CN111028931A - Medical data processing method and device, electronic equipment and storage medium - Google Patents
Medical data processing method and device, electronic equipment and storage medium Download PDFInfo
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Abstract
The disclosure provides a medical data processing method, a medical data processing device, electronic equipment and a computer readable storage medium, and belongs to the technical field of computers. The method comprises the following steps: responding to the change of a medical data table in a medical item, and determining a changed field in the medical data table as a field to be counted; and updating the filling rate of the field to be counted according to the changed data in the field to be counted. The method and the device can effectively calculate the filling rate of the medical data, save the calculation resources of the system and further efficiently process the medical data.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to a medical data processing method, a medical data processing apparatus, an electronic device, and a computer-readable storage medium.
Background
With the rapid development of medical informatization, medical data is growing in large quantities. Many doctors or researchers often perform statistical analysis on medical data to make medical decisions. At this time, the quality of the medical data has a great influence on the statistical analysis, and if the content of the medical data is not perfect enough and more null values or wrong values appear, the statistical analysis consumes more resources and an effective analysis result cannot be obtained, so that the medical data needs to be reasonably processed.
In the medical data processing method, in order to effectively evaluate the quality of the medical data, the filling rate of the medical data is generally calculated, and particularly, when new medical data is added, a user accesses the medical data or modifies the medical data, and the like, the situation that the filling rate of all the medical data is recalculated is triggered. However, in practical applications, each time medical data is changed, the calculation of the total amount of data is triggered, and unnecessary medical data may be repeatedly calculated, which increases the workload of the system for calculating medical data, consumes more resources and time, and greatly affects the processing efficiency of medical data.
Therefore, how to efficiently and reasonably process the medical data to effectively calculate the filling rate of the medical data is an urgent problem to be solved in the prior art.
It is to be noted that the information disclosed in the above background section is only for enhancement of understanding of the background of the present disclosure, and thus may include information that does not constitute prior art known to those of ordinary skill in the art.
Disclosure of Invention
The present disclosure provides a medical data processing method, a medical data processing apparatus, an electronic device, and a computer-readable storage medium, thereby overcoming, at least to some extent, the problem of low processing efficiency of medical data in the prior art.
Additional features and advantages of the disclosure will be set forth in the detailed description which follows, or in part will be obvious from the description, or may be learned by practice of the disclosure.
According to an aspect of the present disclosure, there is provided a medical data processing method including: responding to the change of a medical data table in a medical item, and determining a changed field in the medical data table as a field to be counted; and updating the filling rate of the field to be counted according to the changed data in the field to be counted.
In an exemplary embodiment of the present disclosure, the updating the filling rate of the field to be counted according to the changed data in the field to be counted includes: acquiring the current effective data quantity of the field to be counted; determining effective data increment of the field to be counted according to the changed data in the field to be counted; and updating the filling rate of the field to be counted according to the current effective data quantity and the effective data increment of the field to be counted.
In an exemplary embodiment of the present disclosure, after determining the field to be counted, the method further includes: determining the current stage of the medical item according to the operation log of the medical data table; if the medical project is currently in a data entry stage, adding the field to be counted into a field cache pool; and when the accumulated number of the fields to be counted in the field cache pool reaches a first threshold value, updating the filling rate of the fields to be counted according to the changed data in the fields to be counted for the fields to be counted in the field cache pool.
In an exemplary embodiment of the present disclosure, the method further comprises: and if the medical project is in a data use stage at present, executing a step of updating the filling rate of the field to be counted according to the changed data in the field to be counted through an asynchronous queue.
In an exemplary embodiment of the present disclosure, the step of updating the filling rate of the field to be counted according to the changed data in the field to be counted through the asynchronous queue includes: if the weight of the field to be counted is larger than a second threshold value, executing a step of updating the filling rate of the field to be counted according to changed data in the field to be counted through a first asynchronous queue; if the weight of the field to be counted is smaller than the second threshold value, executing a step of updating the filling rate of the field to be counted according to changed data in the field to be counted through a second asynchronous queue; wherein the resource allocation ratio of the first asynchronous queue is higher than that of the second asynchronous queue.
In an exemplary embodiment of the present disclosure, the weight of the field to be counted is determined by: and determining the weight of the field to be counted through a pre-configured value network.
In an exemplary embodiment of the disclosure, the determining, from the oplog of the medical data table, the stage at which the medical item is currently located includes: counting the times of data change operation and the times of data use operation in the latest preset time in an operation log of the medical data table; determining that the medical item is currently in a data entry stage if a ratio of the number of data alteration operations to the number of data usage operations is greater than a third threshold; determining that the medical item is currently in a data use phase if a ratio of the number of data change operations to the number of data use operations is less than a fourth threshold.
According to an aspect of the present disclosure, there is provided a medical data processing apparatus including: the determining module is used for responding to the change of a medical data table in a medical item, and determining a field which is changed in the medical data table as a field to be counted; and the updating module is used for updating the filling rate of the field to be counted according to the changed data in the field to be counted.
In an exemplary embodiment of the present disclosure, the update module includes: the quantity obtaining unit is used for obtaining the current effective data quantity of the field to be counted; an increment determining unit, configured to determine, according to the changed data in the field to be counted, an effective data increment of the field to be counted; and the filling rate updating unit is used for updating the filling rate of the field to be counted according to the current effective data quantity and the effective data increment of the field to be counted.
In an exemplary embodiment of the present disclosure, the medical data processing apparatus further includes: the stage determining module is used for determining the stage of the medical item according to the operation log of the medical data table after the field to be counted is determined; the first judgment module is used for adding the field to be counted into a field cache pool if the medical item is currently in a data entry stage; and when the accumulated number of the fields to be counted in the field cache pool reaches a first threshold value, updating the filling rate of the fields to be counted according to the changed data in the fields to be counted for the fields to be counted in the field cache pool.
In an exemplary embodiment of the present disclosure, the medical data processing apparatus further includes: and the second judgment module is used for executing the step of updating the filling rate of the field to be counted according to the changed data in the field to be counted through the asynchronous queue if the medical item is currently in the data use stage.
In an exemplary embodiment of the present disclosure, the second determination module includes: a weight judging unit, configured to, if the weight of the field to be counted is greater than a second threshold, execute, by using a first asynchronous queue, a step of updating the filling rate of the field to be counted according to changed data in the field to be counted; if the weight of the field to be counted is smaller than the second threshold value, updating the filling rate of the field to be counted according to the changed data in the field to be counted through a second asynchronous queue; wherein the resource allocation ratio of the first asynchronous queue is higher than that of the second asynchronous queue.
In an exemplary embodiment of the present disclosure, the weight of the field to be counted is determined by: and determining the weight of the field to be counted through a pre-configured value network.
In an exemplary embodiment of the present disclosure, the phase determination module includes: the number counting unit is used for counting the number of data change operations and the number of data use operations in the latest preset time in the operation log of the medical data table; the number judgment unit is used for determining that the medical item is currently in a data entry stage if the ratio of the number of the data change operations to the number of the data use operations is larger than a third threshold; and determining that the medical item is currently in a data use phase if a ratio of the number of data change operations to the number of data use operations is less than a fourth threshold.
According to an aspect of the present disclosure, there is provided an electronic device including: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to perform the method of any one of the above via execution of the executable instructions.
According to an aspect of the present disclosure, there is provided a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the method of any one of the above.
Exemplary embodiments of the present disclosure have the following advantageous effects:
and responding to the change of the medical data table in the medical item, determining the changed field in the medical data table as the field to be counted, and updating the filling rate of the field to be counted according to the changed data in the field to be counted. On one hand, the exemplary embodiment provides a new medical data processing method, and compared with the prior art that the filling rate is recalculated when any change occurs in the medical data, the exemplary embodiment can provide a good strategy for calculating the filling rate of the medical data, and avoid the problem of wasting calculation resources caused by invalid data calculation; on the other hand, by determining the changed field in the medical data table and updating the filling rate of the field to be counted according to the changed data in the field, the instantaneity of filling rate calculation is improved, the calculation of meaningless fields is avoided, and the efficiency and effectiveness of the medical data filling rate calculation are improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure. It is to be understood that the drawings in the following description are merely exemplary of the disclosure, and that other drawings may be derived from those drawings by one of ordinary skill in the art without the exercise of inventive faculty.
Fig. 1 schematically shows a flow chart of a medical data processing method in the present exemplary embodiment;
fig. 2 schematically illustrates a sub-flowchart of a medical data processing method in the present exemplary embodiment;
fig. 3 schematically shows a sub-flowchart of another medical data processing method in the present exemplary embodiment;
fig. 4 schematically shows a sub-flowchart of yet another medical data processing method in the present exemplary embodiment;
fig. 5 schematically shows a flowchart of another medical data processing method in the present exemplary embodiment;
fig. 6 is a block diagram schematically showing the structure of a medical data processing apparatus in the present exemplary embodiment;
fig. 7 schematically illustrates an electronic device for implementing the above method in the present exemplary embodiment;
fig. 8 schematically illustrates a computer-readable storage medium for implementing the above-described method in the present exemplary embodiment.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
An exemplary embodiment of the present disclosure first provides a medical data processing method, and an application scenario of the method of the present embodiment may be: when a doctor carries out research on a certain subject medical project, calculating a data filling rate for medical data contained in the doctor and newly-entered medical data so as to make a good decision on the medical data; or when the medical data in the medical system is subjected to real-time statistical analysis, the quality of the medical data is judged by updating the filling rate of the data, and the like.
The exemplary embodiment is further described with reference to fig. 1, and as shown in fig. 1, the medical data processing method may include the following steps S110 to S120:
step S110, responding to the change of a medical data sheet in a medical project, and determining a field which is changed in the medical data sheet as a field to be counted;
and step S120, updating the filling rate of the field to be counted according to the changed data in the field to be counted.
In the medical field, the generated medical data can provide a certain basis for researchers to study specific diseases, besides helping doctors understand the conditions of patients and giving reasonable treatment schemes. When a researcher is conducting a study of a disease or a subject of a certain type, it is common to establish a corresponding medical item, such as a study item for a disease (e.g., a study item for lung disease, a study item for heart, etc.), a treatment item for a patient of a certain type (e.g., a treatment item for heart disease patients, etc.), or other medical-related items.
To determine whether the medical data in the medical project is complete, the present exemplary embodiment may calculate a fill rate of the medical data in the medical project. Specifically, when the medical data sheet in the medical item is changed, the field in the medical data sheet that is changed may be determined first, and the field is used as the field to be counted. Before the medical data table is changed, that is, when the initial medical data is batched into a group (added to the medical item), the calculation of the full filling rate may be triggered in advance for comparison and analysis with the calculation result of the filling rate.
The medical data refers to relevant data generated by a patient during diagnosis and treatment, and may include basic information of the patient and specific contents of the diagnosis and treatment, such as a patient name, a visit number, a contact number, an identification number, a disease name, medication data (e.g., data on what kind of medicine and dosage the patient has been prescribed), test data (e.g., blood routine data obtained by testing blood of the patient), or examination data (e.g., data on basic examination of the patient such as heart rate and blood pressure). Accordingly, the medical data table is a record table for storing medical data related to the medical project in the medical project, and may include a plurality of indexes of medical data of a plurality of patients and index values corresponding to the indexes.
In this exemplary embodiment, each medical project may include a corresponding medical data table, which includes medical data of a patient related to the project, and the medical data in the medical project is dynamically variable, that is, the medical data may be added to or deleted from the medical project, so that a researcher can obtain target medical data required by the medical project. The fields may refer to keywords in the medical data table that can reflect indicators or attributes of the medical data, such as name, number, identification number, blood pressure, heart rate, blood lipid, white blood cells, and so on.
Further, the change of the medical data table may include adding new medical data to the medical data table, deleting medical data from the medical data table, modifying data of the current medical data table, or replacing medical data in the current medical data table. When the medical data table is changed, the field to be counted of the changed related medical data is determined, and then the filling rate of the medical data in the medical project can be updated according to the changed data in the field to be counted.
Specifically, in an exemplary embodiment, the step S120 may include the following steps:
step S210, acquiring the current effective data quantity of the field to be counted;
step S220, determining effective data increment of the field to be counted according to the changed data in the field to be counted;
and step S230, updating the filling rate of the field to be counted according to the current effective data quantity and the effective data increment of the field to be counted.
In practical application, the medical data in each index in the medical data table may have a situation of missing, error or incomplete data, that is, invalid medical data, and the current valid data quantity is data in the index which can be used for data analysis normally and has no situation of missing, error or incomplete data. For example, 100 pieces of data are in the medical data table, the field to be counted is a leukocyte, wherein, if there are 80 data values of the leukocyte as valid data, the current valid data amount is recorded as 80, if there are 20 new pieces of data added to the medical data table, there are 15 data values of the leukocyte as valid data, the valid data increment is 15, the updated valid data amount is 95, and the filling rate of the field related to the leukocyte is updated based on the updated valid data amount and the valid data increment.
The exemplary embodiment can instantly calculate the filling rate of the medical data by only persisting the number of the medical valid data values without recording the total number of the medical data (such as the total number of patients), so that when the medical data is changed, only the existing medical data in the medical data table needs to be calculated, the rest invalid data does not need to be triggered again, the calculation range of the medical data is reduced, and the calculation efficiency of the filling rate is improved.
Based on the above description, in the present exemplary embodiment, in response to a change in the medical data table in the medical item, a field in the medical data table that has been changed is determined as a field to be counted, and the fill rate of the field to be counted is updated according to the data in the field to be counted that has been changed. On one hand, the exemplary embodiment provides a new medical data processing method, and compared with the prior art that the filling rate is recalculated when any change occurs in the medical data, the exemplary embodiment can provide a good strategy for calculating the filling rate of the medical data, and avoid the problem of wasting calculation resources caused by invalid data calculation; on the other hand, by determining the changed field in the medical data table and updating the filling rate of the field to be counted according to the changed data in the field, the instantaneity of filling rate calculation is improved, the calculation of meaningless fields is avoided, and the efficiency and effectiveness of the medical data filling rate calculation are improved.
In an exemplary embodiment, after determining the field to be counted, the medical data processing method may further include the steps of:
step S310, determining the current stage of the medical item according to the operation log of the medical data table;
step S320, if the medical project is currently in a data entry stage, adding the field to be counted into a field cache pool;
step S330, when the accumulated number of the fields to be counted in the field cache pool reaches a first threshold value, executing step S120 on the fields to be counted in the field cache pool.
The operation log of the medical data table may include various operation behaviors on the medical data table, such as data writing operation, data query operation, data browsing operation, data modification operation or data use operation. Generally, a medical project can be divided into three phases, namely a data entry phase, an intermediate phase and a data use phase, wherein the data entry phase is a data acquisition or data collection process in the medical project, and in the process, medical data related to the medical project is obtained; the intermediate stage is a short data conversion stage from the end of the data entry stage to the front of the data use stage; the data using stage is a stage in which the researcher performs data analysis according to the collected data, and in the data using stage, the researcher can determine whether the medical item meets the expected standard or meets a certain requirement according to the acquired medical data.
In an exemplary embodiment, the current stage of the medical item may be determined according to the operation log, and specifically, the step S310 may include the following steps:
step S410, counting the times of data change operation and the times of data use operation in the latest preset time in an operation log of the medical data table;
step S420, if the ratio of the number of data changing operations to the number of data using operations is greater than a third threshold value, determining that the medical project is currently in a data entry stage;
in step S430, if the ratio of the number of data change operations to the number of data use operations is less than the fourth threshold, it is determined that the medical item is currently in the data use stage.
The data change operation may be any operation that changes data in the medical data table, such as a data write operation, a data modification operation, a data delete operation, and the like, and the data use operation is an operation that analyzes data in the medical data table, such as data calculation, data lookup, data comparison, and the like. It is considered that the number of operations of the data change operation will be significantly higher than that of the data use operation in the data entry phase, and the number of operations of the data change operation will be significantly lower than that of the data use operation in the data use phase. Therefore, the stage where the medical item is currently located can be determined by determining the ratio of the number of data change operations to the number of data use operations, the third threshold is a determination condition for determining whether the medical item is in the data entry stage, and the fourth threshold is a determination condition for determining whether the medical item is in the data use stage. The setting of the fourth threshold is similar to the third threshold, and the lower the setting of the fourth threshold, the more obvious the degree that the number of data change operations is lower than the number of data use operations, and the specific numerical value settings of the third threshold and the fourth threshold are not specifically limited herein in this disclosure.
In this exemplary embodiment, if the medical item is in the data entry stage, it indicates that the data in the current medical data table is still unstable, and in order to avoid frequent filling rate calculation by the system, the field to be counted may be added to the field cache pool, and when the accumulated number of the field to be counted in the field cache pool reaches the first threshold, the field to be counted performs the step of updating the filling rate of the field to be counted according to the changed data in the field to be counted.
In addition, other conditions for triggering execution of filling rate calculation can be set in the field cache pool, for example, a time condition, and when the time for the field cache pool to cache the field exceeds a specific time, the filling rate of the field contained in the field cache pool can be uniformly calculated; or the field weight is cached, and when the weight of a certain field cached in the cache pool is higher than a certain degree, the filling rate calculation and the like can be triggered, which is not specifically limited in the present disclosure.
In an exemplary embodiment, the medical data processing method may further include:
if the medical item is currently in the data use phase, step S120 is performed through the asynchronous queue.
When the medical project is currently in a data use stage, the medical data in the current medical data table can be considered to be kept in a relatively stable state, and the filling rate of each field to be counted can be calculated through an asynchronous queue, that is, the filling rates of a plurality of fields to be counted can be calculated at the same time. Particularly, in order to ensure the efficiency of calculation during calculation, different shares of resources can be allocated to different fields to be counted, so that the important fields to be counted can be calculated preferentially, and the analysis process of the medical project is improved.
In an exemplary embodiment, the step of updating the filling rate of the field to be counted according to the changed data in the field to be counted performed through the asynchronous queue may include:
if the weight of the field to be counted is larger than a second threshold value, executing a step of updating the filling rate of the field to be counted according to the changed data in the field to be counted through the first asynchronous queue;
if the weight of the field to be counted is smaller than a second threshold value, a step of updating the filling rate of the field to be counted according to the changed data in the field to be counted is executed through a second asynchronous queue;
and the resource allocation ratio of the first asynchronous queue is higher than that of the second asynchronous queue.
In order to effectively calculate the filling rate of each field to be counted, the field to be counted may be divided into high-weight counting fields, that is, more important fields, and specifically, the field to be counted may relate to indexes of medical data related to a medical item, such as blood pressure, blood fat, and white blood cells, while indexes of medical data related to a medical item with a lower degree, such as a patient name, an identification number, a mobile phone number, and the like, may be regarded as low-weight fields. The high-weight field and the low-weight field may be determined by a second threshold, which may be customized according to actual needs in this exemplary embodiment, and the weight of the field may be different for each medical item, for example, in a medical item for studying diabetes, the relevant field of a digestive system ultrasound examination may be considered as a low-weight field, and so on.
In this exemplary embodiment, after different weight categories of the fields to be counted are determined, the calculation of the filling rate may be performed through the corresponding asynchronous queues, the first asynchronous queue may be used to update the filling rate of the fields to be counted with a higher weight, that is, the queue may be allocated with a higher resource quota, and the second asynchronous queue may be used to update the filling rate of the fields to be counted with a lower weight, that is, the queue may be allocated with a lower resource quota. By reasonably dividing asynchronous queues of different types of fields to be counted, the calculation efficiency of the filling rate of each field in the medical data table can be improved.
In an exemplary embodiment, the weight of the field to be counted is determined by:
and determining the weight of the field to be counted through a pre-configured value network.
In the context of medical research, medical data included in a medical project is generally data under standard indexes or attributes, for example, data related to blood tests or blood pressure tests of patients in most medical projects, and the white blood cell value and the blood pressure value are common standard fields in medical projects. The exemplary embodiment can establish a value network according to the standard fields, wherein the value network can include the frequency of the plurality of standard fields in the historical medical data, the relevance to various diseases, the importance degree in the disease treatment period, and the like. Based on this, after the field to be counted is determined, the information of the frequency of occurrence of the field to be counted, the correlation with the current medical project and the like can be obtained from the value network to determine whether the field to be counted has higher value, and higher weight is given to the field to be counted which is highly related with high frequency, for example, in a certain medical project, the statistical fields such as the doctor number, the identity card number and the mobile phone number have lower analysis significance and can be considered as lower value and given lower weight, while the statistical fields such as the heart rate, the blood pressure and the bone density have higher analysis significance and can be considered as higher value and given higher weight and the like. In the exemplary embodiment, the establishment of the value network may be based on medical data in a medical journal, a medical system, or other specific medical database, etc., in addition to historical medical data, which is not specifically limited by the present disclosure.
Fig. 5 shows a flowchart of another medical data processing method in the present exemplary embodiment, which may specifically include the following steps:
step S510, detecting whether a medical data sheet in a medical item is changed; if the medical data sheet is not changed then step S510 continues to be periodically executed,
step S520, if the medical data sheet is changed, determining the changed field in the medical data sheet as the field to be counted;
step S530, acquiring an operation log of the medical data sheet, and determining the current stage of the medical project according to the operation log; if the medical item is currently in a data use phase, then execution is performed
Step S540, determining the weight of the field to be counted according to a pre-configured value network;
step S550, if the weight of the field to be counted is greater than a second threshold value, calculating the filling rate of the field to be counted through the first asynchronous queue;
step S560, if the weight of the field to be counted is less than the second threshold, the calculation of the filling rate of the field to be counted is executed through the second asynchronous queue;
in addition, after step S530, if the medical item is currently in the data entry stage, step S570 is executed to add the field to be counted into the field cache pool;
step S580, detecting whether the accumulated number of the fields to be counted in the field cache pool reaches a first threshold value;
step S590, if the accumulated quantity reaches a first threshold value, extracting the field to be counted in the field cache pool, and executing step S540 on the field to be counted; and if the accumulated number does not reach the first threshold value, continuously and periodically detecting the accumulated number of the fields to be counted in the field cache pool.
The embodiment of the invention provides an effective strategy for calculating the filling rate of medical data in the field by judging the current stage of the medical project and allocating different weights to different fields according to the value network so as to calculate the filling rate of the field to be counted, thereby avoiding the problem that the system wastes calculation resources due to the calculation of invalid data, improving the calculation efficiency and saving a large amount of time.
It should be noted that, after the field to be counted is added to the field cache pool in step S570, in addition to step S580, when the field to be counted is accumulated to a certain number, the calculation of the filling rate of the field to be counted may be triggered, and in addition, other calculation conditions for triggering the calculation of the filling rate of the field to be counted in the cache pool may also exist, for example, through user behavior analysis, medical data in the cache pool enters the function module and is used by the user in advance, the calculation of the filling rate of the trigger may also be triggered.
Exemplary embodiments of the present disclosure also provide a medical data processing apparatus. Referring to fig. 6, the apparatus 600 may include a determining module 610, configured to determine, in response to a medical data table in a medical item being changed, a field in the medical data table that is changed as a field to be counted; and the updating module 620 is configured to update the filling rate of the field to be counted according to the changed data in the field to be counted.
In an exemplary embodiment of the present disclosure, the update module includes: the quantity obtaining unit is used for obtaining the current effective data quantity of the field to be counted; the increment determining unit is used for determining the effective data increment of the field to be counted according to the changed data in the field to be counted; and the filling rate updating unit is used for updating the filling rate of the field to be counted according to the current effective data quantity and the effective data increment of the field to be counted.
In an exemplary embodiment of the present disclosure, the medical data processing apparatus may further include: the stage determining module is used for determining the stage of the medical item according to the operation log of the medical data table after the field to be counted is determined; the first judgment module is used for adding the field to be counted into a field cache pool if the medical item is currently in a data entry stage; and when the accumulated number of the fields to be counted in the field cache pool reaches a first threshold value, updating the filling rate of the fields to be counted according to the changed data in the fields to be counted for the fields to be counted in the field cache pool.
In an exemplary embodiment of the present disclosure, the medical data processing apparatus may further include: and the second judgment module is used for executing the step of updating the filling rate of the field to be counted according to the changed data in the field to be counted through the asynchronous queue if the medical item is currently in the data use stage.
In an exemplary embodiment of the present disclosure, the second determination module may include: the weight judgment unit is used for executing the step of updating the filling rate of the field to be counted according to the changed data in the field to be counted through the first asynchronous queue if the weight of the field to be counted is greater than a second threshold; if the weight of the field to be counted is smaller than a second threshold value, executing a step of updating the filling rate of the field to be counted according to the changed data in the field to be counted through a second asynchronous queue; and the resource allocation ratio of the first asynchronous queue is higher than that of the second asynchronous queue.
In an exemplary embodiment of the present disclosure, the weight of the field to be counted may be determined by: and determining the weight of the field to be counted through a pre-configured value network.
In an exemplary embodiment of the present disclosure, the phase determination module may include: the number counting unit is used for counting the number of data change operations and the number of data use operations in the latest preset time in an operation log of the medical data table; the number judgment unit is used for determining that the medical item is currently in a data entry stage if the ratio of the number of data change operations to the number of data use operations is greater than a third threshold; and determining that the medical item is currently in the data use phase if the ratio of the number of data change operations to the number of data use operations is less than a fourth threshold.
The specific details of each module/unit in the above-mentioned apparatus have been described in detail in the embodiment of the method section, and the details that are not disclosed may refer to the contents of the embodiment of the method section, and therefore are not described herein again.
Exemplary embodiments of the present disclosure also provide an electronic device capable of implementing the above method.
As will be appreciated by one skilled in the art, aspects of the present disclosure may be embodied as a system, method or program product. Accordingly, various aspects of the present disclosure may be embodied in the form of: an entirely hardware embodiment, an entirely software embodiment (including firmware, microcode, etc.) or an embodiment combining hardware and software aspects that may all generally be referred to herein as a "circuit," module "or" system.
An electronic device 700 according to such an exemplary embodiment of the present disclosure is described below with reference to fig. 7. The electronic device 700 shown in fig. 7 is only an example and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.
As shown in fig. 7, electronic device 700 is embodied in the form of a general purpose computing device. The components of the electronic device 700 may include, but are not limited to: the at least one processing unit 710, the at least one memory unit 720, a bus 730 connecting different system components (including the memory unit 720 and the processing unit 710), and a display unit 740.
Where the memory unit stores program code, the program code may be executed by the processing unit 710 such that the processing unit 710 performs the steps according to various exemplary embodiments of the present disclosure as described in the above-mentioned "exemplary methods" section of this specification. For example, the processing unit 710 may execute steps S110 to S120 shown in fig. 1, or may execute steps S210 to S230 shown in fig. 2, or the like.
The storage unit 720 may include readable media in the form of volatile memory units, such as a random access memory unit (RAM)721 and/or a cache memory unit 722, and may further include a read only memory unit (ROM) 723.
The memory unit 720 may also include programs/utilities 724 having a set (at least one) of program modules 725, such program modules 725 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may comprise an implementation of a network environment.
The electronic device 700 may also communicate with one or more external devices 900 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device 700, and/or with any devices (e.g., router, modem, etc.) that enable the electronic device 700 to communicate with one or more other computing devices. Such communication may occur via an input/output (I/O) interface 750. Also, the electronic device 700 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network such as the internet) via the network adapter 760. As shown, the network adapter 760 communicates with the other modules of the electronic device 700 via the bus 730. It should be appreciated that although not shown in the figures, other hardware and/or software modules may be used in conjunction with the electronic device 700, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the exemplary embodiments of the present disclosure.
Exemplary embodiments of the present disclosure also provide a computer-readable storage medium having stored thereon a program product capable of implementing the above-described method of the present specification. In some possible embodiments, various aspects of the disclosure may also be implemented in the form of a program product comprising program code for causing a terminal device to perform the steps according to various exemplary embodiments of the disclosure described in the above-mentioned "exemplary methods" section of this specification, when the program product is run on the terminal device.
Referring to fig. 8, a program product 800 for implementing the above method according to an exemplary embodiment of the present disclosure is described, which may employ a portable compact disc read only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present disclosure is not limited thereto, and in this document, a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
A computer readable signal medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable signal medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations for the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
Furthermore, the above-described figures are merely schematic illustrations of processes included in methods according to exemplary embodiments of the present disclosure, and are not intended to be limiting. It will be readily understood that the processes shown in the above figures are not intended to indicate or limit the chronological order of the processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, e.g., in multiple modules.
It should be noted that although in the above detailed description several modules or units of the device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functions of two or more modules or units described above may be embodied in one module or unit according to an exemplary embodiment of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is to be limited only by the terms of the appended claims.
Claims (10)
1. A medical data processing method, comprising:
responding to the change of a medical data table in a medical item, and determining a changed field in the medical data table as a field to be counted;
and updating the filling rate of the field to be counted according to the changed data in the field to be counted.
2. The method according to claim 1, wherein the updating the filling rate of the field to be counted according to the changed data in the field to be counted comprises:
acquiring the current effective data quantity of the field to be counted;
determining effective data increment of the field to be counted according to the changed data in the field to be counted;
and updating the filling rate of the field to be counted according to the current effective data quantity and the effective data increment of the field to be counted.
3. The method of claim 1, wherein after determining the field to be counted, the method further comprises:
determining the current stage of the medical item according to the operation log of the medical data table;
if the medical project is currently in a data entry stage, adding the field to be counted into a field cache pool;
and when the accumulated number of the fields to be counted in the field cache pool reaches a first threshold value, updating the filling rate of the fields to be counted according to the changed data in the fields to be counted for the fields to be counted in the field cache pool.
4. The method of claim 3, further comprising:
and if the medical project is in a data use stage at present, executing a step of updating the filling rate of the field to be counted according to the changed data in the field to be counted through an asynchronous queue.
5. The method according to claim 4, wherein the step of updating the filling rate of the field to be counted according to the changed data in the field to be counted through the asynchronous queue comprises:
if the weight of the field to be counted is larger than a second threshold value, executing a step of updating the filling rate of the field to be counted according to changed data in the field to be counted through a first asynchronous queue;
if the weight of the field to be counted is smaller than the second threshold value, executing a step of updating the filling rate of the field to be counted according to changed data in the field to be counted through a second asynchronous queue;
wherein the resource allocation ratio of the first asynchronous queue is higher than that of the second asynchronous queue.
6. The method according to claim 5, wherein the weight of the field to be counted is determined by:
and determining the weight of the field to be counted through a pre-configured value network.
7. The method of claim 3, wherein determining the current stage of the medical item from the oplog of the medical data sheet comprises:
counting the times of data change operation and the times of data use operation in the latest preset time in an operation log of the medical data table;
determining that the medical item is currently in a data entry stage if a ratio of the number of data alteration operations to the number of data usage operations is greater than a third threshold;
determining that the medical item is currently in a data use phase if a ratio of the number of data change operations to the number of data use operations is less than a fourth threshold.
8. A medical data processing apparatus, characterized by comprising:
the determining module is used for responding to the change of a medical data table in a medical item, and determining a field which is changed in the medical data table as a field to be counted;
and the updating module is used for updating the filling rate of the field to be counted according to the changed data in the field to be counted.
9. An electronic device, comprising:
a processor; and
a memory for storing executable instructions of the processor;
wherein the processor is configured to perform the method of any of claims 1-7 via execution of the executable instructions.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the method of any one of claims 1 to 7.
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