A geographic position-based peaceful therapy resource scheduling method and device

Abstract

This invention provides a method and apparatus for scheduling palliative care resources based on geographic location. The method includes: acquiring emergency call coordinate data and situation description data; obtaining a target emergency level based on the situation description data and preset level determination conditions; obtaining candidate data based on the emergency call coordinate data, the situation description data, and a preset palliative care resource database; obtaining matching data based on the candidate data and the target emergency level; polling based on the matching data to obtain responder data; and scheduling palliative care resources based on the responder data to obtain a palliative care resource scheduling result. This invention can achieve effective scheduling of palliative care resources, which is beneficial to improving emergency response capabilities and user satisfaction.

Description

Technical Field

[0001] This invention relates to the field of palliative care technology, and also to a method and apparatus for scheduling palliative care resources based on geographical location. Background Technology

[0002] Palliative care is a specialized medical care service focused on improving the quality of life for terminally ill patients, alleviating physical pain, providing psychological and emotional support, and upholding the dignity of life. Service scenarios encompass diverse settings including palliative wards in medical institutions, community day care centers, home-based palliative care, and elderly care facilities. Compared to general elderly care and routine medical services, palliative care recipients are characterized by rapid disease progression, frequent sudden emergencies, severe symptom reactions, and high frequency of emergency needs. Common emergencies include acute attacks of severe cancer pain, acute respiratory distress, near-death agitation, altered consciousness, sudden heart failure, psychological crises, and emotional breakdowns by family members. This places extremely high demands on service response speed, staff professionalism, and standardized on-site procedures. However, existing palliative care resource allocation methods largely rely on manual experience-based dispatching, lacking standardized professional databases. This can lead to dispatching tasks to unqualified personnel, delaying effective intervention. Furthermore, the lack of real-time monitoring of working hours, fatigue, and on-the-go workload means that heavily overloaded personnel are still assigned during emergency calls. Therefore, existing palliative care resource allocation methods suffer from a lack of emergency response capabilities and an inability to promptly meet user needs. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to provide a method and apparatus for scheduling palliative care resources based on geographical location, so as to improve emergency response capabilities and the effectiveness of palliative care resource scheduling.

[0004] To solve the above-mentioned technical problems, the technical solution of the present invention is as follows: A first aspect of the present invention provides a method for scheduling palliative care resources based on geographic location, comprising: Obtain emergency call coordinate data and situation description data; Based on the situation description data and preset level determination conditions, the target emergency level is obtained; Candidate data is obtained based on the emergency call coordinate data, the situation description data, and the preset palliative care resource database; Based on the candidate data and the target urgency level, matching data is obtained; The responder data is obtained by polling based on the matching data. Based on the responder data, palliative care resources are allocated to obtain the palliative care resource allocation results.

[0005] Optionally, based on the situation description data and preset level determination conditions, the target emergency level is obtained, including: Obtain preset level determination conditions; the preset level determination conditions include: emergency level standards, corresponding level definition data, preset determination conditions, preset descriptive keywords, and preset scenario keywords; Keyword extraction is performed on the situation description data to obtain keywords; The target emergency level is obtained based on the keywords and the preset level determination conditions.

[0006] Optionally, candidate data can be obtained based on the emergency call coordinate data, the situation description data, and the preset palliative care resource database, including: Access a pre-defined database of palliative care resources; Keyword extraction is performed on the situation description data to obtain keywords; Based on the emergency call coordinates, the preset search radius, and the keywords, the preset palliative care resource database is searched to obtain candidate data.

[0007] Optionally, access a pre-defined palliative care resource database, including: Obtain entity data of hospice care institutions, hospice care volunteers, and hospice care medical experts; An initial hospice resource database is obtained based on the entity data of the hospice care institutions, the entity data of the hospice care volunteers, and the entity data of the hospice care medical experts. Based on the acquired real-time status data of volunteers and medical experts, the initial palliative care resource database is updated to obtain a real-time palliative care resource database. The real-time palliative care resource database is visualized to obtain a visualized palliative care resource database; Based on the real-time palliative care resource database and the visualized palliative care resource database, a preset palliative care resource database is obtained.

[0008] Optionally, matching data is obtained based on the candidate data and the target emergency level, including: Based on the target urgency level, determine the adjustable weighting coefficient; pass The matching degree is obtained; where, For matching degree, , , , All are adjustable weighting coefficients. This represents the straight-line distance between the candidate and the emergency call point in the candidate data. This is the maximum value of the preset search radius. This represents the similarity between skill tags and keywords in the candidate data. This represents the real-time status of the candidate, with a value of 1 or 0. This is the ratio of the total service time accumulated on that day to the maximum service time limit. Matching data is obtained based on the matching degree and the candidate data.

[0009] Optionally, polling is performed based on the matching data to obtain responder data, including: The matching data is sorted according to the matching degree to obtain a matching sequence; The candidates in the matching sequence are polled in batches according to preset polling conditions to obtain response information; Based on the response information, responder data is obtained.

[0010] Optionally, palliative care resources are allocated based on the responder data to obtain palliative care resource allocation results, including: Send the responder data to the user terminal; Evaluation data is obtained based on the received user feedback data; Based on the responder data and the evaluation data, the results of the palliative care resource allocation are obtained.

[0011] A second aspect of the present invention provides a location-based palliative care resource scheduling device, comprising: The acquisition module is used to acquire emergency call coordinate data and situation description data; The processing module is used to obtain a target emergency level based on the situation description data and preset level determination conditions; obtain candidate data based on the emergency call coordinate data, the situation description data, and a preset palliative care resource database; obtain matching data based on the candidate data and the target emergency level; poll based on the matching data to obtain responder data; and schedule palliative care resources based on the responder data to obtain a palliative care resource scheduling result.

[0012] A third aspect of the present invention provides a computing device, comprising: a processor and a memory storing a computer program, wherein the computer program, when executed by the processor, performs the method described in the first aspect.

[0013] A fourth aspect of the present invention provides a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the method as described in the first aspect.

[0014] The above-described solution of the present invention has at least the following beneficial effects: The above-described solution of the present invention obtains emergency call coordinate data and situation description data, and determines the target emergency level based on the situation description data and preset level determination conditions. It then obtains candidate data based on the emergency call coordinate data, the situation description data, and a preset palliative care resource database. Next, it obtains matching data based on the candidate data and the target emergency level. Finally, it performs polling based on the matching data to obtain responder data. Finally, it schedules palliative care resources based on the responder data to obtain the palliative care resource scheduling result. This approach enables effective scheduling of palliative care resources, which is beneficial for improving emergency response capabilities and user satisfaction. Attached Figure Description

[0015] Figure 1 This is a flowchart illustrating the location-based palliative care resource scheduling method in an embodiment of the present invention. Figure 2 This is a schematic diagram of the structure of the geographical location-based palliative care resource scheduling device in an embodiment of the present invention. Detailed Implementation

[0016] Exemplary embodiments of the invention will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this invention will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.

[0017] like Figure 1 As shown, an embodiment of the present invention proposes a method for scheduling palliative care resources based on geographical location, including the following steps: Step 101: Obtain emergency call coordinate data and situation description data; Step 102: Based on the situation description data and preset level determination conditions, obtain the target emergency level; Step 103: Based on the emergency call coordinate data, the situation description data, and the preset palliative care resource database, candidate data is obtained; Step 104: Obtain matching data based on the candidate data and the target emergency level; Step 105: Poll the matching data to obtain responder data; Step 106: Perform palliative care resource scheduling based on the responder data to obtain palliative care resource scheduling results.

[0018] The geolocation-based palliative care resource scheduling method of this invention acquires emergency call coordinate data and situation description data, and obtains a target emergency level based on the situation description data and preset level determination conditions. It then obtains candidate data based on the emergency call coordinate data, the situation description data, and a preset palliative care resource database. Next, it obtains matching data based on the candidate data and the target emergency level, performs polling based on the matching data to obtain responder data, and finally schedules palliative care resources based on the responder data to obtain the palliative care resource scheduling result. This method can achieve effective scheduling of palliative care resources, which is beneficial for improving emergency response capabilities and user satisfaction.

[0019] In an optional embodiment of the present invention, step 101 involves acquiring emergency call coordinate data and situation description data; Specifically, emergency call coordinate data and situation description data are information contained in the emergency call request sent by the patient's family through the user terminal. Among them, the emergency call coordinate data is the GPS (Global Positioning System) coordinates of the user terminal, which is used to locate the patient and to calculate the distance between the candidate and the patient when screening candidates later. The situation description data is a descriptive text (or text converted from speech recognition) of the patient's or their own physical or psychological condition by the patient's family, which is used to determine the emergency level and to match the corresponding medical experts.

[0020] In an optional embodiment of the present invention, step 102, obtaining the target emergency level based on the situation description data and preset level determination conditions, may include: Step 1021: Obtain preset level determination conditions; the preset level determination conditions include: emergency level standards, corresponding level definition data, preset determination conditions, preset descriptive keywords, and preset scenario keywords; Specifically, as shown in Table 1, the preset level determination criteria need to include emergency level standards, corresponding level definition data, preset determination criteria, preset descriptive keywords, and preset scenario keywords, so as to facilitate the rapid determination of the target emergency level.

[0021] Table 1 Preset Level Determination Criteria

[0022] Step 1022: Extract keywords from the situation description data to obtain keywords; Specifically, keyword extraction can be performed through the following steps: The situation description data is preprocessed to obtain preprocessed data; here, interjections (such as ah, ya, oh, etc.) in the situation description data can be deleted, and the core sentences are retained as preprocessed data; Medical keywords are extracted from the preprocessed data. Here, medical keywords can be extracted from the preprocessed data according to preset medical standard keywords (including synonyms, colloquial derivatives, etc.). Words that meet or are similar to the preset medical standard keywords in the preprocessed data are extracted as medical keywords. Emotional keywords are extracted from the preprocessed data. Here, emotional keywords can be extracted from the preprocessed data according to preset emotional standard keywords (including synonyms, colloquial derivatives, etc.). Words that meet or are similar to the preset emotional standard keywords in the preprocessed data are extracted as emotional keywords. Keywords are obtained based on the medical keywords and the emotional keywords. Here, keywords include both medical keywords and emotional keywords.

[0023] Step 1023: Obtain the target emergency level based on the keywords and the preset level determination conditions.

[0024] Specifically, when determining the target urgency level, the keywords are first compared with the preset descriptive keywords / preset scenario keywords in the preset level determination criteria to determine whether the keywords contain the preset descriptive keywords or preset scenario keywords. When the keywords contain the preset descriptive keywords, the target urgency level is Level 1; when the keywords only contain the preset scenario keywords, the target urgency level is Level 2. The purpose of determining the target urgency level is to provide support for the subsequent allocation of palliative care resources, to allocate appropriate resources to patients or their families, and to improve suitability.

[0025] In an optional embodiment of the present invention, step 103, obtaining candidate data based on the emergency call coordinate data, the situation description data, and the preset palliative care resource database, may include: Step 1031: Obtain the preset palliative care resource database; Specifically, the pre-set palliative care resource database can be a database that integrates relevant resources such as palliative care institutions, volunteers, and experts within a target area, providing data support for subsequent resource allocation.

[0026] Step 1032: Extract keywords from the situation description data to obtain keywords; Specifically, keywords are extracted from the situation description data using the method in step 1022 to obtain keywords, which can be used directly to search the database and find suitable resources.

[0027] Step 1033: Based on the emergency call coordinate data, the preset search radius, and the keywords, search the preset palliative care resource database to obtain candidate data.

[0028] Specifically, using the coordinates in the emergency call coordinate data as the center, the preset search radius is... (e.g., 3 kilometers) Search the preset palliative care resource database for candidates who meet the following criteria: Palliative care volunteers: online status, and service skill tags matching keywords (e.g., end-of-life care or respiratory distress care); Palliative care institution entities: on-duty status available; If the number of candidates found is less than the preset candidate number threshold (e.g., 3 people), then the preset search radius will be expanded. Increase the step size by a preset step size (e.g., 1 kilometer) until the preset search radius is reached. Reaching the upper limit (e.g., 10 kilometers). Data on eligible palliative care volunteers and / or palliative care institutions and / or palliative care medical experts (e.g., real-time coordinates, name / title, status, skill tags, etc.) will be used as candidate data.

[0029] In an optional embodiment of the present invention, step 1031 includes: Step 10311: Obtain entity data of hospice care institutions, hospice care volunteers, and hospice care medical experts; Specifically, a hospice care institution can be any of the following: a hospice care hospital, a community health service center, a hospice ward, or a hospice section within a senior care facility. The entity data for a hospice care institution includes its name, address, latitude and longitude (or GPS coordinates, etc.), service type tags (inpatient, home-based, day care), contact number, and qualification level.

[0030] The entity data of palliative care volunteers includes skill tags, permanent location (cluster centers based on historical service trajectories), current status (online / offline / in service), contact information, etc.

[0031] Palliative care medical experts can be pain specialists, palliative care physicians, and psychologists, among others. The entity data for palliative care medical experts includes their institution of practice, available consultation hours, and areas of expertise.

[0032] Data for each entity can be obtained through the following methods: official filing data, platform registration and certification data, API pushes from partner institutions, crawling from public directories and manual verification, etc.

[0033] Step 10312: Based on the entity data of the palliative care institution, the entity data of the palliative care volunteer, and the entity data of the palliative care medical expert, an initial palliative care resource database is obtained; Specifically, the entity data of hospice care institutions, hospice care volunteers, and hospice care medical experts can be stored in an orderly manner in tabular form to form an initial hospice care resource database.

[0034] Step 10313: Update the initial palliative care resource database based on the obtained real-time status data of volunteers and medical experts to obtain a real-time palliative care resource database; Specifically, the initial palliative care resource database can be updated in the following ways: Volunteer data updates: Volunteers regularly report their heart rate via mobile devices, including real-time status data such as current GPS coordinates and status flags. Dynamic adjustment of heart rate intervals: Volunteers report every 5 minutes when online but not accepting orders, and every minute after accepting an order. If no report is received for three consecutive heart rate cycles, the corresponding status in the initial palliative care resource database is automatically marked as "offline," and the volunteer is temporarily removed from the available resource pool.

[0035] Institution and Expert Data Updates: Based on real-time data such as bed availability and patient capacity obtained from the hospital information system or scheduling system, the initial palliative care resource database is updated with data on palliative care institution entities and palliative care medical expert entities. Here, the expert's available consultation time slots are synchronized by the expert or their assistant via a calendar interface.

[0036] By updating the initial palliative care resource database, a real-time palliative care resource database is obtained, which enables real-time querying of the status of relevant personnel when responding to user needs, thereby improving the effectiveness of scheduling.

[0037] Step 10314: Visualize the real-time palliative care resource database to obtain a visualized palliative care resource database; Specifically, the target area can be mapped into a grid. Based on coordinate data from a real-time palliative care resource database, the number of available volunteers and institutions within each grid can be counted and rendered using varying shades of color, forming a visual palliative care resource database. This facilitates user queries based on the map and helps administrators identify service blind spots. This visual palliative care resource database can be loaded into a mini-program. Users can input query criteria (service type, distance range, skill requirements) through the mini-program or webpage. Based on the user's current location, the great circle distance or road network distance to each resource point is calculated, and the results are returned sorted by a comprehensive score. The comprehensive score = distance weight × distance score + status weight × online status bonus + evaluation weight × historical score. Users select institutions, etc., based on the comprehensive score.

[0038] Step 10315: Obtain a preset palliative care resource database based on the real-time palliative care resource database and the visualized palliative care resource database.

[0039] Specifically, the pre-defined palliative care resource database includes a real-time palliative care resource database and a visualized palliative care resource database. The real-time palliative care resource database is mainly used to search for candidates and allocate resources when responding to user calls, while the visualized palliative care resource database is used to intuitively understand the resource range and to allow users to query and select resources.

[0040] In an optional embodiment of the present invention, step 104, obtaining matching data based on the candidate data and the target emergency level, may include: Step 1041: Determine the adjustable weighting coefficient based on the target urgency level; Specifically, adjustable weighting coefficients , , , The sum is 1. When the target urgency level is Level 1, the weighting coefficient can be adjusted. This weakens the time limit. In one specific embodiment, when the target urgency level is level one, The initial value can be set to 0.2. The initial value can be set to 0.5. The initial value can be set to 0.2. The initial value can be set to 0.1.

[0041] When the target's urgency level is level two, the weighting coefficient can be adjusted. Appropriate consideration should be given to time balance. In one specific embodiment, when the target urgency level is level two, The initial value can be set to 0.4. The initial value can be set to 0.2. The initial value can be set to 0.3. The initial value can be set to 0.1.

[0042] Step 1042, through The matching degree is obtained; where, For matching degree, , , , All are adjustable weighting coefficients. This represents the straight-line distance between the candidate and the emergency call point in the candidate data. This is the maximum value of the preset search radius. This represents the similarity between skill tags and keywords in the candidate data. This represents the real-time status of the candidate, with a value of 1 or 0. This is the ratio of the total service time accumulated on that day to the maximum service time limit. Specifically, the straight-line distance between the candidate and the emergency call point in the candidate data. , Let i be the coordinates of the i-th candidate. For emergency call coordinates, if If the match is not found, the candidate is removed and their match score is not calculated; the similarity between skill tags and keywords in the candidate data. A is the keyword. Let i be the set of skill tags for the i-th candidate. Represents the number of elements in the set, with a value range of [0,1]. The more matching keywords, the higher the similarity. The real-time status of the i-th candidate when it is on duty, available, or can accept orders (valid status). The value is 1 if it is set to 1, and 0 otherwise; the ratio of the cumulative service time to the maximum service time limit for the day. , The cumulative service time for the i-th candidate on that day, To preset a maximum daily service time limit for a single person (e.g., 10 hours), to prevent excessive fatigue and improve the rationality of matching degree calculation.

[0043] Step 1043: Obtain matching data based on the matching degree and the candidate data.

[0044] Specifically, the matching data includes candidate data and their corresponding matching degrees.

[0045] In an optional embodiment of the present invention, step 105, polling based on the matching data to obtain responder data, may include: Step 1051: Sort the matching data according to the matching degree in the matching data to obtain a matching sequence; Specifically, the candidates in the matching data are sorted in descending order of matching degree to obtain a matching sequence. The matching sequence includes the matching degree and the corresponding matching data, and is an ordered sequence of data.

[0046] Step 1052: Poll the candidates in the matching sequence in batches according to the preset polling conditions to obtain response information; Specifically, emergency call requests are simultaneously pushed to the top K candidates (e.g., 5 people) in the matching sequence according to the matching degree from high to low. The "first confirmation, first assignment" mechanism is adopted, and the candidates corresponding to the first n response information received are used as responders in sequence. The responder data is obtained based on the data of the first n responders.

[0047] If no one accepts the order within the preset time threshold (e.g., 30 seconds) in the first round, the candidate set is expanded to the next batch of K people until someone accepts the order or the maximum round is reached.

[0048] Step 1053: Obtain responder data based on the response information.

[0049] Specifically, based on the response information, the responder's real-time location, skill tags, and other information can be determined. The distance between the responder and the patient and the estimated arrival time can be calculated. The responder data includes at least the arrival time.

[0050] In an optional embodiment of the present invention, step 106, which involves scheduling palliative care resources based on the responder data to obtain a palliative care resource scheduling result, may include: Step 1061: Send the responder data to the user terminal; Specifically, after determining the responder's data, the responder's real-time location and estimated arrival time are pushed to the patient's family member's end (i.e., the user's end).

[0051] Step 1062: Obtain evaluation data based on the received user feedback data; Specifically, after the service is completed, the patient's family can evaluate the emergency response and obtain evaluation data. This evaluation data is fed back to the responder's historical scores and stored in the palliative care resource database for iterative optimization of subsequent comprehensive scoring.

[0052] Step 1063: Based on the responder data and the evaluation data, obtain the hospice care resource scheduling result.

[0053] Specifically, respondent data, evaluation data, etc., can be filled into the preset palliative care resource scheduling template one by one to form a palliative care resource scheduling report, which serves as the result of palliative care resource scheduling and facilitates consent management and data backtracking.

[0054] A specific embodiment of the location-based palliative care resource scheduling method of the present invention includes: Step 111: Obtain emergency call coordinate data and situation description data; The system receives emergency call coordinates and condition description data sent by the patient's family through the terminal. The condition description data is a brief description provided by the family (such as "shortness of breath, needs someone to accompany him / her").

[0055] Step 112: Obtain the target emergency level based on the situation description data and preset level determination conditions; Based on preset grading criteria and situation description data, the system automatically identifies the target emergency level (Level 1: Requires medical treatment; Level 2: Requires psychological support and companionship).

[0056] Step 113: Based on the emergency call coordinate data, the situation description data, and the preset palliative care resource database, candidate data is obtained; A palliative care resource database is constructed by acquiring entity data from institutions, volunteers, and medical experts. This database is updated based on regularly submitted heart rate packets from volunteers (including current GPS coordinates and status markers) and real-time information from institutions and experts, resulting in a pre-defined palliative care resource database. Keywords are extracted from the condition description data and compared with the skill tags of various personnel in the pre-defined palliative care resource database, along with matching distance and other methods, to determine suitable candidates.

[0057] Step 114: Obtain matching data based on the candidate data and the target emergency level; After determining the weights based on the target urgency level, the matching degree of each candidate in the candidate data is calculated using the matching degree calculation formula. The matching degree and the candidate data are then used together as the matching data.

[0058] Step 115: Poll the matching data to obtain responder data; The matching data is sorted from highest to lowest according to the matching degree, and an emergency call request is sent to the top K candidates simultaneously. If no one accepts the order within 30 seconds in the first round, the candidate set is expanded to the next batch of K people, until someone accepts the order or the maximum round is reached. The respondent data is determined according to the response order.

[0059] Step 116: Perform palliative care resource scheduling based on the responder data to obtain palliative care resource scheduling results.

[0060] Upon arrival, the responder confirms "arrival" via a terminal and completes a brief service record after service is provided. Family members can evaluate the emergency response; this evaluation data is fed back to the responder's historical ratings for iterative optimization of subsequent comprehensive ratings. Data from the entire call-to-service completion process is populated into a preset template to generate palliative care resource allocation results.

[0061] The geolocation-based palliative care resource scheduling method of this invention reduces resource data update latency from an average of over 24 hours to less than 5 minutes; the average emergency call response time is less than 45 seconds, and the responder's arrival time at the scene is reduced by approximately 60% compared to traditional manual contact. It can provide a safety net of "psychological first aid" for families of patients receiving palliative care at home, reducing panic and helplessness caused by terminal emergencies; and improve the utilization rate of volunteer and community resources. It constructs a real-time resource map and emergency response network in the field of palliative care, which can be reused in related fields such as home-based elderly care and community nursing.

[0062] Another specific embodiment of the location-based palliative care resource scheduling method of the present invention includes: The pre-built palliative care resource database includes a directory of over 300 registered palliative care institutions, and has over 1,500 registered and certified volunteers and over 200 experts through the platform. Volunteer Xiao D registered by filling in the skill tags "companionship and conversation, respite care," and listed his / her usual location as XXX. He / she has a service assistant app installed on his / her mobile device and has granted background location permissions.

[0063] At 9:00 AM one morning, Xiao D opened the app and clicked "Online." The app started reporting her heart rate (latitude and longitude, status = online) every 5 minutes. At 10:30 AM, Xiao D received a scheduled companionship task, and her status changed to "In Service," with her heart rate frequency switching to reporting every minute.

[0064] At 11:15 AM, Ms. E, a family member living in the YYY residential area, pressed the "emergency call" button through a mini-program because her mother suddenly experienced difficulty breathing and emotional breakdown. The system obtained the coordinates of the call location and identified "difficulty breathing" and "panic" based on the emergency description keywords, classifying it as a Level 1 emergency.

[0065] Four online volunteers were found within an initial radius of 3 kilometers. Among them, Xiao D was 1.2 kilometers away from the call point, had a high semantic similarity between his skill tag and "companionship," and had no current tasks, making him the best match. Another volunteer, Xiao F, was 0.9 kilometers away, but his skill tag was "hairdressing service," which did not match.

[0066] Simultaneously, an emergency request was sent to the top 3 matching volunteers. A notification popped up on Xiao D's phone; after clicking "Accept Order," the family member's app immediately displayed, "Volunteer Xiao D has accepted the order and is expected to arrive in 12 minutes." Upon arrival, Xiao D assisted in calming the patient and guided the family member to adjust the patient's position. The service was recorded after completion.

[0067] The regional administrator checked the palliative care resource database in the backend and found that the volunteer coverage density in the area was high, but there was a gap in a newly built community to the south, so a targeted recruitment was planned.

[0068] like Figure 2 As shown, an embodiment of the present invention proposes a location-based palliative care resource scheduling device 200, comprising: Module 201 is used to acquire emergency call coordinate data and situation description data; The processing module 202 is used to obtain a target emergency level based on the situation description data and preset level determination conditions; obtain candidate data based on the emergency call coordinate data, the situation description data and a preset palliative care resource database; obtain matching data based on the candidate data and the target emergency level; poll based on the matching data to obtain responder data; and perform palliative care resource scheduling based on the responder data to obtain a palliative care resource scheduling result.

[0069] Optionally, based on the situation description data and preset level determination conditions, the target emergency level is obtained, including: Obtain preset level determination conditions; the preset level determination conditions include: emergency level standards, corresponding level definition data, preset determination conditions, preset descriptive keywords, and preset scenario keywords; Keyword extraction is performed on the situation description data to obtain keywords; The target emergency level is obtained based on the keywords and the preset level determination conditions.

[0070] Optionally, candidate data can be obtained based on the emergency call coordinate data, the situation description data, and the preset palliative care resource database, including: Access a pre-defined database of palliative care resources; Keyword extraction is performed on the situation description data to obtain keywords; Based on the emergency call coordinates, the preset search radius, and the keywords, the preset palliative care resource database is searched to obtain candidate data.

[0071] Optionally, access a pre-defined palliative care resource database, including: Obtain entity data of hospice care institutions, hospice care volunteers, and hospice care medical experts; An initial hospice resource database is obtained based on the entity data of the hospice care institutions, the entity data of the hospice care volunteers, and the entity data of the hospice care medical experts. Based on the acquired real-time status data of volunteers and medical experts, the initial palliative care resource database is updated to obtain a real-time palliative care resource database. The real-time palliative care resource database is visualized to obtain a visualized palliative care resource database; Based on the real-time palliative care resource database and the visualized palliative care resource database, a preset palliative care resource database is obtained.

[0072] Optionally, matching data is obtained based on the candidate data and the target emergency level, including: Based on the target urgency level, determine the adjustable weighting coefficient; pass The matching degree is obtained; where, For matching degree, , , , All are adjustable weighting coefficients. This represents the straight-line distance between the candidate and the emergency call point in the candidate data. This is the maximum value of the preset search radius. This represents the similarity between skill tags and keywords in the candidate data. This represents the real-time status of the candidate, with a value of 1 or 0. This is the ratio of the total service time accumulated on that day to the maximum service time limit. Matching data is obtained based on the matching degree and the candidate data.

[0073] Optionally, polling is performed based on the matching data to obtain responder data, including: The matching data is sorted according to the matching degree to obtain a matching sequence; The candidates in the matching sequence are polled in batches according to preset polling conditions to obtain response information; Based on the response information, responder data is obtained.

[0074] Optionally, palliative care resources are allocated based on the responder data to obtain palliative care resource allocation results, including: Send the responder data to the user terminal; Evaluation data is obtained based on the received user feedback data; Based on the responder data and the evaluation data, the results of the palliative care resource allocation are obtained.

[0075] The geolocation-based palliative care resource scheduling device of this invention acquires emergency call coordinate data and situation description data, and obtains a target emergency level based on the situation description data and preset level determination conditions. It then obtains candidate data based on the emergency call coordinate data, the situation description data, and a preset palliative care resource database. Next, it obtains matching data based on the candidate data and the target emergency level, performs polling based on the matching data to obtain responder data, and finally schedules palliative care resources based on the responder data to obtain the palliative care resource scheduling result. This device can achieve effective scheduling of palliative care resources, which is beneficial for improving emergency response capabilities and user satisfaction.

[0076] It should be noted that this device corresponds to the method described above, and all implementations in the method embodiments described above are applicable to the embodiments of this device and can achieve the same technical effect. Further details are omitted in this embodiment.

[0077] This invention also provides a computing device, including: a processor and a memory storing a computer program, wherein the computer program, when executed by the processor, performs the method as described in any of the above embodiments. All implementations in the above method embodiments are applicable to the embodiments of this device and can achieve the same technical effects. Further details are omitted in this embodiment.

[0078] This invention also provides a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the method as described in any of the above embodiments. All implementations in the above method embodiments are applicable to the embodiments of this device and can achieve the same technical effects. Further details are omitted in this embodiment.

[0079] It should be noted that in the apparatus and method of the present invention, the components or steps can obviously be decomposed and / or recombined. These decompositions and / or recombinations should be considered equivalent solutions of the present invention. Furthermore, the steps for performing the above series of processes can naturally be performed in the order described and in chronological order, but are not necessarily required to be performed in chronological order. Some steps can be performed in parallel, overlapping, or independently of each other.

[0080] It should be noted that in the above embodiments, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments described above is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0081] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for allocating palliative care resources based on geographical location, characterized in that, include: Obtain emergency call coordinate data and situation description data; Based on the situation description data and preset level determination conditions, the target emergency level is obtained; Candidate data is obtained based on the emergency call coordinate data, the situation description data, and the preset palliative care resource database; Based on the candidate data and the target urgency level, matching data is obtained; The responder data is obtained by polling based on the matching data. Based on the responder data, palliative care resources are allocated to obtain the palliative care resource allocation results.

2. The method of claim 1, wherein, Based on the situation description data and preset level determination conditions, the target emergency level is obtained, including: Obtain preset level determination conditions; the preset level determination conditions include: emergency level standards, corresponding level definition data, preset determination conditions, preset descriptive keywords, and preset scenario keywords; Keyword extraction is performed on the situation description data to obtain keywords; The target emergency level is obtained based on the keywords and the preset level determination conditions.

3. The method of claim 1, wherein, Based on the emergency call coordinate data, the situation description data, and the preset palliative care resource database, candidate data is obtained, including: Access a pre-defined database of palliative care resources; Keyword extraction is performed on the situation description data to obtain keywords; Based on the emergency call coordinates, the preset search radius, and the keywords, the preset palliative care resource database is searched to obtain candidate data.

4. The method of claim 3, wherein, Access a pre-built database of palliative care resources, including: Obtain entity data of hospice care institutions, hospice care volunteers, and hospice care medical experts; An initial hospice resource database is obtained based on the entity data of the hospice care institutions, the entity data of the hospice care volunteers, and the entity data of the hospice care medical experts. Based on the acquired real-time status data of volunteers and medical experts, the initial palliative care resource database is updated to obtain a real-time palliative care resource database. The real-time palliative care resource database is visualized to obtain a visualized palliative care resource database; Based on the real-time palliative care resource database and the visualized palliative care resource database, a preset palliative care resource database is obtained.

5. The method of claim 1, wherein, Based on the candidate data and the target emergency level, matching data is obtained, including: Based on the target urgency level, determine the adjustable weighting coefficient; pass The matching degree is obtained; where, For matching degree, , , , All are adjustable weighting coefficients. This represents the straight-line distance between the candidate and the emergency call point in the candidate data. This is the maximum value of the preset search radius. This represents the similarity between skill tags and keywords in the candidate data. This represents the real-time status of the candidate, with a value of 1 or 0. This is the ratio of the total service time accumulated on that day to the maximum service time limit. Matching data is obtained based on the matching degree and the candidate data.

6. The method for allocating palliative care resources based on geographical location according to claim 1, characterized in that, Based on the matching data, polling is performed to obtain responder data, including: The matching data is sorted according to the matching degree to obtain a matching sequence; The candidates in the matching sequence are polled in batches according to preset polling conditions to obtain response information; Based on the response information, responder data is obtained.

7. The method for allocating palliative care resources based on geographical location according to claim 1, characterized in that, Based on the responder data, palliative care resources are allocated to obtain palliative care resource allocation results, including: Send the responder data to the user terminal; Evaluation data is obtained based on the received user feedback data; Based on the responder data and the evaluation data, the results of the palliative care resource allocation are obtained.

8. A location-based palliative care resource scheduling device, characterized in that, include: The acquisition module is used to acquire emergency call coordinate data and situation description data; The processing module is used to obtain the target emergency level based on the situation description data and preset level determination conditions; Candidate data is obtained based on the emergency call coordinate data, the situation description data, and the preset palliative care resource database; matching data is obtained based on the candidate data and the target emergency level; responder data is obtained by polling based on the matching data; palliative care resources are scheduled based on the responder data to obtain the palliative care resource scheduling result.

9. A computing device, characterized in that, include: A processor, a memory storing a computer program, wherein the computer program, when executed by the processor, performs the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The system stores instructions that, when executed on a computer, cause the computer to perform the method as described in any one of claims 1 to 7.

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