Cloud PACS radiation report intelligent distribution method
By introducing intelligent distribution services in the cloud PACS system, the distribution of radiation reports is automatically distributed according to queues and job strategies, the problems of low distribution efficiency and high maintenance difficulty in the existing technology are solved, efficient report distribution is achieved, cost reduction is reduced, and the Diagnostic accuracy and user experience.
Patent Information
- Application Number
- CN202411219806.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-02
- Publication Date
- 2025-01-10
AI Technical Summary
The distribution efficiency of radiation reports in the existing cloud PACS system is low, the maintenance is difficult, and the lack of intelligent distribution mechanisms, resulting in low diagnostic efficiency, high maintenance cost, and requires professional operation.
A cloud PACS radiation report intelligent distribution method was designed. By introducing intelligent distribution services in the cloud PACS system, using the background thread detection task pool, intelligently match and allocate reports to the appropriate doctors according to the queue strategy and job strategy, considering the doctor's work to achieve automated distribution of information.
It significantly improves distribution efficiency, shortens doctor diagnosis time, improves medical efficiency, reduces maintenance difficulty, reduces dependence on R&D personnel, saves labor costs, and improves user experience.
Smart Images
Figure CN119296712A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of medical imaging, and in particular to a cloud PACS radiology report intelligent distribution method. Background Art
[0002] In the existing technology, cloud PACS (Cloud Picture Archiving and Communication System) refers to the technology of deploying medical image archiving and communication systems on a cloud platform and accessing and managing image data through the network. Cloud PACS technology has the advantages of strong scalability, lower cost, convenient access, and secure and reliable data. It has been widely used in the medical field in recent years.
[0003] Traditional radiology report distribution mainly relies on passive pulling, that is, doctors need to manually select the reports they need to read. This model usually uses some fixed options + complex SQL code to implement queue strategy management, which has the following problems:
[0004] 1) Inefficiency: Doctors need to manually select queues or reports, which is inefficient and affects diagnostic efficiency.
[0005] 2) High maintenance difficulty: R&D personnel are required to write SQL code, that is, to generate SQL code through queue strategies to continuously poll the database, which not only increases the database access pressure, but also leads to low SQL efficiency and requires frequent optimization.
[0006] The maintenance cost is high and requires professional personnel to operate.
[0007] 3) Lack of intelligence: There is a lack of intelligent allocation mechanism, and it is impossible to make intelligent allocations based on factors such as the doctor’s workload and areas of expertise. Summary of the invention
[0008] In order to solve the above problems, the present invention provides a cloud PACS radiology report intelligent distribution method.
[0009] In order to achieve the above object, the cloud PACS radiology report intelligent distribution method designed by the present invention comprises the following steps:
[0010] S1. After the cloud PACS system completes the inspection QA, push the inspection data to the intelligent distribution service;
[0011] S2. After receiving the inspection data, the intelligent distribution service places it into different task pools according to the report status;
[0012] S3. The background thread detects the task pool. If there is a distribution task, the distribution task thread is started. The distribution task thread includes the following steps:
[0013] S3.1. Check whether the data has been distributed. If it has been distributed, end the distribution task thread. Otherwise, synchronize the distribution queue strategy of the cloud PACS system.
[0014] S3.2. Match the qualified distribution queue according to the queue strategy. If there are multiple qualified distribution queues, terminate the distribution task thread;
[0015] S3.3. Obtain the associated positions according to the queue strategy, and determine whether the inspection data matches the position according to the content of the inspection data. If not, the inspection data is delayed until the position data that matches the conditions appears most recently before being assigned;
[0016] S3.4. Determine the distribution position according to the queue strategy and obtain the position strategy; if the position strategy is not set, distribute it to the position task pool for the next step of distribution;
[0017] S3.5. Assign tasks to doctors according to the job strategy;
[0018] S3.6. Obtain the assigned doctors and update the job workload;
[0019] S4. Update the report distribution position, distribute doctor information, and end the distribution task thread.
[0020] A further solution is that in step S2, the task pool includes but is not limited to a pool of tasks to be written and a pool of tasks to be reviewed.
[0021] A further solution is that in step S3, the distribution queue strategy includes but is not limited to queue name, department name, allocation rule and priority.
[0022] A further solution is that in step S3, the position strategy includes but is not limited to the doctor's name, the doctor's area of expertise, the doctor's workload, the doctor's current work status and scheduling information.
[0023] A further solution is that in step S3.4, the job task pool is allocated by manual intervention, or the job task pool allocates the examination data to a designated doctor in the job according to a preset default rule.
[0024] A further solution is that in step S3.2, when there are multiple distribution queues that meet the conditions, the inspection data is put into a waiting queue, and the waiting queue is selected and allocated by manual intervention.
[0025] The cloud PACS radiology report intelligent distribution method designed by the present invention can significantly improve the distribution efficiency, shorten the doctor's diagnosis time, and improve medical efficiency; at the same time, by intelligently distributing reports according to factors such as the doctor's workload, areas of expertise, and scheduling information, it can avoid workload imbalance, improve the doctor's work efficiency, and improve the accuracy of diagnosis; in addition, it also reduces the difficulty of maintenance, reduces dependence on R&D personnel, saves labor costs, and improves user experience. BRIEF DESCRIPTION OF THE DRAWINGS
[0026] Figure 1 It is a schematic diagram of the distribution method provided in the embodiment of the present application;
[0027] Figure 2 It is a schematic diagram of the distribution task thread flow provided in an embodiment of the present application. DETAILED DESCRIPTION
[0028] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.
[0029] Example 1.
[0030] like Figure 1 As shown, the cloud PACS radiology report intelligent distribution method described in this embodiment includes the following steps:
[0031] S1. After the cloud PACS system inspection QA is completed, the inspection data is pushed to the intelligent distribution service.
[0032] In specific implementation, after completing the examination, the patient needs to conduct a preliminary quality control (QA) check on the examination results, that is, to ensure that the image data is complete and there is no missing or damaged part, and to evaluate whether the image quality meets the diagnostic requirements, for example, whether the image clarity, contrast, noise level, etc. meet the standards, and whether the patient information, examination information, examination time and other information are accurate. Once the examination results are confirmed to be qualified, the cloud PACS system will automatically push the examination data to the intelligent distribution service.
[0033] S2. After receiving the inspection data, the intelligent distribution service places it in different task pools according to the report status. After receiving the inspection data, the intelligent distribution service will first parse the data to obtain the key information of the inspection data, such as: patient name, gender, age, medical history, etc., as well as inspection site, inspection type, inspection method, etc.
[0034] Optionally, in an implementation of an embodiment of the present invention, the task pool includes but is not limited to a task pool to be written and a task pool to be reviewed. In this way, if the inspection data has not yet generated a report, it will be placed in the task pool to be written, waiting for the doctor to write the report; if the inspection data has generated a report but has not yet been reviewed, it will be placed in the task pool to be reviewed, waiting for other doctors to review and prepare for subsequent operations.
[0035] S3. The background thread detects the task pool. If there is a distribution task, the distribution task thread is started. The distribution task thread includes the following steps:
[0036] S3.1. Check whether the data has been distributed. If it has been distributed, end the distribution task thread; otherwise, synchronize the distribution queue strategy of the cloud PACS system.
[0037] For example, patient Mr. Liu had a head CT scan in the hospital. The cloud PACS system has completed quality control and pushed it to the intelligent distribution service. The examination data is placed in the "task pool to be written". The background thread of the cloud PACS system detects that there is unprocessed examination data in the "task pool to be written" and starts the corresponding distribution task thread: the cloud PACS system will first determine whether Mr. Liu's head CT examination data has been assigned to the doctor for report writing. If the examination data has been assigned, it is considered that the data has been distributed, and the current distribution task thread will be terminated immediately to avoid duplicate allocation; if the examination data has not been assigned, it will continue to the next step to synchronize the latest distribution queue strategy of the cloud PACS system.
[0038] S3.2. Match the qualified distribution queue according to the queue strategy. If there are multiple qualified distribution queues, terminate the distribution task thread.
[0039] Specifically, the dispatch queue strategy includes but is not limited to queue name, department name, allocation rule and priority. In this way, each queue has its specific name, associated department, allocation rule and priority, for example:
[0040] Cohort names include: "Emergency CT Report Cohort", "Neurology CT Report Cohort", etc.
[0041] Department name: "Emergency Department", "Neurology Department", etc.
[0042] Allocation rules: For example, allocation is performed based on association, with priority given to corresponding queues.
[0043] Priority: For example, the priority of the emergency CT report queue is higher than the general CT report queue.
[0044] Therefore, assuming that the head CT scan of patient Mr. Liu is an emergency and related to neurological diseases, the data meets both the "Emergency CT Report Queue" and the "Neurology CT Report Queue". Since the test data meets multiple queues, the system will stop the current distribution task thread to avoid duplicate allocation.
[0045] Preferably, when there are multiple distribution queues that meet the conditions, the examination data is placed in a waiting queue, which is selected and allocated by manual intervention. In this way, through manual intervention, the administrator can select the most suitable queue based on patient information, examination type, examination time, etc., combined with the doctor's expertise, and allocate the examination data to the queue to ensure the accuracy of distribution.
[0046] S3.3.According to the queue strategy, the relevant positions are obtained, and the examination data content is judged whether it matches the position. If it does not match, the examination data is delayed until the position data that matches the conditions appears. In this way, when the conditions do not match, the examination data is delayed and the workload of the doctor in the matching position decreases before allocation, so as to avoid allocating the examination data to irrelevant doctors and avoid incorrect allocation.
[0047] S3.4. Determine the distribution position according to the queue strategy and obtain the position strategy; if the position strategy is not set, distribute it to the position task pool for the next step of distribution.
[0048] Specifically, the position strategy includes but is not limited to the doctor's name, the doctor's area of expertise, the doctor's workload, the doctor's current work status and scheduling information.
[0049] Preferably, the post task pool is allocated by manual intervention, or the post task pool allocates the examination data to the designated doctor in the post according to the preset default rules. The default rules can ensure that all examination data are allocated according to the same standards, such as being allocated to designated duty posts for processing, which improves the consistency of the allocation results; while manual intervention can select the most suitable doctor for allocation based on the specific situation, taking into account factors such as the doctor's workload, areas of expertise, and scheduling information. In particular, in the face of doctors taking leave and sudden increases in workload, manual intervention can be handled flexibly to avoid system rigidity and ensure smooth distribution.
[0050] S3.5. Assign tasks to doctors according to the job strategy.
[0051] In this way, the cloud PACS system will select the most suitable doctor for assignment according to the strategy of the position. For example, according to the strategy of "giving priority to doctors who are good at brain tumor diagnosis", the system will assign the examination data to Dr. Li who is good at brain tumor diagnosis; if no position strategy is set, the system will temporarily place the examination data in the task pool of the position and wait for the next operation.
[0052] S3.6. Obtain the assigned doctor and update the job workload.
[0053] The cloud PACS system records the doctor information to which the examination data is assigned, for example, the examination data is assigned to Dr. Li. At the same time, the cloud PACS system will update Dr. Li’s workload information, for example, how many CT reports Dr. Li has processed.
[0054] S4. Update the report distribution position, distribute doctor information, and end the distribution task thread.
[0055] By recording the distribution positions and distribution doctor information, we can clearly understand which position each examination data is assigned to and which doctor is responsible for processing it. This is conducive to improving the transparency of the system and facilitating subsequent traceability and inquiry. For example, doctors can view all reports they have processed for easy review and re-examination; managers can count the workload of each doctor and make reasonable allocations and performance evaluations.
[0056] The cloud PACS radiology report intelligent distribution method provided in this embodiment can significantly improve the distribution efficiency, shorten the doctor's diagnosis time, and improve medical efficiency; at the same time, by intelligently distributing reports based on factors such as the doctor's workload, areas of expertise, and scheduling information, it can avoid workload imbalance, improve the doctor's work efficiency, and improve the accuracy of diagnosis; in addition, it also reduces the difficulty of maintenance, reduces dependence on R&D personnel, saves labor costs, and improves user experience.
[0057] In the description of the present invention, it should be noted that the terms "vertical", "up", "down", "horizontal", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention.
[0058] In the description of the present invention, it is also necessary to explain that, unless otherwise clearly specified and limited, the terms "set", "install", "connect", and "connect" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.
[0059] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.
Claims
1. A cloud PACS radiology report intelligent distribution method, characterized in that: The following steps are involved: S1. After the cloud PACS system completes the inspection QA, push the inspection data to the intelligent distribution service; S2. After receiving the inspection data, the intelligent distribution service places it into different task pools according to the report status; S3. The background thread detects the task pool. If there is a distribution task, the distribution task thread is started. The distribution task thread includes the following steps: S3.
1. Check whether the data has been distributed. If it has been distributed, end the distribution task thread. Otherwise, synchronize the distribution queue strategy of the cloud PACS system. S3.
2. Match the qualified distribution queue according to the queue strategy. If there are multiple qualified distribution queues, terminate the distribution task thread; S3.
3. Obtain the associated positions according to the queue strategy, and determine whether the inspection data matches the position according to the content of the inspection data. If not, the inspection data is delayed until the position data that matches the conditions appears most recently before being assigned; S3.
4. Determine the distribution position according to the queue strategy and obtain the position strategy; if the position strategy is not set, distribute it to the position task pool for the next step of distribution; S3.
5. Assign tasks to doctors according to the job strategy; S3.
6. Obtain the assigned doctors and update the job workload; S4. Update the report distribution position, distribute doctor information, and end the distribution task thread.
2. The cloud PACS radiology report intelligent distribution method according to claim 1 is characterized in that: In step S2, the task pool includes but is not limited to a pool of tasks to be written and a pool of tasks to be reviewed.
3. The cloud PACS radiology report intelligent distribution method according to claim 1 is characterized in that: In step S3, the distribution queue strategy includes but is not limited to queue name, department name, allocation rule and priority.
4. The cloud PACS radiology report intelligent distribution method according to claim 3 is characterized in that: In step S3, the position strategy includes but is not limited to the doctor's name, the doctor's area of expertise, the doctor's workload, the doctor's current work status and scheduling information.
5. The cloud PACS radiology report intelligent distribution method according to claim 3 or 4, characterized in that: In step S3.4, the job task pool is allocated by manual intervention, or the job task pool allocates the examination data to a designated doctor in the job according to a preset default rule.
6. The cloud PACS radiology report intelligent distribution method according to claim 1 is characterized in that: In step S3.2, when there are multiple distribution queues that meet the conditions, the inspection data is put into a waiting queue, and the waiting queue is selected and allocated by manual intervention.