CN113010540A

CN113010540A - Information correlation method, device, medium and equipment between heterogeneous systems

Info

Publication number: CN113010540A
Application number: CN201911329270.6A
Authority: CN
Inventors: 吉建岭; 张华明
Original assignee: Yidu Cloud Beijing Technology Co Ltd
Current assignee: Yidu Cloud Beijing Technology Co Ltd
Priority date: 2019-12-20
Filing date: 2019-12-20
Publication date: 2021-06-22

Abstract

The disclosure provides a method and a device for information association between heterogeneous systems, a medium and electronic equipment, and relates to the technical field of data processing. The method comprises the following steps: obtaining screening conditions for matching patient identification, and determining matching keywords according to the screening conditions; performing patient identification association on the first system data and the second system data on the patient identification dimension according to the matched keywords; acquiring first clinic history data of a target patient identifier in a first system, and acquiring second clinic history data of the target patient identifier in a second system; and associating the first medical treatment historical data with the second medical treatment historical data on the medical treatment dimension corresponding to the target patient identifier to obtain medical treatment history data corresponding to the target patient identifier. This technical scheme is favorable to promoting the information analysis efficiency of seeing a doctor, simultaneously, promotes data sharing efficiency between the heterogenous system, and then is favorable to promoting scientific research efficiency.

Description

Information correlation method, device, medium and equipment between heterogeneous systems

Technical Field

The present disclosure relates to the field of data processing technologies, and in particular, to a method and an apparatus for information association between heterogeneous systems, and a computer-readable medium and an electronic device for implementing the method for information association between heterogeneous systems.

Background

With the development of information technology, the types of medical information systems are becoming more abundant. For example, different hospitals may employ different information systems, and the same hospital may employ various subsystems. Information sharing between various information systems/subsystems is also becoming increasingly important from a medical research perspective.

However, the existing medical information systems are distributed more dispersedly, and the recent interconnection and intercommunication performance of the systems is not considered when different medical information systems are involved. And each information system is in an isolated island, and data of each information system of a patient cannot be effectively correlated. Therefore, based on the existing medical information system, the difficulty of data sharing is high and the efficiency is low.

It is to be noted that the information disclosed in the above background section is only for enhancement of understanding of the background of the present disclosure, and thus may include information that does not constitute prior art known to those of ordinary skill in the art.

Disclosure of Invention

An object of the embodiments of the present disclosure is to provide an information association method between heterogeneous systems, an information association apparatus between heterogeneous systems, and a computer readable medium and an electronic device for implementing the method, so as to reduce the difficulty of data sharing between heterogeneous systems at least to a certain extent, thereby improving the efficiency of data sharing between heterogeneous systems.

Additional features and advantages of the disclosure will be set forth in the detailed description which follows, or in part will be obvious from the description, or may be learned by practice of the disclosure.

According to a first aspect of the embodiments of the present disclosure, there is provided a method for information association between heterogeneous systems, the method including:

obtaining screening conditions for matching patient identification, and determining matching keywords according to the screening conditions;

performing patient identification association on the first system data and the second system data on the patient identification dimension according to the matched keywords;

acquiring first clinic history data in the first system according to the identification of the target patient, and acquiring second clinic history data in the second system according to the identification of the target patient;

and associating the first medical history data with the second medical history data on the medical dimension corresponding to the target patient identifier to obtain medical history data corresponding to the target patient identifier.

In an embodiment of the present disclosure, based on the foregoing scheme, obtaining a screening condition for matching patient identifiers, and determining matching keywords according to the screening condition includes:

and under the condition that the screening condition is that the accuracy priority is greater than the recall rate priority, determining that the first matching keyword combination contains at least two of the following information: name, year and month of birth, gender, and identification number.

and under the condition that the screening condition is that the recall rate is greater than the accuracy priority, determining that the second matching key combination is as follows: name, gender and contact, or determining the combination of the third matching keywords as: name, gender, and address information.

In an embodiment of the present disclosure, based on the foregoing scheme, performing patient identification association on the first system data and the second system data in a patient identification dimension according to the matching keyword includes:

for each matching keyword, acquiring a first value corresponding to the matching keyword in the first system data, and acquiring a second value corresponding to the matching keyword in the second system data;

performing data cleansing and data desensitization on the first value, and performing data cleansing and data desensitization on the second value;

and performing data matching on the first value and the second value to unify the patient identification in the first system and the patient identification in the second system.

In an embodiment of the present disclosure, based on the foregoing solution, associating the first medical history data and the second medical history data in a medical dimension corresponding to the target patient identifier includes:

determining first effective treatment information in the first treatment history data and determining second effective treatment information in the second treatment history data;

and determining an association field in the date field to associate the first and second available medical treatment information according to the association field.

In an embodiment of the present disclosure, based on the foregoing scheme, determining the first valid medical treatment information in the first medical treatment history data includes:

under the condition that the first clinic historical data are clinic data, determining first effective clinic information in the first clinic historical data according to clinic appointment status information and clinic number-returning status information;

and determining first effective clinic information in the first clinic history data according to the hospital reservation state information and the hospital returning state information when the first clinic history data is the hospital data.

In an embodiment of the present disclosure, based on the foregoing scheme, obtaining the visit history data corresponding to the target patient identifier includes:

in the first system or the second system, acquiring target clinic historical data according to the target patient identification;

and acquiring a plurality of target date fields in the target clinic history data to obtain clinic history data corresponding to the target patient identifier.

According to a second aspect of the embodiments of the present disclosure, there is provided an apparatus for associating information between heterogeneous systems, the apparatus including: the system comprises a matching keyword determining module, a first correlation module, a clinic history data acquiring module and a second correlation module.

Wherein the matching keyword determination module is configured to: obtaining screening conditions for matching patient identification, and determining matching keywords according to the screening conditions;

the first association module is configured to: performing patient identification association on the first system data and the second system data on the patient identification dimension according to the matched keywords;

the visit history data acquisition module is configured to: acquiring first clinic history data in the first system according to the identification of the target patient, and acquiring second clinic history data in the second system according to the identification of the target patient; and the number of the first and second groups,

the second association module is configured to: and associating the first medical history data with the second medical history data on the medical dimension corresponding to the target patient identifier to obtain medical history data corresponding to the target patient identifier.

According to a third aspect of the embodiments of the present disclosure, there is provided a computer readable medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the method for associating information between heterogeneous systems as described above in any one of the first aspect of the embodiments.

According to a fourth aspect of the embodiments of the present disclosure, there is provided an electronic apparatus including: one or more processors; a storage device, configured to store one or more programs, where when the one or more programs are executed by the one or more processors, the one or more processors implement the method for associating information between heterogeneous systems according to any one of the technical solutions of the first aspect of the embodiments.

The technical scheme provided by the embodiment of the disclosure can have the following beneficial effects:

in some embodiments of the present disclosure, in one aspect, the first system data and the second system data are patient-identification correlated in a patient-identification dimension. Therefore, a user (such as a doctor) can conveniently acquire the visit data of the target patient in a plurality of different information systems, and further comprehensively know the illness state of the target patient. Therefore, the technical scheme is favorable for improving the analysis efficiency of the information of the treatment, and simultaneously, the data sharing efficiency among the heterogeneous systems is improved. On the other hand, on the basis of associating different systems through patient identifiers, first clinic history data is obtained in the first system and second clinic history data is obtained in the second system according to the target patient identifier, and in clinic dimension, the first clinic history data and the second clinic history data are associated to obtain clinic history data corresponding to the target patient identifier. Therefore, the diagnosis data of the whole life cycle of the target patient can be conveniently acquired, and the scientific research efficiency is favorably improved.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure. It is to be understood that the drawings in the following description are merely exemplary of the disclosure, and that other drawings may be derived from those drawings by one of ordinary skill in the art without the exercise of inventive faculty. In the drawings:

FIG. 1 is a schematic diagram of a system architecture for implementing a method and apparatus for information association between heterogeneous systems in an exemplary embodiment of the disclosure;

FIG. 2 shows a flow diagram of a method of information correlation between heterogeneous systems according to an embodiment of the present disclosure;

FIG. 3 shows a flow diagram of a method of association of patient identification dimensions according to an embodiment of the present disclosure;

figure 4 shows a flow diagram of a method of correlating patient visit dimensions, in accordance with an embodiment of the present disclosure;

figure 5 illustrates a flow diagram of a method of determination of target encounter history data according to an embodiment of the present disclosure;

FIG. 6 shows a schematic structural diagram of an information association apparatus between heterogeneous systems according to an embodiment of the present disclosure;

FIG. 7 shows a schematic diagram of a structure of a computer storage medium in an exemplary embodiment of the disclosure; and the number of the first and second groups,

fig. 8 shows a schematic structural diagram of an electronic device in an exemplary embodiment of the present disclosure.

Detailed Description

Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art.

Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the disclosure. One skilled in the relevant art will recognize, however, that the subject matter of the present disclosure can be practiced without one or more of the specific details, or with other methods, components, devices, steps, and so forth. In other instances, well-known methods, devices, implementations, or operations have not been shown or described in detail to avoid obscuring aspects of the disclosure.

The block diagrams shown in the figures are functional entities only and do not necessarily correspond to physically separate entities. I.e. these functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor means and/or microcontroller means.

The flow charts shown in the drawings are merely illustrative and do not necessarily include all of the contents and operations/steps, nor do they necessarily have to be performed in the order described. For example, some operations/steps may be decomposed, and some operations/steps may be combined or partially combined, so that the actual execution sequence may be changed according to the actual situation.

The present exemplary embodiment first provides a system architecture for implementing an information association method between heterogeneous systems, which can be applied to various data processing scenarios. Referring to fig. 1, the system architecture 100 may include

terminal devices

101, 102, 103, a network 104, and a server 105. The network 104 serves as a medium for providing communication links between the

terminal devices

101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.

The user may use the

terminal devices

101, 102, 103 to interact with the server 105 via the network 104 to receive or send request instructions or the like. The

terminal devices

101, 102, 103 may have various communication client applications installed thereon, such as a photo processing application, a shopping application, a web browser application, a search application, an instant messaging tool, a mailbox client, social platform software, and the like.

The

terminal devices

101, 102, 103 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like.

The server 105 may be a server providing various services, for example, the server 105 acquires filtering conditions for matching patient identification input with the

terminal devices

101, 102, 103. The server 105 determines matching keywords based on the screening criteria (for example only). The server 105 associates the first system data and the second system data in a patient identification dimension according to the matching keywords (for example only). The server 105 obtains first medical history data in the first system based on the target patient identification and second medical history data in the second system based on the target patient identification. Finally, the server 105 correlates the first medical history data and the second medical history data in the medical dimension corresponding to the target patient identifier to obtain medical history data corresponding to the target patient identifier.

The most important information system in various information systems of a hospital is the patient information, because a plurality of information systems may be involved in the patient information process, and the data structures of the plurality of information systems are different, the patient information is usually dispersed in the plurality of systems, and the systems are respectively stored, only related to the patient business, and the interconnection and intercommunication of the systems are not considered, so that the complete patient information analysis cannot be obtained. And by combining the patient treatment correlation angle in the heterogeneous system, the data fusion of the heterogeneous system is solved by utilizing various data correlation relations, so that scientific research personnel can analyze the data of the whole life cycle of the patient.

Based on the technical level of history, an information islanding phenomenon occurs in a medical institution, in a big data clinical scientific research use scene, statistics and analysis are carried out based on historical data, and in order to solve the problem of clinical scientific research data use, the technical scheme provides an information association method and device among heterogeneous systems, a computer storage medium and electronic equipment.

The following description will first be made of an information association method between heterogeneous systems:

fig. 2 shows a flow diagram of a method of information correlation between heterogeneous systems according to an embodiment of the present disclosure. The information association method between heterogeneous systems provided by the embodiment overcomes the above problems in the prior art at least to some extent.

Referring to fig. 2, the method for associating information between heterogeneous systems provided in this embodiment includes:

step S210, obtaining screening conditions for matching patient identification, and determining matching keywords according to the screening conditions;

step S220, carrying out patient identification association on the first system data and the second system data on the dimension of patient identification according to the matched keywords;

step S230, acquiring first clinic history data in the first system according to the target patient identification, and acquiring second clinic history data in the second system according to the target patient identification; and the number of the first and second groups,

step S240, associating the first medical history data and the second medical history data in the medical dimension corresponding to the target patient identifier to obtain medical history data corresponding to the target patient identifier.

In the solution provided by the embodiment shown in fig. 2, on the one hand, the first system data and the second system data are correlated in patient identification dimension. Therefore, a user (such as a doctor) can conveniently acquire the visit data of the target patient in a plurality of different information systems, and further comprehensively know the illness state of the target patient. Therefore, the technical scheme is favorable for improving the analysis efficiency of the information of the treatment, and simultaneously, the data sharing efficiency among the heterogeneous systems is improved. On the other hand, on the basis of associating different systems through patient identifiers, first clinic history data is obtained in the first system and second clinic history data is obtained in the second system according to the target patient identifier, and in clinic dimension, the first clinic history data and the second clinic history data are associated to obtain clinic history data corresponding to the target patient identifier. Therefore, the user (such as a scientific research staff) can conveniently acquire the visit data of the target patient in the whole life cycle, and the scientific research efficiency is favorably improved.

The following explains the specific embodiments of the steps of the solution shown in fig. 2:

in step S210, a screening condition for matching the patient identifier is obtained, and a matching keyword is determined according to the screening condition.

In an exemplary embodiment, the screening conditions include recall rate and accuracy rate. Specifically, the priority of recall rate and the priority of accuracy rate are different according to the actual requirements of the association between the heterogeneous systems. Specifically, the method comprises the following steps:

(1) determining that the first matching keyword combination contains at least two of the following information in the case that the screening condition is that the accuracy priority is greater than the recall rate priority: name, year and month of birth, gender, and identification number.

(2) And under the condition that the screening condition is that the recall rate is greater than the accuracy priority, determining that the combination of the second matching key words is as follows: name, gender and contact, or determining the combination of the third matching keywords as: name, gender, and address information.

The above-mentioned matching word combination is used for subsequent data cleansing and other operations on the first system/second system (which will be explained in detail in the following embodiments). In the technical scheme, different matching keyword combinations are determined based on the actual association requirements among different heterogeneous systems, so that abundant choices are provided for associating the heterogeneous systems, and the individual requirements of users can be met.

In step S220, the first system data and the second system data are associated with the patient identifier in the dimension of the patient identifier according to the matching keyword.

In an exemplary embodiment, the first system and the second system are used to represent heterologous systems. The first System and the second System may be any two systems of a Hospital Information System (HIS for short), a radiology Information management System (RIS for short), and a laboratory Information System (LIS for short).

In an exemplary embodiment, fig. 3 shows a flowchart of a method for associating a patient identification dimension according to an embodiment of the present disclosure, which may be specifically implemented as one specific implementation manner of step S220. Referring to fig. 3, for each of the matching keywords, executing the embodiment shown in the figure includes steps S310 to S330.

In step S310, for each matching keyword, a first value corresponding to the matching keyword is obtained in the first system data, and a second value corresponding to the matching keyword is obtained in the second system data.

In this embodiment, the first system is an HIS system, and the second system is an RIS system.

In an exemplary embodiment, the value (denoted as a first value for distinction) corresponding to the above-mentioned first matching keyword combination (name, birth year and month, sex, and identification number) is acquired in the HIS system, and the value (denoted as a second value) corresponding to the above-mentioned first matching keyword combination is acquired in the RIS system. For example, a set of first values obtained in the HIS system includes: zhang three (name), 1991-12-12 (date of birth), male (gender), and (identification number, e.g., identification number). The set of second values obtained in the RIS system includes: san Zhang (name), 1991/12/12 (month of birth), 1 (gender, where gender is indicated by "1" for male and "2" for female in RIS system), and an identification number (e.g., identification number).

In step S320, data cleansing and data desensitization are performed on the first value, and data cleansing and data desensitization are performed on the second value.

In an exemplary embodiment, in different information systems, the expression modes of the same matching keyword are different, and therefore, data cleaning should be performed on the first value and the second value. For example, for a first value/a second value corresponding to a matching keyword "name", cleaning processing of a front space, a rear space and a special character is required; regarding a first value/a second value corresponding to a matching keyword 'year and month of birth', the data needs to be cleaned into a standard date format, and the data with hour, minute and second needs to be deleted; regarding the first value/the second value corresponding to the matching keyword 'gender', the first value/the second value needs to be converted into standard value range content, such as men and women, and the identification number needs to process data which do not meet the requirement of the identification number; in addition, the 15-digit ID card before updating is converted into the format of the ID card after updating according to the first value/second value corresponding to the matching keyword 'identification number (ID card number').

In an exemplary embodiment, the cleansing is followed by desensitization in a standard desensitization manner to enhance data privacy.

In step S330, the first value and the second value are data matched to unify patient identification in the first system and patient identification in the second system.

In an exemplary embodiment, data matching is performed based on the first value after the washing process and the desensitization process and the Dirichlet, so that the patient information table of the RIS system stores the patient unique number of the HIS system, thereby realizing information association of the patient identification dimension between the heterogeneous systems.

Through the technical scheme provided by the embodiment shown in fig. 3, after the information of the patient identification dimension is associated among the heterogeneous systems, a user (e.g., a doctor) can check medical data such as examination and inspection in the patient dimension, that is, the medical data of a target patient in a plurality of different information systems can be conveniently acquired, and the condition of the target patient can be comprehensively known. Therefore, the technical scheme is favorable for improving the analysis efficiency of the information of the treatment, and simultaneously, the data sharing efficiency among the heterogeneous systems is improved.

With continued reference to fig. 2, after the correlation of the patient dimension information is achieved, in step S230, first visit history data is acquired in the first system according to the target patient identification, and second visit history data is acquired in the second system; and, in step S240, associating the first and second encounter history data in the encounter dimension corresponding to the target patient identification.

For example, fig. 4 shows a flowchart of a method for associating the patient visit dimension according to an embodiment of the present disclosure, which can be specifically implemented as one specific implementation manner of step S240. Referring to fig. 4, the embodiment shown in the figure includes step S410 and step S420.

In step S410, first valid encounter information in the first encounter history data is determined, and second valid encounter information in the second encounter history data is determined.

In an exemplary embodiment, the following description is given by taking the determination of the first valid medical treatment information in the first medical treatment history data as an example:

and under the condition that the first clinic historical data is clinic data, determining first effective clinic information in the first clinic historical data according to the clinic appointment status information and the clinic number-returning status information. Illustratively, because the outpatient service appointment information and the outpatient service number information of the patient exist in the outpatient service information table, the data can be distinguished as the real and effective service data through the state information, and therefore the effective service data of the outpatient service information table can be determined.

And under the condition that the first clinic history data is the hospitalization data, determining first effective clinic information in the first clinic history data according to the hospitalization reservation state information and the retirement state information. For example, in the in-hospital information table, there are information of patient's admission and withdrawal in advance, and it can be distinguished by these status information which data can be used as real and effective in-hospital data, so as to determine effective in-hospital data of the in-hospital information table.

In step S420, the first and second valid encounter information acquisition date fields are determined in the first valid encounter information, and an association field is determined in the date field to associate the first and second valid encounter information according to the association field.

In the case where the first encounter history data is clinic data, after valid clinic data for the clinic encounter information table is determined, the date field of the clinic information table needs to be determined as the associated field. For example, the date field in the outpatient clinic visit information that can be associated fields includes: registration time, charging time, number calling time, treatment time and the like.

In the case where the first medical-treatment history data is the hospitalization data, after the effective medical-treatment data of the hospitalization medical-treatment information table is determined, it is necessary to determine which date field of the medical-treatment information table is used as the associated field. For example, the date field in the in-patient visit information that can be associated fields includes: time of admission, time of discharge, time of admission, time of registration, etc.

Further, associating the first and second available encounter information according to the association fields may enable association of the first and second systems in the patient encounter dimension. Specifically, the method comprises the following steps:

the correlation of visit dimensions for outpatient data between heterogeneous systems is as follows: and judging the difference between the inspection date of the inspection system and the clinic visit date, wherein the time of the inspection date is one day before the visit date, or the inspection date is within 60 days after the visit date, and judging the inspection item as one visit within the range. The rule judgment shows that the time of the examination date is the day before the visit date because the historical data of the hospital has certain errors, the date of the system is inaccurate, and the examination date is before the visit date. The examination date is within 60 days after the visit date, the patients are often required to make appointment and queue according to the examination items of the hospital, even the individual examination items are required to wait for more than 1 month, and the examination date is judged to be 60 days according to the appointment.

The correlation of visit dimensions for hospitalization data between heterogeneous systems is as follows: and judging the difference between the check date of the check system and the admission date and the discharge date of the hospital, wherein the check date is one day before the admission date or within 30 days after the discharge date, and judging the check item as one in-hospital visit within the range. The rules state that the date of examination is the day before the date of admission, because the individual examination systems' examination dates are generated from the computer client system, resulting in examination dates before the date of admission. If the examination date is within 30 days after the discharge date, the patient is often reported for one week or more after the discharge of the patient for examination items such as pathology in a hospital, and the examination date is determined to be 30 days.

Therefore, according to the technical scheme, on the basis of information correlation of patient identification dimensions among different source systems, first clinic historical data is obtained in the first system and second clinic historical data is obtained in the second system according to the target patient identification, and in the clinic dimensions, the first clinic historical data and the second clinic historical data are correlated to obtain clinic history data corresponding to the target patient identification. Therefore, the diagnosis data of the whole life cycle of the target patient can be conveniently acquired, and the scientific research efficiency is favorably improved.

With continued reference to fig. 2, based on the establishment of patient encounter dimensional associations between disparate systems, in step S240, encounter history data corresponding to the target patient identification is determined. For example, fig. 5 is a flowchart illustrating a method for determining target visit history data according to an embodiment of the present disclosure, which may be specifically implemented as one specific implementation manner of step S240. Referring to fig. 5, the embodiment shown in this figure comprises:

step S510, in the first system or the second system, obtaining target clinic historical data according to the target patient identification; and step S520, if a plurality of target date fields are obtained from the target clinic history data, obtaining clinic history data corresponding to the target patient identifier.

In an exemplary embodiment, the visit history data of the target patient identification in the heterogeneous system is determined based on the patient identification association between the first system and the second system. Further, at least one date field to be queried is determined based on the incidence relation of the consultation dimension between the two systems. And acquiring data about the date field to be inquired in the first system and the second system, and determining the clinic history data corresponding to the target patient identification. Thereby obtaining the visit life cycle of the target patient. Furthermore, the user (such as a doctor and a scientific research staff) can conveniently check the medical record data of the patient on the time axis of the diagnosis dimension, so that the treatment efficiency of the patient is favorably improved, and the scientific research efficiency is favorably improved.

Those skilled in the art will appreciate that all or part of the steps for implementing the above embodiments are implemented as computer programs executed by a processor, including a Central Processing Unit (CPU) and a Graphics Processing Unit (GPU). When the computer program is executed by a CPU or a GPU, the above-described functions defined by the above-described methods provided by the present disclosure are performed. The program may be stored in a computer readable storage medium, which may be a read-only memory, a magnetic or optical disk, or the like.

Furthermore, it should be noted that the above-mentioned figures are only schematic illustrations of the processes involved in the methods according to exemplary embodiments of the present disclosure, and are not intended to be limiting. It will be readily understood that the processes shown in the above figures are not intended to indicate or limit the chronological order of the processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, e.g., in multiple modules.

The following describes embodiments of the information association apparatus between heterogeneous systems according to the present disclosure, which can be used to perform the information association method between heterogeneous systems according to the above embodiments of the present disclosure.

Fig. 6 is a schematic structural diagram illustrating an information association apparatus between heterogeneous systems according to an embodiment of the present disclosure, and referring to fig. 6, an information association apparatus 600 between heterogeneous systems provided in this embodiment includes: a matching keyword determination module 601, a first association module 602, a visit history data acquisition module 603, and a second association module 604.

The matching keyword determining module 601 is configured to: obtaining screening conditions for matching patient identification, and determining matching keywords according to the screening conditions;

the first association module 602 is configured to: performing patient identification association on the first system data and the second system data on the patient identification dimension according to the matched keywords;

the visit history data acquisition module 603 is configured to: acquiring first clinic history data in the first system according to the identification of the target patient, and acquiring second clinic history data in the second system according to the identification of the target patient; and the number of the first and second groups,

the second associating module 604 is configured to: and associating the first medical history data with the second medical history data on the medical dimension corresponding to the target patient identifier to obtain medical history data corresponding to the target patient identifier.

In an embodiment of the present disclosure, based on the foregoing scheme, the matching keyword determining module 601 is specifically configured to: and under the condition that the screening condition is that the accuracy priority is greater than the recall rate priority, determining that the first matching keyword combination contains at least two of the following information: name, year and month of birth, gender, and identification number.

In an embodiment of the present disclosure, based on the foregoing scheme, the matching keyword determining module 601 is further specifically configured to: and under the condition that the screening condition is that the recall rate is greater than the accuracy priority, determining that the second matching key combination is as follows: name, gender and contact, or determining the combination of the third matching keywords as: name, gender, and address information.

In an embodiment of the present disclosure, based on the foregoing solution, the first associating module 602 is configured to:

performing data cleansing and data desensitization on the first value, and performing data cleansing and data desensitization on the second value; and the number of the first and second groups,

In an embodiment of the present disclosure, based on the foregoing solution, the second associating module 604 includes: a valid information determination unit and an associated field determination unit.

Wherein the valid information determining unit is configured to: determining first effective treatment information in the first treatment history data and determining second effective treatment information in the second treatment history data;

the above-mentioned associated field determination unit is configured to: and determining an association field in the date field to associate the first and second available medical treatment information according to the association field.

In an embodiment of the present disclosure, based on the foregoing scheme, the valid information determining unit is specifically configured to:

In an embodiment of the present disclosure, based on the foregoing scheme, the second associating module 604 further includes: and a clinic history data determining unit.

Wherein the visit history data determination unit is configured to:

in the first system or the second system, acquiring target clinic historical data according to the target patient identification; and the number of the first and second groups,

For details that are not disclosed in the embodiment of the information association apparatus between heterogeneous systems of the present disclosure, please refer to the embodiment of the information association method between heterogeneous systems of the present disclosure for details that are not disclosed in the embodiment of the information association apparatus between heterogeneous systems of the present disclosure.

Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, a mobile terminal, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.

In an exemplary embodiment of the present disclosure, there is also provided a computer storage medium capable of implementing the above method. On which a program product capable of implementing the above-described method of the present specification is stored. In some possible embodiments, various aspects of the present disclosure may also be implemented in the form of a program product including program code for causing a terminal device to perform the steps according to various exemplary embodiments of the present disclosure described in the "exemplary methods" section above of this specification when the program product is run on the terminal device.

Referring to fig. 7, a program product 700 for implementing the above method according to an embodiment of the present disclosure is described, which may employ a portable compact disc read only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present disclosure is not limited thereto, and in this document, a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.

The program product described above may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a Read-Only Memory (ROM), an erasable programmable Read-Only Memory (EPROM or flash Memory), an optical fiber, a portable compact disk Read-Only Memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

A computer readable signal medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable signal medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

Program code embodied on a readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

Program code for carrying out operations for the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of Network, including a Local Area Network (LAN) or Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).

In addition, in an exemplary embodiment of the present disclosure, an electronic device capable of implementing the above method is also provided.

As will be appreciated by one skilled in the art, aspects of the present disclosure may be embodied as a system, method or program product. Accordingly, various aspects of the present disclosure may be embodied in the form of: an entirely hardware embodiment, an entirely software embodiment (including firmware, microcode, etc.) or an embodiment combining hardware and software aspects that may all generally be referred to herein as a "circuit," module "or" system.

An electronic device 800 according to this embodiment of the disclosure is described below with reference to fig. 8. The electronic device 800 shown in fig. 8 is only an example and should not bring any limitations to the functionality and scope of use of the embodiments of the present disclosure.

As shown in fig. 8, electronic device 800 is in the form of a general purpose computing device. The components of the electronic device 800 may include, but are not limited to: the at least one processing unit 810, the at least one memory unit 820, and a bus 830 that couples the various system components including the memory unit 820 and the processing unit 810.

Wherein the storage unit stores program codes, and the program codes can be executed by the processing unit 810, so that the processing unit 810 executes the steps according to various exemplary embodiments of the present disclosure described in the "exemplary method" section above in this specification. For example, the processing unit 810 may perform the following as shown in fig. 2: step S210, obtaining screening conditions for matching patient identification, and determining matching keywords according to the screening conditions; step S220, carrying out patient identification association on the first system data and the second system data on the dimension of patient identification according to the matched keywords; step S230, acquiring first clinic history data in the first system according to the target patient identification, and acquiring second clinic history data in the second system according to the target patient identification; step S240, associating the first medical history data and the second medical history data in the medical dimension corresponding to the target patient identifier to obtain medical history data corresponding to the target patient identifier.

Illustratively, the processing unit 810 may further perform a processing method of the medical variable relationship as shown in any one of fig. 3 to 5.

Storage 820 may include readable media in the form of volatile storage such as: a Random Access Memory (RAM) 8201 and/or a cache Memory 8202, and may further include a Read-Only Memory (ROM) 8203.

The storage unit 820 may also include a program/utility 8204 having a set (at least one) of program modules 8205, such program modules 8205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may comprise an implementation of a network environment.

Bus 830 may be any of several types of bus structures including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

The electronic device 800 may also communicate with one or more external devices 900 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device 800, and/or with any devices (e.g., router, modem, etc.) that enable the electronic device 800 to communicate with one or more other computing devices. Such communication may be through an Input/Output (I/O) interface 850. Further, the I/O interface 850 is connected with the display unit 840 to transmit content to be displayed to the display unit 840 through the I/O interface 850 for viewing by a user.

Also, the electronic device 800 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public Network, such as the internet) via the Network adapter 860. As shown, the network adapter 860 communicates with the other modules of the electronic device 800 via the bus 830. It should be appreciated that although not shown, other hardware and/or software modules may be used in conjunction with the electronic device 800, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.

Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.

Furthermore, the above-described figures are merely schematic illustrations of processes included in methods according to exemplary embodiments of the present disclosure, and are not intended to be limiting. It will be readily understood that the processes shown in the above figures are not intended to indicate or limit the chronological order of the processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, e.g., in multiple modules.

Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.

Claims

1. A method for associating information between heterogeneous systems, the method comprising:

and associating the first medical treatment history data with the second medical treatment history data on the medical treatment dimension corresponding to the target patient identifier to obtain medical treatment history data corresponding to the target patient identifier.

2. The method of claim 1, wherein obtaining a screening criteria for matching patient identification, determining matching keywords from the screening criteria comprises:

determining that the first matching keyword combination contains at least two of the following information in the case that the screening condition is that the accuracy priority is greater than the recall rate priority: name, year and month of birth, gender, and identification number.

3. The method of claim 1, wherein obtaining a screening criteria for matching patient identification, determining matching keywords from the screening criteria comprises:

and under the condition that the screening condition is that the recall rate is greater than the accuracy priority, determining that the combination of the second matching key words is as follows: name, gender and contact, or determining the combination of the third matching keywords as: name, gender, and address information.

4. The method of any one of claims 1 to 3, wherein associating the first system data and the second system data in a patient identification dimension according to the matching keyword comprises:

for each matched keyword, acquiring a first value corresponding to the matched keyword in the first system data, and acquiring a second value corresponding to the matched keyword in the second system data;

data matching the first and second values to unify patient identification in the first system and patient identification in the second system.

5. The method of any one of claims 1 to 3, wherein correlating the first and second visit history data in a visit dimension corresponding to the target patient identification comprises:

determining first effective visit information in the first visit history data and determining second effective visit information in the second visit history data;

and determining an association field in the date field to associate the first and second available encounter information according to the association field.

6. The method of claim 5, wherein determining first valid encounter information in the first encounter history data comprises:

under the condition that the first clinic historical data are clinic data, determining first effective clinic information in the first clinic historical data according to clinic appointment state information and clinic number-returning state information;

and under the condition that the first clinic history data is the hospitalization data, determining first effective clinic information in the first clinic history data according to the hospitalization reservation state information and the retirement state information.

7. The method of any one of claims 1 to 3, wherein obtaining visit history data corresponding to the target patient identification comprises:

acquiring target clinic historical data according to the target patient identification in the first system or the second system;

and acquiring a plurality of target date fields in the target clinic historical data to obtain clinic history data corresponding to the target patient identifier.

8. An apparatus for correlating information between heterogeneous systems, the apparatus comprising:

a matching keyword determination module configured to: obtaining screening conditions for matching patient identification, and determining matching keywords according to the screening conditions;

a first association module configured to: performing patient identification association on the first system data and the second system data on the patient identification dimension according to the matched keywords;

a visit history data acquisition module configured to: acquiring first clinic history data in the first system according to the identification of the target patient, and acquiring second clinic history data in the second system according to the identification of the target patient;

a second association module configured to: and associating the first medical treatment history data with the second medical treatment history data on the medical treatment dimension corresponding to the target patient identifier to obtain medical treatment history data corresponding to the target patient identifier.

9. A computer-readable medium, on which a computer program is stored, which, when being executed by a processor, carries out a method of information correlation between heterogeneous systems according to any one of claims 1 to 7.

10. An electronic device, comprising:

one or more processors;

storage means for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to implement the method of information association between heterogeneous systems according to any of claims 1 to 7.