care state identifier to form a follow-up state set for uniformly representing the current follow-up state of the child patient.
3. The method of joint follow-up for pediatric chronic patient care according to claim 1, wherein the generating a follow-up execution strategy corresponding to a current follow-up state based on the set of follow-up states comprises: Analyzing state identifiers representing the current disease state, nursing execution state and family care state of the child patient in the follow-up state set to form a state analysis result for strategy generation; Based on the state analysis result, determining a follow-up control target matched with the current follow-up state, wherein the follow-up control target at least comprises a disease control target, a nursing implementation target and a family cooperation target; Around the follow-up control target, respectively generating a corresponding medical execution sub-strategy, a corresponding nursing execution sub-strategy and a corresponding family execution sub-strategy; performing collaborative constraint matching on the medical execution sub-strategy, the nursing execution sub-strategy and the home execution sub-strategy, eliminating execution conflict among sub-strategies, and forming a consistent strategy combination; and determining the strategy combination matched by the cooperative constraint as the follow-up execution strategy.
4. A pediatric chronic patient healthcare joint follow-up clinic method as defined in claim 3, wherein determining a follow-up control target that matches a current follow-up status based on the status resolution results comprises: Respectively acquiring state identifiers corresponding to the disease state, the nursing execution state and the family care state of the child patient from the state analysis result, and distributing corresponding state weights for the state identifiers, wherein the state weights are used for representing the influence degree of the states in the current follow-up stage; Constructing a target evaluation function based on the state identifier and the state weight, and performing quantitative calculation on the disease control requirement value, the nursing implementation requirement value and the family cooperation requirement value in the current follow-up state to obtain a target evaluation result; Comparing the target evaluation result with a preset target threshold interval, and determining a disease control priority, a nursing implementation priority and a family cooperation priority according to the comparison result, wherein the disease control priority, the nursing implementation priority and the family cooperation priority are used for reflecting the relative importance degree of different follow-up targets; Generating a disease control target, a care implementation target and a home coordination target respectively based on the disease control priority, the care implementation priority and the home coordination priority; And combining the disease control target, the nursing implementation target and the family cooperation target to form the follow-up control target.
5. The method of claim 3, wherein the collaborative constraint matching is performed on the medical execution sub-strategy, the nursing execution sub-strategy and the home execution sub-strategy to eliminate execution conflicts among sub-strategies and form a consistent strategy combination, and the method comprises the following steps: acquiring execution elements in the medical execution sub-strategy, the nursing execution sub-strategy and the home execution sub-strategy, and normalizing the execution elements into a strategy element set, wherein the execution elements at least comprise a follow-up frequency element, a task item element and a reminding synchronization element; Based on the policy element set, identifying conflict types among sub-policies, wherein the conflict types at least comprise time conflicts, responsibility conflicts and dependency conflicts, the time conflicts are used for representing competing relations of different sub-policies on the same follow-up time window, the responsibility conflicts are used for representing inconsistent responsibility boundaries between medical care actions and family cooperation actions, and the dependency conflicts are used for representing that the execution preconditions of one sub-policy are not satisfied by the other sub-policy; generating a collaboration constraint condition aiming at the conflict type, wherein the collaboration constraint condition at least comprises a time constraint condition, a responsibility constraint condition and a dependency constraint condition, and binding the collaboration constraint condition to the policy element set; Based on the collaborative constraint condition, performing conflict resolution processing on the medical execution sub-policy, the nursing execution sub-policy and the home execution sub-policy to output candidate policy combinations meeting the collaborative constraint condition; And executing policy consistency check on the candidate policy combination to confirm cooperative consistency of the candidate policy combination among medical execution, nursing execution and home execution, and determining the candidate policy combination passing the policy consistency check as the consistent policy combination.
6. The method of claim 1, wherein the continuously receiving new follow-up data and updating the set of follow-up states based on the new follow-up data to form new follow-up states comprises: continuously receiving new follow-up data from an outpatient follow-up scene, a nursing follow-up scene and a home monitoring scene; performing time consistency verification on the new follow-up data, and classifying and sorting the new follow-up data according to data sources and data semantics to form standardized incremental follow-up data; Comparing and analyzing the increment follow-up data with the history follow-up data stored in the current follow-up period, and extracting state difference parameters for reflecting follow-up state change; Based on the state difference parameters, judging the stability change of each state identifier in the follow-up state set, and determining the corresponding state evolution direction; And carrying out reconstruction updating on the follow-up state set according to the state evolution direction to form a new follow-up state used for representing the current follow-up stage.
7. The method for medical care joint follow-up clinic for children chronic patients according to claim 1, wherein the automatic triggering of the reconstruction of the follow-up execution strategy and the synchronous application of the reconstructed follow-up execution strategy to the medical care end and the home end comprises the following steps: Judging whether the follow-up state set meets a preset strategy reconstruction triggering condition or not based on the new follow-up state; When the strategy reconstruction triggering condition is judged to be met, generating a strategy reconstruction request based on the change condition of each state identifier in the follow-up state set; Analyzing the strategy reconstruction request, determining follow-up execution elements which need to be adjusted, and forming a reconstructed follow-up execution strategy; consistency verification is carried out on the reconstructed follow-up execution strategy to confirm that the reconstructed follow-up execution strategy is consistent in coordination among medical execution, nursing execution and home execution; After the consistency verification is completed, the reconstructed follow-up execution strategy is synchronously issued to the medical care end and the home end, so that the medical care end and the home end execute updated follow-up flow based on the reconstructed follow-up execution strategy.
8. A pediatric chronic patient healthcare joint follow-up outpatient system, comprising: the acquisition unit is used for acquiring multi-source follow-up data formed by the child in an outpatient scene, a nursing follow-up scene and a home monitoring scene; The construction unit is used for constructing a follow-up state set used for representing the disease state, the nursing execution state and the home care state of the child patient based on the multi-source follow-up data; The generation unit is used for generating a follow-up execution strategy corresponding to the current follow-up state based on the follow-up state set, wherein the follow-up execution strategy at least comprises a cooperative relationship among doctor diagnosis and treatment actions, nursing intervention actions and home cooperation actions; The updating unit is used for continuously receiving new follow-up data in the implementation process of the follow-up execution strategy and updating the follow-up state set based on the new follow-up data so as to form a new follow-up state; and the reconstruction unit is used for automatically triggering the reconstruction of the follow-up execution strategy when the new follow-up state meets the preset state transition condition, and synchronously applying the reconstructed follow-up execution strategy to the medical care end and the home end.
9. An electronic device comprising a memory and a processor, wherein the processor is adapted to implement the steps of the pediatric chronic patient healthcare joint follow-up outpatient method of any one of claims 1-7 when executing a computer program stored in the memory.
10. A computer readable storage medium having stored thereon a computer program, wherein the computer program when executed by a processor implements the steps of the pediatric chronic patient healthcare joint follow-up outpatient method of any one of claims 1-7.

Description

Medical care joint follow-up outpatient method and related equipment for chronic patients of children Technical Field The present disclosure relates to the field of health management, and more particularly, to a method and apparatus for joint follow-up visit of chronic patients in children. Background The children chronic diseases such as epilepsy, diabetes, asthma and the like have the characteristics of long disease course, large management period span and high degree of dependence on families, and follow-up visit management quality directly influences the disease control and life quality of the children. The existing chronic disease follow-up system is mainly based on an adult scene, physiological characteristics, disease manifestations and family care demand differences of children in different development stages are not fully considered, follow-up content is not matched with actual demands of the children, and personalized management capability is insufficient. Meanwhile, doctors and nurses still take offline communication and decentralized recording as main materials, a systematic collaborative work flow is lacked, and medical advice, nursing guidance and home feedback are difficult to link in time, so that the continuity of follow-up intervention is affected. On the other hand, multisource data such as clinic, nursing and home monitoring are stored in a scattered manner, a unified integration and real-time interaction mechanism is lacked, and comprehensive and timely follow-up decisions are difficult to support. In addition, the follow-up schedule adopts a fixed frequency and a static mode, cannot be dynamically adjusted according to the change of illness state and family care capacity, and is easy to cause insufficient intervention or resource waste. Therefore, it is necessary to provide a dynamic follow-up management technical scheme for children chronic disease characteristics, fusion of multi-source data and reinforcement of medical care coordination. Disclosure of Invention In the summary, a series of concepts in a simplified form are introduced, which will be further described in detail in the detailed description. The summary of the application is not intended to define the key features and essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter. In a first aspect, the application provides a method for medical care joint follow-up clinic for children chronic patients, comprising the following steps: Acquiring multi-source follow-up data formed by the child in an outpatient scene, a nursing follow-up scene and a home monitoring scene; constructing a follow-up state set for representing the disease state, the nursing execution state and the family care state of the child patient based on the multi-source follow-up data; Generating a follow-up execution strategy corresponding to the current follow-up state based on the follow-up state set, wherein the follow-up execution strategy at least comprises a cooperative relationship among doctor diagnosis and treatment actions, nursing intervention actions and family cooperation actions; continuously receiving new follow-up data in the implementation process of the follow-up execution strategy, and updating the follow-up state set based on the new follow-up data to form a new follow-up state; when the new follow-up state meets the preset state transition condition, automatically triggering the reconstruction of the follow-up execution strategy, and synchronously applying the reconstructed follow-up execution strategy to the medical care end and the home end. In a possible embodiment, the constructing a follow-up state set for characterizing a disease state, a care execution state, and a home care state of the infant based on the multi-source follow-up data includes: Carrying out data type identification and semantic classification on the multi-source follow-up data, and dividing the multi-source follow-up data into disease-related data, nursing-related data and household care-related data; Based on the related disease data, extracting disease state parameters for reflecting the change trend of the infant illness state, and mapping the disease state parameters into disease state identifiers; based on the nursing related data, extracting nursing execution parameters for reflecting the implementation degree of nursing measures, and mapping the nursing execution parameters into nursing execution state identifiers; based on the related data of the family care, extracting family care parameters for reflecting the family care capability and the compliance, and mapping the family care parameters into family care state identifiers; and performing association combination on the disease state identifier, the nursing execution state identifier and the family care state identifier to form a follow-up state set for uniformly representing the current follow-up state of the child pa