CN-121983280-A - VPU system and method for centralized management of pain patient information

CN121983280ACN 121983280 ACN121983280 ACN 121983280ACN-121983280-A

Abstract

The invention relates to the technical field of health data processing, in particular to a VPU system and a method for centralized management of pain patient information. The method comprises the steps of collecting multi-source state data and current pain scores, analyzing sleep rhythm disorder degree and extreme behavior product based on the multi-source state data, calculating behavior analysis severity, determining heart rate characteristic vision degree based on the multi-source state data, calculating a disease condition change stability coefficient according to the fact that the severity is analyzed by the behavior analysis severity and the counted times of high probability of pain influence, calculating pain care urgency degree according to the current pain scores and time intervals from last nursing, calculating a VPU monitoring requirement index according to the pain care urgency degree and the disease condition change stability coefficient, and triggering a preset acute nursing interval condition if the VPU monitoring requirement index exceeds a preset acute nursing threshold. The invention solves the technical problem of low postoperative care monitoring efficiency of patients suffering from pain in the prior art, and meets the requirement of clinical accurate management.

Inventors

Luo Fangping
PAN HAIQING
HU HONGLING
XIAO PEI
YU YALI
JIAN ERMEI

Assignees

金华市中心医院

Dates

Publication Date: 20260505
Application Date: 20260113

Claims (10)

1. A VPU method for centralized management of pain patient information, the method comprising the steps of: Collecting multi-source status data and a current pain score; Based on the multi-source state data, analyzing sleep rhythm disorder degree and behavior product extreme, and calculating behavior analysis severity; determining heart rate characteristic vision degree based on the multi-source state data, analyzing the severity and the counted times of high probability of pain influence by combining behaviors, and calculating a symptom change stability coefficient; analyzing the current pain score and the time interval from the last nursing to calculate the pain nursing urgency; And calculating a VPU monitoring demand index by combining the pain nursing forcing degree and the disease change stability coefficient, and triggering a preset acute nursing interval condition if the VPU monitoring demand index exceeds a preset acute nursing threshold.
2. The VPU method for centralized management of pain patient information according to claim 1, wherein the multi-source status data comprises sleep status data, surveillance video data, sign status data, and care information data.
3. The VPU method for centralized management of pain patient information according to claim 1, wherein the sleep rhythm disorder is determined by: Dividing a regular sleep period and an irregular sleep period based on a preset rule; Based on sleep state data in the multi-source state data, obtaining turn-over frequency data of a target object belonging to a conventional sleep period and turn-over frequency data of a whole object at the same time period; And respectively acquiring the bedridden time length proportion of the target object in the normal sleep period and the unconventional sleep period, and calculating the sleep rhythm disorder degree by combining the sleep abnormal factors.
4. The VPU method for centralized management of pain patient information according to claim 1, wherein the behavioral product is determined by: Acquiring the total distance from a target object to the activity in the current preset period based on the monitoring video data in the multi-source state data; acquiring the total distance of the whole object in the same time period; and comparing the total movement distance of the target object with the total movement distance of the whole object to determine the extreme behavior product.
5. The VPU method for centralized management of pain patient information according to claim 1, wherein the determining heart rate characteristic degree of re-vision based on multi-source status data comprises: acquiring heart rate values of the target object based on the sign state data in the multi-source state data; constructing a heart rate value sequence of the target object in a preset time period based on the heart rate value, and determining the heart rate variation trend slope of the target object; And calculating the heart rate characteristic degree of re-vision based on the heart rate value and the heart rate variation trend slope.
6. The VPU method for centralized management of pain patient information according to claim 5, wherein the combining behavior analysis severity and statistical high probability of pain affecting time-of-day times, calculating a symptom change stability factor, comprising: acquiring pre-calculated behavior analysis severity and heart rate characteristic vision; Counting the times that the characteristic degree of the heart rate of a target object exceeds a preset threshold value within a time interval from the current preset time interval, and taking the times as times of high probability of pain influence; the symptom change stability coefficient is calculated based on the heart rate characteristic degree of vision, the pain high probability influence time and behavior analysis.
7. The VPU method for centralized management of pain patient information according to claim 1, wherein the analyzing the current pain score and the time interval from last care to calculate pain care urgency comprises: combining the historical pain scores, and determining the pain score intensity corresponding to the current pain score; Acquiring a time interval from the adjacent primary nursing time to the current real-time; Pain care urgency was calculated based on pain score intensity and time interval.
8. The VPU method for centralized management of pain patient information according to claim 7, wherein the determining a pain score intensity corresponding to a current pain score in combination with historical pain scores comprises: acquiring a current pain score and a historical pain score based on the care information data in the multi-source status data; Constructing a pain score sequence based on the historical pain scores, and determining a pain score change trend; the intensity of the pain score is calculated in combination with the current pain score and the trend of the change in the pain score.
9. The VPU method for centralized management of pain patient information according to claim 1, wherein the combining pain management urgency and disorder stability factor, calculating VPU monitoring demand indicators, comprises: taking pain nursing degree as a molecule, taking a disease change stability coefficient as a denominator, carrying out normalization treatment on the corresponding ratio, and taking the normalized result value as a VPU monitoring requirement index.
10. A VPU system for centralized management of pain patient information, the system comprising the following modules: The acquisition module is used for acquiring the multi-source state data and the current pain score; The behavior analysis severity determination module is used for analyzing sleep rhythm disorder degree and behavior product extreme based on the multi-source state data and calculating behavior analysis severity; The disease change stability coefficient determining module is used for determining the characteristic degree of gravity of heart rate based on the multi-source state data, analyzing the degree of gravity and the counted times of high probability of pain influence moment by combining the behaviors, and calculating a disease change stability coefficient; The pain nursing urgency determining module is used for analyzing the current pain score and the time interval from the last nursing to calculate the pain nursing urgency; And the triggering module is used for combining the pain nursing forced degree and the disease change stability coefficient, calculating the VPU monitoring demand index, and triggering a preset acute nursing interval condition if the VPU monitoring demand index exceeds a preset acute nursing threshold.

Description

VPU system and method for centralized management of pain patient information Technical Field The invention relates to the technical field of health data processing, in particular to a VPU system and a method for centralized management of pain patient information. Background The virtual ward unit (Virtual Patient Unit, VPU) breaks through the service boundary of the traditional ward through an informatization means, and the virtual ward unit shows remarkable advantages in the field of acute pain management. The system aims at realizing informatization, institutionalization and humanization of pain management, and optimizes the nursing process by collecting postoperative monitoring data of patients. Currently, VPU systems rely mainly on analyzing patient-to-caregiver call frequency to assess care needs, and accordingly adjust post-operative care periods and treatment strategies, thereby enhancing the information-centric management of post-operative acute pain. The conventional VPU system only depends on a single index of calling frequency for analysis, and has obvious limitations that on one hand, the evaluation method is too subjective and lacks the accuracy of multi-source information fusion analysis, and on the other hand, because the hospital pain patients have large scale and individual recovery conditions are different, the monitoring system based on the single index is difficult to realize individualized nursing interval strategy adaptation, so that the postoperative nursing monitoring efficiency is reduced, and the requirement of clinical accurate management cannot be met. Disclosure of Invention In order to solve the technical problem of low postoperative care monitoring efficiency of a pain patient, the invention aims to provide a VPU system and a VPU method for centralized management of pain patient information, and the adopted technical scheme is as follows: in a first aspect, embodiments of the present invention provide a VPU method for centralized management of pain patient information, the method comprising the steps of: Collecting multi-source status data and a current pain score; Based on the multi-source state data, analyzing sleep rhythm disorder degree and behavior product extreme, and calculating behavior analysis severity; determining heart rate characteristic vision degree based on the multi-source state data, analyzing the severity and the counted times of high probability of pain influence by combining behaviors, and calculating a symptom change stability coefficient; analyzing the current pain score and the time interval from the last nursing to calculate the pain nursing urgency; And calculating a VPU monitoring demand index by combining the pain nursing forcing degree and the disease change stability coefficient, and triggering a preset acute nursing interval condition if the VPU monitoring demand index exceeds a preset acute nursing threshold. In one embodiment, the multi-source status data includes sleep status data, surveillance video data, sign status data, and care information data. In one embodiment, the sleep rhythm disorder is determined by: Dividing a regular sleep period and an irregular sleep period based on a preset rule; Based on sleep state data in the multi-source state data, obtaining turn-over frequency data of a target object belonging to a conventional sleep period and turn-over frequency data of a whole object at the same time period; And respectively acquiring the bedridden time length proportion of the target object in the normal sleep period and the unconventional sleep period, and calculating the sleep rhythm disorder degree by combining the sleep abnormal factors. In one embodiment, the behavioral product is determined extremely by: Acquiring the total distance from a target object to the activity in the current preset period based on the monitoring video data in the multi-source state data; acquiring the total distance of the whole object in the same time period; and comparing the total movement distance of the target object with the total movement distance of the whole object to determine the extreme behavior product. In one embodiment, the determining heart rate feature vision based on the multi-source state data comprises: acquiring heart rate values of the target object based on the sign state data in the multi-source state data; constructing a heart rate value sequence of the target object in a preset time period based on the heart rate value, and determining the heart rate variation trend slope of the target object; And calculating the heart rate characteristic degree of re-vision based on the heart rate value and the heart rate variation trend slope. In one embodiment, the combining behavior analyzes the severity and the number of times the statistical high probability of pain affects the moment, and calculates the disorder change stability factor, including: acquiring pre-calculated behavior analysis severity and heart rate characteristic vision; C