A home service quality evaluation method and system

Abstract

This invention relates to the field of software and discloses a method and system for assessing the quality of home-based services. The method includes: signing out a work order through the service manager app and sending a command to the intelligent monitoring device to disable nursing supervision, thereby controlling the intelligent monitoring device to stop data collection; processing the received nursing data through the data processing and report generation module to generate a service validity verification report, and transmitting the service validity verification report to the PC terminal of the elderly care service guidance center for display. This invention can effectively identify abnormal patterns such as a person arriving but not performing any work, or the device displaying prolonged inactivity of the elderly after signing out, making it difficult to conceal fraudulent services and idle behavior, and significantly improving the credibility of service assessment.

Description

Technical Field

[0001] This invention relates to the field of software, and more particularly to a method and system for assessing the quality of in-home services. Background Technology

[0002] In the daily services of home-based elderly care and long-term care insurance, verifying whether caregivers arrive on time and whether services are actually provided has always been a thorny issue for regulators. For a long time, the industry has relied mainly on paper sign-ins, telephone follow-ups, or having caregivers take photos at designated locations. While these methods are simple, they are almost incapable of preventing fraud. For example, caregivers can sign in from a place far from the elderly person's door, or sign in and leave, or sign out early, without actually providing complete service. This kind of "hanging out" makes the duration of care unclear. Furthermore, these methods only record the caregiver's actions and completely ignore changes in the elderly person's condition. This means that even if service records appear complete, it's impossible to cross-verify whether the elderly person received effective care. For example, regulators are completely unaware of whether the position of a long-term bedridden elderly person has been adjusted or whether there have been any abnormal movements. When disputes arise or long-term care insurance expense audits are required, the traceability of the service process is very poor. There is often no strong, intuitive data to back it up; usually, only scattered records and verbal descriptions are available, making it difficult to support liability determination and compliance review.

[0003] In addition, the network conditions in the homes of the elderly are often poor. If they rely solely on mobile networks to send instructions or transmit data to bedside monitoring devices, it is easy for instructions to be lost or monitoring to be interrupted due to weak signals, making the already unreliable monitoring process even more vulnerable.

[0004] Therefore, there is an urgent need for a quality assessment method that can combine caregiver on-duty status, changes in the elderly’s condition, reliable issuance of instructions, and full traceability of services to form a closed-loop verification and present it in an intuitive way. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides a method for assessing the quality of in-home services, comprising the following steps:

[0006] Service orders are generated through the PC terminal of the elderly care service guidance center and then dispatched to the service manager App.

[0007] The service manager app is used to sign in work orders and send a nursing monitoring command to the smart monitoring device; the nursing monitoring command is sent in a dual mode of Bluetooth communication and 4G HTTP communication.

[0008] During the nursing process, nursing data is continuously collected through the intelligent monitoring device and transmitted to the data processing and report generation module. The nursing data includes: location information of the caregiver and the elderly, the elderly's bed status, the elderly's physical movement data, and the location trajectory of the caregiver within the service area.

[0009] The service manager app is used to sign out work orders and send a command to the smart monitoring device to shut down nursing supervision, thereby controlling the smart monitoring device to stop data collection.

[0010] The received nursing data is processed by the data processing and report generation module to generate a service effectiveness verification report, which is then transmitted to the PC terminal of the elderly care service guidance center for display.

[0011] This invention also relates to a home-based in-home service quality assessment system, the system comprising:

[0012] The PC version of the elderly care service guidance center is used to generate service work orders and dispatch them to the service manager app, as well as to receive and display service effectiveness verification reports;

[0013] The Service Manager App is used to receive dispatched service work orders, perform work order check-in and check-out operations, and send instructions to the intelligent monitoring device to enable and disable nursing supervision; the instruction to enable nursing supervision is sent using both Bluetooth and 4G HTTP communication modes.

[0014] The intelligent monitoring device is used to continuously collect nursing data and transmit the nursing data after receiving the instruction to activate nursing supervision, and to stop collecting data after receiving the instruction to deactivate nursing supervision; the nursing data includes: location information of the caregiver and the elderly, the elderly's bed status, the elderly's physical movement data, and the location trajectory of the caregiver within the service area;

[0015] The data processing and report generation module is used to receive nursing data transmitted by the intelligent monitoring device, process the nursing data to generate the service effectiveness verification report, and transmit the service effectiveness verification report to the PC terminal of the elderly care service guidance center.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0017] First, the issuance of instructions is less prone to disconnection. Considering the unstable signal in many elderly people's residences, the issuance of care monitoring instructions no longer relies on only one communication method, but simultaneously supports Bluetooth and 4G HTTP bidirectional channels. On-site, the mobile phone and device prioritize Bluetooth interaction, and automatically switch to the 4G network when Bluetooth is unavailable. This ensures that instructions to start and end care are delivered almost without any blind spots, avoiding monitoring gaps due to network outages and ensuring uninterrupted monitoring of the entire work order process.

[0018] Secondly, the authenticity of services can be cross-verified. The system not only records the location and duration of caregivers but also simultaneously collects the elderly person's physical movement data, such as large, medium, and small movements, or an unattended state. By combining the caregiver's trajectory at the bedside with the changes in the elderly person's physical movement during the same period, abnormal patterns such as the caregiver arriving but not performing any work, or the device showing that the elderly person has not moved for a long time after checking out, can be effectively identified. This makes it difficult to conceal fraudulent services and abandoned calls, significantly improving the credibility of service assessments.

[0019] Third, the service process is transformed into visible and readable data reports. After each service session, the system automatically summarizes the distribution of care duration, changes in the elderly person's physical activity, the caregiver's location trajectory, and heat maps, generating multi-dimensional visual reports. Supervisors no longer need to sift through fragmented logs; they can quickly determine the compliance of a work order's service through charts and graphs, such as whether the caregiver left the elderly person for an extended period or whether the elderly person engaged in any potentially necessary physical activity during the care period. These reports also provide intuitive evidence for subsequent dispute resolution.

[0020] Fourth, the data chain is complete and auditable. From work order dispatch, check-in, equipment startup and data collection, check-out to report generation, the time and data collected at each step are closely linked and bound to a single work order, forming a service evidence chain that cannot be tampered with afterward. For periodic audits and ad-hoc spot checks of long-term care insurance, the data reports and original equipment records of the corresponding work orders can be directly retrieved to prove that the required services were indeed provided, and it also facilitates internal performance evaluation and quality improvement by service organizations. Attached Figure Description

[0021] Figure 1 This is a flowchart of the home-based in-home service quality assessment method described in this invention.

[0022] Figure 2 This is an architecture diagram of the home-based in-home service quality assessment system described in this invention;

[0023] Figure 3 This is an example interface diagram of the service validity verification report described in this invention. Detailed Implementation

[0024] The terms first, second, third, fourth, etc. (if present) in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a particular order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms include or have, and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0025] like Figure 1 A method for assessing the quality of home-based services includes the following steps: Generating a service order through the PC terminal of the elderly care service guidance center and dispatching the service order to the service manager App; Signing in the service order through the service manager App and issuing a nursing supervision activation command to the intelligent monitoring device; the nursing supervision activation command is issued using both Bluetooth and 4G HTTP communication modes; During the nursing process, continuously collecting nursing data through the intelligent monitoring device and transmitting the nursing data to the data processing and report generation module; the nursing data includes: location information of the caregiver and the elderly, the elderly's bed-keeping status, the elderly's physical movement data, and the caregiver's location trajectory within the service area; Signing out the service order through the service manager App and issuing a nursing supervision deactivation command to the intelligent monitoring device to control the intelligent monitoring device to stop data collection; Processing the received nursing data through the data processing and report generation module to generate a service effectiveness verification report and transmitting the service effectiveness verification report to the PC terminal of the elderly care service guidance center for display.

[0026] This step defines a complete service monitoring loop. From generating and dispatching work orders on the PC, to the caregiver checking in via a mobile app and triggering the bedside device to start data collection, to checking out and shutting down the device after the service, and finally automatically generating a visual report, the entire process is seamlessly integrated, transforming all previously manual confirmation steps into automated system connections. The dual-mode command issuance ensures that even with unstable network conditions at the elderly person's home, a reliable monitoring session can still be established between the mobile phone and the long-term care device, preventing monitoring gaps due to lost commands. The collected nursing data not only covers the caregiver's location but also simultaneously records the elderly person's bedside status and changes in body movement, allowing for a multi-dimensional reconstruction of the service process.

[0027] As one embodiment of the present invention, transmitting the nursing data to the data processing and report generation module includes: the intelligent monitoring device directly sending the continuously collected nursing data to the data processing and report generation module.

[0028] The advantage of this setup is that the raw data collected by the long-term care device is not relayed through the caregiver's mobile app, but is directly reported to the cloud processing module via the device's built-in cellular network or Wi-Fi module. This design eliminates the possibility of data tampering or intentional delays at the terminal stage, ensuring the independence and real-time nature of information during the care process. Even if the caregiver's mobile phone is turned off during service or the app is abnormally closed, the long-term care device with monitoring enabled can still continuously collect and transmit data until the check-out instruction is successfully issued, making the monitoring chain more robust.

[0029] As one embodiment of the present invention, the elderly body movement data includes large body movement data, medium body movement data, small body movement data, and unattended state data.

[0030] Long-term care devices, through built-in millimeter-wave radar or piezoelectric sensors, can identify and differentiate the intensity of an elderly person's physical activity. Large movements typically correspond to significant actions such as turning over or sitting up; medium movements are usually manifested as body shifting or noticeable hand and foot movements; small movements are subtle movements other than breathing fluctuations, such as slight movements of the fingers or head; and an "unmanned" state indicates that no human body is detected within the sensing area. By statistically analyzing these movement types by time period, the true state of the elderly person during care can be reflected: for example, if the elderly person is almost entirely unmanned or only slightly moving throughout the service period, but the caregiver's location is displayed nearby, this can serve as an abnormal signal for alert.

[0031] As one embodiment of the present invention, the step of processing the received nursing data and generating a service effectiveness verification report through the data processing and report generation module includes: cleaning and aggregating the received nursing data; determining the service effectiveness based on the cleaned and aggregated data and generating the service effectiveness verification report.

[0032] The data processing module first removes abnormal jumps caused by sensor jitter or brief disconnections, and then aggregates the raw records, which are in seconds or milliseconds, into minute-level granularity to form continuous nursing time slices. Next, based on preset judgment logic—such as whether the caregiver's time spent with the elderly meets the standard, whether the elderly's physical movement distribution during the care period is reasonable, and whether there are long periods of unattended status—the module automatically gives a conclusion of verification pass or fail, and assembles a structured verification report based on this, without requiring manual analysis.

[0033] As one embodiment of the present invention, the service effectiveness verification report includes service effectiveness judgment conclusions, nursing duration effectiveness data, service recipient behavior fluctuation data, nursing location change data, and nursing location distribution heat map; wherein, the nursing duration effectiveness data includes data on the percentage of nursing time spent near the patient, data on the percentage of nursing time spent alone, and data on the percentage of nursing time spent alone.

[0034] The report integrates intuitive displays across four dimensions: the judgment conclusion is placed at the top of the report, allowing regulators to see the results at a glance; the section on the effectiveness of care duration uses a pie chart or progress bar to show the proportion of time a caregiver spends with the elderly person out of the total work order duration, the percentage of single-person cases where only the elderly person is in bed and the caregiver is not present, and the percentage of cases where neither caregiver nor caregiver is present—these data directly quantify the on-duty status of services; the section on fluctuations in the behavior of service recipients uses a bar chart to show the changes in the proportion of different types of physical movement, used to assess whether the elderly person's activity is normal; and the data on changes in care location and the heat map use trajectory points and color intensity to reconstruct the main activity areas of caregivers in the room—for example, if caregivers consistently gather in the living room rather than the bedroom, it will deviate from the care requirements. This entire design transforms abstract data into readable and traceable audit evidence.

[0035] like Figure 2 This invention also relates to a home-based in-home service quality assessment system, comprising: a PC terminal for an elderly care service guidance center, used to generate service work orders and dispatch them to a service manager app, and to receive and display service effectiveness verification reports; a service manager app, used to receive dispatched service work orders, perform work order check-in and check-out operations, and issue instructions to start and stop nursing supervision to a smart monitoring device; the instruction to start nursing supervision is sent using both Bluetooth and 4G HTTP communication modes; a smart monitoring device, used to continuously collect nursing data after receiving the instruction to start nursing supervision, and to transmit the nursing data, and to stop data collection after receiving the instruction to stop nursing supervision; the nursing data includes: location information of the caregiver and the elderly, the elderly's bed-keeping status, the elderly's physical movement data, and the location trajectory of the caregiver within the service area; and a data processing and report generation module, used to receive the nursing data transmitted by the smart monitoring device, process the nursing data to generate the service effectiveness verification report, and transmit the service effectiveness verification report to the PC terminal of the elderly care service guidance center.

[0036] This system translates the methodology into a deployable product architecture. The PC-based elderly care service guidance center serves as the management hub, providing work order management and report viewing interfaces for institution administrators. The service manager app runs on caregivers' mobile phones, leveraging the phone's Bluetooth and 4G capabilities to achieve dual-channel command control of bedside devices. Smart monitoring devices are typically installed at the elderly person's bedside, acting as data collection terminals and continuously operating once monitoring is initiated. The data processing and report generation module is deployed on a cloud server, undertaking the tasks of data cleaning, analysis, and report generation. All modules exchange data through predefined interfaces, collaboratively completing paperless operations from work order dispatch to assessment.

[0037] In one embodiment of the present invention, the intelligent monitoring device is directly connected to the data processing and report generation module.

[0038] The direct communication connection here refers to the integrated 4G or Wi-Fi internet access capability of the long-term care device. The collected nursing data is packaged and sent directly to a designated server address without going through the service manager app. In this way, the caregiver's mobile phone only acts as a remote control for monitoring instructions and does not participate in data transmission. This avoids data interruptions caused by mobile network switching, app background clearing, etc., and also makes the nursing process data a separate original evidence stream independent of the caregiver's operations.

[0039] As one embodiment of the present invention, the intelligent monitoring device is configured to collect elderly body movement data, including large body movement data, medium body movement data, small body movement data, and unattended state data.

[0040] The body movement detection function of the long-term care device relies on continuous analysis of reflected signals or pressure changes. Before leaving the factory, the device's firmware is configured with thresholds corresponding to different body movement amplitudes, which are used to determine the intensity of human movements in real time and add time tags. The collected body movement classification data is not only used to assess the elderly person's activity level, but can also be compared with the service period: if the record shows an unattended status for a long time after check-in, it means that the elderly person may not be in bed, and the care behavior itself is questionable. This configuration provides key material for subsequent cross-validation.

[0041] In one embodiment of the present invention, the data processing and report generation module is specifically used to clean, analyze and visualize the received nursing data, and output the service effectiveness verification report containing the service effectiveness determination conclusion.

[0042] The data processing and report generation module is the core of the system's backend computing. Following a preset analysis workflow, it performs cleaning operations on the raw data stream, including filtering, deduplication, and time alignment, before extracting indicators such as nursing duration, time spent together, and frequency of physical movement. After analysis, the module initiates a report rendering service, transforming abstract indicators into visual elements such as bar charts, pie charts, trajectory graphs, and heatmaps. It also dynamically writes conclusive text into the report template, ultimately generating a directly viewable electronic report file. This entire process is fully automated, and the report can be viewed on a PC within seconds of the work order being checked out.

[0043] As one embodiment of the present invention, when the data processing and report generation module generates the service effectiveness verification report, it calculates the proportion of different types of physical movement data based on the elderly's physical movement data, and generates the nursing location distribution heat map based on the location trajectory of the caregiver in the service area.

[0044] When calculating the percentage of physical activity, the module divides the cumulative time spent in large, medium, small, and unattended states during the entire service period by the total effective data collection time to obtain the respective percentage, making the elderly person's activity composition clear at a glance. When generating a heatmap, the module calculates the density of caregiver location points based on time weights and uses a gradient from cool to warm colors to show the frequency of caregiver stays in different locations in the room. For example, the darkest color near the bedside indicates that most of the time is spent at the bedside, while abnormally concentrated colors in the kitchen or doorway suggest that the service is outside the core care area. These intuitive presentation methods significantly lower the interpretation threshold for auditors.

[0045] The specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0046] This embodiment uses a home-based elderly care service scenario as an example to illustrate the complete implementation process of the service quality assessment system and method described in this invention.

[0047] System Architecture and Module Description

[0048] As shown in Figure 2, this system mainly consists of four parts:

[0049] PC version of the management system: As the central platform for service management, it is responsible for work order dispatch, service supervision, report viewing and quality auditing;

[0050] Service Manager App: Deployed on caregivers' mobile terminals, used for receiving work orders, checking in / out of services, and issuing supervisory instructions;

[0051] Intelligent monitoring equipment: Deployed at the bedside of the patient to collect location, body movement, and trajectory data during the nursing process;

[0052] Data processing and report generation module: As a background service, it is responsible for data reception, cleaning, analysis and automatic generation of service reports.

[0053] The modules interact through standardized interfaces to form a closed-loop management process.

[0054] Business process execution steps

[0055] like Figure 1 As shown, the complete service quality assessment process is carried out according to the following steps:

[0056] Work order dispatch stage: The management system PC terminal generates a work order containing the service recipient, nursing time, service location and items based on the nursing level and service plan of the service recipient, and dispatches it to the service manager App of the designated caregiver.

[0057] Service check-in and monitoring activation: After arriving at the service location, the caregiver completes the work order check-in in the service manager app; the app sends a nursing monitoring activation command to the smart monitoring device via Bluetooth / 4G network, and the device immediately enters the data collection state.

[0058] Nursing process data collection: Throughout the service process, intelligent monitoring devices continuously collect location, body movement, and trajectory data, and upload them directly to the data processing and report generation module via communication, without going through the App, ensuring the real-time nature and independence of the data.

[0059] Service check-out and monitoring shutdown: After the nursing service is completed, the caregiver checks out in the App; the App sends a command to the device to shut down nursing monitoring, and the device stops collecting data and enters a low-power standby state.

[0060] Data processing and report generation: The data processing and report generation module cleans, analyzes, and visualizes the collected raw data, and automatically generates a service effectiveness verification report.

[0061] Report feedback and PC display: The generated report is fed back to the PC version of the management system and displayed on the corresponding work order details page, providing objective evidence for service supervision and quality assessment.

[0062] Report Presentation and Application

[0063] As shown in Figure 3, the service validity verification report generated by the system presents the service quality assessment results intuitively from multiple dimensions. The core content includes:

[0064] Service validity assessment: The system automatically outputs a pass / fail conclusion based on multi-dimensional data and marks key indicators;

[0065] Nursing time effectiveness analysis: By using indicators such as the percentage of time spent caring for patients alone, the percentage of time spent caring for patients without care, and the percentage of time spent caring for patients without care, the actual service time of nursing staff at the patient's side is quantified, and invalid time periods are excluded;

[0066] Service recipient behavior analysis: By analyzing physical movement data, we can statistically determine the percentages of large, medium, small, and no physical movement to help assess the activity status of service recipients and their response to nursing services.

[0067] Nursing staff location trajectory and heat map distribution: Through the schematic diagram and heat map of nursing location changes, the location distribution of nursing staff during the service process is displayed intuitively, and the execution location of nursing services is verified to meet the service standards.

[0068] Through the above process, this invention achieves automated and objective supervision and quality assessment of the entire process of home-based nursing services, solving the problems of strong subjectivity, incomplete data, and difficulty in post-event traceability in traditional manual supervision methods.

[0069] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for evaluating the quality of in-home services, characterized in that, Includes the following steps: Service orders are generated through the PC terminal of the elderly care service guidance center and then dispatched to the service manager App. The service manager app is used to sign in work orders and send a nursing supervision command to the intelligent monitoring device. During the nursing process, nursing data is continuously collected through the intelligent monitoring device and transmitted to the data processing and report generation module. The nursing data includes: location information of the caregiver and the elderly, the elderly's bed status, the elderly's physical movement data, and the location trajectory of the caregiver within the service area. The service manager app is used to sign out work orders and send a command to the smart monitoring device to shut down nursing supervision, thereby controlling the smart monitoring device to stop data collection. The received nursing data is processed by the data processing and report generation module to generate a service effectiveness verification report, which is then transmitted to the PC terminal of the elderly care service guidance center for display.

2. The method for evaluating the quality of home-based in-home services according to claim 1, characterized in that, The step of transmitting the nursing data to the data processing and report generation module includes: The intelligent monitoring device will continuously collect the nursing data and send it directly to the data processing and report generation module.

3. The method for evaluating the quality of home-based in-home services according to claim 1, characterized in that, The elderly person's physical movement data includes large physical movement data, medium physical movement data, small physical movement data, and data of being in an unattended state.

4. The method for evaluating the quality of home-based in-home services according to claim 1, characterized in that, The process of processing the received nursing data through the data processing and report generation module to generate a service effectiveness verification report includes: The received nursing data is cleaned and aggregated; The service validity is determined based on the cleaned and aggregated data, and a service validity verification report is generated.

5. The method for evaluating the quality of home-based in-home services according to claim 4, characterized in that, The service effectiveness verification report includes service effectiveness judgment conclusions, nursing duration effectiveness data, service recipient behavior fluctuation data, nursing location change data, and a nursing location distribution heat map. The validity data of nursing time includes data on the percentage of time spent caring for someone nearby, data on the percentage of time spent caring for a single person, and data on the percentage of time spent caring for someone without a caregiver.

6. A home-based in-home service quality assessment system, characterized in that, The system, employing the home-based in-home service quality assessment method according to any one of claims 1-5, comprises: The PC version of the elderly care service guidance center is used to generate service work orders and dispatch them to the service manager app, as well as to receive and display service effectiveness verification reports; The Service Manager App is used to receive dispatched service work orders, perform work order check-in and check-out operations, and send instructions to the intelligent monitoring device to enable and disable nursing supervision; the instruction to enable nursing supervision is sent using both Bluetooth and 4G HTTP communication modes. The intelligent monitoring device is used to continuously collect nursing data and transmit the nursing data after receiving the instruction to activate nursing supervision, and to stop collecting data after receiving the instruction to deactivate nursing supervision; the nursing data includes: location information of the caregiver and the elderly, the elderly's bed status, the elderly's physical movement data, and the location trajectory of the caregiver within the service area; The data processing and report generation module is used to receive nursing data transmitted by the intelligent monitoring device, process the nursing data to generate the service effectiveness verification report, and transmit the service effectiveness verification report to the PC terminal of the elderly care service guidance center.

7. A home-based in-home service quality assessment system according to claim 6, characterized in that, The intelligent monitoring device is directly connected to the data processing and report generation module.

8. The home-based in-home service quality assessment system according to claim 6, characterized in that, The intelligent monitoring device is configured to collect elderly people's movement data, including large body movement data, medium body movement data, small body movement data, and unattended state data.

9. A home-based in-home service quality assessment system according to claim 6, characterized in that, The data processing and report generation module is specifically used to clean, analyze, and visualize the received nursing data, and output the service effectiveness verification report containing the service effectiveness determination conclusion.

10. A home-based in-home service quality assessment system according to claim 9, characterized in that, When the data processing and report generation module generates the service effectiveness verification report, it calculates the proportion of different types of physical activity data based on the elderly's physical activity data, and generates a heat map of nursing location distribution based on the location trajectory of the caregiver in the service area.

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