A decision-making method for elderly care programs

Abstract

The present invention discloses a decision-making method for elderly care programs, comprising the following steps: S1: refine the text evaluation scale; S2: collect a number of data and combine them with the refined scale data to mine the potential associations between different data features; S3: assign corresponding weights to indicators through a weighted algorithm to obtain a comprehensive evaluation score, and update the weighted algorithm at regular intervals; S4: build a distributed computing environment, establish a chain derivation between evaluation results, and output a care plan. The beneficial effects of the present invention are: by combining data with refined scale data, mining the potential associations between different data features, and then assigning corresponding weights to indicators through a weighted algorithm to obtain a comprehensive evaluation score, and finally building a distributed computing environment to output a care plan, so that a large amount of elderly ability evaluation data can be efficiently processed, and a care plan is automatically and synchronously generated, replacing manual evaluation and improving work efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of elderly care, and in particular to a decision-making method for elderly care plans. Background Art

[0002] The selection of elderly care service projects should be based on the ability of the service recipients. Different ability of service recipients means different care service needs. Through ability assessment, care problems can be found, care plans can be proposed, and service projects that match the care plans can be selected for implementation. The existing assessment method is that the staff of the care service agency manually reviews the results of the service recipient's ability assessment, combines their actual physical condition, refers to their personal wishes, determines their care needs, and manually ticks them in the service plan table. There are two main disadvantages of this working mode: First, this working mode is greatly limited by the personal professional level of the staff of the care service agency, and the accuracy of the agency's service projects is uneven, resulting in a large-scale lack of personalized service needs or undiscovered potential needs; second, it takes about 30 minutes to 2 hours to manually assess the ability of the elderly, and it takes 2-4 hours to formulate a personalized care plan, which is not efficient. Summary of the invention

[0003] The purpose of the present invention is to overcome the shortcomings of the prior art and provide a decision-making method for elderly care programs.

[0004] The object of the present invention is achieved by the following technical solution: A decision-making method for elderly care plans, comprising the following steps: S1: Refine the text evaluation scale; S2: Collect some data and combine them with the refined scale data to explore the potential correlation between different data features; S3: Assign corresponding weights to the indicators through a weighted algorithm to obtain a comprehensive evaluation score, and update the weighted algorithm at regular intervals; S4: Build a distributed computing environment, establish chain deduction between evaluation results, and output care plan solutions.

[0005] Preferably, in step S2, the knowledge graph technology is used to sort out the network relationship between each evaluation indicator, actual result and evaluation criteria to construct a knowledge graph.

[0006] Preferably, the indicators in step S3 are divided into high importance indicators, medium importance indicators and low importance indicators, wherein the weight range of high importance indicators is 0.3~0.5, the weight range of medium importance indicators is 0.2~0.3, and the weight range of low importance indicators is 0.1~0.2.

[0007] Preferably, in step S3, the comprehensive evaluation score is calculated The calculation formula is: ; in, is the number of evaluation indicators, For the The score of the indicator, For the The weight of an indicator.

[0008] Preferably, in step S4, the specific steps of building a distributed computing environment are: S41: Deploy Linux service nodes based on Kubernetes containerized clusters and deploy dependent libraries; S42: partitioning and storing the elderly assessment data according to certain rules; S43: When new evaluation data is input, it is dynamically allocated to idle or lightly loaded computing nodes according to the current load of the computing nodes and the partition where the data is located.

[0009] Preferably, in step S42, the partitioning is performed by region, age and evaluation time.

[0010] The present invention has the following advantages: the present invention combines the data with the refined scale data, explores the potential correlation between different data features, assigns corresponding weights to the indicators through a weighted algorithm, obtains a comprehensive evaluation score, and finally builds a distributed computing environment to output a care plan, thereby efficiently processing a large amount of elderly ability assessment data and automatically and synchronously generating a care plan, replacing manual assessment and improving work efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 A schematic diagram of the decision-making process for elderly care options; Figure 2 It is a schematic diagram of the chain deduction principle; Figure 3 Schematic diagram of the process of generating a bath-based care program. DETAILED DESCRIPTION

[0012] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0013] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0014] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0015] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0016] In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inside", "outside", etc. indicate positions or positional relationships based on the positions or positional relationships shown in the accompanying drawings, or the positions or positional relationships in which the product of the invention is usually placed when in use, or the positions or positional relationships commonly understood by those skilled in the art, which are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

[0017] In the description of the present invention, it is also necessary to explain that, unless otherwise clearly specified and limited, the terms "set", "install", "connect", and "connect" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0018] In this embodiment, if Figure 1 As shown, a decision-making method for elderly care plans includes the following steps: S1: Refine the text assessment scale; that is, convert the elderly ability assessment scale, which is mainly based on text descriptions, into structured data that can be recognized and processed by computers. For example, the assessment content involving core indicators such as self-care ability, basic motor skills, mental state, perception and social participation should be converted one by one into a digital + code data format. For sub-items such as dressing and eating in self-care ability, different score ranges or code identifiers should be set according to the difficulty and degree of dependence of completion, providing a basis for subsequent algorithm processing.

[0019] S2: Collect some data and combine them with the refined scale data to explore the potential correlation between different data features; specifically, use knowledge graph technology to sort out the network relationship between each evaluation indicator, actual results and evaluation criteria to construct a knowledge graph.

[0020] S3: Assign corresponding weights to the indicators through a weighted algorithm to obtain a comprehensive evaluation score, and update the weighted algorithm at regular intervals; further, the indicators in step S3 are divided into high-importance indicators, medium-importance indicators and low-importance indicators, where the weight of the high-importance indicator ranges from 0.3 to 0.5, the weight of the medium-importance indicator ranges from 0.2 to 0.3, and the weight of the low-importance indicator ranges from 0.1 to 0.2. Specifically, the core evaluation categories such as self-care ability, basic motor skills, mental state, perception and social participation are sorted out, and specific indicators such as dressing, eating, walking, cognitive level, vision and hearing conditions, and social frequency are further subdivided. These indicators serve as the basic variables of the weighted algorithm, each reflecting different key dimensions of the life and health status of the elderly. Invite elderly care experts, geriatric doctors, and scholars who have been engaged in elderly care service research for a long time to form an expert group, and distribute questionnaires to them to score the criticality of each evaluation indicator in the overall care decision-making. For example, a scoring system of 1-10 points is used, with 1 point indicating the least important and 10 points indicating extremely critical. Combined with expert opinions and data analysis results, the importance level of each evaluation indicator is determined, divided into three levels: high, medium, and low, corresponding to the subsequent higher, medium, and lower weight allocations. When there are special circumstances such as large-scale public health events and the release of new elderly care research results, the weights are updated in a timely manner. For example, during the epidemic, the "smell and taste ability" in "perception" has a stronger correlation with the early detection of infection risks, and the weight of this indicator is appropriately increased.

[0021] S4: Build a distributed computing environment, establish chain derivation between evaluation results, and output care plan solutions. Specifically, Figure 2As shown in the figure, based on the "NNN link", a chain deduction between the evaluation results is established, that is, for the problems found in the elderly ability assessment scale, the "NNN link" association relationship is established based on the three international nursing language classification systems (Nursing Diagnosis (NANDA-I), Nursing Outcome Classification (NIC), and Nursing Action Classification (NOC)) according to the nursing procedure of "assessment-diagnosis-measure-implementation-evaluation". For example, the bathing ability assessment result is associated with the level walking score. If the bathing score is low, the walking ability is further checked, and the appropriate bathing method is determined based on the walking score. By combining the data with the refined scale data, the potential associations between different data features are mined, and then the corresponding weights are assigned to the indicators through the weighted algorithm to obtain the comprehensive evaluation score. Finally, a distributed computing environment is built to output the care plan, so that the massive elderly ability assessment data can be efficiently processed and the care plan can be automatically and synchronously generated, replacing the manual evaluation and improving the work efficiency.

[0022] In this embodiment, in step S3, the comprehensive evaluation score is calculated. The calculation formula is: ; in, is the number of evaluation indicators, For the The score of the indicator, For the The weight of an indicator.

[0023] Furthermore, in step S4, the specific steps of building a distributed computing environment are: S41: Deploy Linux service nodes based on Kubernetes containerized clusters and deploy dependent libraries; specifically, use container orchestration to achieve more flexible resource allocation and elastic scaling, which can greatly accelerate the data processing process.

[0024] S42: The elderly assessment data is partitioned and stored according to certain rules, the purpose of which is to reduce cross-regional data access and improve local computing efficiency. Furthermore, in step S42, the data is partitioned by region, age and assessment time.

[0025] S43: When new evaluation data is input, it is dynamically allocated to each idle or lightly loaded computing node based on the current load of the computing node and the partition where the data is located. Figure 3As shown, taking bathing as an example, when the assessment result shows 0 points for bathing, the care problem of assisting with bathing will be triggered. The NNN link will automatically look for further information in the assessment result to formulate a more accurate service plan, that is, combined with the scoring result of the item walking on flat ground, when the score is 0-5, it will be judged that the service recipient has weak lower limb ability and is not suitable for bathing in the bathroom, and is more suitable for the service item of bed bathing; on the contrary, the service item of bathing is recommended for service recipients with a score of 5-10. Since the bathroom is slippery, we also need to combine whether the service recipient has the risk of falling and recommend safety care service items for the service recipient.

[0026] Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A decision-making method for elderly care programs, characterized by: The following steps are involved: S1: Refine the text evaluation scale; S2: Collect some data and combine them with the refined scale data to explore the potential correlation between different data features; S3: Assign corresponding weights to the indicators through a weighted algorithm to obtain a comprehensive evaluation score, and update the weighted algorithm at regular intervals; S4: Build a distributed computing environment, establish chain deduction between evaluation results, and output care plan solutions.

2. The decision-making method for elderly care programs according to claim 1 is characterized in that: In step S2, the knowledge graph technology is used to sort out the network relationships between various evaluation indicators, actual results and evaluation criteria to construct a knowledge graph.

3. The decision-making method for elderly care programs according to claim 2 is characterized in that: In step S3, the indicators are divided into high importance indicators, medium importance indicators and low importance indicators, wherein the weight range of high importance indicators is 0.3~0.5, the weight range of medium importance indicators is 0.2~0.3, and the weight range of low importance indicators is 0.1~0.

2.

4. The decision-making method for elderly care programs according to claim 3 is characterized by: In step S3, the comprehensive evaluation score is calculated. The calculation formula is: ； in, is the number of evaluation indicators, For the The score of the indicator, For the The weight of an indicator.

5. The decision-making method for elderly care programs according to claim 4 is characterized in that: In step S4, the specific steps of building a distributed computing environment are: S41: Deploy Linux service nodes based on Kubernetes containerized clusters and deploy dependent libraries; S42: partitioning and storing the elderly assessment data according to certain rules; S43: When new evaluation data is input, it is dynamically allocated to idle or lightly loaded computing nodes according to the current load of the computing nodes and the partition where the data is located.

6. The decision-making method for elderly care programs according to claim 5 is characterized in that: In step S42, the partitioning is performed according to region, age and evaluation time.

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