CN112908489A

CN112908489A - Method, apparatus and computer storage medium for generating a pharmacographical alertness health index

Info

Publication number: CN112908489A
Application number: CN202110348863.8A
Authority: CN
Inventors: 万帮喜; 周俊辉; 徐菊萍
Original assignee: Zhejiang Taimei Medical Technology Co Ltd
Current assignee: Zhejiang Taimei Medical Technology Co Ltd
Priority date: 2021-03-31
Filing date: 2021-03-31
Publication date: 2021-06-04

Abstract

The present invention provides a method, apparatus, and computer storage medium for generating a pharmacovigilance health index. The method comprises the following steps: pre-acquiring an authentication standard table based on a drug alert management specification, wherein the authentication standard table has a plurality of dimensions, each dimension has one or more data acquisition rules, each data acquisition rule corresponds to one item of data and has one or more scores associated with the data; acquiring a plurality of items of data associated with the plurality of dimensions; determining a score associated with each item of data according to a data acquisition rule corresponding to the data; and calculating the health index of the pharmacovigilance based on the score associated with each item of data.

Description

Method, apparatus and computer storage medium for generating a pharmacographical alertness health index

Technical Field

The present invention relates generally to the field of pharmacovigilance, and more particularly to a method, apparatus, and computer storage medium for generating a pharmacovigilance health index.

Background

In the field of medicine alert, in order to standardize the development of medicine alert work, ensure the balance of medicine risk and benefit, ensure the safety and effectiveness of public medication, and establish the management standard of medicine alert. For example, GVP (EU Good Pharmacovigilance practise) is a system that is important in the field of pharmacographical vigilance.

At present, mature pharmacovigilance management system logic is lacking in the field of pharmacovigilance. Enterprises operate on their own systems but lack clear standards, methods of system evaluation, and a share of best practices. For this reason, it is desirable to have a method that can reasonably evaluate a pharmacovigilance management regime and help establish the pharmacovigilance management regime.

Moreover, the data involved in the vigilance management system is numerous and is accumulated in the vigilance system, which also challenges the evaluation of the system.

Disclosure of Invention

The technical problem to be solved by the present invention is to provide a method, apparatus and computer storage medium for generating a pharmacovigient health index that can generate quantifiable and time-sensitive health indices based on data associated with a pharmacovigient management system.

In order to solve the above technical problems, the present invention provides a method for generating a pharmacomatic vigilance health index, comprising the steps of: the method comprises the steps of obtaining an authentication standard table based on a drug alert management standard in advance, wherein the authentication standard table has multiple dimensions; acquiring a plurality of items of data associated with the plurality of dimensions; and calculating a health index for the pharmacovigilance system using the plurality of pieces of data. Wherein the step of obtaining a plurality of items of data associated with the plurality of dimensions comprises: receiving a plurality of items of first data associated with a first dimension of the plurality of dimensions; establishing a first link, and sending a slave server data request to a master server where a master database for storing the drug alert data is located, so as to enable the master server to push a log file, wherein the log file is generated by modifying the drug alert data in the master database through the master server; acquiring a log file pushed by the main server by using the first link; establishing a second link, and sending a database connection request to the master database to acquire a plurality of field names associated with the log file; determining the field name of the latest version according to the acquired field names; and analyzing the log file by using the latest version field name to obtain a plurality of items of second data associated with a second dimension of the plurality of dimensions.

In an embodiment of the present invention, each of the dimensions has one or more data acquisition rules, each of the data acquisition rules corresponds to one item of data and has one or more scores associated with the item of data, wherein the step of calculating the health index of the pharmacovigilance using the plurality of items of data comprises: determining a score associated with each item of data according to a data acquisition rule corresponding to the data; and calculating the health index of the pharmacoviginal alert system according to the score associated with each item of data.

In an embodiment of the present invention, after the step of determining the score associated with each item of data, the method further comprises the steps of: and when the score is lower than a preset threshold value, marking the data corresponding to the score as a question item.

In an embodiment of the present invention, after the step of calculating the pharmacoviginal health index based on the score associated with each item of data, the method further comprises: and displaying the health index and the question item on the terminal equipment.

In an embodiment of the present invention, the step of parsing the log file using the latest version field name includes: and establishing a mapping relation between the field name of the latest version and corresponding data in the log file.

In an embodiment of the present invention, the method further includes recording a position when the log file is parsed, where the position indicates a starting position of a next parsing.

In an embodiment of the present invention, the method further includes storing the field names and the sites as metadata.

In an embodiment of the present invention, the method further includes: providing configuration options of a plurality of storage positions, wherein each storage position comprises a memory and a database; and saving the metadata to a corresponding saving position according to the selection of the configuration option.

In an embodiment of the invention, after the step of generating the plurality of items of second data associated with the second dimension of the plurality of dimensions, the method further comprises: pushing the plurality of items of second data to message middleware; monitoring data sent by the message middleware; and forwarding the data to a flow calculation engine for calculating a health index for the pharmaceutical surveillance system.

In an embodiment of the present invention, the step of determining the score associated with each item of data according to the data acquisition rule corresponding to the data includes: tracking, at the stream computation engine, a pre-formulated dynamic examination item and determining at least a portion of the plurality of second data associated with the dynamic examination item; and determining a score associated with each item of the at least partial second data according to a data acquisition rule corresponding to the at least partial second data.

Another aspect of the present invention provides an apparatus for generating a pharmacovigilance health index comprising an interface, a listening component, and a stream calculation engine. The interface is to receive a plurality of items of first data associated with a first dimension of a plurality of dimensions; the listening component is configured to: establishing a first link, and sending a slave server data request to a master server where a master database for storing the drug alert data is located, so as to enable the master server to push a log file, wherein the log file is generated by modifying the drug alert data in the master database through the master server; acquiring a log file pushed by the main server by using the first link; establishing a second link, and sending a database connection request to the master database to acquire a plurality of field names associated with the log file; determining the field name of the latest version according to the acquired field names; parsing the log file using the latest version field name to obtain a plurality of items of second data associated with a second dimension of the plurality of dimensions; the stream computation engine configured to: acquiring an authentication standard table based on a drug alert management specification in advance, wherein the authentication standard table has the plurality of dimensions; obtaining a plurality of items of data associated with the plurality of dimensions, the plurality of items of data including the first data and second data; and calculating a health index for the pharmacovigilance system using the plurality of pieces of data.

The present application also provides an apparatus for generating a pharmacovigilance health index comprising: a memory for storing instructions executable by the processor; and a processor for executing the instructions to implement the method as described above.

The present application also provides a computer storage medium having stored thereon computer program code which, when executed by a processor, implements a method as described above.

In contrast to the prior art, the present invention can generate a quantifiable health index based on data associated with a pharmacovigilance management system, thereby facilitating user assessment of the pharmacovigilance management system. In addition, the method monitors the incremental log file generated by the main database modifying data, and analyzes the log file to obtain data with strong timeliness, so that the health index is calculated according to a plurality of data, and high timeliness is achieved.

Drawings

The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the principle of the invention. In the drawings:

fig. 1 is a block diagram of an apparatus for generating a pharmacovigilance health index according to an embodiment of the present application.

Fig. 2 is a flow chart of a method of generating a pharmacovigilance health index according to an embodiment of the present application.

FIG. 3 is a flow diagram of a method of obtaining items of data associated with a plurality of dimensions according to an embodiment of the present application.

FIG. 4 illustrates an apparatus hardware implementation environment for generating a pharmacovigilance health index according to an embodiment of the present application.

Detailed Description

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings used in the description of the embodiments will be briefly introduced below. It is obvious that the drawings in the following description are only examples or embodiments of the application, from which the application can also be applied to other similar scenarios without inventive effort for a person skilled in the art. Unless otherwise apparent from the context, or otherwise indicated, like reference numbers in the figures refer to the same structure or operation.

As used in this application and the appended claims, the terms "a," "an," "the," and/or "the" are not intended to be inclusive in the singular, but rather are intended to be inclusive in the plural unless the context clearly dictates otherwise. In general, the terms "comprises" and "comprising" merely indicate that steps and elements are included which are explicitly identified, that the steps and elements do not form an exclusive list, and that a method or apparatus may include other steps or elements.

The relative arrangement of the components and steps, the numerical expressions, and numerical values set forth in these embodiments do not limit the scope of the present application unless specifically stated otherwise. Meanwhile, it should be understood that the sizes of the respective portions shown in the drawings are not drawn in an actual proportional relationship for the convenience of description. Techniques, methods, and apparatus known to those of ordinary skill in the relevant art may not be discussed in detail but are intended to be part of the specification where appropriate. In all examples shown and discussed herein, any particular value should be construed as merely illustrative, and not limiting. Thus, other examples of the exemplary embodiments may have different values. It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, further discussion thereof is not required in subsequent figures.

It should be noted that the terms "first", "second", and the like are used to define the components, and are only used for convenience of distinguishing the corresponding components, and the terms have no special meanings unless otherwise stated, and therefore, the scope of protection of the present application is not to be construed as being limited. Further, although the terms used in the present application are selected from publicly known and used terms, some of the terms mentioned in the specification of the present application may be selected by the applicant at his or her discretion, the detailed meanings of which are described in relevant parts of the description herein. Further, it is required that the present application is understood not only by the actual terms used but also by the meaning of each term lying within.

It will be understood that when an element is referred to as being "on," "connected to," "coupled to" or "contacting" another element, it can be directly on, connected or coupled to, or contacting the other element or intervening elements may be present. In contrast, when an element is referred to as being "directly on," "directly connected to," "directly coupled to" or "directly contacting" another element, there are no intervening elements present. Similarly, when a first component is said to be "in electrical contact with" or "electrically coupled to" a second component, there is an electrical path between the first component and the second component that allows current to flow. The electrical path may include capacitors, coupled inductors, and/or other components that allow current to flow even without direct contact between the conductive components.

Embodiments of the present application describe methods, apparatus, and computer storage media for generating a health index for a pharmacovigilance system (hereinafter referred to as a pharmacovigilance health index). In the context of this application, a pharmacovigilance is a system established around pharmacovigilance, typically in compliance with certain pharmacovigilance management specifications. The pharmacovigilance typically includes two broad categories of compliance work and pharmacovigilance work. The compliance work is embodied in the integrity, good planning, executable, traceable of the system flow. All conscientious work must be done to call compliance. The drug warning work is mainly based on data, focuses on the safety of the product, and carries out data analysis and risk summary discovery.

When evaluated, the degree of compliance of the pharmacoaching system with the pharmacoaching management guidelines is measured by a health index. The medication alert management specification is a textual specification and lacks a quantifiable operational flow. To this end, according to an embodiment of the present application, an authentication criteria table is formulated for quantifying a health index of a pharmacovigilance. The authentication standard table has a plurality of dimensions, such as personnel information, system information, material information, process information, environment information, and the like. The personnel information may include persons and organizations related to vigilance of medications. For example, the staff information may include modules such as a Pharmacovigilance (PV) responsible, a pharmacovigilance full-time staff, and a pharmacovigilance department. In the context of the present application. One or more rules may also be included under each module. For example, the medication alert leader module may include a scholarly background, a work background, a hiring situation, a docketing situation, and the like. The system information may include modules such as a medication alert database, a MedDRA dictionary, office software, etc. Take the example of a medication alert database module that includes a plurality of rules for case report storage and management, vendor capabilities, database system, security, etc. Profile information may be adverse event reports from various sources including, for example, documentation reports, feedback data, aggregate events, post-market studies, and the like. Likewise, each module may include one or more rules. The process may include modules such as a technical guide method, a regulation and Standard Operation Process (SOP). The environmental information may be corporate culture, social impact, etc., including, for example, training, document management, and risk communication modules.

Each rule in the authentication criteria table may include a data acquisition rule. Each data acquisition rule corresponds to an item of data and has one or more scores. These scores are associated with, e.g., determined by, the corresponding data. The types of data include boolean and singleton types. The boolean type is a judgment of no, and the single selection type is one of a plurality of options.

Table 1 below is an example of the contents of one dimension of an authentication criteria table according to an embodiment of the present application. As shown with reference to table 1, each rule may include a name, an option type, an option, a data acquisition rule, and the like. The data acquisition rules determine the scores of the options. The options come from the previous data entry.

TABLE 1

Table 2 below is an example of the contents of another dimension of the authentication criteria table according to an embodiment of the present application. As shown with reference to table 2, each rule may include a name, an option type, an option, a data acquisition rule, and the like.

TABLE 2

According to the disclosed framework of authentication criteria tables, and the disclosed examples, an authentication criteria table may be formulated. It will be appreciated that many embodiments of the authentication criteria table are possible and are within the scope of the practice of the present application.

FIG. 1 is a block diagram of an apparatus for generating a pharmacovigilance health index in accordance with an embodiment of the present application. Referring to fig. 1, the apparatus 100 may include an interface 101 for receiving a plurality of items of first data associated with a first dimension of a plurality of dimensions. Here, the plurality of dimensions are dimensions in the authentication criteria table 11, as discussed previously. The data in the first dimension here is typically the initial underlying data, such as business information, product information, etc. Such data may be entered by the enterprise or by an administrator of device 100. Moreover, after logging, the data can be maintained for a long time without modification or updating. Data received by the interface 101 may be pushed to the message middleware 105. Message middleware 105 sends the data to stream computation engine 103 for subsequent processing and computation. The message middleware 105 is Kafka, for example. The listening component 102 can acquire a plurality of items of second data associated with a second dimension of the plurality of dimensions at intervals during use of the vigilance system of the vigilance hierarchy. The data in the second dimension here is typically business extension data. In particular, the second data is the collection of data in connection with a specific service during a medication alert. The server 200 of the vigilance medication system is, for example, a master server having a master database 21 and a disk 22, the master database 21 being for storing vigilance medication data. The vigilance data 13 in the master database 21 is modified during use of the vigilance system, at which time a log file 14 is generated and stored on the disk 22. The listening component 102 can listen to the log file 14 and parse the log file 14 to obtain the aforementioned plurality of items of second data. The main database 21 is here, for example, a MySQL database, and the log file 14 is, for example, a binlog file, which is in a regular binary format.

More specifically, the listening component 102 establishes an internal link on behalf of the slave server during use of the vigilance medication system, sends a data request to the master server 200, and has the master server 200 send a log file to the listening component 102. The data request is, for example, a dump request in MySQL. In one embodiment, listening component 102 sends the dump request using a replication protocol. Thus, the master server 200 receives the data request transmitted from the slave server. In response to the data request, primary server 200 continues to actively push incremental log files 14 to listening component 102. In some embodiments, the intervals between pushes may reach a real-time level on the order of milliseconds. Thus, listening component 102 can continue to retrieve log files 14 pushed by primary server 200 using the first link.

For retrieving the data modified by the database 21, it is conventionally possible to implement active message pushing by the service logic. Alternatively, an interceptor is used to push data to be computed to message middleware 105. However, if other business logic is developed later, pushing of a message of the new business logic is forgotten, which may result in incomplete data. In addition, if the data needs to be revised manually to the database due to some logic exception, the message is incomplete. There are also old module modifications that certainly result in incomplete data when not familiar with old logic. In the embodiment of the present application, the interception component 102 is intercepting at the database level, and thus the problem of incomplete messages does not occur.

It should be noted that only the value of the data is saved in the log file 14, the field corresponding to the data is not saved, and the field name is changed continuously in the actual operation, so that the field name acquisition and management become important. To this end, according to an embodiment of the present application, the listening component 102 establishes a second link, sending a database connection request to the master database 21 to obtain a plurality of field names associated with the log file. The database connection request may include a target table name by which the field name may be queried. In one embodiment, the Database connection request may be a jdbc (java Database connectivity) request. Listening component 102 determines the most recent version field name from the plurality of field names obtained. Specifically, if the field name is not stored in the listening component 102, the latest acquired field name is used as the latest version field name; if the field name is stored by the monitoring component 102, the stored field name is directly used as the field name of the latest version; if the master database 21 provides a form of the modification table, the latest version of the field name is requested from the master database 21.

In one embodiment, upon receiving the log file 14, the listening component 102 parses the log file 14 using the latest version field name to obtain the second data. When log file 14 is in a regular binary format as described above, listening component 102 parses incremental log file 14 into human-understandable string data. And the step of parsing includes establishing a mapping of the latest version field name to the corresponding data in the log file 14. The parsing result includes field names and data mapped thereto.

In one embodiment, listening component 102 records the location at which log file 14 was parsed. The position indicates the starting position of the next resolution. In this way, when listening component 102 can parse at a new time, the end position of the previous parsing is used as the start position of the current parsing, and the parsing is continued. The sites comprise a collection of data needed by two positioning modes, namely a file name + bias and a GTID (Global Transaction Identifier). In one embodiment, the High Availability (HA) requirements of different scenarios can be met by integrating the collections into one complete piece of location information.

The location and the plurality of field names are stored as metadata for parsing. In one embodiment, configuration options for multiple storage locations are provided. For example, the storage locations include memory and databases. The database may include various types of databases, such as MySQL, H2DB, and so forth. And saving the metadata to the corresponding saving position according to the selection of the configuration option. For example, for upper layer applications, memory storage is more convenient to use. The use of MySQL saves scenarios appropriate for the need to build a separate library, and the use of H2DB saves scenarios appropriate for saving in file form without relying on permissions.

In one embodiment, listening component 102 pushes the parsed items of second data to message middleware 105. Part of the data can be directly calculated by the stream calculation engine 103 as raw data, and the other part can be shared by multiple parties as message middleware. Here, the plurality of parties may include other parties not described in the present application. In one embodiment, the push may be real-time with delays as low as milliseconds. The stream computation engine 103 may perform analysis, structuring, etc. operations on the second data, which is then stored in the management database 104. In another embodiment, the second data can also be sent to the management database 104 by the listening component 102 if it does not need to be processed.

The flow calculation engine 103 acquires the authentication criteria table 11 and the calculation rule 12 in advance. The authentication criteria table 11 has been described previously. The calculation rule 12 is used to determine the total score of the sum of the individual scores. The stream computation engine 103 retrieves a plurality of items of data associated with a plurality of dimensions. Here, the plurality of items of data include the aforementioned first data and second data. Stream computation engine 103 can retrieve such data from listening component 102 and message middleware 105, as well as from data already stored to management database 104. Next, the flow calculation engine 103 dynamically determines a score associated with each item of data according to a plurality of data acquisition rules in the authentication criteria table 11. For the first data mentioned above, it is stable, so it does not need to be calculated frequently. As for the aforementioned second data, it often changes, so the stream calculation engine 103 needs to perform calculation dynamically. Even more, the stream calculation engine 103 may perform calculations in real time. In one embodiment, the stream computation engine 103 is a Flink computation engine. The Flink calculation engine can keep the intermediate state, so that old data does not need to be counted every time, the efficiency is improved, and resources are saved. Meanwhile, as the Flink calculation engine has an intermediate state, the old data does not need to be calculated.

As previously described, the log file is dynamically generated and retrieved. Accordingly, the second data generated by the log file is also dynamically changed. In one embodiment, the dynamic check items may be predefined in the stream computing engine 103 and tracked to determine some or all of the plurality of second data associated with the dynamic check items. The second data of these associations is that which requires dynamic examination and determination of the score. Further, the score associated with each item of second data is dynamically determined according to data acquisition rules corresponding to some or all of the associated second data. In this way, the stream calculation engine 103 can always generate the associated score according to the latest second data, thereby improving timeliness and accuracy of score calculation and subsequent index calculation.

Finally, the stream calculation engine 103 calculates a medication alert health index based on the score associated with each item of data. Where stream computation engine 103 may use computation rules 12 for the computation.

The dynamic or real-time processing relies on modifying the log files of the database 21, and is decoupled from the completion of business logic, so that the influence on the processing is little no matter the development of new business or the transformation and the processing of old business.

In an embodiment of the present application, the apparatus 100 may further display the health index and the question item at the terminal device. The problem item is the one with a lower pharmacographical alert system score. In one embodiment of the present application, stream calculation engine 103 compares the score of each item of data to a preset threshold. When the score is lower than a preset threshold, the stream calculation engine 103 marks the data corresponding to the score as a question item. Thus, the user may be prompted as to which aspects score lower, thereby making further improvements.

In one embodiment, the stream computation engine 103 alerts or blocks the operation of the business system according to rules.

For example, a bad report entry would select day0, and when saved to the database 21, the listening component 102 would obtain day 0. If a bad report requires 7 days to report, then the flow calculation engine 103 calculates whether the current time and day0 are greater than 7 days, and if so, issues a severe warning: "does not meet the regulatory requirements that severe adverse reactions must be reported within 7 days". The entry personnel must check whether day0 is filled in by mistake.

In another example, only poor reports suspected of drug development need to be reported, while poor reports for control drug development need not be reported, but often are not known or noticed by the user or the operation and maintenance personnel. When they click to save the report in the business system, the flow calculation engine 103 can calculate whether a rule is satisfied, and the report action can be stopped in real time after the rule is found to be violated.

Fig. 2 is a flow chart of a method for generating a pharmacovigilance health index according to an embodiment of the present application. Referring to fig. 2, from another perspective, a method of generating a pharmacovigilance health index of the present application comprises the steps of:

in step 201, an authentication criteria table based on a vigilance management specification of a medication is acquired in advance.

The authentication criteria table 11 is already as described above and is not expanded here.

At step 202, a plurality of items of data associated with a plurality of dimensions are obtained. In particular, a plurality of items of first data associated with a first dimension of a plurality of dimensions is received, and a plurality of items of second data associated with a second dimension of the plurality of dimensions is dynamically received during use of the vigilance system of the vigilance hierarchy.

At step 203, a pharmacovigilance health index is calculated based on the plurality of data.

Specifically, the score associated with each item of data may be determined according to the data acquisition rule corresponding to the data, and the pharmacovigilance health index may be calculated according to the score associated with each item of data.

FIG. 3 is a flow diagram of a method of obtaining items of data associated with a plurality of dimensions according to an embodiment of the present application. Referring to fig. 3, step 202 may further include:

at step 301, receiving a plurality of items of first data associated with a first dimension of a plurality of dimensions;

referring to FIG. 1, a plurality of items of first data associated with a first dimension of a plurality of dimensions are received through an interface 101. Data received by the interface 101 may be pushed to the message middleware 105. Message middleware 105 sends the data to stream computation engine 103 for subsequent processing and computation.

At step 302, a first link is established, and a slave server data request is sent to a master server where the master database is located, so that the master server pushes a log file generated by the master server modifying the medication alert data in the master database.

Referring to FIG. 1, the listening component 102 establishes a first link, sends a slave server data request to the master server 200 for listening, and the master server 200 pushes the log file 14. The log file 14 is generated by the master server 200 modifying the medication alert data 13 in the master database 21.

In step 303, the log file pushed by the main server is obtained by using the first link.

Referring to FIG. 1, listening component 102 uses a first link to retrieve log file 14 pushed by primary server 200.

At step 304, a second link is established, and a database connection request is sent to the master database to obtain a plurality of field names associated with the log file.

Referring to FIG. 1, listening component 102 establishes a second link and sends a database connection request to master database 21 to obtain a plurality of field names associated with log file 14.

In step 305, the latest version field name is determined from the acquired plurality of field names.

At step 205, the log file is parsed using the latest version field name to obtain a plurality of items of second data associated with a second dimension of the plurality of dimensions.

Here, listening component 102 can parse the log file to generate a plurality of items of second data and send to stream computation engine 103 or message middleware 105. When sent to the stream computation engine 103, the stream computation engine 103 performs computations using these data. When sending to message middleware 105, listening component 102 listens for data sent by message middleware 105 and forwards to stream computation engine 103 when data is listened to. The advantage of using messaging middleware 105 is that multiple parties can use these second data.

Further details of the method can be found in the description above and will not be further elaborated upon here.

Flow charts are used herein to illustrate operations performed by systems according to embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed in the exact order in which they are performed. Rather, various steps may be processed in reverse order or simultaneously. Meanwhile, other operations are added to or removed from these processes.

FIG. 4 illustrates an apparatus hardware implementation environment for generating a pharmacovigilance health index according to an embodiment of the present application. Device 300 may include an internal communication bus 401, a Processor (Processor)402, a Read Only Memory (ROM)403, a Random Access Memory (RAM)404, and a communication port 405. When implemented on a personal computer, the apparatus 400 may also include a hard disk 407. An internal communication bus 401 may enable data communication among the components of the apparatus 400. The processor 402 may make the determination and issue the prompt. In some embodiments, processor 402 may be comprised of one or more processors. The communication port 405 may enable data communication of the apparatus 400 with the outside. In some embodiments, the device 400 may send and receive information and data from a network through the communication port 405. The apparatus 400 may also include various forms of program storage units and data storage units such as a hard disk 407, Read Only Memory (ROM)403 and Random Access Memory (RAM)404, capable of storing various data files for computer processing and/or communication, as well as possible program instructions for execution by the processor 402. The processor executes these instructions to implement the main parts of the method. The result processed by the processor is transmitted to the terminal equipment through the communication port and displayed on the user interface.

The above-described method of generating a pharmacovigient health index may be implemented as a computer program stored in the hard disk 407 and executable by the processor 402 to implement the method of generating a pharmacovigint health index of the present application.

Having thus described the basic concept, it will be apparent to those skilled in the art that the foregoing disclosure is by way of example only, and is not intended to limit the present application. Various modifications, improvements and adaptations to the present application may occur to those skilled in the art, although not explicitly described herein. Such modifications, improvements and adaptations are proposed in the present application and thus fall within the spirit and scope of the exemplary embodiments of the present application.

Also, this application uses specific language to describe embodiments of the application. Reference throughout this specification to "one embodiment," "an embodiment," and/or "some embodiments" means that a particular feature, structure, or characteristic described in connection with at least one embodiment of the present application is included in at least one embodiment of the present application. Therefore, it is emphasized and should be appreciated that two or more references to "an embodiment" or "one embodiment" or "an alternative embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, some features, structures, or characteristics of one or more embodiments of the present application may be combined as appropriate.

Those of skill would further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.

Aspects of the present application may be embodied entirely in hardware, entirely in software (including firmware, resident software, micro-code, etc.) or in a combination of hardware and software. The above hardware or software may be referred to as "data block," module, "" engine, "" unit, "" component, "or" system. The processor may be one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), digital signal processing devices (DAPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, or a combination thereof. Furthermore, aspects of the present application may be represented as a computer product, including computer stored program code, located in one or more computer storage media. For example, computer storage media may include, but are not limited to, magnetic storage devices (e.g., hard disk, floppy disk, magnetic tape … …), optical disks (e.g., Compact Disk (CD), Digital Versatile Disk (DVD) … …), smart cards, and flash memory devices (e.g., card, stick, key drive … …).

The computer storage medium may comprise a propagated data signal with the computer program code embodied therewith, for example, on baseband or as part of a carrier wave. The propagated signal may take any of a variety of forms, including electromagnetic, optical, and the like, or any suitable combination. A computer storage medium may be any computer storage medium that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code located on a computer storage medium may be propagated over any suitable medium, including radio, electrical cable, fiber optic cable, radio frequency signals, or the like, or any combination of the preceding.

Similarly, it should be noted that in the preceding description of embodiments of the application, various features are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure aiding in the understanding of one or more of the embodiments. This method of disclosure, however, is not intended to require more features than are expressly recited in the claims. Indeed, the embodiments may be characterized as having less than all of the features of a single embodiment disclosed above.

Numerals describing the number of components, attributes, etc. are used in some embodiments, it being understood that such numerals used in the description of the embodiments are modified in some instances by the use of the modifier "about", "approximately" or "substantially". Unless otherwise indicated, "about", "approximately" or "substantially" indicates that the number allows a variation of ± 20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximations that may vary depending upon the desired properties of the individual embodiments. In some embodiments, the numerical parameter should take into account the specified significant digits and employ a general digit preserving approach. Notwithstanding that the numerical ranges and parameters setting forth the broad scope of the range are approximations, in the specific examples, such numerical values are set forth as precisely as possible within the scope of the application.

Although the present application has been described with reference to the present specific embodiments, it will be recognized by those skilled in the art that the foregoing embodiments are merely illustrative of the present application and that various changes and substitutions of equivalents may be made without departing from the spirit of the application, and therefore, it is intended that all changes and modifications to the above-described embodiments that come within the spirit of the application fall within the scope of the claims of the application.

Claims

1. A method of generating a pharmacovigilance health index comprising the steps of:

the method comprises the steps of obtaining an authentication standard table based on a drug alert management standard in advance, wherein the authentication standard table has multiple dimensions;

acquiring a plurality of items of data associated with the plurality of dimensions;

calculating a health index for the pharmacovigilance system using the plurality of pieces of data;

wherein the step of obtaining a plurality of items of data associated with the plurality of dimensions comprises:

receiving a plurality of items of first data associated with a first dimension of the plurality of dimensions;

establishing a first link, and sending a slave server data request to a master server where a master database for storing the drug alert data is located, so as to enable the master server to push a log file, wherein the log file is generated by modifying the drug alert data in the master database through the master server;

acquiring a log file pushed by the main server by using the first link;

establishing a second link, and sending a database connection request to the master database to acquire a plurality of field names associated with the log file;

determining the field name of the latest version according to the acquired field names;

and analyzing the log file by using the latest version field name to obtain a plurality of items of second data associated with a second dimension of the plurality of dimensions.

2. The method of claim 1, wherein each of the dimensions has one or more data acquisition rules, each of the data acquisition rules corresponding to a piece of data and having one or more scores associated with the piece of data, wherein the step of using the plurality of pieces of data to calculate the health index for the pharmacovigilance comprises:

determining a score associated with each item of data according to a data acquisition rule corresponding to the data; and

calculating the health index of the pharmacovigilance based on the score associated with each of the data items.

3. The method of claim 1, wherein after the step of determining a score associated with each item of data, the method further comprises the steps of:

and when the score is lower than a preset threshold value, marking the data corresponding to the score as a question item.

4. The method according to claim 3, wherein after the step of calculating the pharmacoviginal wellness index based on the score associated with each data item, the method further comprises:

and displaying the health index and the question item on the terminal equipment.

5. The method of claim 1, wherein parsing the log file using the latest version field name comprises: and establishing a mapping relation between the field name of the latest version and corresponding data in the log file.

6. The method of claim 1, further comprising recording a location when the log file is parsed, the location indicating a starting location of a next parsing.

7. The method of claim 6, further comprising saving the plurality of field names and the location as metadata.

8. The method of claim 7, further comprising:

providing configuration options of a plurality of storage positions, wherein each storage position comprises a memory and a database; and

and saving the metadata to a corresponding saving position according to the selection of the configuration option.

9. The method of claim 1, wherein after the step of generating a plurality of items of second data associated with a second dimension of the plurality of dimensions, the method further comprises:

pushing the plurality of items of second data to message middleware;

monitoring data sent by the message middleware; and

forwarding the data to a flow computation engine for computing a health index for the pharmaceutical surveillance system.

10. The method of claim 9, wherein determining a score associated with each of the data according to a data acquisition rule corresponding to the data comprises:

tracking, at the stream computation engine, a pre-formulated dynamic examination item and determining at least a portion of the plurality of second data associated with the dynamic examination item; and

and determining the score associated with each item of the at least part of the second data according to a data acquisition rule corresponding to the at least part of the second data.

11. An apparatus for generating a pharmacographically healthy index, comprising:

an interface to receive a plurality of items of first data associated with a first dimension of a plurality of dimensions;

a listening component configured to: establishing a first link, and sending a slave server data request to a master server where a master database for storing the drug alert data is located, so as to enable the master server to push a log file, wherein the log file is generated by modifying the drug alert data in the master database through the master server; acquiring a log file pushed by the main server by using the first link; establishing a second link, and sending a database connection request to the master database to acquire a plurality of field names associated with the log file; determining the field name of the latest version according to the acquired field names; parsing the log file using the latest version field name to obtain a plurality of items of second data associated with a second dimension of the plurality of dimensions;

a stream computation engine configured to:

acquiring an authentication standard table based on a drug alert management specification in advance, wherein the authentication standard table has the plurality of dimensions;

obtaining a plurality of items of data associated with the plurality of dimensions, the plurality of items of data including the first data and second data; and

calculating a health index for the pharmacovigilance system using the plurality of pieces of data.

12. An apparatus for generating a pharmacographically healthy index, comprising:

a memory for storing instructions executable by the processor; and

a processor for executing the instructions to implement the method of any one of claims 1-10.

13. A computer storage medium having computer program code stored thereon, which when executed by a processor implements the method of any of claims 1-10.