CN-121641494-B - Intelligent interaction method and system for improving cooperation of patient service and information in hospital

CN121641494BCN 121641494 BCN121641494 BCN 121641494BCN-121641494-B

Abstract

The invention relates to the technical field of patient service management, in particular to an intelligent interaction method and system for improving the coordination of patient service and information in a hospital, comprising the following steps: constructing a three-dimensional feature vector of a hospital service state, deploying a demand guide response strategy, setting a dual-delay gradient under a service collaborative framework, loading the optimized interaction response parameters to a terminal cluster in combination with a consultation constraint condition, and configuring a communication interaction protocol and a collaborative semantic mapping rule corresponding to the information collaborative network. The method solves the technical problems that the existing service response mode is solidified, the coupling relation between the core demand of the patient and the medical care resource supply is difficult to accurately mine, and the resource scheduling decision is delayed from the service dynamic change, so that the technical effects of constructing a three-dimensional feature vector containing the patient, the medical care and the environment, extracting the coupling relation between the core demand feature of the patient and the medical care resource supply feature, dynamically deploying the demand guiding strategy and collecting the interaction parameters, and improving the response efficiency and the information collaborative reliability of the in-hospital service are realized.

Inventors

JIA JIE
DI FEI
SONG WEI
LIU XIAOJIAO

Assignees

首都医科大学附属首都儿童医学中心

Dates

Publication Date: 20260508
Application Date: 20251208

Claims (7)

1. An intelligent interaction method for promoting the cooperation of in-hospital patient service and information, which is characterized by comprising the following steps: Collecting patient treatment information, medical care resource states and in-hospital environment parameters, and constructing three-dimensional feature vectors of in-hospital service states; based on the three-dimensional feature vector of the hospital service state, deploying a demand guide response strategy, tracking the interaction behavior of the patient, and collecting interaction response parameters; At the edge computing node in the hospital, aligning the time sequence data of the treatment with the patient service log stream, extracting the coupling relation between the core demand characteristics of the patient and the medical care resource supply characteristics, and setting a double delay gradient under the service collaborative framework by combining the demand guidance response strategy; Based on the dual-delay gradient under the service collaborative framework, dynamically optimizing the interaction response parameters in combination with the consultation constraint condition, loading the optimized interaction response parameters into a terminal cluster, and configuring a communication interaction protocol and a collaborative semantic mapping rule corresponding to the information collaborative network; Wherein, and track patient interaction behavior, collect interaction response parameter, still include: setting a patient behavior dynamics analysis unit, wherein the patient behavior dynamics analysis unit is used for extracting task propulsion rate and operation path offset from a multi-mode interaction log; Tracking a cross-equipment service jump track of a patient among a self-service terminal, a mobile application service interface and a ward screen, and extracting a waiting tolerance threshold of a key node; Constructing a service load portrait according to the task advancing rate and the operation path offset degree and combining the waiting tolerance threshold, and dynamically adjusting content pushing frequency, information density and guiding voice complexity in the interactive response parameters based on the service load portrait; Wherein, still include: Establishing an associated mapping model of patient behavior characteristics and medical care resource occupation intensity, and automatically triggering a pacifying intervention strategy of a waiting area when the task interruption frequency or rollback operation sudden increase exceeding a preset safety threshold is detected; meanwhile, adopting a federal edge learning architecture, under the conditions that end-side data are encrypted and original logs do not go out of a domain, aggregating interactive satisfaction scores and behavior residual data of a plurality of patients in a disease area, and iteratively optimizing attention mechanism weight parameters of the patient behavior dynamics analysis unit; wherein at the in-hospital edge computing node, aligning the time series data of the visit with the patient service log stream comprises: Dynamically adjusting the time window denoising parameters of the patient service log stream according to the outpatient service flow, and embedding a service event synchronous control node in a log preprocessing stage; And at the edge computing node in the hospital, the service event synchronous control node is utilized to align registration completion time, check reservation triggering time and terminal first interaction response starting time.
2. The intelligent interaction method for promoting the coordination of the patient service and the information in the hospital according to claim 1, wherein a generator built in the service coordination framework is used for simulating an interaction response sequence under a standard treatment process; And the identifier built in the service collaborative framework is used for identifying abnormal deviation events of the service by the distribution difference of the interaction response parameters of the in-hospital patient service interface and the interaction response sequence.
3. The intelligent interaction method for enhancing the coordination of patient services and information in a hospital of claim 1, wherein the method further comprises: deploying a dynamic dimension-reducing encoder, and adaptively selecting characteristic dimension-reducing dimensions according to the historical treatment frequency of a patient, the treatment type of the patient and the chronic degree of the disease; meanwhile, updating a reference interaction template library, and triggering online reconstruction of a service semantic feature space if service request combination which is overlapped by multiple items of a cross-department and is dynamically upgraded in emergency degree is detected.
4. An intelligent interaction method for enhancing the coordination of patient services and information within a hospital as claimed in claim 3, wherein the on-line reconstruction of the service semantic feature space is triggered, and wherein the method further comprises: Acquiring a real-time moving track of a patient in a hospital by using an indoor positioning device; and performing cross-correlation analysis on the real-time moving track and the service request time sequence, and dynamically setting a collaborative time sequence instruction of pushing the multi-terminal content by locking the arrival time of the key service node comprising the inspection room gate and the pharmacy window.
5. The intelligent interaction method for improving the coordination of patient services and information in a hospital of claim 4, wherein the coordinated timing instructions of the multi-terminal content push are dynamically set, and the method further comprises: When detecting that the space-time dislocation exists between the position state of the patient and the terminal service response, activating a time sequence compensation strategy, and carrying out projection correction on the three-dimensional feature vector of the hospital service state.
6. The intelligent interaction method for enhancing the coordination of patient services and information in a hospital of claim 5, wherein the method further comprises: under the load service state, the acquisition granularity and the reporting frequency of the patient service log stream are dynamically determined according to the residual electric quantity of the equipment; When the reconstructed residual error of the three-dimensional feature vector of the service state in the hospital exceeds a dynamic threshold set based on the combination of the electric quantity state and the service key grade, activating a sparse interaction sampling mode under the corresponding acquisition granularity; And in the information cooperative network, executing a piecewise linear scheduling strategy under the joint optimization target of the terminal energy consumption constraint and the service quality guarantee index in the sparse interactive sampling mode.
7. An intelligent interactive system for enhancing the coordination of patient services and information in a hospital, comprising the steps of implementing an intelligent interactive method for enhancing coordination of patient services and information in a hospital as claimed in any one of claims 1 to 6, said system comprising: The three-dimensional feature vector construction module is used for collecting patient treatment information, medical care resource states and hospital environment parameters and constructing three-dimensional feature vectors of the hospital service states; the interactive response parameter collection module is used for deploying a demand guide response strategy based on the three-dimensional feature vector of the hospital service state, tracking the interactive behavior of a patient and collecting interactive response parameters; The coupling relation extracting module is used for aligning the diagnosis time sequence data with the patient service log stream at the edge computing node in the hospital, extracting the coupling relation between the core demand characteristics of the patient and the medical care resource supply characteristics, and setting a double delay gradient under the service collaborative framework by combining the demand guidance response strategy; And the terminal cluster loading module is used for dynamically optimizing the interaction response parameters based on the dual-delay gradient under the service collaborative framework and combining with the diagnosis constraint conditions, loading the optimized interaction response parameters to the terminal clusters, and configuring the communication interaction protocol and the collaborative semantic mapping rule corresponding to the information collaborative network.

Description

Intelligent interaction method and system for improving cooperation of patient service and information in hospital Technical Field The invention relates to the technical field related to patient service management, in particular to an intelligent interaction method and system for improving the coordination of patient service and information in a hospital. Background The population is ageing and aggravated, chronic patients are increased, so that the flow of the hospital clinic is continuously increased, the requirements of multi-department collaboration and cross-scene service are more frequent, however, the current hospital patient service and information collaboration mechanism is imperfect, the service requirements under digital transformation are difficult to adapt, the existing service carriers such as self-service terminals, mobile applications and the like mostly adopt immobilized interaction modes, the resource scheduling is lagged, the data processing capacity at the edge side is insufficient, the continuous improvement of the service capacity is difficult to realize under the premise of ensuring the data safety, and the improvement of the hospital service quality and the information collaboration efficiency is restricted. In summary, the prior art has the technical problems that the existing service response mode is solidified and poor in adaptability, the coupling relation between the core requirement of the patient and the medical care resource supply is difficult to accurately mine, and the resource scheduling decision is delayed from the service dynamic change. Disclosure of Invention The application provides an intelligent interaction method and system for improving the coordination of patient service and information in a hospital, and aims to solve the technical problems that an existing service response mode in the prior art is solidified and poor in adaptability, the coupling relation between the core requirement of a patient and medical care resource supply is difficult to accurately mine, and a resource scheduling decision is delayed from service dynamic change. In view of the above problems, the technical scheme for realizing the application is as follows: The application provides an intelligent interaction method for improving the coordination of patient service and information in a hospital, which comprises the steps of collecting patient treatment information, medical care resource states and hospital environment parameters, constructing three-dimensional feature vectors of the patient treatment state, deploying a demand guiding response strategy based on the three-dimensional feature vectors of the patient treatment state, tracking patient interaction behaviors, collecting interaction response parameters, aligning treatment time sequence data with patient service log streams at an edge computing node, extracting coupling relations between core demand features of the patient and medical care resource supply features, setting double delay gradients under a service coordination frame by combining the demand guiding response strategy, dynamically optimizing the interaction response parameters by combining treatment constraint conditions by combining the double delay gradients under the service coordination frame, loading the optimized interaction response parameters into a terminal cluster, and configuring communication interaction protocols and coordination semantic mapping rules corresponding to a network. Preferably, the generator arranged in the service collaborative framework is used for simulating an interaction response sequence under a standard treatment process, and the discriminator arranged in the service collaborative framework is used for identifying a service abnormality deviation event according to the distribution difference between the interaction response parameters of the in-hospital patient service interface and the interaction response sequence. Preferably, a patient behavior dynamics analysis unit is set, wherein the patient behavior dynamics analysis unit is used for extracting task pushing rate and operation path offset from a multi-mode interaction log, tracking a cross-equipment service jump track of a patient among a self-service terminal, a mobile application service interface and a ward screen, extracting a waiting tolerance threshold of a key node, constructing a service load portrait according to the task pushing rate and the operation path offset and combining the waiting tolerance threshold, and dynamically adjusting content pushing frequency, information density and guiding speech complexity in the interaction response parameters based on the service load portrait. And meanwhile, under the conditions that end-side data are encrypted and original logs do not go out of a domain, aggregating interactive satisfaction degree scores and behavior residual data of a plurality of sick area patients, and iteratively optimizing the attention mechanism weight param