CN113486073A - Aged care caregiver care information collaborative optimization method oriented to digital environment - Google Patents
Aged care caregiver care information collaborative optimization method oriented to digital environment Download PDFInfo
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
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- G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
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Abstract
The invention discloses a cooperative optimization method for care information of nursing care providers in a digital environment, which classifies daily information cooperative behaviors of the nursing care providers according to a qualitative and quantitative combined method aiming at the conditions of high pressure, complex information cooperative behaviors and low cooperative efficiency in the care process of the nursing care providers in the nursing care, and automatically matches one or more cooperative objects according to the result. Meanwhile, partial information contribution tasks of the nursing staff are split, so that the information coordination efficiency is improved, and the burden of the nursing staff is reduced. The invention can well solve the problems of overweight care tasks and difficult information coordination of the nursing staff in the digital environment, relieves the pressure of the nursing staff in the information coordination, enables the nursing staff to concentrate on the care behavior, and provides better care quality for the old.
Description
Technical Field
The invention relates to the field of human-computer interaction and social computing, in particular to a nursing information collaborative optimization method for nursing care personnel in a digital environment, which aims at the information collaborative problem in the field of supporting health care by a computer communication technology.
Background
With the increasing aging problem of the population, the care for the aged people becomes an important civil problem facing the current society. In recent years, the rapid development of information communication technology provides a revolutionary solution path for relieving the current pressure of old people and promoting the development of the old people industry. New endowment concepts such as digital endowment, intelligent endowment, Internet and endowment are continuously proposed, and a plurality of technical services for endowment and care are designed, developed and applied, such as an endowment and care management system, a lost positioning system, a home shopping system and the like.
It is not easy to find from these existing technologies that the current digital products for elderly care services are mainly oriented to the elderly or managers, and mainly aim to support the life of the elderly and the health management of the elderly, while the needs of the caregivers are ignored by many design developers. In fact, in the current endowment service system, nursing staff is a direct provider for the elderly services and is a key role for supporting the whole endowment service system. However, under the social background that China comprehensively promotes the development of digital transformation of old people, the environmental complexity and the characteristic of multi-role coordination in the process of old people nursing increase the difficulty of technical support for the coordination of nursing staff. As a weak group with large overall age and low cultural level, nursing staff often have great difficulty in adding the long-term, cross-domain and multi-role coordinated nursing process in a complex digital environment. The nursing staff provides nursing service for the old and needs to continuously cooperate with other nursing roles such as family members, company managers, medical staff and the like through various modes, and the information cooperation process is complex and low in efficiency. How to provide an effective method for optimizing an information coordination network aiming at the problems and challenges of the existing information coordination mechanism of the nursing staff for the aged becomes very important to reduce the burden of the nursing staff.
The technical difficulty is as follows:
1) how to design a computable and extensible caregiver information collaboration framework. At present, in most of old-age care institutions, caregivers as speakers of the old people undertake a large amount of information contribution work, the caregivers need to perform information collaboration with different stakeholders through various digital products every day, a collaboration network with a star-shaped topological result is formed by starting of the caregivers, and how to design an information collaboration framework going to the center is achieved, so that the problem that information collaboration pressure of the caregivers becomes the first technical difficulty in the information collaboration process of the old-age care caregivers is relieved.
2) How to achieve efficient information collaboration between caregivers and other roles. At present, the way of information collaboration between the nursing staff and other care roles is mainly point-to-point communication and broadcast and multicast communication, the nursing staff sends information to a certain person or all persons of a certain group, and the problem of low efficiency or information redundancy is caused.
Disclosure of Invention
The invention aims to creatively provide a nursing care information collaborative optimization method for nursing care personnel in a digital environment aiming at the current situation that the nursing care burden is increased due to the complicated information collaborative process of the nursing care personnel in the digital environment, so as to reduce the pressure of the nursing care personnel and improve the information collaborative efficiency.
The specific implementation scheme of the purpose of the invention is as follows:
a cooperative optimization method for care information of nursing care personnel facing the aged in a digital environment comprises the following specific steps:
step 1: data acquisition
Collecting daily information collaborative data of a caregiver by adopting a social computing method, wherein the daily information collaborative data comprises collaborative objects, collaborative contents, information types, collaborative modes and collaborative time and places;
step 2: collaborative feature analysis
Analyzing the acquired information cooperation data by adopting a qualitative analysis method, and mining the characteristics of information cooperation;
and step 3: setting monitoring capture data
Setting automatic capture data of monitoring video data as part of data input according to the time and place of relatively fixed cooperative behavior of caregiver information in qualitative analysis;
and 4, step 4: classification of collaborative content
Classifying the input data in a quantitative mode to obtain the classification of the information collaborative content of the nursing staff;
and 5: determining collaborative objects
Classifying the caregiver cooperation data input categories by adopting a multi-label classification algorithm, and determining cooperation objects to be forwarded by the data;
step 6: additional description
Adding different descriptions to each piece of information according to different information collaborative content types and collaborative object types;
and 7: data forwarding
And forwarding the processed data to an accurate output end according to the information cooperation object summarized by the qualitative analysis.
The qualitative analysis method comprises the following steps: carrying out three-level data coding and evaluation by adopting open coding, axis coding and selective coding to obtain the data characteristics and categories of each piece of information content; the quantitative mode is as follows: and (3) mining rules and characteristics by using a deep learning algorithm: firstly, each information content has n data characteristics X ═ X1,x2,…,xnAnd a classification label Y; and then training a classifier model by using the historical label data, and finally automatically predicting the classification of the collaborative information content through the newly input information content data.
The multi-label classification algorithm is an ML-KNN algorithm.
The classifier model is an SVM.
The collaborative objects include a family end, a company end and a hospital end.
The invention has the beneficial effects that:
the invention reduces the information cooperation pressure of the nursing staff in the digital environment. The invention separates the tasks of information classification, information forwarding, partial information contribution and the like in the information collaboration undertaken by the old-aged nursing staff, and captures and undertakes the task of partial information contribution by monitoring by utilizing the relatively fixed characteristics of time, place and content of the information collaboration. And a machine learning algorithm is utilized to undertake the task of automatic data classification, so that the information cooperative burden of the nursing staff is reduced.
The invention also improves the efficiency of the cooperation of the nursing staff and other role information. On the basis of data self-classification, accurate one-to-many data transmission is realized through an ML-KNN multi-label algorithm, the problems of low efficiency, information redundancy and the like in original on-demand, multicast and broadcast communication are solved, and the efficiency of the whole information cooperative network is improved.
Drawings
FIG. 1 is a flow chart of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the following specific examples and the accompanying drawings. The procedures, conditions, experimental methods and the like for carrying out the present invention are general knowledge and common general knowledge in the art except for the contents specifically mentioned below, and the present invention is not particularly limited.
Examples
Referring to fig. 1, the present invention employs an embedded mechanism to build the caregiver's entire information collaboration process. Firstly, the information cooperation process of the nursing staff in the digital environment is analyzed in a mode of combining the qualitative mode and the quantitative mode. Collecting the characteristics, the theme and the cooperative objects of the cooperative content of the caregiver information in a qualitative and quantitative mode, and analyzing the cooperative behavior of the caregiver information by adopting a rooting theory; after enough caregiver information collaboration data is collected, rules and features are mined using machine learning algorithms to achieve automatic classification of information collaboration content and automatic selection of collaboration objects. And according to the qualitative analysis result, dividing the collaborative objects into a family end, a company end and a hospital end, and accurately forwarding different information contributed by the nursing staff in a one-to-many way.
The specific operation of this example was carried out as follows:
1) and multi-dimensional data acquisition based on the current situation of caregiver information collaboration. In order to better understand the information collaboration status of the nursing staff in the digital environment, firstly, data acquisition is carried out on the way, content, time, place, object and the like of caregiver information collaboration.
2) And qualitatively finding information synergistic characteristics. After enough data is collected, the characteristic summary and the division of the cooperative content of the caregiver information are carried out in a qualitative mode. The qualitative part adopts the root theory to carry out three-level data coding and evaluation, including open coding, axis coding and selective coding. Open coding is a process of scattering and reorganizing collected data, extracts more general topics, attributes and concepts related to information collaboration from specific examples, and performs formal definition. The axis coding is based on open coding, and the relationship between the two is determined by analyzing related conceptual attributes through induction, deduction and other methods. The selection code is used for determining a certain class as a core class on the basis of the axis code and establishing connection with other classes, so that the cooperative characteristics of the caregiver information are analyzed in a three-level coding mode. Finally, a plurality of categories of information content are output, wherein one category is' sports for the old.
3) And monitoring captured data. And setting monitoring automatic snapshot as a part of data according to the relatively fixed time and place in cooperation with the caregiver information in the qualitative analysis discovery.
4) Information content classification
In the section, the cooperative content of the caregiver information is classified in a quantitative mode, rules and characteristics are mined by using a machine learning algorithm, and data input by the caregiver is classified. After a large amount of caregiver information collaborative data are collected, a machine learning algorithm is utilized to train the model, automatic content classification is achieved, and the workload of participants is reduced. For example, when the information input by the caregiver is a picture of an old person doing an early exercise, the picture can be classified into a category of 'movement of the old person' through a CNN classification algorithm.
5) And determining the cooperative object.
After the data is classified, the object of forwarding needs to be determined.
a) The problems are as follows: realizing precise 1-to-many collaboration
In the caregiver information collaboration process, in most cases, the same batch of information needs to be sent to different collaboration objects. For example, pictures of the old people who are doing a morning exercise belong to the category of 'moving pictures of the old people', and the data needs to be forwarded to a company end (which is convenient for management personnel to check the work) and a family end (which is convenient for the family to check the conditions of the old people).
The problem that a plurality of information cooperative objects can be determined for the same information is realized by using an ML-KNN multi-label classification algorithm. Firstly, K samples closest to the samples are searched through a KNN algorithm, the number of each category in the K samples is counted, the probability of each label is calculated through a naive Bayes algorithm according to the statistics of the step, and the probability of more than 0.5 can be used as output.
6) After the collaborative category and the collaborative object are determined, for the case that the video and the picture information need to be explained, different information explanations are added to each piece of information, and the format of the added explanations can be set as "lovely ' object ' hello, which is collaborative content '", for example, the information collaborative category is "moving picture of old people" and the information collaborative object is "family", and the added explanations are: "respected family is your good, this is the old's moving picture" and forwards to the corresponding data output node.
The protection of the present invention is not limited to the above embodiments. Variations and advantages that may occur to those skilled in the art may be incorporated into the invention without departing from the spirit and scope of the inventive concept, and the scope of the appended claims is intended to be protected.
Claims (5)
1. A cooperative optimization method for care information of nursing care personnel facing the aged in a digital environment is characterized by comprising the following specific steps:
step 1: data acquisition
Collecting daily information collaborative data of a caregiver by adopting a social computing method, wherein the daily information collaborative data comprises collaborative objects, collaborative contents, information types, collaborative modes and collaborative time and places;
step 2: collaborative feature analysis
Analyzing the acquired information cooperation data by adopting a qualitative analysis method, and mining the characteristics of information cooperation;
and step 3: setting monitoring capture data
Setting automatic capture data of monitoring video data as part of data input according to the time and place of relatively fixed cooperative behavior of caregiver information in qualitative analysis;
and 4, step 4: classification of collaborative content
Classifying the input data in a quantitative mode to obtain the classification of the information collaborative content of the nursing staff;
and 5: determining collaborative objects
Classifying the caregiver cooperation data input categories by adopting a multi-label classification algorithm, and determining cooperation objects to be forwarded by the data;
step 6: additional description
Adding different descriptions to each piece of information according to different information collaborative content types and collaborative object types;
and 7: data forwarding
And forwarding the processed data to an accurate output end according to the information cooperation object summarized by the qualitative analysis.
2. The cooperative optimization method for care information of nursing care providers in digital environment according to claim 1, wherein the qualitative analysis method comprises: carrying out three-level data coding and evaluation by adopting open coding, axis coding and selective coding to obtain the data characteristics and categories of each piece of information content; the quantitative mode is as follows: and (3) mining rules and characteristics by using a deep learning algorithm: firstly, each information content has n data characteristics X ═ X1,x2,…,xnAnd a classification label Y; and then training a classifier model by using the historical label data, and finally automatically predicting the classification of the collaborative information content through the newly input information content data.
3. The cooperative optimization method for nursing information of nursing staff in digital environment as claimed in claim 1, wherein said multi-label classification algorithm is ML-KNN algorithm.
4. The cooperative optimization method for care information of nursing staff in digital environment according to claim 1, wherein the cooperative objects include family end, company end and hospital end.
5. The cooperative optimization method for nursing information of nursing staff in digital environment according to claim 2, wherein the classifier model is SVM.
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Cited By (1)
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| CN114117238A (en) * | 2021-12-09 | 2022-03-01 | 福寿康(上海)医疗养老服务有限公司 | Intelligent caregiver recommendation scheduling system |
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Application publication date: 20211008 |