CN112466476A - Epidemiology trend analysis method and device based on medicine flow direction data - Google Patents
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- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
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Abstract
The disclosure relates to an epidemiology trend analysis method and device based on medicine flow direction data. The epidemiological trend analysis method based on the medicine flow direction data comprises the following steps: determining an indication marker for the drug product; determining a degree of association of the drug with the indication based on the indication label of the drug; determining a flow profit and loss index of the medicine within a set time based on the medicine flow direction data, and determining an adaptation fluctuation rate based on the flow profit and loss index and the correlation degree; and determining an epidemiological trend based on the relationship of the adaptive variability rate and the set threshold.
Description
Technical Field
The disclosure relates to an epidemiological trend analysis method, in particular to an epidemiological analysis method based on medicine flow direction data.
Background
The existing epidemiological trend analysis method uses the incidence rate as an analysis index, does not combine drug circulation data, and the drug circulation data is internally associated with the epidemiological trend.
Therefore, there is a need to provide an epidemiological trend analysis method based on drug flow direction data.
Disclosure of Invention
In view of the foregoing, exemplary embodiments of the present disclosure are directed to overcoming the above-mentioned and/or other problems in the art.
Thus, according to one aspect of the present disclosure, there is provided a method for epidemiological trend analysis based on drug flow direction data, comprising:
determining an indication marker for the drug product;
determining a degree of association of the drug with the indication based on the indication label of the drug; and the number of the first and second groups,
determining a flow profit and loss index of the medicine within set time based on the medicine flow direction data, and determining an adaptation fluctuation rate based on the flow profit and loss index and the correlation degree; and the number of the first and second groups,
epidemiological trends are determined based on the relationship of the rate of change of the indication to a set threshold.
Optionally, wherein determining the indication label for the drug product comprises:
determining at least one of a historical cure rate for the indication, an adverse reaction rate for the indication, a number of contraindicated varieties for the indication, and a patient compliance index for the indication for the drug.
Optionally, wherein determining the association of the drug with the indication based on the indication label of the drug comprises:
and determining the clustering association degree of the medicine and the indications by using a fuzzy clustering method based on the indications of the medicine.
Optionally, the determining the adaptive fluctuation rate based on the flow profit-loss index and the relevance includes:
and determining the product of the flow profit and loss index and the relevance as the adaptive fluctuation rate.
Optionally, wherein determining the epidemiological trend based on the relationship of the adaptive variability rate to the set threshold comprises:
when the rate of change of the indication indicates an increase and exceeds a first threshold, the indication is associated with an increased epidemiological trend; when the rate of change of the indication indicates a decrease and is less than a second threshold, the indication is associated with a decreased epidemiological trend.
According to another aspect of the present disclosure, there is provided an epidemiological trend analysis device based on drug flow direction data, comprising:
an indication mark determination unit for determining an indication mark of the drug;
a relevance degree determining unit for determining the relevance degree of the medicine and the indication based on the indication mark of the medicine;
the adaptive change rate determining unit is used for determining a flow profit and loss index of the medicine within set time based on the medicine flow direction data and determining the adaptive change rate based on the flow profit and loss index and the correlation degree;
and the epidemiological trend determining unit is used for determining the epidemiological trend based on the relation between the adaptive change rate and the set threshold value.
Optionally, wherein the indication marker determining unit comprises: at least one unit of a historical cure rate determining unit, an adverse reaction rate determining unit, a incompatibility variety quantity determining unit and a compliance index determining unit.
The historical cure rate determining unit is used for determining the historical cure rate of the medicine to the indication;
the adverse reaction rate determining unit is used for determining the adverse reaction rate of the medicine to the indication;
a incompatibility variety quantity determining unit for determining the number of incompatibility varieties of the medicines for the indications;
a compliance index determination unit for determining a patient compliance index of a drug for an indication.
Optionally, the association degree determining unit includes:
and the clustering association degree determining unit is used for determining the clustering association degree of the medicine and the indications by using a fuzzy clustering method based on the indications of the medicine.
Optionally, wherein the indication change rate determination comprises:
and the first indication change rate determining unit is used for determining the product of the flow profit and loss index and the relevance as the indication change rate.
Optionally, wherein the epidemiological trend determination unit comprises:
a first epidemiological tendency determination unit for determining that an epidemiological tendency corresponding to an indication is increasing when a variation rate of the indication increases and exceeds a first threshold; determining the epidemiological trend corresponding to the indication as decreasing when the rate of change of the indication indicates a decrease and is less than a second threshold.
According to another aspect of embodiments herein, there is provided a computing device comprising a memory, a processor and computer instructions stored on the memory and executable on the processor, the processor when executing the instructions implementing the steps of a method for epidemiological trend analysis based on drug flow direction data as described above.
According to another aspect of the embodiments of the present specification, there is provided a computer readable storage medium storing computer instructions, wherein the instructions when executed by a processor implement the steps of a method for epidemiological trend analysis based on drug flow direction data as described above.
According to the exemplary embodiment, the fuzzy clustering method is used for determining the clustering relevance of the medicines and the indications, the fluctuation rate of the indications is determined based on the clustering relevance and the flow profit and loss indexes of the medicine flow direction data in the set time, the epidemiological trend is determined based on the relation between the fluctuation rate of the indications and the set threshold value, and the medicine flow direction data is applied to the determination of the epidemiological trend.
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The above and other objects, features and advantages of the present disclosure will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings. The drawings described below are merely some embodiments of the present disclosure, and other drawings may be derived from those drawings by those of ordinary skill in the art without inventive effort.
FIG. 1 is a block schematic diagram of a computing device according to an embodiment of the present disclosure;
FIG. 2 is a schematic flow chart diagram of a method for epidemiological trend analysis based on drug flow direction data according to an embodiment of the present disclosure;
fig. 3 is a schematic diagram illustrating an epidemiological trend analysis device method based on drug flow direction data according to an embodiment of the present disclosure.
Detailed Description
In the following description of the embodiments of the present disclosure, it is noted that in the interest of brevity and conciseness, not all features of an actual implementation may be described in detail in this specification. It should be appreciated that in the development of any such actual implementation, as in any engineering or design project, numerous implementation-specific decisions are made to achieve the developers' specific goals, such as compliance with system-related and business-related constraints, which may vary from one implementation to another. Moreover, it should be further appreciated that such a development effort might be complex and tedious, but would nevertheless be a routine undertaking of design, fabrication, and manufacture for those of ordinary skill having the benefit of this disclosure, and it will be appreciated that such a development effort might be complex and tedious.
Unless otherwise defined, technical or scientific terms used in the claims and the specification should have the ordinary meaning as understood by those of ordinary skill in the art to which this disclosure belongs. The use of "first," "second," and similar terms in the description and claims of the present disclosure are not intended to indicate any order, quantity, or importance, but rather are used to distinguish one element from another. The terms "a" or "an," and the like, do not denote a limitation of quantity, but rather denote the presence of at least one. The word "comprise" or "comprises", and the like, means that the element or item listed before "comprises" or "comprising" covers the element or item listed after "comprising" or "comprises" and its equivalent, and does not exclude other elements or items. The terms "connected" or "coupled" and the like are not restricted to physical or mechanical connections, nor are they restricted to direct or indirect connections.
FIG. 1 shows a block diagram of a computing device 100, according to an embodiment of the present description. The components of the computing device 100 include, but are not limited to, memory 110 and processor 120. The processor 120 is coupled to the memory 110 via a bus 130 and a database 150 is used to store data.
Computing device 100 also includes access device 140, access device 140 enabling computing device 100 to communicate via one or more networks 160. Examples of such networks include the Public Switched Telephone Network (PSTN), a Local Area Network (LAN), a Wide Area Network (WAN), a Personal Area Network (PAN), or a combination of communication networks such as the internet. Access device 140 may include one or more of any type of network interface (e.g., a Network Interface Card (NIC)) whether wired or wireless, such as an IEEE802.11 Wireless Local Area Network (WLAN) wireless interface, a worldwide interoperability for microwave access (Wi-MAX) interface, an ethernet interface, a Universal Serial Bus (USB) interface, a cellular network interface, a bluetooth interface, a Near Field Communication (NFC) interface, and so forth.
In one embodiment of the present description, the above-described components of computing device 100 and other components not shown in FIG. 1 may also be connected to each other, such as by a bus. It should be understood that the block diagram of the computing device architecture shown in FIG. 1 is for purposes of example only and is not limiting as to the scope of the description. Those skilled in the art may add or replace other components as desired.
Computing device 100 may be any type of stationary or mobile computing device, including a mobile computer or mobile computing device (e.g., tablet, personal digital assistant, laptop, notebook, netbook, etc.), a mobile phone (e.g., smartphone), a wearable computing device (e.g., smartwatch, smartglasses, etc.), or other type of mobile device, or a stationary computing device such as a desktop computer or PC. Computing device 100 may also be a mobile or stationary server.
Wherein the processor 120 may perform the steps of the method shown in fig. 2.
Fig. 2 is a schematic flow chart diagram illustrating a method for epidemiological trend analysis based on drug flow direction data according to an embodiment of the present application, comprising steps 201 to 204.
In order to make the objects, technical solutions and advantages of the present invention more apparent, embodiments of the present invention will be described in detail with reference to the accompanying drawings.
Step 201: an indication marker for the drug product is determined.
In an embodiment of the application, determining an indication label for a drug product comprises: determining at least one of a historical cure rate for the indication, an adverse reaction rate for the indication, a number of contraindicated varieties for the indication, and a patient compliance index for the indication for the drug. The parameters of the historical cure rate, the adverse reaction rate, the number of incompatibility varieties, the patient compliance index and the like for the indication mark are derived from a medicine circulation data platform, and the platform of the platform medicine circulation data comprises corresponding parameters of the traditional medicines. And according to the medicine dictionary in the platform, performing indication marking on the medicines in the medicine dictionary one by one, so that the relation between each kind of medicine and one or more indications can be established.
Step 202: the association of the drug with the indication is determined based on the indication label of the drug.
In the embodiment of the application, based on the indication mark of the medicine, the clustering relevance of the medicine and the indication is determined by using a fuzzy clustering method. For example, based on the historical cure rate of the drugs for the indications in the indication marks of the drugs, drug varieties are used as clustering objects, the indications are used as clusters, fuzzy C-means clustering is realized by python, a membership matrix of the drug varieties and the indications is determined, and the numerical value in the membership matrix represents the clustering relevance of the drug varieties and the indications.
Step 203: and determining a flow profit and loss index of the medicine within the set time based on the medicine flow direction data, and determining an adaptation fluctuation rate based on the flow profit and loss index and the correlation degree.
In the embodiment of the application, the flow profit and loss index of the medical terminal in the set time for each drug variety can be obtained from the drug circulation data platform. The flow profit and loss index represents the percentage of the increase or decrease of the circulation of each drug variety, and for example, a quantitative index x [ ] [ ] giving the flow profit and loss of each drug variety at each medical terminal. (i.e., the percentage of rise or fall). And, the statistical granularity of the medical terminal is at least one of province, city and district, so the statistical granularity corresponding to the quantization index can be at least one of province, city and district. Therefore, the change condition of each drug variety can be counted according to different statistical granularities, and the change trend of the profit and loss of the drug variety flow can be determined by adopting a statistical method, such as a linear regression method, according to the historical change condition. Moreover, the statistical granularity of the variation trend may be at least one of province, city and district. Of course, the variety with a larger index may be determined according to the relationship between the flow profit-loss index of the drug variety and the set threshold, and the statistical granularity may be at least one of province, city and district. In the embodiment of the application, the product of the flow profit and loss index and the cluster relevance can be determined as the fluctuation rate of the indication.
According to the mapping relation between each variety and the indication and the clustering relevance degree g [ ], the result of the quantization index x [ ] [ ] is used for analyzing that each variety is in each hospital terminal, the periodic fluctuation rate b [ ] [ ] ═ F (x [ ], g [ ]) of each indication is obtained, wherein the function F () is an algorithm for calculating the periodic fluctuation rate b [ ] from x [ ], g [ ], and the algorithm can be automatically or manually configured by a system. In this way, when the flow profit-loss index of the drug with a high degree of association with the indication cluster is increased, the acquired indication fluctuation rate is also increased. When the indication corresponds to the epidemiological attribute and the change rate of the indication is large, the change of the morbidity of the corresponding epidemiological attribute is large, and then the epidemiological trend is determined. Thus, epidemiological trends were determined based on drug distribution data. Specifically, all varieties with the quantitative indicators x > ul and x < dl of medical terminal flow profit and loss in the task cycle are extracted for the thresholds pul (positive value for variety flow upward change threshold) and pdl (negative value for variety flow downward change threshold). Therefore, the trend of the flow direction change of some varieties with large change rate at hospital terminal granularity or provincial, municipal and district granularity is given. The flow profit-loss index statistical granularity can be at least one of province, city and district, so that the determined epidemiology trend statistical granularity is also at least one of province, city and district, and thus, the regional distribution characteristics of the epidemiology are determined. Of course, other functional relationships may be constructed based on the flow profit-loss index and the relevance to obtain the adaptive fluctuation rate.
Step 204: epidemiological trends are determined based on the relationship of the rate of change of the indication to a set threshold.
In the embodiment of the application, when the variation rate of the indication increases and exceeds a first threshold value, the epidemiological trend corresponding to the indication increases, and the first threshold value is a positive value and can be set according to the past statistical data; when the variation rate of the indication is reduced and is smaller than a second threshold value, the epidemiological trend corresponding to the indication is reduced, and the second threshold value is a negative value and can be set according to the previous statistical data. Specifically, all indications of the individual indication cycle fluctuation rates b > sul and b < sdl in the task cycle are extracted for the thresholds sul (positive indication cycle fluctuation rate upward threshold) and sdl (negative indication cycle fluctuation rate downward threshold). And further selecting elements with epidemiological labels from the group of indication sets, thereby making prediction and early warning of epidemiological trends and changes of province, city and district granularity. Thus, epidemiological trends were determined based on the rate of change of the indication.
Corresponding to the above method embodiment, the present specification also provides an embodiment of an epidemiological trend analysis device based on drug flow direction data, and fig. 3 shows a schematic structural diagram of an epidemiological trend analysis device 300 based on drug flow direction data according to an embodiment of the present specification. As shown in fig. 3, the apparatus includes:
an indication label determination unit 301 for determining an indication label of the drug;
a relevance determination unit 302 for determining relevance of the drug to the indication based on the indication label of the drug;
an indication change rate determining unit 303, configured to determine a flow profit and loss index of the drug within a set time based on the drug flow direction data, and determine an indication change rate based on the flow profit and loss index and the association degree;
an epidemiological trend determination unit 304 for determining an epidemiological trend based on the relationship of the adaptive variability rate and the set threshold.
Optionally, wherein the indication flag determining unit 301 comprises: at least one unit of a historical cure rate determining unit, an adverse reaction rate determining unit, a incompatibility variety quantity determining unit and a compliance index determining unit.
The historical cure rate determining unit is used for determining the historical cure rate of the medicine for the indication;
an adverse reaction rate determination unit for determining an adverse reaction rate for the indication;
a incompatibility variety quantity determining unit for determining the number of incompatibility varieties for the indications;
a compliance index determination unit for determining and complying with the compliance index for the patient for the indication.
Optionally, the association degree determining unit 302 includes:
and the clustering association degree determining unit is used for determining the clustering association degree of the medicine and the indications by using a fuzzy clustering method based on the indications of the medicine.
Optionally, wherein the indication change rate determination 303 comprises:
and the first indication fluctuation rate determining unit is used for determining the product of the flow profit and loss index and the relevance as the fluctuation rate of the indication.
Optionally, wherein the epidemiological trend determination unit 304 comprises:
a first epidemiological tendency determination unit for determining that an epidemiological tendency corresponding to an indication is increasing when a variation rate of the indication increases and exceeds a first threshold; determining the epidemiological trend corresponding to the indication as decreasing when the rate of change of the indication indicates a decrease and is less than a second threshold.
The method disclosed by the invention brings each variety into a cluster of each indication through fuzzy clustering, and obtains the clustering association degree g [ ]. Analyzing the periodic variation rate b [ ] [, F (x [ ] [ ], g [ ]) ] of each indication in each hospital terminal according to the mapping relation of each variety and the indication and the clustering relevance degree g [ ] of each indication, and analyzing the characteristics and the trend of the change of the medicine flow direction area according to the basic data of the medicine flow direction data on an IT platform with the medicine flow direction basic data; further, the distribution and the variation trend of regional epidemiology are analyzed according to the corresponding indications of the medicines, and positive effects on regional sanitation and disease prevention can be achieved. And also
An embodiment of the present application also provides a computer readable storage medium storing computer instructions that, when executed by a processor, implement the steps of the method for epidemiological trend analysis based on drug flux data as described above.
The above is an illustrative scheme of a computer-readable storage medium of the present embodiment. It should be noted that the technical solution of the storage medium is the same as that of the above-mentioned method for analyzing epidemiological tendency based on drug flow direction data, and details of the technical solution of the storage medium, which are not described in detail, can be referred to the above-mentioned description of the method for analyzing epidemiological tendency based on drug flow direction data.
The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
The computer instructions comprise computer program code which may be in the form of source code, object code, an executable file or some intermediate form, or the like. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, etc. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
In summary, according to the exemplary embodiment, a fuzzy clustering method is used to determine a cluster relevance of a drug and an indication, an indication fluctuation rate is determined based on the cluster relevance and a flow profit and loss index of drug flow direction data in a set time, an epidemiological trend is determined based on a relation between the indication fluctuation rate and a set threshold, and the drug flow direction data is applied to determine the epidemiological trend.
It is noted that in the apparatus and methods of the present disclosure, it is apparent that individual components or steps may be disassembled and/or recombined. These decompositions and/or recombinations are to be considered equivalents of the present disclosure. Also, the steps of executing the series of processes described above may naturally be executed chronologically in the order described, but need not necessarily be executed chronologically. Some steps may be performed in parallel or independently of each other.
The above detailed description should not be construed as limiting the scope of the disclosure. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions can occur, depending on design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.
Claims (10)
1. An epidemiological trend analysis method based on drug flow direction data, comprising:
determining an indication marker for the drug product;
determining a degree of association of the drug with the indication based on the indication label of the drug; and the number of the first and second groups,
determining a flow profit and loss index of the medicine within set time based on the medicine flow direction data, and determining an adaptation fluctuation rate based on the flow profit and loss index and the correlation degree; and the number of the first and second groups,
epidemiological trends are determined based on the relationship of the rate of change of the indication to a set threshold.
2. The method for epidemiological trend analysis based on drug flux data of claim 1, wherein determining the indication label of the drug comprises:
determining at least one of a historical cure rate for the indication, an adverse reaction rate for the indication, a number of contraindicated varieties for the indication, and a patient compliance index for the indication for the drug.
3. The epidemiological trend analysis method based on drug flux data of claim 1, wherein determining the degree of association of the drug with the indication based on the indication label of the drug comprises:
and determining the clustering association degree of the medicine and the indications by using a fuzzy clustering method based on the indications of the medicine.
4. The epidemiological trend analysis method based on drug flow direction data of claim 1, wherein determining the adaptive variability rate based on the flow profit and loss indicator and the correlation comprises:
and determining the product of the flow profit and loss index and the relevance as the adaptive fluctuation rate.
5. The method for epidemiological trend analysis based on drug flow direction data of claim 1, wherein determining the epidemiological trend based on the relationship of the adaptive variability rate to the set threshold comprises:
when the rate of change of an indication indicates an increase and exceeds a first threshold, the indication corresponds to an increasing epidemiological trend; when the rate of change of the indication indicates a decrease and is less than a second threshold, the indication is associated with a decreased epidemiological trend.
6. An epidemiology trend analysis device based on medicine flow direction data, comprising:
an indication mark determination unit for determining an indication mark of the drug;
a relevance degree determining unit for determining the relevance degree of the medicine and the indication based on the indication mark of the medicine;
the adaptive change rate determining unit is used for determining a flow profit and loss index of the medicine within set time based on the medicine flow direction data and determining the adaptive change rate based on the flow profit and loss index and the correlation degree;
and the epidemiological trend determining unit is used for determining the epidemiological trend based on the relation between the adaptive change rate and the set threshold value.
7. The epidemiology trend analysis device based on the drug flow direction data according to claim 6, wherein the indication sign determining unit comprises: at least one unit of a historical cure rate determining unit, an adverse reaction rate determining unit, a incompatibility variety quantity determining unit and a compliance index determining unit.
In the above-mentioned manner,
a historical cure rate determination unit for determining a historical cure rate of the drug for the indication;
the adverse reaction rate determining unit is used for determining the adverse reaction rate of the medicine to the indication;
a incompatibility variety quantity determining unit for determining the number of incompatibility varieties of the medicines for the indications;
a compliance index determination unit for determining a patient compliance index of a drug for an indication.
8. An epidemiology trend analysis device based on drug flow direction data according to claim 6, wherein the correlation determination unit comprises:
and the clustering association degree determining unit is used for determining the clustering association degree of the medicine and the indications by using a fuzzy clustering method based on the indications of the medicine.
9. An epidemiological trend analysis device based on drug flow direction data according to claim 6, wherein the indication change rate determination comprises:
and the first indication change rate determining unit is used for determining the product of the flow profit and loss index and the clustering relevance as the indication change rate.
10. An epidemiological trend analysis device based on drug flow direction data according to claim 6, wherein the epidemiological trend determining unit comprises:
a first epidemiological tendency determination unit for determining that an epidemiological tendency corresponding to an indication is increasing when a variation rate of the indication increases and exceeds a first threshold; determining the epidemiological trend corresponding to the indication as decreasing when the rate of change of the indication indicates a decrease and is less than a second threshold.
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