A method, device, medium and product for automatic collection and task conversion of multi-source nursing service requirements

Abstract

The application discloses a kind of multi-source nursing business demand automatic collection and task conversion method, equipment, medium and product, it is related to medical information system and task management technical field, the method includes obtaining the nursing business demand data of heterogeneous business system;According to the demand type of each nursing business demand data of pre-set business rule identification;Extract the key field in each nursing business demand data, and the nursing business demand is converted into the task object of uniform structure;Based on patient unique identification, task type and pre-set time window, multiple task objects are de-duplicated and merged, and the task object set after de-duplication is obtained;According to pre-set weighted priority rule, the task object set after de-duplication is sorted, and the sorted task object set is obtained;According to post qualification and jurisdiction, from which the task of right processing is screened out, and personalized task list is generated.The application can significantly reduce the time-consuming of task arrangement and task processing error rate.

Description

Technical Field

[0001] This application relates to the fields of medical information systems and task management technology, and in particular to a method, device, medium and product for the automatic collection and task-oriented conversion of multi-source nursing business needs. Background Technology

[0002] With the advancement of hospital specialization, an increasing number of specialized nursing clinics (such as intravenous catheterization clinics, wound and ostomy clinics, and diabetes care clinics) are undertaking specialized nursing work across multiple departments throughout the hospital. Unlike general ward nursing, specialized nurses need to handle business demands from multiple completely heterogeneous systems simultaneously. Taking intravenous catheterization as an example, its main sources of demand include: Inpatient catheterization / maintenance / removal needs: derived from physician orders in the hospital information system (HIS or EMR); Catheter maintenance needs of discharged patients: These are obtained through patient self-registration in the outpatient registration system. The need for consultation on catheterization for difficult cases originates from clinical department consultation requests in the consultation management module.

[0003] Currently, the common work model in the industry is as follows: nurses need to log into the aforementioned systems daily, manually view and transcribe to-do items, compile them into personal work lists, and then log into each system to update the status after completing the tasks. This model has the following technical problems: Multi-source heterogeneous data cannot be automatically aggregated: different systems have different data formats, interface protocols, and business semantics. Existing general nursing systems connect to a single system and cannot collect outpatient registration and consultation application data at the same time, which means that nurses have to log in to multiple systems every day and spend 30-60 minutes processing the task.

[0004] Repetitive tasks cannot be automatically identified: Taking intravenous catheterization as an example, an inpatient may have a doctor's order for peripherally inserted central venous catheterization in the medical order system; after discharge, the patient needs to regularly register for catheter maintenance at the intravenous catheterization clinic; if complications arise with the catheter, the clinical department may also initiate a consultation through the consultation module. These needs are stored in the medical order system, the outpatient registration system, and the consultation management module, respectively, but all point to the same catheter disposal need for the same patient. The existing system lacks a cross-system need identification and aggregation mechanism, forcing nurses to rely on experience to determine whether a need is repetitive, which is not only time-consuming but also prone to duplicate operations or task omissions.

[0005] Lack of a specialist-appropriate prioritization mechanism: The existing system prioritizes patients based solely on the urgency of medical orders, without taking into account factors such as the severity of the patient's condition, which may lead to delays in high-risk tasks.

[0006] The task execution status cannot be automatically closed: After completing a task, nurses need to manually update the status in multiple source systems, which can easily lead to data inconsistencies and affect medical safety.

[0007] A search revealed several existing nursing task management solutions (such as methods for dynamically generating nursing tasks across all scenarios and automated collection and analysis of nursing data). However, these solutions primarily focus on resource scheduling during the task allocation phase or the collection and formatting of general nursing data. For heterogeneous business needs from different sources (such as medical orders, outpatient registration, and consultation requests), effective mechanisms for automatic data aggregation, deduplication and merging, and cross-system status feedback have not yet been proposed. Therefore, a specialized automatic aggregation and task-oriented conversion technology solution tailored to multi-source nursing business needs remains needed in this field. Summary of the Invention

[0008] The purpose of this application is to provide a method, device, medium, and product for automatically collecting and converting multi-source nursing service needs into tasks, so as to improve the efficiency and accuracy of automatic collection and task processing of multi-source nursing service needs.

[0009] To achieve the above objectives, this application provides the following solution: Firstly, this application provides a method for automatically collecting and task-oriented conversion of multi-source nursing service needs, including: Obtain nursing service demand data from heterogeneous business systems; the heterogeneous business systems include at least two of the following: the medical order system, the appointment registration system, and the consultation application system. The requirement type for each nursing service requirement data is identified according to preset business rules; the requirement type includes at least nursing operation requirements, nursing assessment requirements, and nursing consultation requirements. Extract key fields from each nursing service requirement data, and convert nursing service requirements from different sources into task objects with a unified structure according to a preset standardized format; the key fields include the patient's unique identifier, the time when the requirement was generated, the requirement source identifier, and the requirement urgency level indication information; Based on the patient's unique identifier, task type, and preset time window, multiple task objects are deduplicated and merged to obtain a deduplicated set of task objects; the task type is determined according to the task requirements. The deduplicated task object set is sorted according to a preset weighted priority rule to obtain a sorted task object set; the preset weighted priority rule considers at least three factors: the urgency of the need, the severity of the patient's condition, and the time when the need arises, and assigns a weight to each factor to calculate a comprehensive score. Based on the job qualifications and jurisdiction of the logged-in nursing staff, tasks that the logged-in nursing staff have the authority to handle are selected from the sorted set of task objects, and a personalized task list is generated and displayed.

[0010] In one embodiment, key fields are extracted from each of the nursing service demand data entries, specifically including: Based on the source system identifier of the nursing service demand data, determine the data extraction rules corresponding to the source system; Based on the data extraction rules, key fields are located and extracted from the nursing business demand data; If the key field is empty or the format does not meet the preset requirements, it will be completed or corrected according to the preset default value or data cleaning rules.

[0011] In one embodiment, according to the data extraction rules, key fields are located and extracted from the nursing service demand data, specifically including: Read the value of the specified field directly from the structured data of the nursing service requirements data; Extract the values ​​of specified fields from the semi-structured data of the nursing service demand data according to preset parsing rules; Extract the values ​​of specified fields from the unstructured text of the nursing service demand data according to preset keyword matching or regular expression rules.

[0012] In one embodiment, based on the patient's unique identifier, task type, and preset time window, multiple task objects are deduplicated and merged to obtain a deduplicated set of task objects, specifically including: If multiple task objects of the same task type exist for the same patient within the same preset time window, they are merged into one task object, and information from multiple sources is merged into the context summary field of the current task object.

[0013] In one embodiment, the weight coefficients of each factor in the preset weighted priority rule are set according to the risk level quantitative analysis of nursing services, wherein the weight of the urgency of the need is 45% to 55%, the weight of the severity of the patient's condition is 25% to 35%, and the weight of the time when the need arises is 15% to 25%.

[0014] In one embodiment, it further includes: In response to the logged-in nursing staff's execution operation on a task in the personalized task list, the system obtains the execution result and, in accordance with the interface specifications of the heterogeneous business system associated with the task, feeds the execution result back to the corresponding heterogeneous business system to update the business status.

[0015] In one embodiment, it further includes: A maximum response time is configured for each task type. When there are tasks in the personalized task list that have not been processed after the maximum response time, a reminder is automatically sent to the responsible caregiver for the corresponding task. If the task is still not processed after the preset grace period, the reminder is escalated to the superior management personnel.

[0016] Secondly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-mentioned method for automatically collecting and task-oriented conversion of multi-source nursing service needs.

[0017] Thirdly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned method for automatically collecting and task-oriented conversion of multi-source nursing service requirements.

[0018] Fourthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the above-mentioned method for automatically collecting and task-oriented conversion of multi-source nursing service requirements.

[0019] According to the specific embodiments provided in this application, this application has the following technical effects: This application provides a method, device, medium, and product for automatically collecting and converting multi-source nursing service requirements into tasks. The method includes: acquiring nursing service requirement data from heterogeneous business systems; the heterogeneous business systems include at least two of the following: a medical order system, an appointment registration system, and a consultation application system; identifying the requirement type of each nursing service requirement data according to preset business rules; extracting key fields from each nursing service requirement data and converting nursing service requirements from different sources into task objects with a unified structure according to a preset standardized format; deduplicating and merging multiple task objects based on the patient's unique identifier, task type, and preset time window to obtain a deduplicated task object set; sorting the deduplicated task object set according to a preset weighted priority rule to obtain a sorted task object set; and selecting tasks that the logged-in nursing staff have the authority to handle from the sorted task object set based on the logged-in nursing staff's job qualifications and jurisdiction, generating a personalized task list, and displaying it. This application can significantly reduce the number of times nurses log in to different systems and the time spent on task organization by automatically collecting multi-source data and standardizing tasks; through an intelligent deduplication and merging mechanism, it can effectively avoid task omissions and duplicate operations caused by the dispersion of multi-source demands, and greatly reduce the error rate of task processing; by using a weighted priority ranking model that comprehensively considers the urgency of the demand, the severity of the patient's condition and the time when the demand is generated, combined with an overdue warning mechanism, the response time of high-risk tasks can be significantly shortened. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 A flowchart illustrating a method for automatically collecting and task-oriented conversion of multi-source nursing service needs, provided in an embodiment of this application; Figure 2 A flowchart illustrating the overall process of automatically collecting and task-oriented conversion of multi-source nursing service needs according to an embodiment of this application; Figure 3 A schematic diagram illustrating the specific process of multi-source demand data collection and standardized processing; Figure 4 A flowchart illustrating the intelligent deduplication and merging process and weighted priority sorting; Figure 5 This is a flowchart illustrating the cross-system status feedback and timeout warning process. Figure 6 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0022] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0023] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0024] This application provides a method for automatically collecting and task-orientedly converting multi-source nursing service needs in specialized nursing (particularly applicable to intravenous catheterization, wound and stoma care, and diabetes nursing, but not limited to these), enabling real-time triggered data collection from at least two heterogeneous business systems (medical orders, registration, and consultation); proposing an intelligent deduplication and merging algorithm based on patient identification, task type, and differentiated time windows; establishing a weighted priority model including urgency, patient severity, and time of need generation; implementing dual role filtering based on job qualifications and jurisdiction; and constructing a cross-system automatic status feedback closed loop. This application solves the problems of low efficiency, easy omissions, and data inconsistencies caused by nurses having to manually organize pending tasks across multiple systems. This invention is particularly suitable for scenarios requiring centralized processing of multi-source nursing needs, such as intravenous catheterization, wound and stoma care, and diabetes nursing.

[0025] In one exemplary embodiment, such as Figure 1 As shown, a method for automatically collecting and task-oriented transformation of multi-source nursing service needs is provided, including the following steps: S1: Obtain nursing service demand data from heterogeneous business systems; the heterogeneous business systems include at least two of the following: medical order system, appointment registration system, and consultation application system.

[0026] In this embodiment, at least two heterogeneous business systems are connected to collect nursing business demand data in real time.

[0027] The heterogeneous business systems are specifically: the medical order module in the HIS system, the specialist appointment module in the outpatient registration system, and the consultation application module in the EMR system.

[0028] The nursing service demand data includes at least one of the following types or a combination thereof: (1) Medical order-related demand data: nursing operation medical orders from the medical order system, including at least catheterization medical orders, maintenance medical orders, extubation medical orders, as well as the urgency level indicator, department of entry, entry time information, and execution department carried in the medical orders.

[0029] (2) Registration-related demand data: Patient registration records from the appointment registration system, including at least the registration department, appointment type, consultation time, and basic patient information.

[0030] (3) Consultation-related demand data: Consultation application records from the consultation management system, including at least the consultation department, consultation type, application reason, and urgency level indicator.

[0031] (4) Patient basic information data: Patient information from the hospital information system or electronic medical record system, including at least the patient's unique identifier, the department visited, the current ward, the nursing level, and the severity of the illness.

[0032] S2: Identify the demand type of each nursing business demand data according to preset business rules; the demand type includes at least nursing operation demand, nursing assessment demand, and nursing consultation demand.

[0033] In this embodiment, the preset business rules include at least one of the following types or a combination thereof: (1) Business source-task type mapping rules: used to establish the correspondence between different source business systems and nursing task types; For example, the medical order for "peripherally inserted central venous catheterization" created in the medical order system can be identified as a "catheterization task" in the catheterization system, and the system supports establishing a correspondence between medical orders and tasks.

[0034] (2) Requirement type identification rules: used to identify the task type corresponding to the requirement based on the source system, data type or key field value of nursing business requirement data.

[0035] (3) Deduplication and merging rules: used to determine whether there are duplicate tasks for the same patient within the same time window, and which task to retain as the primary task when merging.

[0036] (4) Priority ranking rules: Factor weight allocation used to calculate the overall score of the task.

[0037] (5) Task screening rules: used to filter executable tasks based on the nursing staff’s job qualifications and jurisdiction.

[0038] S3: Extract key fields from each nursing service requirement data, and convert nursing service requirements from different sources into task objects with a unified structure according to a preset standardized format; the key fields include the patient's unique identifier, the time when the requirement was generated, the identifier of the source of the requirement, and the information indicating the urgency of the requirement.

[0039] In one embodiment, key fields are extracted from each of the nursing service demand data entries, specifically including: S31: Determine the data extraction rules corresponding to the source system based on the source system identifier of the nursing service demand data.

[0040] S32: Based on the data extraction rules, locate and extract key fields from the nursing business demand data.

[0041] In one embodiment, S32 specifically includes: Read the value of the specified field directly from the structured data of the nursing service requirements data; Extract the values ​​of specified fields from the semi-structured data of the nursing service demand data according to preset parsing rules; Extract the values ​​of specified fields from the unstructured text of the nursing service demand data according to preset keyword matching or regular expression rules.

[0042] S33: If the key field is empty or the format does not meet the preset requirements, it shall be completed or corrected according to the preset default value or data cleaning rules.

[0043] S4: Based on the patient's unique identifier, task type, and preset time window, deduplication and merging of multiple task objects are performed to obtain a deduplicated set of task objects; the task type is determined according to the task requirements.

[0044] In one embodiment, based on the patient's unique identifier, task type, and preset time window, multiple task objects are deduplicated and merged to obtain a deduplicated set of task objects, specifically including: If multiple task objects of the same task type exist for the same patient within the same preset time window, they are merged into one task object, and information from multiple sources is merged into the context summary field of the current task object.

[0045] In this embodiment, the preset time window is configured differently for different task types: 24 hours for catheterization operation tasks, 48 ​​hours for maintenance tasks, and 12 hours for consultation tasks.

[0046] S5: Sort the deduplicated task object set according to the preset weighted priority rule to obtain the sorted task object set; the preset weighted priority rule considers at least three factors: the urgency of the need, the severity of the patient's condition, and the time when the need arises, and assigns weights to each factor to calculate the comprehensive score.

[0047] In one embodiment, the weight coefficients of each factor in the preset weighted priority rule are set according to the quantitative analysis of the risk level of nursing services. Among them, the weight of the urgency of the need is 45% to 55%, the weight of the patient's critical condition is 25% to 35%, and the weight of the time when the need arises is 15% to 25%. The urgency level of the need is divided into three levels: high, medium, and low. The high-risk level is identified by the emergency mark in the medical order, the "urgent consultation" mark in the consultation request, or the patient's chief complaint of complications.

[0048] S6: Based on the job qualifications and jurisdiction of the logged-in nursing staff, select the tasks that the logged-in nursing staff have the authority to handle from the sorted task object set, generate a personalized task list and display it.

[0049] In one embodiment, S7 is also included: In response to the logged-in nursing staff's execution operation on a task in the personalized task list, the system obtains the execution result and, in accordance with the interface specifications of the heterogeneous business system associated with the task, feeds the execution result back to the corresponding heterogeneous business system to update the business status.

[0050] In one embodiment, it further includes: A maximum response time is configured for each task type. When there are tasks in the personalized task list that have not been processed after the maximum response time, a reminder is automatically sent to the responsible caregiver for the corresponding task. If the task is still not processed after the preset grace period, the reminder is escalated to the superior management personnel.

[0051] This embodiment uses the intravenous catheterization department of a tertiary hospital as an example, but the present invention is also applicable to other scenarios that require centralized handling of multiple nursing needs, such as wound and stoma care departments and diabetes care departments.

[0052] like Figure 2 As shown, the method for automatically collecting and task-oriented conversion of multi-source nursing service needs in this application includes the following steps: S101: Real-time data acquisition.

[0053] The system interfaces with at least two heterogeneous business systems through standardized interfaces (such as HL7 and WebService). Figure 3 As shown, an event-driven model is preferred: when the medical order system adds a new medical order, the registration system adds a new registration, or the consultation system adds a new consultation request, the source system actively pushes the data. If the source system does not support active pushing, a timed polling method is used: the system calls the source system interface at configurable time intervals (e.g., 1 minute) to query the data added since the last poll. The polling interval can be dynamically adjusted according to the system load. When issuing specific procedure orders (such as "peripherally inserted central catheter") in the medical order system; When patients register for specialist appointments (such as "Intravenous Catheterization Specialist Clinic") in the appointment registration system; When initiating a specialist consultation request in the consultation request system.

[0054] S102: Identification and standardization of demand types.

[0055] The system has a built-in business rule engine and a business source-task type mapping table. For example, configure the following mapping rule: Medical Order System: Medical order items have preset type attributes (such as catheterization, maintenance, and removal) in the system. When a doctor issues a medical order, the system obtains the type attribute of the medical order item and determines whether the executing department is an intravenous catheterization specialist. If the executing department matches and the type attribute is valid, the medical order item type is directly mapped to the corresponding nursing task type (catheterization requirement, maintenance requirement, or removal requirement). Registration System: The specialist appointment slots in the registration system are pre-configured with service types (such as catheter maintenance). When a patient registers for a corresponding specialist appointment, the system identifies the service type as a maintenance request. Consultation System: The consultation request form includes fields for the consultation department or consultation type (e.g., intravenous catheterization consultation). The system directly identifies the consultation request based on the value of this field.

[0056] Extract key fields (patient unique identifier, time of demand, source, urgency, etc.) and convert data from different sources into standardized task objects with a unified structure.

[0057] S103: Intelligent deduplication and merging.

[0058] like Figure 4 As shown, if multiple task objects of the same task type exist for the same patient within the same time window, they are considered duplicate requirements. Only the earliest created task object is retained as the main task. The information of the remaining task objects (source system identifier, original ID, key context) is appended to the context summary field of the main task in a structured format. The merged task is marked as merged (logical deletion, not physical deletion, so as to facilitate traceability).

[0059] Taking intravenous catheterization as an example, the time window for catheterization tasks is set at 24 hours, for maintenance tasks at 48 hours, and for consultation tasks at 12 hours. For instance, if a patient has both a peripherally inserted central venous catheterization order from the medical order system and an intravenous catheterization specialist outpatient appointment from the registration system, the system will identify them as the same task type, and the nurses will not need to process them repeatedly after merging them.

[0060] S104: Weighted priority sorting.

[0061] The system calculates the overall score for each task using a weighted priority model. This model considers three factors: Urgency of need: High = 100 points, Medium = 50 points, Low = 20 points (weight 50%). Patient severity: Normalized criticality index value obtained from the electronic medical record system (weight 30%). The criticality index is determined by one of the following methods: Obtain APACHE II score from electronic medical records: Criticality index = min(score / 71, 1); Based on nursing care level: Special care → 0.8, Level 1 care → 0.6, Level 2 care → 0.4, Level 3 care → 0.2; Based on department type: ICU → 0.8, Emergency Department → 0.6, General Ward → 0.3; If all of the above are missing: the default value is 0.5.

[0062] Time of demand generation: The earlier the task is generated, the higher the score, using reverse time normalization (weight 20%).

[0063] Total score = 0.5 × E + 0.3 × C + 0.2 × T. The system sorts tasks in descending order of score. This weighting is based on a quantitative analysis of a large number of nursing service risk events: delayed handling of emergency tasks may directly endanger the patient's life, therefore it has the highest weight; the severity of the patient's condition reflects their basic risk, and is second; the time of occurrence is used as an auxiliary adjustment factor.

[0064] S105: Personalized task list generation.

[0065] The system retrieves the following information from the nursing staff database for the currently logged-in nurse: ① job qualifications (e.g., intravenous catheterization qualification, general catheter maintenance qualification); ② wards under their jurisdiction (e.g., Oncology Ward 1, General Surgery Ward 3). Then, it filters tasks from the sorted task queue that meet the following conditions: ① the patient's ward is within the nurse's jurisdiction; ② the required qualifications for the task match the nurse's qualifications.

[0066] S106: Execution and Status Feedback.

[0067] like Figure 5 As shown, after a nursing staff member completes a task, the system automatically calls the corresponding source system's interface based on the task's source system identifier to write back the execution result (such as updating the medical order execution confirmation status, registration and consultation status, and consultation completion status). If the interface call fails, the system automatically retryes 3 times, with a 5-minute interval between each attempt; if it still fails, an alarm is generated and the administrator is notified.

[0068] S107: Timeout warning.

[0069] The system configures a maximum response time for each task type (e.g., 1 hour for high-risk tasks, 4 hours for routine catheter placement, and 8 hours for maintenance). If the task is not processed within the maximum response time, the system will query the head nurse or nursing director of the relevant department from the hospital's organizational structure table based on the department information associated with the task, and send an escalation reminder to them through the configured messaging channel.

[0070] The technical solution of this application is also applicable to other specialized nursing scenarios. For example, in wound and ostomy care, nurses also need to handle requests from three heterogeneous systems simultaneously: inpatient orders (dressing changes), outpatient registration (follow-up visits), and consultation requests (difficult wounds). By applying the data acquisition, deduplication and merging, and priority sorting techniques of this invention, the same automated data collection and task conversion effects can be achieved.

[0071] The method for automatically collecting and task-oriented conversion of multi-source nursing service needs in this application has the following beneficial effects: Improve work efficiency: Through automatic collection of multi-source data and task standardization, the number of times nurses log in to different systems and the time spent on task organization can be significantly reduced, enabling specialist nurses to devote more working time to core nursing services. Compared with manual methods, the number of times nurses log in to the system per day can be reduced by more than 80%, and the processing time for a single task can be shortened by more than 50%.

[0072] Reduce error rate: The intelligent deduplication and merging mechanism can effectively avoid task omissions and duplicate operations caused by the dispersion of multiple source requirements, and significantly reduce the task processing error rate.

[0073] Ensuring medical safety: By using a weighted priority ranking model that comprehensively considers the urgency of the need, the severity of the patient's condition, and the time when the need arises, combined with an overdue warning mechanism, the response time for high-risk tasks can be significantly shortened.

[0074] Achieving data closure: Through automatic cross-system status feedback, the data is automatically written back to each source business system after task execution, effectively eliminating data errors and omissions caused by manual updates and ensuring the consistency of data across all systems in the institute.

[0075] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above-described method for automatically collecting and task-oriented conversion of multi-source nursing service requirements.

[0076] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the above-described method for automatically collecting and task-oriented conversion of multi-source nursing service requirements.

[0077] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the above-described method for automatically collecting and task-oriented conversion of multi-source nursing service requirements.

[0078] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal, and its internal structure diagram may be as follows. Figure 6As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operating system and computer programs stored in the non-volatile storage media. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network connection. When executed by the processor, the computer program implements a method for automatically collecting and task-oriented conversion of multi-source nursing service needs.

[0079] Those skilled in the art will understand that Figure 6 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0080] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0081] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0082] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0083] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0084] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for automatically collecting and task-oriented conversion of multi-source nursing service needs, characterized in that, include: Obtain nursing service demand data from heterogeneous business systems; the heterogeneous business systems include at least two of the following: the medical order system, the appointment registration system, and the consultation application system. The requirement type for each nursing service requirement data is identified according to preset business rules; the requirement type includes at least nursing operation requirements, nursing assessment requirements, and nursing consultation requirements. Extract key fields from each nursing service requirement data, and convert nursing service requirements from different sources into task objects with a unified structure according to a preset standardized format; the key fields include the patient's unique identifier, the time when the requirement was generated, the requirement source identifier, and the requirement urgency level indication information; Based on the patient's unique identifier, task type, and preset time window, multiple task objects are deduplicated and merged to obtain a deduplicated set of task objects; the task type is determined according to the task requirements. The deduplicated task object set is sorted according to a preset weighted priority rule to obtain a sorted task object set; the preset weighted priority rule considers at least three factors: the urgency of the need, the severity of the patient's condition, and the time when the need arises, and assigns a weight to each factor to calculate a comprehensive score. Based on the job qualifications and jurisdiction of the logged-in nursing staff, tasks that the logged-in nursing staff have the authority to handle are selected from the sorted set of task objects, and a personalized task list is generated and displayed.

2. The method for automatically collecting and task-oriented conversion of multi-source nursing service needs according to claim 1, characterized in that, Extract the key fields from each of the aforementioned nursing service requirement data, specifically including: Based on the source system identifier of the nursing service demand data, determine the data extraction rules corresponding to the source system; Based on the data extraction rules, key fields are located and extracted from the nursing business demand data; If the key field is empty or the format does not meet the preset requirements, it will be completed or corrected according to the preset default value or data cleaning rules.

3. The method for automatically collecting and task-oriented conversion of multi-source nursing service needs according to claim 2, characterized in that, Based on the data extraction rules, key fields are located and extracted from the nursing service demand data, specifically including: Read the value of the specified field directly from the structured data of the nursing service requirements data; Extract the values ​​of specified fields from the semi-structured data of the nursing service demand data according to preset parsing rules; Extract the values ​​of specified fields from the unstructured text of the nursing service demand data according to preset keyword matching or regular expression rules.

4. The method for automatically collecting and task-oriented conversion of multi-source nursing service needs according to claim 1, characterized in that, Based on the patient's unique identifier, task type, and preset time window, multiple task objects are deduplicated and merged to obtain a deduplicated set of task objects, specifically including: If multiple task objects of the same task type exist for the same patient within the same preset time window, they are merged into one task object, and information from multiple sources is merged into the context summary field of the current task object.

5. The method for automatically collecting and task-oriented conversion of multi-source nursing service needs according to claim 1, characterized in that, In the preset weighted priority rule, the weight coefficients of each factor are set according to the quantitative analysis of the risk level of nursing services. Among them, the weight of the urgency of the need is 45% to 55%, the weight of the severity of the patient's condition is 25% to 35%, and the weight of the time when the need arises is 15% to 25%.

6. The method for automatically collecting and task-oriented conversion of multi-source nursing service needs according to claim 1, characterized in that, Also includes: In response to the logged-in nursing staff's execution operation on a task in the personalized task list, the system obtains the execution result and, in accordance with the interface specifications of the heterogeneous business system associated with the task, feeds the execution result back to the corresponding heterogeneous business system to update the business status.

7. The method for automatically collecting and task-oriented conversion of multi-source nursing service needs according to claim 1, characterized in that, Also includes: Configure a corresponding maximum response time for each task type. When there are tasks in the personalized task list that have not been processed after the maximum response time, an automatic reminder will be sent to the responsible caregiver for the corresponding task. If the issue remains unresolved after the preset grace period, an escalation alert will be sent to the superior administrator.

8. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the method for automatically collecting and task-oriented conversion of multi-source nursing service needs as described in any one of claims 1-7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the method for automatically collecting and task-oriented conversion of multi-source nursing service requirements as described in any one of claims 1-7.

10. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the method for automatically collecting and task-oriented conversion of multi-source nursing service requirements as described in any one of claims 1-7.

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