A user-facing care plan recommendation engine utilizing an integrated care database and recommendation engine.

Abstract

This system reduces the time required to input user evaluation data and provide personalized care plans, thereby streamlining operations and reducing workload. Ultimately, it provides a recommendation engine that collects and analyzes user data to offer recommended care plans, enabling users to receive higher quality care services. [Solution] In the recommendation engine, the data collection module collects user behavior data in real time. Both structured and unstructured data are collected and utilized, the analysis and learning engine analyzes the collected data and generates care plans appropriate to each situation using AI algorithms, the recommendation module provides personalized care plans after an individual assessment of the user based on the learned data, and the service delivery interface learns and updates in real time through interaction with the user to provide the next care plan.

Description

Technical Field

[0001] The present invention relates to a care plan recommendation engine for users that utilizes a care integrated database and a recommendation engine.

Background Art

[0002] In South Korea and Japan, the aging population is rapidly increasing to such an extent that they will enter a super-aged society in 2024. As a result, the population requiring care and nursing is also increasing rapidly. In such a situation, it is urgent to improve the work efficiency of the personnel engaged in care work. In particular, the work of grasping the user's condition and creating an appropriate care plan (care plan) takes an enormous amount of time. In the present invention, a recommendation engine utilizing AI is proposed to shorten this time.

Summary of the Invention

Problems to be Solved by the Invention

[0003] The objectives of the present invention are as follows. 1. Construct a recommendation engine that efficiently collects and analyzes user data and provides personalized services. 2. Utilize artificial intelligence and machine learning algorithms to improve recommendation accuracy. 3. Improve the speed of service provision and realize a SaaS-based platform that can be extended to multiple users.

Means for Solving the Problems

[0004] The present invention consists of the following components.

[0005] 1. Data collection module: Collects user behavior data in real time. Utilizes both structured and unstructured data.

[0006] 2. Analysis and learning engine: Analyzes the collected data and generates a care plan suitable for each situation using AI algorithms.

[0007] 3. Recommendation Module: Based on learned data, it provides personalized care plans after an individual assessment of the user.

[0008] 4. Service Delivery Interface: Learns and updates in real time through interaction with the user, and provides the next care plan. [Effects of the Invention]

[0009] This invention makes it possible to shorten the time required from inputting user evaluation data to providing personalized care plans. Furthermore, it reduces the workload through improved operational efficiency, ultimately enabling users to receive higher quality care services. [Brief explanation of the drawing]

[0010] [Figure 1] This is a system configuration diagram of the recommendation engine (a configuration diagram of the language model). [Figure 2] This is a system configuration diagram of the recommendation engine (care plan creation system). [Figure 3] This is an example of a user interface. [Modes for carrying out the invention]

[0011] 1. User behavior data collection - A specialized care application records user evaluation items, caregiver work history, user condition, and family communication in real time. - Integrate additional data using external APIs. 2. Recommendation Algorithms - User-specific behavioral data is vectorized and input into a machine learning model. - Uses a language model based on the Transformer engine. - Learns from user manual corrections and labeling and continuously improves. 3. Providing personalized results - We provide optimal recommendations, taking into account the user's current rating status. - Improve satisfaction and continuously update care plans based on user information updated in real time.

Claims

1. A recommendation engine that collects and analyzes user data to provide recommended care plans.

2. A recommendation algorithm that combines user filtering using the Transformer method.

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