CN113160976A - Medical data processing method and device based on SaaS service and electronic equipment - Google Patents
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Abstract
The disclosure relates to a method and a device for processing medical data of SaaS (software as a service) service and electronic equipment, wherein the method comprises the following steps: receiving medical data processing information reported by each medical data processing module, wherein the medical data processing information comprises data information reported when the medical data processing module processes medical data to be processed; and performing statistical analysis on the medical data processing information reported by each medical data processing module to obtain a statistical analysis result. The embodiment of the disclosure can realize optimization and improvement aiming at medical services and/or medical data processing modules, thereby improving user experience.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to a medical data processing method and apparatus based on SaaS service, and an electronic device.
Background
With the development of science and technology, Software services can be provided for users through a network by a Service which is deployed in a cloud or an Internet Data Center (IDC) and has a product form of SaaS (Software-as-a-Service).
For example: the medical service cluster is deployed at the cloud or the IDC, and multiple hospitals can be accessed in the medical service cluster, that is, the medical service cluster can provide related medical services for the accessed multiple hospitals.
Disclosure of Invention
The present disclosure presents a technical solution for performing statistical analysis processing of medical data.
According to one aspect of the disclosure, a medical data processing method based on SaaS service is provided, which is applied to a data statistics module and includes:
receiving medical data processing information reported by each medical data processing module, wherein the medical data processing information comprises data information reported when the medical data processing module processes medical data to be processed;
and performing statistical analysis on the medical data processing information reported by each medical data processing module to obtain a statistical analysis result.
According to the medical data processing method based on the SaaS service provided by the embodiment of the disclosure, the medical data processing information related to each link in the medical service scene based on the SaaS service can be subjected to statistical analysis to obtain the corresponding statistical analysis result, and then the data support can be provided for the medical service and/or the medical data processing module through the obtained statistical analysis result, so that the optimization and improvement of the medical service and/or the medical data processing module are realized, and the user experience is improved.
In one possible implementation, the statistical analysis result includes at least one of a performance evaluation result for the medical data processing module, a service usage rate of the medical data processing module, and a proportion of disease types.
In a possible implementation manner, the medical data processing information includes first data information and/or second data information, where the first data information includes information reported when the medical data processing module starts to process the medical data to be processed, and the second data information includes information reported when the medical data processing module obtains a processing result corresponding to the medical data to be processed.
According to the medical data processing method based on the SaaS service provided by the embodiment of the disclosure, the data statistics module can obtain the state information when the medical data processing module starts to execute the medical data to be processed and/or the state information when the medical data processing module completes processing of the medical data to be processed according to the first data information and/or the second data information, and further can obtain a more detailed and higher-dimensional statistical analysis result through the first data information and/or the second data information, so that the medical data processing module can be optimized and improved more accurately and in a targeted manner.
In a possible implementation manner, the first data information includes first time information when the medical data processing module starts to process the medical data to be processed, and the second data information includes second time information when the medical data processing module obtains a processing result corresponding to the medical data to be processed, and the processing result.
In a possible implementation manner, the performing statistical analysis on the medical data processing information reported by each medical data processing module to obtain a statistical analysis result includes:
acquiring first data information and second data information reported by a medical data processing module to be evaluated aiming at any medical data to be processed; determining the processing duration of the medical data processing module to be evaluated aiming at the medical data to be processed according to first time information in the first data information and second time information in the second data information; and determining the performance evaluation result of the medical data processing module to be evaluated according to the processing duration.
According to the medical data processing method based on the SaaS service, provided by the embodiment of the disclosure, the performance evaluation result of the medical data processing module to be evaluated can be determined according to the first time information and the second time information, so that the medical data processing module can be optimized and improved according to the performance evaluation result of the medical data processing module, and further, the user experience can be improved.
In a possible implementation manner, the medical data processing information includes third data information, and the third data information includes information reported when the medical data processing module deletes or modifies the processing result corresponding to the medical data to be processed.
According to the medical data processing method based on the SaaS service provided by the embodiment of the disclosure, the third data information can be reported and used as a data basis for optimizing and improving the medical data processing module, so that the performance of the medical data processing module can be improved in a targeted manner, and the user experience can be improved.
In a possible implementation manner, the performing statistical analysis on the medical data processing information reported by each medical data processing module to obtain a statistical analysis result includes:
determining a first number of processing results deleted or modified by the medical data processing module to be evaluated according to the third data information; and determining the performance evaluation result of the medical data processing module to be evaluated according to the first quantity and the total number of the medical data to be processed by the medical data processing module to be evaluated.
According to the medical data processing method based on the SaaS service, provided by the embodiment of the disclosure, the performance evaluation result of the medical data processing module to be evaluated can be determined according to the third data information, so that the medical data processing module can be optimized and improved in a targeted manner according to the performance evaluation result of the medical data processing module, and further user experience can be improved.
In a possible implementation manner, the processing result in the second data information includes a disease type of the medical data to be processed, and performing statistical analysis on the medical data processing information reported by each medical data processing module to obtain a statistical analysis result may include:
determining a second quantity of second data information corresponding to the target disease category; and determining the proportion of the target disease type according to the second quantity and the total number of the second data information.
According to the medical data processing method based on the SaaS service provided by the embodiment of the disclosure, the ratio of the target disease type can be determined, and then the business state of the hospital can be analyzed through the ratio of the target disease type, so that the business resources can be reasonably distributed according to the business state of the hospital
In a possible implementation manner, the medical data processing information further includes fourth data information, where the fourth data information includes information reported when the medical data processing module is accessed, and the statistical analysis of the medical data processing information reported by each medical data processing module to obtain a statistical analysis result includes:
determining a third number of accessed medical data processing modules to be evaluated according to the fourth data information;
and determining the service utilization rate of the medical data processing module to be evaluated according to the third quantity and the total number of the fourth data information.
According to the medical data processing method based on the SaaS service, the medical data processing module needing key optimization can be determined according to the service utilization rate of the medical data processing module, so that the performance of the medical data processing module is further improved, and further the user experience is improved.
In one possible implementation manner, the medical data processing information includes a processing status of the medical data processing module for the medical data to be processed, and the method further includes:
generating an alarm instruction according to the medical data processing information under the condition that the medical data processing information comprises an abnormal processing state; sending the alarm indication to a specified device, wherein the abnormal processing state is a processing state used for indicating that the medical data processing module has an abnormality in the processing process of the medical data to be processed.
According to the medical data processing method based on the SaaS service, a user can determine the information such as the abnormal medical data processing module and the abnormal time according to the alarm indication, so that the abnormality can be checked in time and rapidly, and the response speed for the abnormality processing can be improved.
In a possible implementation manner, the medical data processing module includes at least one sub-processing module, and the second data information includes processing time information of each sub-processing module for the medical data to be processed and a processing result for the medical data to be processed.
According to the medical data processing method based on the SaaS service provided by the embodiment of the disclosure, when the medical data processing module is subjected to processing such as optimization upgrading, the sub-processing modules of the medical data processing module can be upgraded according to the processing time information of the sub-processing modules to the medical data to be processed and the processing result of the medical data to be processed in the second data information, so that the performance and the optimization speed of the medical data processing module can be effectively improved.
In one possible implementation, the method further includes:
responding to the display operation aiming at the target medical data to be processed, and acquiring medical data processing information corresponding to the target medical data to be processed; and sending medical data processing information corresponding to the target medical data to be processed to a display module so that the display module displays the medical data processing information corresponding to the target medical data to be processed.
According to the medical data processing method based on the SaaS service, provided by the embodiment of the disclosure, the medical data processing information of the medical data to be processed can be displayed, so that the processing process aiming at the medical data to be processed is transparent.
In one possible implementation, the medical data processing module includes at least one of a medical data collection module, a medical data transmission module, a medical data archiving module, and a medical data diagnostic module.
According to an aspect of the present disclosure, a medical data processing method based on SaaS service is provided, which is applied to a medical data processing module, and the method includes:
monitoring the processing state of the medical data processing module aiming at the medical data to be processed;
acquiring medical data processing information corresponding to the processing state of the medical data to be processed;
and sending the medical data processing information to a data statistics module.
According to the medical data processing method based on the SaaS service provided by the embodiment of the disclosure, medical data processing information related to each link in a medical service scene based on the SaaS service can be reported, so that the medical data processing information can be subjected to statistical analysis to obtain a corresponding statistical analysis result, and then data support can be provided for the medical service and/or the medical system through the obtained statistical analysis result, so that optimization and improvement aiming at the medical service and/or the medical system are realized, and further, user experience is improved.
In one possible implementation manner, the obtaining of the medical data processing information corresponding to the processing state of the medical data to be processed includes:
under the condition that the medical data processing module starts to process the medical data to be processed, determining that the medical data to be processed is in an initial processing state; obtaining the first data information according to the initial processing state;
or, under the condition that the medical data processing module obtains the processing result of the medical data to be processed, determining that the medical data to be processed is in a processing ending state; and obtaining the second data information according to the processing ending state.
According to the medical data processing method based on the SaaS service provided by the embodiment of the present disclosure, the performance of the medical data processing module can be evaluated according to the first data information and the second data information reported for the medical data to be processed (the evaluation process may refer to the foregoing embodiment, which is not described herein again), and the medical data processing module can be optimized and improved timely and effectively according to the performance evaluation result of the medical data processing module, so as to improve the user experience.
In a possible implementation manner, the obtaining medical data processing information corresponding to a processing state of the medical data to be processed includes:
determining that the medical data to be processed is in an abnormal processing state under the condition that the medical data processing module does not successfully process the medical data to be processed; and obtaining medical data processing information according to the abnormal processing state, wherein the abnormal processing state is a processing state used for indicating that the medical data processing module has abnormality in the processing process of the medical data to be processed.
According to the medical data processing method based on the SaaS service, provided by the embodiment of the disclosure, the reported medical data processing information including the abnormal processing state can be used for timely and quickly carrying out targeted troubleshooting processing on the abnormality, and the response speed for the abnormal processing can be improved.
In a possible implementation manner, the obtaining medical data processing information corresponding to a processing state of the medical data to be processed includes:
in response to an update instruction for a processing result of the medical data to be processed, determining that the medical data to be processed is in an update state if the processing result of the medical data to be processed is updated; and obtaining medical data processing information according to the updating state, wherein the updating instruction comprises a deleting instruction or a modifying instruction.
According to the medical data processing method based on the SaaS service provided by the embodiment of the disclosure, when the processing result of the medical data processing module aiming at the medical data to be processed is updated, the corresponding third data information can be reported, so that the performance of the medical data processing module can be evaluated according to the third data information, and then the medical data processing module can be optimized and improved according to the performance evaluation result of the medical data processing module, so as to improve the user experience.
According to an aspect of the present disclosure, a medical data processing apparatus based on SaaS service is provided, which is applied to a data statistics module, and includes:
the receiving module is used for receiving medical data processing information reported by each medical data processing module, and the medical data processing information comprises data information reported when the medical data processing module processes medical data to be processed;
and the statistical analysis module is used for performing statistical analysis on the medical data processing information reported by the medical data processing modules to obtain a statistical analysis result.
According to an aspect of the present disclosure, there is provided a medical data processing apparatus based on SaaS service, applied to a medical data processing module, including:
the monitoring module is used for monitoring the processing state of the medical data processing module aiming at the medical data to be processed;
the processing module is used for obtaining medical data processing information corresponding to the processing state of the medical data to be processed;
and the sending module is used for sending the medical data processing information to the data statistics module.
According to an aspect of the present disclosure, there is provided an electronic device including: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to invoke the memory-stored instructions to perform the above-described method.
According to an aspect of the present disclosure, there is provided a computer readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement the above-described method.
In the embodiment of the present disclosure, the data statistics module may receive medical data processing information reported by each medical data processing module, where the medical data processing information includes data information reported when the medical data processing module processes medical data to be processed, and may perform statistical analysis according to the medical data processing information reported by each medical data processing module, so as to obtain a statistical analysis result. The medical data processing method, the medical data processing device and the electronic equipment based on the SaaS service provided by the embodiment of the disclosure can perform statistical analysis on medical data processing information related to each link in a medical service scene based on the SaaS service to obtain a corresponding statistical analysis result, and further can provide data support for a medical service and/or a medical data processing module through the obtained statistical analysis result, so that optimization and improvement for the medical service and/or the medical data processing module are realized, and further user experience is 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. Other features and aspects of the present disclosure will become apparent from the following detailed description of exemplary embodiments, which proceeds with reference to the accompanying drawings.
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.
Fig. 1 shows a schematic diagram of a SaaS service-based medical data processing method according to an embodiment of the present disclosure;
fig. 2 shows a flowchart of a SaaS service-based medical data processing method according to an embodiment of the present disclosure;
fig. 3 shows a schematic diagram of a SaaS service-based medical data processing method according to an embodiment of the present disclosure;
fig. 4 shows a schematic diagram of a SaaS service-based medical data processing method according to an embodiment of the present disclosure;
fig. 5 shows a schematic diagram of a SaaS service-based medical data processing method according to an embodiment of the present disclosure;
fig. 6 shows a flowchart of a SaaS service-based medical data processing method according to an embodiment of the present disclosure;
fig. 7 shows a block diagram of a SaaS service based medical data processing apparatus according to an embodiment of the present disclosure;
fig. 8 shows a block diagram of a SaaS service based medical data processing apparatus according to an embodiment of the present disclosure;
FIG. 9 shows a block diagram of an electronic device 900 in accordance with an embodiment of the disclosure;
fig. 10 shows a block diagram of an electronic device 1900 according to an embodiment of the disclosure.
Detailed Description
Various exemplary embodiments, features and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. In the drawings, like reference numbers can indicate functionally identical or similar elements. While the various aspects of the embodiments are presented in drawings, the drawings are not necessarily drawn to scale unless specifically indicated.
The word "exemplary" is used exclusively herein to mean "serving as an example, embodiment, or illustration. Any embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.
The term "and/or" herein is merely an association describing an associated object, meaning that three relationships may exist, e.g., a and/or B, may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the term "at least one" herein means any one of a plurality or any combination of at least two of a plurality, for example, including at least one of A, B, C, and may mean including any one or more elements selected from the group consisting of A, B and C.
Furthermore, in the following detailed description, numerous specific details are set forth in order to provide a better understanding of the present disclosure. It will be understood by those skilled in the art that the present disclosure may be practiced without some of these specific details. In some instances, methods, means, elements and circuits that are well known to those skilled in the art have not been described in detail so as not to obscure the present disclosure.
For medical services based on SaaS services deployed in a medical service cluster of a service end (cloud or IDC), it is necessary to interface imaging equipment of a hospital or an image informatization system of the hospital to acquire medical data, and in an actual service scene, the medical data needs to go through a plurality of links from acquisition to filing to data processing, and after data processing on the medical data in the last link is successful, a service party for the medical data can be developed, for example: and performing diagnosis, operation planning and other services.
The embodiment of the disclosure provides a medical data processing method based on SaaS service, which can be used for a data statistics module. Referring to the schematic diagram shown in fig. 1, each medical data processing module for performing data processing on medical data to be processed may report corresponding medical data processing information when the medical data to be processed is processed, and the data statistics module may receive the medical data processing information reported by each medical data processing module, and may perform statistical analysis according to the medical data processing information reported by each medical data processing module, so as to obtain a statistical analysis result.
The medical data processing method based on the SaaS service provided by the embodiment of the disclosure can perform statistical analysis and induction on medical data processing information related to each link in a medical service scene based on the SaaS service to obtain a statistical analysis result, and further can provide data support for a medical service and/or a medical data processing module through the statistical analysis result so as to realize optimization and improvement on the medical service and/or the medical data processing module.
Fig. 2 is a flowchart illustrating a medical data processing method based on SaaS service according to an embodiment of the present disclosure, where the medical data processing method based on SaaS service is applied to a data statistics module, where the data statistics module may be implemented by a software module, or may also be an electronic device such as a terminal device or a server, where the terminal device may be a User Equipment (UE), a mobile device, a User terminal, a cellular phone, a cordless phone, a Personal Digital Assistant (PDA), a handheld device, a computing device, a vehicle-mounted device, a wearable device, or the like, and the method may be implemented by a processor calling a computer readable instruction stored in a memory. Alternatively, the method may be performed by a server.
As shown in fig. 2, the SaaS service-based medical data processing method may include:
in step S21, medical data processing information reported by each medical data processing module is received, where the medical data processing information includes data information reported when the medical data processing module processes medical data to be processed.
For example, in a medical service scenario based on SaaS service, which is deployed in a medical service cluster of a server (cloud or IDC), medical data needs to pass through a plurality of links from acquisition to filing to data processing, and a medical data processing module related to each link can report corresponding medical data processing information when processing the medical data to be processed, as shown in fig. 1.
For example, the medical data processing module may report corresponding medical data processing information to the data statistics module when starting to process the to-be-processed medical data, where the medical data processing information may include information such as identification information of the to-be-processed medical data, identification information of the medical data processing module, time for starting processing of the to-be-processed medical data, and a processing state (e.g., an initial processing state, an end processing state, an abnormal processing state, and the like, hereinafter) for the to-be-processed medical data; and/or the medical data processing module may report corresponding medical data processing information to the data statistics module when processing on the medical data to be processed is completed, where the medical data processing information may include information such as identification information of the medical data to be processed, identification information of the medical data processing module, time for completing processing on the medical data to be processed, processing state on the medical data to be processed, and processing result on the medical data to be processed.
In one possible implementation, the medical data processing module may include at least one of a medical data collection module, a medical data transmission module, a medical data archiving module, and a medical data diagnostic module.
For example, the medical data to be processed needs to go through the processes of collection, transmission, archiving and diagnosis calculation, and therefore, the medical data processing module may include at least one of a medical data collection module, a medical data transmission module, a medical data archiving module and a medical data diagnosis module.
Wherein, the medical data collection module is used for collecting medical data to be processed, such as: after the imaging device captures medical images and waits for processing of medical data, the medical data collection module may collect the medical data from the imaging device or a PACS (Picture Archiving and Communication Systems), and for example, the medical data collection module may perform preprocessing such as compression and anonymous encryption on the medical data to be processed when collecting the medical data to be processed. The medical data transmission module is used for transmitting medical data to be processed, for example: the medical data transmission module may transmit the medical data to be processed from the imaging device to the medical data collection module. The medical data filing module is used for filing medical data to be processed after processing such as checking, duplicate removal and the like, for example: the medical data filing module can be used for filing the medical data to be processed into the PACS after checking and duplicate removal. The medical data diagnosis module is used for diagnosing and processing medical data to be processed to obtain a corresponding diagnosis result.
In step S22, statistical analysis is performed on the medical data processing information reported by each medical data processing module to obtain a statistical analysis result.
For example, after the data statistics module receives the medical data processing information reported by each medical data processing module, the medical data processing information may be structurally stored. The data statistical module can perform operations such as information induction and summary, statistical analysis and the like on the medical data processing information stored in the storage area to obtain corresponding statistical analysis results, and the statistical analysis results can include information used for supporting medical services and/or optimizing and improving the medical data processing module.
In one possible implementation, the statistical analysis result may include at least one of a performance evaluation result for the medical data processing module, a service usage rate of the medical data processing module, and a proportion of disease categories.
Wherein the performance evaluation result of the medical data processing module can be used to characterize the performance status of the medical data processing module. Illustratively, the performance evaluation results may include various performance levels, such as: the performance levels of the medical data processing module are excellent, good, general, poor and the like, and the performance state of the medical data processing module can be represented through the performance levels. It should be noted that the performance level is only one example of the performance level dividing manner in the embodiment of the present disclosure, and actually, there are multiple performance level dividing manners, and the embodiment of the present disclosure does not specifically limit the performance level dividing manner. Illustratively, the performance assessment results may also include performance scores, which may also be used to characterize the performance state of the medical data processing module, such as: the performance score of the medical data processing module may be determined based on a processing speed of the medical data processing module for the medical data to be processed.
After obtaining the performance evaluation result of the medical data processing, the medical data processing module may be optimized and improved according to the performance evaluation result of the medical data processing module, for example: under the condition that the performance evaluation result of the medical data processing module represents that the performance of the medical data processing module is poor, the medical data processing module can be optimized and improved so as to improve the performance of the medical data processing module.
The service utilization rate of the medical data processing module can be used for representing the utilization rate of the medical data processing module in a medical service cluster, and then the medical data processing module needing key optimization can be determined according to the service utilization rate of each medical data processing module, so that the performance of the medical data processing module is further improved, and the user experience is improved. For example, in the case that the service usage rate of the intelligent lung diagnosis module in the medical data diagnosis module is high, the intelligent lung diagnosis module may be further optimized, for example: more hardware resources, disk space and the like are provided for the intelligent lung diagnosis module, so that the response speed, the calculation precision and the like of the intelligent lung diagnosis module are improved, and the user experience is further improved. Or, the hospital can also perform service configuration more flexibly and accurately according to the service utilization rate of each medical data processing module, so as to configure the medical data processing module more meeting the service requirement for the hospital.
The ratio of the disease types can be used for representing the ratio of various diseases processed by the hospital, and the business state of the hospital is analyzed through the ratio of the disease types, such as: under the condition that the occupation ratio of the A-type diseases is high, the fact that a lot of A-type disease patients are received by a hospital can be determined, the workload of medical staff of departments corresponding to the A-type diseases is high, and the hospital is good at handling the business states of the A-type diseases and the like.
In fact, the statistical analysis result may further include information such as a total data number, a data usage rate, and high-frequency access data, and the statistical analysis result is not specifically limited in the embodiment of the present disclosure, and all results obtained by performing statistical induction on the reported medical data processing information may be included in the statistical analysis result.
In this way, the data statistical module can receive the medical data processing information reported by each medical data processing module, the medical data processing information includes the data information reported by the medical data processing module when processing the medical data to be processed, and the statistical analysis can be performed according to the medical data processing information reported by each medical data processing module, so as to obtain the statistical analysis result. The medical data processing method based on the SaaS service provided by the embodiment of the disclosure can perform statistical analysis on medical data processing information related to each link in a medical service scene based on the SaaS service to obtain a corresponding statistical analysis result, and further can provide data support for a medical service and/or a medical data processing module through the obtained statistical analysis result, so as to realize optimization and improvement for the medical service and/or the medical data processing module, and further improve user experience.
In a possible implementation manner, the medical data processing information includes first data information and/or second data information, where the first data information includes information reported when the medical data processing module starts to process the medical data to be processed, and the second data information includes information reported when the medical data processing module obtains a processing result corresponding to the medical data to be processed.
For example, when the medical data processing module starts to process the medical data to be processed, first data information for the medical data to be processed may be reported to the data statistics module; and/or when the medical data processing completes the processing of the medical data to be processed and obtains and outputs the processing result aiming at the medical data to be processed, the second data information aiming at the medical data to be processed can be reported to the data statistics module.
Therefore, the data statistical module can obtain the state information when the medical data processing module starts to execute the medical data to be processed and/or the state information when the medical data processing module finishes processing the medical data to be processed according to the first data information and/or the second data information, and further can obtain a more detailed and higher-dimension statistical analysis result through the first data information and/or the second data information so as to perform optimization and improvement on the medical data processing module more accurately and pertinently.
In a possible implementation manner, the first data information includes first time information when the medical data processing module starts to process the medical data to be processed, and the second data information includes second time information when the medical data processing module obtains a processing result corresponding to the medical data to be processed, and the processing result.
For example, when the medical data processing module starts to process the to-be-processed medical data, the medical data processing module sends first data information to the data statistics module, where the first data information may include identification information of the to-be-processed medical data and first time information when the medical data processing module starts to process the to-be-processed medical data. When the medical data processing module obtains a processing result of the medical data to be processed, second data information is sent to the data statistics module, and the second data information may include identification information of the medical data to be processed, second time information of the processing result corresponding to the medical data to be processed obtained by the medical data processing module, and the processing result. Wherein, the processing result corresponding to the medical data to be processed may include disease diagnosis information corresponding to the medical data to be processed, such as: the disease diagnosis information may include information such as a disease type, disease-related descriptive information (for example, in the case where the disease type is a lung nodule, the disease-related descriptive information may include the number, position, size, and benign or malignant information of the lung nodule), and the like.
For example, the medical data processing module may obtain timestamp information of the current time (for example: 20/2/20/12/00/30/20/2021) as first time information when processing of the medical data to be processed is started, and report the first data information to the data processing module, where the first time information is included in the first data information. When the medical data processing module finishes processing the medical data to be processed and obtains and outputs a processing result corresponding to the medical data to be processed, the medical data processing module acquires timestamp information of the current time (for example, 12: 00/47 seconds at 2/20/2021) as second time information and reports the second data information to the data processing module, wherein the second data information comprises the second time information.
In a possible implementation manner, the performing statistical analysis on the data information reported by each medical data processing module to obtain a statistical analysis result may include:
acquiring first data information and second data information reported by a medical data processing module to be evaluated aiming at any medical data to be processed;
determining the processing duration of the medical data processing module to be evaluated aiming at the medical data to be processed according to first time information in the first data information and second time information in the second data information;
and determining the performance evaluation result of the medical data processing module to be evaluated according to the processing duration.
For example, the medical data processing module to be evaluated may be any medical data processing module requiring performance evaluation. For example, a user may determine a medical data processing module to be evaluated by selecting the medical data processing module or inputting a name, a code, and the like of the medical data processing module, or may periodically evaluate the performance of each medical data processing module by using each medical data processing module as the medical data processing module to be evaluated, where an evaluation period of the medical data processing module may be a preset period or a period defined by a user, and this is not particularly limited in this embodiment of the disclosure.
The first data information and the second data information reported by the medical data processing module to be evaluated for any medical data to be processed may be obtained in response to an evaluation operation for the medical data processing module to be evaluated (for example, after the medical data processing module to be evaluated is determined, a determination control/evaluation control or other related control may be triggered).
In a possible implementation manner, the first data information and the second data information reported by the to-be-evaluated medical data processing module to any to-be-processed medical data within the first evaluation time range may be obtained, for example: the first evaluation time range is one week, and the first data information and the second data information reported by the medical data processing module to be evaluated on the medical data to be processed within one week can be acquired. The first evaluation time range may be set by a user in a self-defined manner, or may be a preset fixed time range, and a determination manner of the first evaluation time range in the embodiment of the present disclosure is not specifically limited.
After the first data information and the second data information reported for at least one piece of medical data to be processed are acquired, first time information for starting processing the medical data to be processed may be acquired from the first data information, second time information for outputting a processing result of the medical data to be processed may be acquired from the second data information, and a processing duration of the medical data processing module to be evaluated for the medical data to be processed may be obtained according to the first time information and the second time information, for example: the time difference between the first time information and the second time information may be determined as a processing time period for the medical data to be processed. Taking the above example as an example, if the first time information is 2021 year 2 month 20 day 12 point 00 minute 30 seconds, and the second time information is 2021 year 2 month 20 day 12 point 00 minute 47 seconds, it may be determined that the processing time length of the medical data processing module to be evaluated for the medical data to be processed is 17 seconds.
By analogy, the processing time of the medical data processing module to be evaluated for each piece of medical data to be processed can be determined, and the performance of the medical data processing module to be evaluated can be evaluated according to the processing time of the medical data processing module to be evaluated for each piece of medical data to be processed, so as to obtain a corresponding performance evaluation result. For example, a mean value of the processing time length of the medical data processing module to be evaluated for each piece of medical data to be processed may be determined, and a performance evaluation result of the medical data processing module to be evaluated may be determined according to the mean value of the processing time length of the medical data to be processed, for example: the mean value ranges corresponding to different performance levels can be set, and corresponding performance evaluation results can be obtained according to the performance levels corresponding to the mean values of the medical data processing duration to be processed.
Therefore, according to the medical data processing method based on the SaaS service provided by the embodiment of the disclosure, the performance evaluation result of the medical data processing module to be evaluated can be determined according to the first time information and the second time information, so that the medical data processing module can be optimized and improved according to the performance evaluation result of the medical data processing module, and further, the user experience can be improved.
In a possible implementation manner, the medical data processing information may include third data information, where the third data information includes information reported when the medical data processing module deletes or modifies the processing result corresponding to the to-be-processed medical data.
For example, the user may modify or delete the processing result of the medical data to be processed when the medical data processing module has an error in the processing result of the medical data to be processed, the medical data processing module may respond to a modification operation or a deletion operation of the processing result corresponding to the medical data to be processed, and report third data information to the data statistics module when the processing result corresponding to the medical data to be processed is modified or deleted, where the third data information may include information such as identification information of the medical data to be processed, identification information of the medical data processing module, a processing result before modification or deletion, and a processing result after modification.
Therefore, the medical data processing method based on the SaaS service provided by the embodiment of the present disclosure can report the third data information, so that the third data information can be used as a data basis for optimizing and improving the medical data processing module, and further, the performance of the medical data processing module can be improved in a targeted manner, and the user experience can be improved.
In a possible implementation manner, the performing statistical analysis on the data information reported by each medical data processing module to obtain a statistical analysis result may include:
determining a first number of processing results deleted or modified by the medical data processing module to be evaluated according to the third data information;
and determining the performance evaluation result of the medical data processing module to be evaluated according to the first quantity and the total number of the medical data to be processed by the medical data processing module to be evaluated.
For example, in response to an evaluation operation for the medical data processing module to be evaluated, third data information reported by the medical data processing module to be evaluated may be obtained according to the identification information of the medical data processing module to be evaluated, and the number of the third data information may be determined as the first number of processing results deleted or modified by the medical data processing module to be evaluated. The total number of the to-be-processed medical data processed by the to-be-evaluated medical data processing module may be counted, for example, the total number of the second data information reported by the to-be-evaluated medical data processing module may be determined as the total number of the to-be-processed medical data processed by the to-be-evaluated medical data processing module, or the identification information of the to-be-processed medical data in all the medical data processing information reported by the to-be-evaluated medical data processing module may be counted, so as to obtain the total number of the to-be-processed medical data processed by the to-be-evaluated medical data processing module.
The ratio of the first quantity of the third data information to the total number of the to-be-processed medical data processed by the to-be-evaluated medical data processing module may be determined, and the ratio is determined as the error rate of the to-be-evaluated medical data processing module, so that the performance evaluation result of the to-be-evaluated medical data processing module may be obtained through the error rate. For example, the performance evaluation result of the medical data processing module to be evaluated may be determined according to the error rate, for example: and setting error rate ranges corresponding to different performance levels, and obtaining corresponding performance evaluation results according to the performance levels corresponding to the error rates of the medical data processing modules to be evaluated.
In one possible implementation, the performance of the medical data processing module to be evaluated may be evaluated through the third data information within the specified time period. For example, the first quantity of the third data information reported by the medical data processing module to be evaluated within the second evaluation time range and the total quantity of the medical data processing information reported by the medical data processing module to be evaluated within the second evaluation time range may be determined to determine the error rate of the medical data processing module to be evaluated, and then the performance evaluation result of the medical data processing module to be evaluated may be obtained according to the error rate. The determining manner of the second evaluation time range is the same as the determining manner of the first evaluation time range, and the second evaluation time range may be the same as or different from the first evaluation time range.
For example: the medical data processing module to be evaluated processes 10 pieces of medical data to be processed in total in the second evaluation time range, that is, the total number of the medical data to be processed is 10. Assuming that the user successively modifies the processing result of the medical data to be processed 2 times, that is, the medical data processing module to be evaluated successively reports 2 pieces of third data information for the medical data to be processed 2, the first number of the third data information is 2, and it can be determined that the error rate of the medical data processing module to be evaluated is 0.2; or, assuming that the user successively modifies the processing result of the medical data to be processed 2 for 8 times and the processing result of the medical data to be processed 3 for 3 times, that is, the medical data processing module to be evaluated successively reports 8 pieces of third data information for the medical data to be processed 2 and 3 pieces of third data information for the medical data to be processed 3, the first number of the third data information is 11, and the error rate of the medical data processing module to be evaluated can be determined to be 1.1. The higher the error rate of the medical data processing module to be evaluated, the worse the performance of the medical data processing module to be evaluated.
Therefore, according to the medical data processing method based on the SaaS service provided by the embodiment of the disclosure, the performance evaluation result of the medical data processing module to be evaluated can be determined according to the third data information, so that the medical data processing module can be optimized and improved in a targeted manner according to the performance evaluation result of the medical data processing module, and further, the user experience can be improved.
In a possible implementation manner, the processing duration of the medical data processing module to be evaluated with respect to the medical data to be processed and the error rate of the medical data processing module to be evaluated can be integrated to obtain the comprehensive performance evaluation result of the medical data processing module to be evaluated. For example: the medical data processing module to be evaluated can perform weighted summation on the average value of the processing time of the medical data to be evaluated and the error rate of the medical data processing module to be evaluated to obtain a performance evaluation score, and then the comprehensive performance evaluation result of the medical data processing module to be evaluated is obtained according to the performance evaluation score. Alternatively, a first performance evaluation result may be obtained according to a processing duration of the to-be-evaluated medical data processing module for the to-be-processed medical data (the specific process may refer to the foregoing embodiment, which is not described herein again), a second performance evaluation result may be obtained according to an error rate of the to-be-evaluated medical data processing module (the specific process may refer to the foregoing embodiment, which is not described herein again), a performance graph may be drawn according to the first evaluation result and the second evaluation result, and the performance graph is used as a comprehensive performance evaluation result.
Therefore, the performance of the medical data processing module to be evaluated can be more comprehensively reflected through the comprehensive performance evaluation result, comprehensive optimization and improvement can be carried out on the medical data processing module to be evaluated according to the comprehensive performance evaluation result, the performance of the medical data processing module to be evaluated can be improved, and user experience is improved.
In a possible implementation manner, the processing result in the second data information includes a disease type of the medical data to be processed, and performing statistical analysis on the data information reported by each medical data processing module to obtain a statistical analysis result may include:
determining a second quantity of second data information corresponding to the target disease category;
and determining the proportion of the target disease type according to the second quantity and the total number of the second data information.
For example, the second data information reported by the medical data processing module includes a processing result for the medical data to be processed, and the processing result may include a type of a disease, for example: pneumonia, pulmonary tuberculosis, fracture, etc. The target disease category may be any disease category, for example, the target disease category may be determined by selecting the disease category or inputting the name of the disease category, or the target disease category may be periodically determined by taking each disease category as the target disease category, so as to periodically count the traffic status of each disease category.
After the target disease type is determined, the processing result may be determined to include the second data information of the target disease type, a second quantity of the second data information including the target disease type may be counted, a total number of the second data information reported by all the medical data processing modules may be counted, and a ratio of the second quantity to the total number of the second data information may be used as a ratio of the target disease type.
Thus, the method for processing medical data based on SaaS service provided by the embodiment of the present disclosure can determine the ratio of the target disease type, and further can analyze the business state of the hospital according to the ratio of the target disease type, so as to reasonably allocate business resources according to the business state of the hospital, for example: under the condition that the occupation ratio of the class A disease types is high, the fact that a plurality of class A disease patients are in hospital reception can be determined, the workload of medical staff of departments corresponding to the class A disease is high, and hands, equipment and the like can be preferentially assigned to the departments corresponding to the class A disease.
In a possible implementation manner, the medical data processing information may further include fourth data information, where the fourth data information includes information reported when the medical data processing module is accessed, and performing statistical analysis on the data information reported by each medical data processing module to obtain a statistical analysis result may include:
determining a third number of accessed medical data processing modules to be evaluated according to the fourth data information;
and determining the service utilization rate of the medical data processing module to be evaluated according to the third quantity and the total number of the fourth data information.
For example, if the medical data processing module is called, it may be determined that the medical data processing module is accessed, and then the fourth data information may be reported to the data statistics module. The third quantity of the fourth data information reported by the medical data processing modules to be evaluated can be obtained, and the total quantity of the fourth data information reported by all the medical data processing modules can be determined. The ratio of the third quantity of the fourth data information reported by the medical data processing module to be evaluated to the total quantity of the fourth data information can be determined as the service utilization rate of the medical data processing module to be evaluated.
In one possible implementation, the traffic usage of the medical data processing module to be evaluated during the session time may be determined. For example, a third amount of the fourth data information reported by the medical data processing module to be evaluated within the third evaluation time range and a total amount of the fourth data information reported by all the medical data processing modules within the third evaluation time range may be determined, so as to determine the service usage rate of the medical data processing module to be evaluated within the third evaluation time range. The determination method of the third evaluation time range is the same as the determination method of the first evaluation time range, and the third evaluation time range may be the same as or different from the first evaluation time range.
Therefore, the medical data processing method based on the SaaS service provided by the embodiment of the disclosure can determine the medical data processing module needing important optimization according to the service utilization rate of the medical data processing module, so as to further improve the performance of the medical data processing module and further improve the user experience.
In one possible implementation manner, the medical data processing information includes a processing status of the medical data processing module for the medical data to be processed, and the method may further include:
generating an alarm instruction according to the medical data processing information under the condition that the medical data processing information comprises an abnormal processing state;
sending the alarm indication to a specified device,
the exception handling state is a handling state used for indicating that the medical data handling module has an exception in the handling process of the medical data to be handled.
For example, the medical data processing information sent by the medical data processing module may include a processing status of the medical data processing module with respect to the medical data to be processed. For example, the medical data processing module may send medical data processing information to the data statistics module according to the processing status for the medical data to be processed, such as: when the medical data to be processed is processed, if the processing state of the medical data to be processed is an initial processing state, first data information including the initial processing state can be sent to the data statistics module; when the processing result for the medical data to be processed is output, and the processing state for the medical data to be processed is the processing ending state, second data information including the processing ending state can be sent to the data statistics module; when the medical data to be processed is abnormal and the medical data to be processed is not successfully processed, the processing state of the medical data to be processed is an abnormal processing state, and then the medical data processing information including the abnormal processing state can be sent to the data statistics module.
Therefore, when the received medical data processing information includes an abnormal processing state, it may be determined that the medical data processing module sending the medical data processing information has an abnormality in the processing process of the medical data to be processed, and therefore, an alarm instruction may be generated according to the medical data processing information, and the alarm instruction may be used to notify a user of the abnormal situation occurring in the medical data processing module.
For example, when the received medical data processing information includes an abnormal processing state, the identification information of the medical data to be processed, the identification information of a medical data processing module reporting the medical data processing information, the time information reporting the medical data processing information, the abnormal state information and other information can be acquired from the medical data processing information to generate a corresponding alarm instruction, and the alarm instruction is sent to the designated device, so that after the designated device receives the alarm instruction, a user can determine the abnormal medical data processing module and the abnormal time and other information according to the alarm instruction, and further can perform targeted troubleshooting on the abnormality timely and quickly, and can improve the response speed for the abnormal processing. The above-mentioned designated device may be a preset device that receives the alarm indication, for example: if the mailbox for receiving the alarm indication can be preset, the equipment for logging in the mailbox is the specified equipment.
In a possible implementation manner, the medical data processing module includes at least one sub-processing module, and the second data information includes processing time information of each sub-processing module for the medical data to be processed and a processing result for the medical data to be processed.
For example, at least one sub-processing module may be configured in the medical data processing module, such as: the intelligent lung diagnosis module can be configured with a nodule diagnosis submodule and a pneumonia diagnosis submodule, wherein the nodule diagnosis submodule is used for determining the number of nodules, benign and malignant properties and the like in the CT image, and the pneumonia diagnosis submodule is used for diagnosing whether a patient has pneumonia diseases according to the CT image.
When the medical data processing module starts to process the medical data to be processed, the medical data to be processed can be sequentially or synchronously diagnosed and processed through the at least one sub-processing module. In the process of diagnosing and processing the medical data to be processed by each sub-processing module, time information of starting processing the medical data to be processed, time information of finishing processing the medical data to be processed, a processing result aiming at the medical data to be processed and the like of each processing sub-module can be recorded. After all the sub-processing modules complete the diagnosis of the medical data to be processed, the diagnosis result of the medical data to be processed of each sub-processing module can be obtained, the diagnosis result can include the processing result of at least one sub-processing module for the medical data to be processed, and second data information can be sent to the data statistics module according to the processing record of the medical data to be processed of each sub-processing module, and the second data information can include processing time information (including time information for starting processing the medical data to be processed and time information for completing the processing of the medical data to be processed) of each sub-processing module for the medical data to be processed and the processing result for the medical data to be processed.
Taking the above intelligent lung diagnosis module as an example, the processing record of the node diagnosis submodule and the pneumonia diagnosis submodule in the intelligent lung diagnosis module on the medical data to be processed includes: the processing record 1 (the identification information of the nodule diagnosis submodule, the identification information of the medical data to be processed, the processing start time information 1, the processing end time information 1, and the processing result 1) and the processing record 2 (the identification information of the pneumonia diagnosis submodule, the identification information of the medical data to be processed, the processing start time information 2, the processing end time information 2, and the processing result 2) may be included in the second data information reported by the intelligent lung diagnosis module.
Therefore, according to the medical data processing method based on the SaaS service provided by the embodiment of the present disclosure, when the medical data processing module is subjected to processing such as optimization and upgrade, the sub-processing modules of the medical data processing module can be upgraded in a targeted manner according to the processing time information of the to-be-processed medical data and the processing result of the to-be-processed medical data of each sub-processing module in the second data information, so that the performance and the optimization speed of the medical data processing module can be effectively improved.
In one possible implementation, the method may further include:
responding to the display operation aiming at the target medical data to be processed, and acquiring medical data processing information corresponding to the target medical data to be processed;
and sending medical data processing information corresponding to the target medical data to be processed to a display module so that the display module displays the medical data processing information corresponding to the target medical data to be processed.
For example, the user may specify target pending medical data to be viewed, such as: the medical data to be processed associated with at least one of the specified time information, the identification information of the medical data to be processed, the identification information of the medical data processing module and the like may be determined as the target medical data by specifying at least one of the time information, the identification information of the medical data to be processed (which may include the identification information of the patient to which the medical data to be processed belongs, the identification information of the imaging device to which the medical data to be processed belongs, and the like), the identification information of the medical data processing module and the like.
After the target medical data to be processed is determined, in response to a display operation (for example, an operation of triggering a determination control/a display control or other controls) for the target medical data to be processed, medical data processing information corresponding to the target medical data to be processed is acquired, and the medical data processing information corresponding to the target medical data to be processed is sent to a display module, where the display module may be an electronic device with a display interface, so as to display the medical data processing information through the display module.
For example, the user may input information related to the target medical data to be processed through an input box in the display interface, such as: at least one of patient ID information, imaging device ID information, time information, and the like may be input, and the target medical data to be treated may be determined according to the relevant information of the target medical data to be treated. After medical data processing information of target medical data to be processed is acquired, displaying the medical data through a display module, for example: a corresponding information list may be generated according to the acquired medical data processing information, and the information list may be displayed in a display interface of the display module, as shown in fig. 3.
Further, any medical data processing information in the information list can be selected, a display interface of the medical data processing information can be skipped, and specific information of the medical data processing information is displayed in the display interface.
As another example, the user may determine that the image information of the patient acquired by the imaging device is the target medical data to be processed by setting the identification information of the patient and the identification information of the imaging device. After medical data processing information of the target medical data to be processed is acquired, a processing link trace map of the target medical data to be processed is generated according to the acquired medical data processing information, and the processing link trace map is displayed on a display interface, for example, the link trace map may be as shown in fig. 4. The processing link trace diagram may include time information and processing state information of medical data processing information reported when the target medical data to be processed is processed in each medical data processing module.
As shown in fig. 4, for any target medical data to be processed, each node in the processing link trace graph 400 corresponds to medical data processing information reported by a medical data processing module for the target medical data to be processed, and the medical data processing information may be sorted in time in the processing link trace graph according to processing time included in the medical data processing information. In fig. 4, the medical data collection module is referred to as collection (the collection module corresponds to 401 in fig. 4), the medical data transmission module is referred to as transmission (the transmission module corresponds to 402 in fig. 4), the medical data archiving module is referred to as archiving (the archiving module corresponds to 403 in fig. 4), and the medical data diagnosis module is referred to as diagnosis (the diagnosis module corresponds to 404 in fig. 4).
For another example, for the second data information reported by the medical data processing module including multiple sub-processing modules (for example, the data information "2020-11-1409: 19:19, end" with the end state reported by the diagnosis module 404 in fig. 4), further display may be performed to display the processing information of each sub-processing module in the medical data processing module on the target medical data to be processed, for example: a diagnostic trace map for the target medical data to be processed may be generated from the processing information of the sub-processing modules, and may be presented.
For example, on the basis of fig. 4, a user may select second data information reported by the medical data diagnosis module 404 for the first target to-be-processed medical data (a node whose state reported by the diagnosis module 404 in fig. 4 is end represents the second data information), so as to obtain processing information corresponding to each sub-processing module in the second data information reported for the first target to-be-processed medical data, generate a diagnosis track map according to the processing information corresponding to each sub-processing module, and display the diagnosis track map on a display interface, where for example, the diagnosis track map may be as shown in fig. 5. Each node in the diagnosis track map corresponds to processing information of the first target medical data to be processed by one sub-processing module.
For example, taking the diagnostic module 404 shown in fig. 4 as an intelligent lung diagnostic module as an example, the trajectory diagnostic graph 500 shown in fig. 5 may include a processing record of the medical data to be processed by each processing submodule in the intelligent lung diagnostic module, including: processing information 1 for medical data to be processed reported by a lung nodule diagnosis submodule 501 (referred to as a lung nodule in fig. 5 for short) in fig. 5 (the processing information 1 includes node information whose state reported by the lung nodule diagnosis submodule 501 is start and end), processing information 2 for medical data to be processed reported by a pneumonia diagnosis submodule 502 (referred to as pneumonia in fig. 5 for short) in fig. 5 (the processing information 2 includes node information whose state reported by the pneumonia diagnosis submodule 502 is start and end), and processing information 3 for medical data to be processed reported by a fracture diagnosis submodule 503 (referred to as fracture in fig. 5 for short) in fig. 5 (the processing information 3 includes node information whose state reported by the fracture diagnosis submodule 503 is start and end).
That is, in the embodiment of the present disclosure, each medical data processing module may report corresponding medical data processing information when processing medical data to be processed, so that a user may obtain a corresponding processing link trace map and a corresponding diagnosis trace map by searching for medical data processing information corresponding to any medical data to be processed (for example, obtaining the processing link trace map 400 shown in fig. 4 and the diagnosis trace map 500 shown in fig. 5) so as to obtain a processing state of the medical data to be processed in the whole processing link through the processing link trace map and the diagnosis trace map, so that a processing process for the medical data to be processed is transparent.
Therefore, the medical data processing method based on the SaaS service provided by the embodiment of the disclosure can display the medical data processing information of the medical data to be processed, so that the processing process of the medical data to be processed is transparent.
Fig. 6 shows a flowchart of a SaaS service-based medical data processing method according to an embodiment of the present disclosure, where the SaaS service-based medical data processing method employs a medical data processing module, where the medical data processing module may be implemented by a software module, or may also be an electronic device such as a terminal device or a server, where the terminal device may be a User Equipment (UE), a mobile device, a User terminal, a cellular phone, a cordless phone, a Personal Digital Assistant (PDA), a handheld device, a computing device, a vehicle-mounted device, a wearable device, or the like, and the method may be implemented by a processor calling a computer readable instruction stored in a memory. Alternatively, the method may be performed by a server.
As shown in fig. 6, the method may include:
in step S61, the processing status of the medical data processing module for the medical data to be processed is monitored.
For example, the medical data processing module may include at least one of a medical data collection module, a medical data transmission module, a medical data archiving module, and a medical data diagnosis module. The medical data processing module may monitor a processing status for the medical data to be processed in real time. The processing state for the medical data to be processed may include an initial processing state, an end processing state, an abnormal processing state, and the like.
In step S62, medical data processing information corresponding to the processing state of the medical data to be processed is obtained;
for example, the medical data processing module may generate corresponding medical data processing information according to the processing state of the medical data to be processed when monitoring that the processing state of the medical data processing module for the medical data to be processed changes; or, the medical data processing module may generate corresponding medical data processing information according to the current processing state of the medical data to be processed when the processing state is not monitored to change in the monitoring period.
For example, identification information of the medical data to be processed, identification information of the medical data processing module, timestamp information for the current time, the current processing state of the medical data to be processed, and the like may be acquired, and the medical data processing information may be generated according to the acquired information.
In step S63, the medical data processing information is sent to a data statistics module.
For example, after obtaining the medical data processing information, the medical data processing module may send the medical data processing information to the data statistics module. After receiving the medical data processing information, the data statistics module may perform structured storage on the medical data processing information, and may perform statistical analysis on the medical data processing information stored in the storage area to obtain a statistical analysis result (the specific process of the statistical analysis may refer to the foregoing embodiment, which is not described herein again in this disclosure embodiment).
In this way, the medical data processing module may monitor a processing state of the medical data processing module with respect to the medical data to be processed, and obtain medical data processing information corresponding to the processing state of the medical data to be processed. And sending the medical data processing information to a data statistics module so that the data statistics module obtains a statistical analysis result by performing statistical analysis on the medical data processing information. The medical data processing method based on the SaaS service provided by the embodiment of the disclosure can report medical data processing information related to each link in a medical service scene based on the SaaS service, so that the medical data processing information can be subjected to statistical analysis to obtain a corresponding statistical analysis result, and then data support can be provided for the medical service and/or the medical system through the obtained statistical analysis result, so that optimization and improvement aiming at the medical service and/or the medical system are realized, and further, user experience is improved.
In a possible implementation manner, the obtaining of the medical data processing information corresponding to the processing state of the medical data to be processed includes:
under the condition that the medical data processing module starts to process the medical data to be processed, determining that the medical data to be processed is in an initial processing state;
obtaining the first data information according to the initial processing state; alternatively, the first and second electrodes may be,
determining that the medical data to be processed is in a processing ending state under the condition that the medical data processing module obtains the processing result of the medical data to be processed;
and obtaining the second data information according to the processing ending state.
For example, when the medical data to be processed is input into the medical data processing module and starts to be processed, the medical data processing module may monitor that the processing state of the medical data to be processed changes from a waiting state (or an empty state) to an initial processing state, and then may determine that the medical data to be processed is currently in the initial processing state, may obtain first data information according to the initial processing state, and report the first data information to the data statistics module. The first data information may include the initial processing state, and may further include identification information of the medical data to be processed, identification information of the medical data processing module, and first time information (timestamp information of the current time) when processing of the medical data to be processed is started.
After the medical data processing module completes processing on the medical data to be processed and obtains a processing result of the medical data to be processed, the medical data processing module may output the processing result of the medical data to be processed, and at this time, the medical data processing module may determine that the medical data to be processed is in a processing ending state. That is, if the medical data processing module monitors that the processing state of the medical data to be processed changes from the initial processing state to the end processing state, the medical data processing module may obtain the second data information according to the end processing state and report the second data information to the data statistics module. The second data information may include the processing end state, and may further include identification information of the medical data to be processed, identification information of a medical data processing module, second time information (timestamp information of the current time) when the processing of the medical data to be processed is ended, and a processing result for the medical data to be processed.
Therefore, the medical data processing method based on the SaaS service provided by the embodiment of the present disclosure can evaluate the performance of the medical data processing module according to the first data information and the second data information reported for the medical data to be processed (the evaluation process may refer to the foregoing embodiment, which is not described herein again), and can optimize and improve the medical data processing module timely and effectively according to the performance evaluation result of the medical data processing module, thereby improving user experience.
In a possible implementation manner, the obtaining medical data processing information corresponding to a processing state of the medical data to be processed may include:
determining that the medical data to be processed is in an abnormal processing state under the condition that the medical data processing module does not successfully process the medical data to be processed;
and obtaining medical data processing information according to the abnormal processing state, wherein the abnormal processing state is a processing state used for indicating that the medical data processing module has abnormality in the processing process of the medical data to be processed.
For example, in the event that the medical data processing module does not successfully process the medical data to be processed, the medical data processing module may determine that the medical data to be processed is in an exception processing state. For example: the method may determine that the medical data to be processed is in an abnormal processing state when the medical data to be processed is not successfully processed within a preset time, or may determine that the medical data to be processed is in an abnormal processing state when the medical data processing module fails/interrupts processing of the medical data to be processed. When the medical data to be processed is determined to be in the abnormal processing state, the medical data processing information can be obtained according to the abnormal processing state, and the medical data processing information is reported to the data statistics module. The medical data processing information may include an exception handling state, and may further include identification information of medical data to be processed, identification information of a medical data processing module, and third time information (timestamp information of a current time) for generating the exception.
Therefore, the medical data processing method based on the SaaS service provided by the embodiment of the present disclosure can perform targeted troubleshooting on the abnormality in time and quickly through the reported medical data processing information including the abnormality processing state, and can improve the response speed for the abnormality processing.
In a possible implementation manner, the obtaining medical data processing information corresponding to a processing state of the medical data to be processed may include:
in response to an update instruction for a processing result of the medical data to be processed, determining that the medical data to be processed is in an update state if the processing result of the medical data to be processed is updated;
and obtaining medical data processing information according to the updating state, wherein the updating instruction comprises a deleting instruction or a modifying instruction.
For example, the user may modify or delete the processing result of the medical data to be processed when the processing result of the medical data processing module for the medical data to be processed is incorrect. The medical data processing module can respond to the modification instruction or the deletion instruction of the processing result of the medical data to be processed, and modify or delete the processing result of the medical data to be processed so as to update the processing result of the medical data to be processed. At this time, the medical data processing module may determine that the medical data to be processed is in an updated state at the current time, and may further report third data information to the data statistics module, where the third data information may include the updated state, and may also include identification information of the medical data to be processed, identification information of the medical data processing module, a processing result before modification or deletion, a processing result after modification, and other information.
Therefore, the medical data processing method based on the SaaS service provided by the embodiment of the present disclosure can report the corresponding third data information when the processing result of the medical data processing module for the medical data to be processed is updated, so that the performance of the medical data processing module can be evaluated according to the third data information, and further, the medical data processing module can be optimized and improved according to the performance evaluation result of the medical data processing module, so as to improve the user experience.
The medical data processing method based on the SaaS service provided by the embodiment of the disclosure can be applied to medical services based on the SaaS service deployed in a medical service cluster of a service end (cloud or IDC), and can collect and summarize information such as the state of the whole life cycle of medical data to be processed, so as to provide sufficient data basis for maintenance and update iteration of accessed medical services, technical services and the whole medical system. For example, the IDC/cloud deploys a medical service cluster, which has access to more than 10 hospitals, and each hospital deploys a pre-device data automatic collection and pre-processing medical data. The medical data is automatically collected and processed before the front-end device is generated, is transmitted to the IDC for filing through an uploading service on the front-end device and triggers a series of diagnosis calculation, after the calculation is successful, a user can develop specific services aiming at the medical data according to the calculation result, and information such as the processing state of the medical data on the whole data link is reported to the data statistics module for induction, record and statistics.
Therefore, for the service operation and maintenance of the business, the time for quick response can be prolonged due to the sufficient data basis; for the medical system, the system has sufficient data basis, so that continuous update iteration of the system is facilitated; there is sufficient data for the accessing user to analyze his traffic scenario.
It is understood that the above-mentioned method embodiments of the present disclosure can be combined with each other to form a combined embodiment without departing from the logic of the principle, which is limited by the space, and the detailed description of the present disclosure is omitted. Those skilled in the art will appreciate that in the above methods of the specific embodiments, the specific order of execution of the steps should be determined by their function and possibly their inherent logic.
In addition, the present disclosure also provides a medical data processing apparatus, an electronic device, a computer-readable storage medium, and a program based on SaaS service, which can all be used to implement any one of the SaaS service-based medical data processing methods provided by the present disclosure, and the corresponding technical solutions and descriptions and corresponding descriptions in the method section are not repeated.
Fig. 7 shows a block diagram of a SaaS service-based medical data processing apparatus according to an embodiment of the present disclosure, applied to a data statistics module, and as shown in fig. 7, the apparatus includes:
the receiving module 71 may be configured to receive medical data processing information reported by each medical data processing module, where the medical data processing information includes data information reported when the medical data processing module processes medical data to be processed;
the statistical analysis module 72 may be configured to perform statistical analysis on the medical data processing information reported by each medical data processing module to obtain a statistical analysis result.
In this way, the data statistical module can receive the medical data processing information reported by each medical data processing module, the medical data processing information includes the data information reported by the medical data processing module when processing the medical data to be processed, and the statistical analysis can be performed according to the medical data processing information reported by each medical data processing module, so as to obtain the statistical analysis result. The medical data processing device based on the SaaS service provided by the embodiment of the disclosure can perform statistical analysis on medical data processing information related to each link in a medical service scene based on the SaaS service to obtain a corresponding statistical analysis result, and further can provide data support for a medical service and/or a medical data processing module through the obtained statistical analysis result, so as to realize optimization and improvement for the medical service and/or the medical data processing module, and further improve user experience. In one possible implementation, the statistical analysis result includes at least one of a performance evaluation result for the medical data processing module, a service usage rate of the medical data processing module, and a proportion of disease types.
In a possible implementation manner, the medical data processing information includes first data information and/or second data information, where the first data information includes information reported when the medical data processing module starts to process the medical data to be processed, and the second data information includes information reported when the medical data processing module obtains a processing result corresponding to the medical data to be processed.
In a possible implementation manner, the first data information includes first time information when the medical data processing module starts to process the medical data to be processed, and the second data information includes second time information when the medical data processing module obtains a processing result corresponding to the medical data to be processed, and the processing result.
In a possible implementation manner, the statistical analysis module 71 is further configured to:
acquiring first data information and second data information reported by a medical data processing module to be evaluated aiming at any medical data to be processed;
determining the processing duration of the medical data processing module to be evaluated aiming at the medical data to be processed according to first time information in the first data information and second time information in the second data information;
and determining the performance evaluation result of the medical data processing module to be evaluated according to the processing duration.
In a possible implementation manner, the medical data processing information includes third data information, and the third data information includes information reported when the medical data processing module deletes or modifies the processing result corresponding to the medical data to be processed.
In a possible implementation manner, the statistical analysis module 71 is further configured to:
determining a first number of processing results deleted or modified by the medical data processing module to be evaluated according to the third data information;
and determining the performance evaluation result of the medical data processing module to be evaluated according to the first quantity and the total number of the medical data to be processed by the medical data processing module to be evaluated.
In a possible implementation manner, the processing result in the second data information includes a disease category of the medical data to be processed, and the statistical analysis module 71 is further configured to:
determining a second quantity of second data information corresponding to the target disease category;
and determining the proportion of the target disease type according to the second quantity and the total number of the second data information.
In a possible implementation manner, the medical data processing information further includes fourth data information, where the fourth data information includes information reported when the medical data processing module is accessed, and the statistical analysis module 71 is further configured to:
determining a third number of accessed medical data processing modules to be evaluated according to the fourth data information;
and determining the service utilization rate of the medical data processing module to be evaluated according to the third quantity and the total number of the fourth data information.
In one possible implementation manner, the medical data processing information includes a processing status of the medical data processing module for the medical data to be processed, and the apparatus further includes:
the generating module may be configured to generate an alarm instruction according to the medical data processing information when the medical data processing information includes an abnormal processing state;
a first sending module operable to send the alert indication to a specified device,
the exception handling state is a handling state used for indicating that the medical data handling module has an exception in the handling process of the medical data to be handled.
In a possible implementation manner, the medical data processing module includes at least one sub-processing module, and the second data information includes processing time information of each sub-processing module for the medical data to be processed and a processing result for the medical data to be processed.
In one possible implementation, the apparatus further includes:
the acquisition module can be used for responding to display operation aiming at the target medical data to be processed and acquiring medical data processing information corresponding to the target medical data to be processed;
the second sending module may be configured to send medical data processing information corresponding to the target to-be-processed medical data to a display module, so that the display module displays the medical data processing information corresponding to the target to-be-processed medical data.
In one possible implementation, the medical data processing module includes at least one of a medical data collection module, a medical data transmission module, a medical data archiving module, and a medical data diagnostic module.
Fig. 8 shows a block diagram of a SaaS service-based medical data processing apparatus according to an embodiment of the present disclosure, applied to a medical data processing module, the apparatus including:
a monitoring module 81, which can be used to monitor the processing status of the medical data processing module for the medical data to be processed;
a processing module 82, configured to obtain medical data processing information corresponding to a processing status of the medical data to be processed;
a sending module 83, configured to send the medical data processing information to a data statistics module.
In this way, the medical data processing module may monitor a processing state of the medical data processing module with respect to the medical data to be processed, and obtain medical data processing information corresponding to the processing state of the medical data to be processed. And sending the medical data processing information to a data statistics module so that the data statistics module obtains a statistical analysis result by performing statistical analysis on the medical data processing information. The medical data processing device based on the SaaS service provided by the embodiment of the disclosure can report medical data processing information related to each link in a medical service scene based on the SaaS service, so that the medical data processing information can be subjected to statistical analysis to obtain a corresponding statistical analysis result, and then data support can be provided for the medical service and/or the medical system through the obtained statistical analysis result, so that optimization and improvement for the medical service and/or the medical system are realized, and further user experience is improved.
In one possible implementation, the medical data processing information includes first data information or second data information, and the processing module 82 is further configured to:
under the condition that the medical data processing module starts to process the medical data to be processed, determining that the medical data to be processed is in an initial processing state;
obtaining the first data information according to the initial processing state;
or, under the condition that the medical data processing module obtains the processing result of the medical data to be processed, determining that the medical data to be processed is in a processing ending state;
and obtaining the second data information according to the processing ending state.
In one possible implementation, the processing module 82 may further be configured to:
determining that the medical data to be processed is in an abnormal processing state under the condition that the medical data processing module does not successfully process the medical data to be processed;
and obtaining medical data processing information according to the abnormal processing state, wherein the abnormal processing state is a processing state used for indicating that the medical data processing module has abnormality in the processing process of the medical data to be processed.
In one possible implementation, the processing module 82 may further be configured to:
in response to an update instruction for a processing result of the medical data to be processed, determining that the medical data to be processed is in an update state if the processing result of the medical data to be processed is updated;
and obtaining medical data processing information according to the updating state, wherein the updating instruction comprises a deleting instruction or a modifying instruction.
In some embodiments, functions of or modules included in the apparatus provided in the embodiments of the present disclosure may be used to execute the method described in the above method embodiments, and specific implementation thereof may refer to the description of the above method embodiments, and for brevity, will not be described again here.
Embodiments of the present disclosure also provide a computer-readable storage medium having stored thereon computer program instructions, which when executed by a processor, implement the above-mentioned method. The computer readable storage medium may be a non-volatile computer readable storage medium.
An embodiment of the present disclosure further provides an electronic device, including: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to invoke the memory-stored instructions to perform the above-described method.
The embodiments of the present disclosure also provide a computer program product, which includes computer readable code, and when the computer readable code runs on a device, a processor in the device executes instructions for implementing the SaaS service-based medical data processing method provided in any of the above embodiments.
The disclosed embodiments also provide another computer program product for storing computer readable instructions, which when executed, cause a computer to perform the operations of the SaaS service-based medical data processing method provided in any of the above embodiments.
The electronic device may be provided as a terminal, server, or other form of device.
Fig. 9 illustrates a block diagram of an electronic device 900 in accordance with an embodiment of the disclosure. For example, the electronic device 900 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, or the like terminal.
Referring to fig. 9, electronic device 900 may include one or more of the following components: processing component 902, memory 904, power component 906, multimedia component 908, audio component 910, input/output (I/O) interface 912, sensor component 914, and communication component 916.
The processing component 902 generally controls overall operation of the electronic device 900, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. Processing component 902 may include one or more processors 920 to execute instructions to perform all or a portion of the steps of the methods described above. Further, processing component 902 can include one or more modules that facilitate interaction between processing component 902 and other components. For example, the processing component 902 can include a multimedia module to facilitate interaction between the multimedia component 908 and the processing component 902.
The memory 904 is configured to store various types of data to support operation at the electronic device 900. Examples of such data include instructions for any application or method operating on the electronic device 900, contact data, phonebook data, messages, pictures, videos, and so forth. The memory 904 may be implemented by any type or combination of volatile or non-volatile memory devices such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks.
The power supply component 906 provides power to the various components of the electronic device 900. The power components 906 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the electronic device 900.
The multimedia components 908 include a screen that provides an output interface between the electronic device 900 and a user. In some embodiments, the screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive an input signal from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 908 includes a front facing camera and/or a rear facing camera. The front camera and/or the rear camera may receive external multimedia data when the electronic device 900 is in an operating mode, such as a shooting mode or a video mode. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.
The audio component 910 is configured to output and/or input audio signals. For example, the audio component 910 includes a Microphone (MIC) configured to receive external audio signals when the electronic device 900 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals may further be stored in the memory 904 or transmitted via the communication component 916. In some embodiments, audio component 910 also includes a speaker for outputting audio signals.
I/O interface 912 provides an interface between processing component 902 and peripheral interface modules, which may be keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to: a home button, a volume button, a start button, and a lock button.
The sensor component 914 includes one or more sensors for providing status evaluations of various aspects of the electronic device 900. For example, sensor assembly 914 may detect an open/closed state of electronic device 900, the relative positioning of components, such as a display and keypad of electronic device 900, sensor assembly 914 may also detect a change in the position of electronic device 900 or a component of electronic device 900, the presence or absence of user contact with electronic device 900, orientation or acceleration/deceleration of electronic device 900, and a change in the temperature of electronic device 900. The sensor assembly 914 may include a proximity sensor configured to detect the presence of a nearby object in the absence of any physical contact. The sensor assembly 914 may also include a light sensor, such as a Complementary Metal Oxide Semiconductor (CMOS) or Charge Coupled Device (CCD) image sensor, for use in imaging applications. In some embodiments, the sensor assembly 914 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.
The communication component 916 is configured to facilitate wired or wireless communication between the electronic device 900 and other devices. The electronic device 900 may access a wireless network based on a communication standard, such as a wireless network (WiFi), a second generation mobile communication technology (2G) or a third generation mobile communication technology (3G), or a combination thereof. In an exemplary embodiment, the communication component 916 receives a broadcast signal or broadcast associated information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 916 further includes a Near Field Communication (NFC) module to facilitate short-range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, Ultra Wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.
In an exemplary embodiment, the electronic device 900 may be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, micro-controllers, microprocessors or other electronic components for performing the above-described methods.
In an exemplary embodiment, a non-transitory computer readable storage medium, such as the memory 904, is also provided, including computer program instructions executable by the processor 920 of the electronic device 900 to perform the above-described methods.
Fig. 10 shows a block diagram of an electronic device 1900 according to an embodiment of the disclosure. For example, the electronic device 1900 may be provided as a server. Referring to fig. 10, electronic device 1900 includes a processing component 1922 further including one or more processors and memory resources, represented by memory 1932, for storing instructions, e.g., applications, executable by processing component 1922. The application programs stored in memory 1932 may include one or more modules that each correspond to a set of instructions. Further, the processing component 1922 is configured to execute instructions to perform the above-described method.
The electronic device 1900 may also include a power component 1926 configured to perform power management of the electronic device 1900, a wired or wireless network interface 1950 configured to connect the electronic device 1900 to a network, and an input/output (I/O) interface 1958. The electronic device 1900 may operate based on an operating system, such as the Microsoft Server operating system (Windows Server), stored in the memory 1932TM) Apple Inc. of the present application based on the graphic user interface operating System (Mac OS X)TM) Multi-user, multi-process computer operating system (Unix)TM) Free and open native code Unix-like operating System (Linux)TM) Open native code Unix-like operating System (FreeBSD)TM) Or the like.
In an exemplary embodiment, a non-transitory computer readable storage medium, such as the memory 1932, is also provided that includes computer program instructions executable by the processing component 1922 of the electronic device 1900 to perform the above-described methods.
The present disclosure may be systems, methods, and/or computer program products. The computer program product may include a computer-readable storage medium having computer-readable program instructions embodied thereon for causing a processor to implement various aspects of the present disclosure.
The computer readable storage medium may be a tangible device that can hold and store the instructions for use by the instruction execution device. The computer readable storage medium may be, for example, but is not limited to, an electronic memory device, a magnetic memory device, an optical memory device, an electromagnetic memory device, a semiconductor memory device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a Static Random Access Memory (SRAM), a portable compact disc read-only memory (CD-ROM), a Digital Versatile Disc (DVD), a memory stick, a floppy disk, a mechanical coding device, such as punch cards or in-groove projection structures having instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media as used herein is not to be construed as transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission medium (e.g., optical pulses through a fiber optic cable), or electrical signals transmitted through electrical wires.
The computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to a respective computing/processing device, or to an external computer or external storage device via a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. The network adapter card or network interface in each computing/processing device receives computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in the respective computing/processing device.
The computer program instructions for carrying out operations of the present disclosure may be assembler instructions, Instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider). In some embodiments, the electronic circuitry that can execute the computer-readable program instructions implements aspects of the present disclosure by utilizing the state information of the computer-readable program instructions to personalize the electronic circuitry, such as a programmable logic circuit, a Field Programmable Gate Array (FPGA), or a Programmable Logic Array (PLA).
Various aspects of the present disclosure are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions.
These computer-readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer-readable program instructions may also be stored in a computer-readable storage medium that can direct a computer, programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer-readable medium storing the instructions comprises an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.
The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer, other programmable apparatus or other devices implement the functions/acts specified in the flowchart and/or block diagram block or blocks.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The computer program product may be embodied in hardware, software or a combination thereof. In an alternative embodiment, the computer program product is embodied in a computer storage medium, and in another alternative embodiment, the computer program product is embodied in a Software product, such as a Software Development Kit (SDK), or the like.
Having described embodiments of the present disclosure, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen in order to best explain the principles of the embodiments, the practical application, or improvements made to the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
Claims (21)
1. A medical data processing method based on SaaS service is applied to a data statistics module, and comprises the following steps:
receiving medical data processing information reported by each medical data processing module, wherein the medical data processing information comprises data information reported when the medical data processing module processes medical data to be processed;
and performing statistical analysis on the medical data processing information reported by each medical data processing module to obtain a statistical analysis result.
2. The method of claim 1, wherein the statistical analysis results comprise at least one of performance evaluation results for the medical data processing module, business usage of the medical data processing module, and a proportion of disease categories.
3. The method according to claim 1 or 2, wherein the medical data processing information includes first data information and/or second data information, wherein the first data information includes information reported when the medical data processing module starts processing the medical data to be processed, and the second data information includes information reported when the medical data processing module obtains a processing result corresponding to the medical data to be processed.
4. The method according to claim 3, wherein the first data information includes first time information when the medical data processing module starts processing the medical data to be processed, and the second data information includes second time information when the medical data processing module obtains a processing result corresponding to the medical data to be processed, and the processing result.
5. The method according to claim 4, wherein the performing statistical analysis on the medical data processing information reported by each medical data processing module to obtain a statistical analysis result comprises:
acquiring first data information and second data information reported by a medical data processing module to be evaluated aiming at any medical data to be processed;
determining the processing duration of the medical data processing module to be evaluated aiming at the medical data to be processed according to first time information in the first data information and second time information in the second data information;
and determining the performance evaluation result of the medical data processing module to be evaluated according to the processing duration.
6. The method according to any one of claims 1 to 5, wherein the medical data processing information includes third data information, and the third data information includes information reported when the medical data processing module deletes or modifies the processing result corresponding to the medical data to be processed.
7. The method according to claim 6, wherein the performing statistical analysis on the medical data processing information reported by each medical data processing module to obtain a statistical analysis result comprises:
determining a first number of processing results deleted or modified by the medical data processing module to be evaluated according to the third data information;
and determining the performance evaluation result of the medical data processing module to be evaluated according to the first quantity and the total number of the medical data to be processed by the medical data processing module to be evaluated.
8. The method according to any one of claims 3 to 5, wherein the processing result in the second data information includes a disease type of the medical data to be processed, and the performing statistical analysis on the medical data processing information reported by each medical data processing module to obtain a statistical analysis result includes:
determining a second quantity of second data information corresponding to the target disease category;
and determining the proportion of the target disease type according to the second quantity and the total number of the second data information.
9. The method according to any one of claims 1 to 8, wherein the medical data processing information further includes fourth data information, the fourth data information includes information reported when the medical data processing module is accessed, and the performing statistical analysis on the medical data processing information reported by each medical data processing module to obtain a statistical analysis result includes:
determining a third number of accessed medical data processing modules to be evaluated according to the fourth data information;
and determining the service utilization rate of the medical data processing module to be evaluated according to the third quantity and the total number of the fourth data information.
10. The method according to any one of claims 1 to 9, wherein the medical data processing information includes a processing status of the medical data processing module for the medical data to be processed, the method further comprising:
generating an alarm instruction according to the medical data processing information under the condition that the medical data processing information comprises an abnormal processing state;
sending the alarm indication to a specified device,
the exception handling state is a handling state used for indicating that the medical data handling module has an exception in the handling process of the medical data to be handled.
11. The method according to claim 3, wherein the medical data processing module comprises at least one sub-processing module, and the second data information comprises processing time information for the medical data to be processed and a processing result for the medical data to be processed of each sub-processing module.
12. The method according to any one of claims 1 to 11, further comprising:
responding to the display operation aiming at the target medical data to be processed, and acquiring medical data processing information corresponding to the target medical data to be processed;
and sending medical data processing information corresponding to the target medical data to be processed to a display module so that the display module displays the medical data processing information corresponding to the target medical data to be processed.
13. The method of any one of claims 1 to 12, wherein the medical data processing module comprises at least one of a medical data collection module, a medical data transmission module, a medical data archiving module, a medical data diagnostic module.
14. A medical data processing method based on SaaS service is applied to a medical data processing module, and comprises the following steps:
monitoring the processing state of the medical data processing module aiming at the medical data to be processed;
acquiring medical data processing information corresponding to the processing state of the medical data to be processed;
and sending the medical data processing information to a data statistics module.
15. The method according to claim 14, wherein the medical data processing information includes first data information or second data information, and the obtaining of the medical data processing information corresponding to the processing status of the medical data to be processed includes:
under the condition that the medical data processing module starts to process the medical data to be processed, determining that the medical data to be processed is in an initial processing state;
obtaining the first data information according to the initial processing state;
alternatively, the first and second electrodes may be,
determining that the medical data to be processed is in a processing ending state under the condition that the medical data processing module obtains the processing result of the medical data to be processed;
and obtaining the second data information according to the processing ending state.
16. The method according to claim 14, wherein the obtaining of the medical data processing information corresponding to the processing status of the medical data to be processed comprises:
determining that the medical data to be processed is in an abnormal processing state under the condition that the medical data processing module does not successfully process the medical data to be processed;
and obtaining medical data processing information according to the abnormal processing state, wherein the abnormal processing state is a processing state used for indicating that the medical data processing module has abnormality in the processing process of the medical data to be processed.
17. The method according to claim 14, wherein the obtaining of the medical data processing information corresponding to the processing status of the medical data to be processed comprises:
in response to an update instruction for a processing result of the medical data to be processed, determining that the medical data to be processed is in an update state if the processing result of the medical data to be processed is updated;
and obtaining medical data processing information according to the updating state, wherein the updating instruction comprises a deleting instruction or a modifying instruction.
18. A medical data processing device based on SaaS service is applied to a data statistics module and comprises:
the receiving module is used for receiving medical data processing information reported by each medical data processing module, and the medical data processing information comprises data information reported when the medical data processing module processes medical data to be processed;
and the statistical analysis module is used for performing statistical analysis on the medical data processing information reported by the medical data processing modules to obtain a statistical analysis result.
19. A medical data processing device based on SaaS service is applied to a medical data processing module and comprises:
the monitoring module is used for monitoring the processing state of the medical data processing module aiming at the medical data to be processed;
the processing module is used for obtaining medical data processing information corresponding to the processing state of the medical data to be processed;
and the sending module is used for sending the medical data processing information to the data statistics module.
20. An electronic device, comprising:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to invoke the memory-stored instructions to perform the method of any one of claims 1 to 17.
21. A computer readable storage medium having computer program instructions stored thereon, which when executed by a processor implement the method of any one of claims 1 to 17.
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