Method and device for processing resident data

Abstract

The invention provides a resident data processing method and device, and the method comprises the steps: obtaining resident data from a plurality of domains, and injecting the resident data into a summary sheet; performing data cleaning on the resident data in the summary sheet; performing matching calculation on the resident data in the summary sheet, and dividing the resident data in the summary sheet into a plurality of groups; performing data integration on the resident data of each group to generate corresponding resident health archives and resident identifiers; wherein different groups correspond to different resident identifiers. By building a unique resident identifier, the medical service efficiency can be improved in the regional medical field, a medical institution can quickly identify patient information through the unique identifier, and resource waste caused by repeated information input is reduced; accurate and coherent medical services can be obtained in the medical treatment process of residents; meanwhile, through the unique identification, resident information interconnection and intercommunication between medical institutions can be promoted, and sharing and integration of medical data are promoted.

Description

Technical Field

[0001] The present invention relates to the field of medical information technology, and in particular to a method and device for processing resident data. Background Art

[0002] As the main recipients of medical services and public health services, residents are the key to connecting medical business data and public health service data. However, in the current regional medical service information construction, these data are scattered in hospital information systems and grassroots public health systems, and cannot display the health record data of residents throughout their life cycle in the jurisdiction. This is an obstacle to improving the level of regional medical and health informationization and regional medical service capabilities. Due to the different responsibilities of medical institutions and public health service institutions, hospital information systems and public health systems have their own patient and resident systems, and the resident identity information between these systems cannot be interoperable, which increases the difficulty of building a fusion scenario of medical and health residents' health records in the region. Summary of the invention

[0003] In view of this, the purpose of the present invention is to provide a method and device for processing resident data, so as to improve the efficiency of medical services in the regional medical field by constructing a unique identification of residents. Through the unique identification, medical institutions can quickly identify patient information and reduce the waste of resources caused by repeated entry of information; it can also ensure that residents can receive accurate and consistent medical services during the medical process; at the same time, through the unique identification, it can promote the interconnection of resident information between medical institutions and promote the sharing and integration of medical data.

[0004] In the first aspect, an embodiment of the present invention provides a method for processing resident data, the method comprising: obtaining resident data from multiple domains, and injecting the resident data into a summary table; performing data cleaning on the resident data in the summary table; performing matching calculations on the resident data in the summary table, and dividing the resident data in the summary table into multiple groups; integrating the resident data of each group to generate corresponding resident health records and resident identifications; wherein different groups have different corresponding resident identifications.

[0005] In an optional embodiment of the present application, the above-mentioned multiple domains include: basic information of residents registered in the hospital, and basic information of residents registered in the public health system; resident data includes at least one of the following: diagnosis and treatment file data, home service data, health examination data, family doctor contract data, self-service equipment file data or institution shared data.

[0006] In an optional embodiment of the present application, the above-mentioned step of data cleaning of the resident data in the summary table includes at least one of the following: deduplication of the resident data in the summary table; data standardization of the resident data in the summary table; missing value processing of the resident data in the summary table; outlier processing of the resident data in the summary table; data consistency verification of the resident data in the summary table.

[0007] In an optional embodiment of the present application, the above-mentioned step of performing matching calculations on the resident data in the summary table includes: performing matching calculations on the resident data in the summary table based on designated fields; wherein the designated fields include at least one of the following: identity information, natural information, address information or biometric information.

[0008] In an optional embodiment of the present application, the resident data of each of the above groups corresponds to the same resident, and the resident data of different groups corresponds to different residents; the step of dividing the resident data in the summary table into multiple groups includes: if the information of the designated field of the first resident data is the same as the information of the designated field of the second resident data, dividing the first resident data and the second resident data into the same group.

[0009] In an optional embodiment of the present application, the above-mentioned step of dividing the resident data in the summary table into multiple groups includes: determining the similarity between the first resident data and the second resident data based on information of multiple specified fields; if the similarity is greater than a preset first threshold, dividing the first resident data and the second resident data into the same group; if the similarity is less than or equal to a preset second threshold, not dividing the first resident data and the second resident data into the same group; wherein the first threshold is greater than the second threshold; if the similarity is less than or equal to the first threshold and the similarity is greater than the second threshold, manually determining whether to divide the first resident data and the second resident data into the same group.

[0010] In an optional embodiment of the present application, the above-mentioned step of integrating the resident data of each group to generate corresponding resident health records and resident identifications includes: generating resident health records based on the resident data of each group; wherein the data of the resident health records are the latest resident data; and generating resident identifications for the resident health records.

[0011] In an optional embodiment of the present application, after the above-mentioned step of integrating the resident data of each group to generate corresponding resident health records and resident identifications, the method also includes: conducting resident business in medical institutions or public health institutions based on the resident identifications.

[0012] In an optional embodiment of the present application, after the above-mentioned step of integrating the resident data of each group to generate corresponding resident health records and resident identifications, the method also includes: obtaining newly added target resident basic information, and determining whether the target resident basic information has a corresponding target resident identification; if the target resident identification exists, updating the resident health record corresponding to the target resident identification based on the target resident basic information; if the target resident identification does not exist, adding a resident health record and resident identification based on the target resident basic information.

[0013] In a second aspect, an embodiment of the present invention also provides a device for processing resident data, the device comprising: a data acquisition module, used to acquire resident data from multiple domains and inject the resident data into a summary table; a data cleaning module, used to clean the resident data in the summary table; a data matching calculation module, used to perform matching calculations on the resident data in the summary table, and divide the resident data in the summary table into multiple groups; a data integration module, used to integrate the resident data of each group to generate corresponding resident health records and resident identifications; wherein different groups have different corresponding resident identifications.

[0014] The embodiments of the present invention bring the following beneficial effects:

[0015] The embodiment of the present invention provides a method and device for processing resident data, which obtains resident data from multiple domains and injects the resident data into a summary table; performs data cleaning on the resident data in the summary table; performs matching calculations on the resident data in the summary table and divides the resident data in the summary table into multiple groups; integrates the resident data of each group to generate corresponding resident health records and resident identification. In this way, by constructing a unique identification for residents, the efficiency of medical services can be improved in the regional medical field. Through the unique identification, medical institutions can quickly identify patient information and reduce the waste of resources caused by repeated entry of information; it can also ensure that residents can receive accurate and coherent medical services during their medical treatment; at the same time, through the unique identification, it can promote the interconnection of resident information between medical institutions and promote the sharing and integration of medical data.

[0016] Other features and advantages of the present disclosure will be set forth in the following description, or some features and advantages may be inferred or unambiguously determined from the description, or may be learned by implementing the above-mentioned technology of the present disclosure.

[0017] In order to make the above-mentioned objectives, features and advantages of the present disclosure more obvious and easy to understand, preferred embodiments are specifically cited below and described in detail with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0019] Figure 1 A flowchart of a method for processing resident data provided by an embodiment of the present invention;

[0020] Figure 2 A flowchart of another method for processing resident data provided by an embodiment of the present invention;

[0021] Figure 3 A schematic diagram of the structure of a resident data processing device provided by an embodiment of the present invention;

[0022] Figure 4 A schematic diagram of the structure of another resident data processing device provided by an embodiment of the present invention;

[0023] Figure 5 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0024] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0025] At present, there are the following problems in the construction of regional medical informationization:

[0026] 1) It is difficult to identify and match the identities of residents in the area. When residents seek medical treatment, their identities may be confused due to forgetting to bring their medical cards or registering multiple times.

[0027] 2) Within the region, data redundancy occurs due to duplicate card creation and incomplete key data.

[0028] 3) Due to the lack of unique identification for residents, it is impossible to effectively link patient information between medical institutions and provide the most comprehensive patient information support, resulting in higher medical costs for residents and lower efficiency of medical services in the region.

[0029] 4) Data integration is difficult. When managing patient information in a region, there may be problems with incomplete data integration, leading to repeated examinations and diagnostic operations.

[0030] Based on this, a method and device for processing resident data provided by an embodiment of the present invention specifically provides a method for generating a unique resident identifier in a health record. It can solve the current problems in regional medical information construction by collecting patient information scattered in various medical business systems and public health business system domains in various hospitals in the region, and building a unique regional resident identifier for residents in the region.

[0031] This embodiment can be based on the current construction needs of regional resident information. By constructing a unique identification for regional residents, the resident information in the region can be uniformly managed to solve the problems of patient identity recognition, data redundancy, and reduced medical service efficiency in medical institutions and public health systems, and provide basic data information support for exploring medical and health integration scenarios in the region.

[0032] To facilitate understanding of this embodiment, a method for processing resident data disclosed in an embodiment of the present invention is first introduced in detail.

[0033] Embodiment 1:

[0034] The embodiment of the present invention provides a method for processing resident data to ensure the consistency, integrity and controllability of resident information in a region. This embodiment can construct a unique identifier for residents in a region to achieve the connection of all diagnosis and treatment business data of residents in the region, assist in the construction of regional medical informationization, and improve the medical experience of residents.

[0035] Among them, this embodiment involves the following concepts:

[0036] Hospital Information System: A system based on computer technology and network communication technology that comprehensively manages the information of people, objects, patients, etc. in various departments within the hospital, providing comprehensive management and services for the overall operation of the hospital.

[0037] Basic public health system: refers to a comprehensive public health service and management system established in communities, villages, streets and other grassroots units, aiming to maintain the health of grassroots residents, prevent the occurrence and spread of diseases, improve the public health level, and promote the construction of healthy communities.

[0038] Health records: records of all vital signs changes and all health-related behaviors and events from birth to death. It is a standardized and scientific record of the process of residents' physical and mental health (including normal health, disease prevention in sub-healthy states, health protection and promotion, and disease treatment, etc.).

[0039] Resident unique identification (also called resident identification or unique identification): is a unique, specific code used to identify and confirm the identity of a resident. It can determine the accuracy and uniqueness of the identity. It is designed and allocated based on certain standards and specifications and has a wide range of applications in medical business scenarios within the region.

[0040] UUID / GUID: A globally unique identifier (UUID) or GUID is a unique identifier generated by an algorithm, usually represented as a string of 32 hexadecimal digits (0-9, AF). The algorithm used to generate the UUID / GUID ensures its uniqueness worldwide.

[0041] Based on the above description, see Figure 1 A flowchart of a method for processing resident data is shown, and the method for processing resident data includes the following steps:

[0042] Step S102, obtaining resident data from multiple domains and injecting the resident data into a summary table.

[0043] In the first step, resident data can be aggregated from multiple domains to inject the resident data into the summary table.

[0044] In some embodiments, the above-mentioned multiple domains include: basic information of residents registered in the hospital, and basic information of residents registered in the public health system; the above-mentioned resident data includes at least one of the following: diagnosis and treatment file data, home service data, health examination data, family doctor contract data, self-service equipment file data or institution shared data.

[0045] This embodiment can aggregate resident data by providing multiple data source channels, and the resident data includes at least one of the following: diagnosis and treatment file data, door-to-door service data, health examination data, family doctor contract data, self-service equipment file data or institution shared data, etc.

[0046] This embodiment can also inject the resident information of all domains into the summary table according to the summary table requirements. All domains include the basic information of residents registered in the hospital and the basic information of residents registered in the public health system.

[0047] Step S104, cleaning the resident data in the summary table.

[0048] The second step is to clean the summary table data, which includes: converting the custom value domain data in different domains into standardized value domain data for subsequent matching calculations.

[0049] In some embodiments, cleaning can be performed by one or more of the following methods: deduplication of resident data in the summary table; standardization of resident data in the summary table; processing of missing values ​​of resident data in the summary table; processing of outliers of resident data in the summary table; and data consistency verification of resident data in the summary table.

[0050] 1. Data deduplication.

[0051] Purpose: To remove duplicate records and avoid confusion during the matching process.

[0052] Specific operation: Deduplication based on unique identifiers: Deduplication is performed using unique identifiers such as ID card number and medical insurance card number.

[0053] Deduplication based on field combination: For data without a unique identifier, multiple fields (such as name, gender, and date of birth) can be combined to deduplicate.

[0054] 2. Data standardization.

[0055] Purpose: To unify data formats and representation methods and improve data consistency.

[0056] Specific operations: Format conversion: convert data in different formats into a unified format, such as date format, phone number format, etc. Spelling correction: correct spelling errors in fields such as resident names. Data normalization: normalize non-standard characters or formats in fields such as addresses and phone numbers.

[0057] 3. Missing value processing.

[0058] Purpose: To handle missing values ​​in the data and avoid inaccuracies caused by missing information during the matching process.

[0059] Specific operations: Fill missing values: Use default values, mode, median, average, etc. to fill missing values. Delete missing records: If a record has too many missing values, consider deleting the record.

[0060] 4. Outlier processing.

[0061] Purpose: To identify and process outliers in the data to ensure the rationality of the data.

[0062] Specific operations: Identify outliers: Use statistical methods (such as standard deviation, interquartile range) or business rule-based methods to identify outliers. Handle outliers: Depending on business needs, you can choose to delete outliers, correct outliers, or treat outliers as missing values.

[0063] 5. Data consistency check.

[0064] Purpose: To verify whether the logical relationship between data is consistent, such as whether the ID number and date of birth match.

[0065] Specific operations: Rule verification: Verify data according to business rules, such as whether the ID number conforms to the specified format and verification rules. Logical verification: Verify whether the logical relationship between data is consistent, such as whether the gender field is consistent with the gender information in the ID number.

[0066] Step S106, performing matching calculations on the resident data in the summary table, and dividing the resident data in the summary table into multiple groups.

[0067] The third step is to prepare data through algorithms. After data cleaning is completed, the resident data is matched and calculated through the unique identification algorithm, and based on this, the resident records that are determined to be the same person after calculation are grouped for subsequent unique identification generation.

[0068] Among them, the resident unique identification algorithm is mainly based on the following principles for matching: Uniqueness: Ensure that each resident has only one unique resident identification in the system. Accuracy: Identify different records of the same resident as accurately as possible and prepare to integrate them into the health record data. Completeness: Cover as many resident information fields as possible to ensure the integrity of the file.

[0069] In some embodiments, a matching calculation can be performed on the resident data in the summary table based on designated fields; wherein the designated fields include at least one of the following: identity information, natural information, address information, or biometric information.

[0070] The resident unique identification algorithm usually uses the following specified fields for matching: Identity information: such as ID card number, medical insurance card number, passport number, etc. Natural information: such as name, gender, date of birth, age, etc. Address information: such as home address, contact number, etc. Biometric information: such as fingerprints, facial recognition, etc.

[0071] The resident health record matching algorithm in this embodiment can be divided into two types: complete matching and fuzzy matching.

[0072] In some embodiments, each group of resident data corresponds to the same resident, and different groups of resident data correspond to different residents; if the information of a designated field of the first resident data is the same as the information of a designated field of the second resident data, the first resident data and the second resident data are divided into the same group.

[0073] Complete match: The information in the designated fields of the resident information (such as ID card number, medical insurance card number and other key items) is compared for complete consistency. If the key items are completely consistent, the two records are considered to belong to the same resident and are automatically merged.

[0074] In some embodiments, the similarity between the first resident data and the second resident data can also be determined based on the information of multiple specified fields; if the similarity is greater than a preset first threshold, the first resident data and the second resident data are divided into the same group; if the similarity is less than or equal to a preset second threshold, the first resident data and the second resident data are not divided into the same group; wherein the first threshold is greater than the second threshold; if the similarity is less than or equal to the first threshold and the similarity is greater than the second threshold, whether to divide the first resident data and the second resident data into the same group is manually determined.

[0075] Fuzzy matching: When key items are not completely consistent, a fuzzy matching algorithm is used. Select multiple fields of resident information (such as name, gender, date of birth, etc.) for similarity calculation. Configure the range of similarity intervals to correspond to the three processing flows of automatic merging, manual merging, and non-merging. Fuzzy matching can calculate the similarity between two records based on statistical probability, which is suitable for scenarios with large amounts of duplicate data and low requirements for matching result accuracy.

[0076] Step S108, integrating the resident data of each group to generate corresponding resident health records and resident identifications; wherein different groups have different corresponding resident identifications.

[0077] After grouping the resident data, you can also integrate the data according to the group information of each resident to generate your own resident health file. You can merge multiple data records of residents into one data with the latest and most comprehensive resident data with a unique resident identifier. According to the UUID / GUID, the unique identifier of the resident health file is generated one by one, and all the archive data related to this resident in the domain can be connected in series through the unique resident identifier.

[0078] The embodiment of the present invention provides a method for processing resident data, which obtains resident data from multiple domains and injects the resident data into a summary table; performs data cleaning on the resident data in the summary table; performs matching calculations on the resident data in the summary table, and divides the resident data in the summary table into multiple groups; integrates the resident data of each group to generate corresponding resident health records and resident identification. In this method, by constructing a unique identification for residents, the efficiency of medical services can be improved in the regional medical field. Through the unique identification, medical institutions can quickly identify patient information and reduce the waste of resources caused by repeated entry of information; it can also ensure that residents can receive accurate and coherent medical services during their medical treatment; at the same time, through the unique identification, it can promote the interconnection of resident information between medical institutions and promote the sharing and integration of medical data.

[0079] Embodiment 2:

[0080] This embodiment provides another method for processing resident data. This method is implemented on the basis of the above embodiment, focusing on the application and addition of resident unique identification. Figure 2 A flowchart of another method for processing resident data is shown, the method for processing resident data comprises the following steps:

[0081] Step S202, obtaining resident data from multiple domains and injecting the resident data into a summary table.

[0082] Step S204, cleaning the resident data in the summary table.

[0083] Step S206, performing matching calculations on the resident data in the summary table, and dividing the resident data in the summary table into multiple groups.

[0084] Step S208, integrating the resident data of each group to generate corresponding resident health records and resident identifications; wherein different groups have different corresponding resident identifications.

[0085] Step S210, conducting resident services in medical institutions or public health institutions based on the resident identification.

[0086] Step 5: Application and addition of unique identification for residents. After the resident generates a unique identification, when a medical institution or public health institution has new resident services, even if the resident does not bring a medical card, the personal identity can be determined through information such as the ID number to conduct business.

[0087] In some embodiments, newly added basic information of the target resident can also be obtained to determine whether there is a corresponding target resident identification for the target resident basic information; if there is a target resident identification, the resident health record corresponding to the target resident identification is updated based on the target resident basic information; if there is no target resident identification, a new resident health record and resident identification are added based on the target resident basic information.

[0088] When a unique resident identifier already exists, the basic resident information is directly returned for adding new resident information. After the resident information is added, the latest record is directly added to the resident information in multiple domains in the first step and an index identifier is assigned, and the current resident file data is updated.

[0089] Among them, after obtaining the newly added basic information of the target resident, it is possible to first determine whether the basic information of the target resident has a corresponding target resident identifier.

[0090] If there is no corresponding target resident identification, after the new resident information is added, the index algorithm is used to match the newly added resident information. If the corresponding target resident identification already exists, the resident health record data is updated; if the match fails, a new resident health record is added.

[0091] Therefore, this embodiment can provide resident information services to all medical information systems in the region by constructing a unique resident identifier. When a resident's basic information is required, such as when the resident seeks medical treatment, a query can be made based on the resident's ID information to obtain the most accurate resident information, and medical services can be carried out based on this.

[0092] The above method provided in this embodiment specifically provides:

[0093] 1. Multi-source data collection and cleaning methods can clean the basic information of residents with different standards from different sources and systems into data with unified standards and consistent formats, which is convenient for subsequent matching.

[0094] 2. The method for generating unique identification of residents can calculate the basic information of residents in the group according to the matching algorithm, and generate the most comprehensive and accurate resident information, and provide resident information application services.

[0095] 3. The management method of the unique identification of residents, in addition to providing external resident search services, can also link the resident new services of other systems based on the search results to realize the addition and update of resident health record data.

[0096] 4. Resident health record information management method based on resident unique identification.

[0097] The above method provided in this embodiment has the following advantages:

[0098] 1. The sharing and reuse of resident information data is enhanced. By building a unique resident identifier, it can help different institutions and departments share resident information more conveniently and reduce the isolated situation of resident health diagnosis and treatment data in the region.

[0099] 2. The accuracy of business decisions is improved. The unique identification of residents can be used as a data source for resident information in the region, providing unified resident information data services, which can more accurately analyze resident health information and provide data support for the formulation of more scientific and reasonable regional resident health management policies.

[0100] 3. Improve service quality. Through the unique identification of residents, more comprehensive patient diagnosis and treatment and public health service information can be integrated, which can help doctors provide more accurate diagnosis and treatment plans.

[0101] 4. Improve residents' self-management capabilities. Based on the residents' unique identification, more complete personal diagnosis and treatment data can be provided to residents, helping them better understand their own health status and improve their ability to self-manage their personal health.

[0102] In summary, the above method provided in this embodiment can generate unique identity identifiers for regional residents based on patient diagnosis and treatment data and residents' basic public health service information, which can help the region improve the quality of medical services, optimize the allocation of regional medical resources, and achieve improved regional medical informationization effects.

[0103] Embodiment three:

[0104] Corresponding to the above method embodiment, the present invention provides a device for processing resident data, see Figure 3 A schematic diagram of the structure of a resident data processing device shown in FIG. 1 , wherein the resident data processing device comprises:

[0105] A data acquisition module 31 is used to acquire resident data from multiple domains and inject the resident data into a summary table;

[0106] A data cleaning module 32 is used to clean the resident data in the summary table;

[0107] A data matching calculation module 33 is used to perform matching calculation on the resident data in the summary table and divide the resident data in the summary table into multiple groups;

[0108] The data integration module 34 is used to integrate the resident data of each group to generate corresponding resident health records and resident identifications; wherein different groups have different corresponding resident identifications.

[0109] The embodiment of the present invention provides a resident data processing device, which obtains resident data from multiple domains and injects the resident data into a summary table; performs data cleaning on the resident data in the summary table; performs matching calculations on the resident data in the summary table, and divides the resident data in the summary table into multiple groups; integrates the resident data of each group to generate corresponding resident health records and resident identification. In this way, by constructing a unique identification for residents, the efficiency of medical services can be improved in the regional medical field. Through the unique identification, medical institutions can quickly identify patient information and reduce the waste of resources caused by repeated entry of information; it can also ensure that residents can receive accurate and consistent medical services during their medical treatment; at the same time, through the unique identification, it can promote the interconnection of resident information between medical institutions and promote the sharing and integration of medical data.

[0110] The above-mentioned multiple domains include: basic information of residents registered in hospitals and basic information of residents registered in the public health system; the above-mentioned resident data includes at least one of the following: diagnosis and treatment file data, home service data, health examination data, family doctor contract data, self-service equipment file data or institution shared data.

[0111] The above-mentioned data cleaning module is used for at least one of the following: deduplication of resident data in the summary table; data standardization of resident data in the summary table; missing value processing of resident data in the summary table; outlier processing of resident data in the summary table; data consistency verification of resident data in the summary table.

[0112] The above-mentioned data matching calculation module is used to perform matching calculations on the resident data in the summary table based on designated fields; wherein the designated fields include at least one of the following: identity information, natural information, address information or biometric information.

[0113] The resident data of each of the above groups corresponds to the same resident, and the resident data of different groups corresponds to different residents; the above data matching calculation module is used to divide the first resident data and the second resident data into the same group if the information of the designated field of the first resident data is the same as the information of the designated field of the second resident data.

[0114] The above-mentioned data matching calculation module is used to determine the similarity between the first resident data and the second resident data based on the information of multiple specified fields; if the similarity is greater than a preset first threshold, the first resident data and the second resident data are divided into the same group; if the similarity is less than or equal to a preset second threshold, the first resident data and the second resident data are not divided into the same group; wherein the first threshold is greater than the second threshold; if the similarity is less than or equal to the first threshold and the similarity is greater than the second threshold, whether to divide the first resident data and the second resident data into the same group is manually determined.

[0115] The above-mentioned data integration module is used to generate a resident health record based on the resident data of each group; wherein the data of the resident health record is the latest resident data; and to generate a resident identification for the resident health record.

[0116] See also Figure 4 The structural diagram of another resident data processing device shown in the figure further includes: a resident business development module 35 for developing resident business in medical institutions or public health institutions based on resident identification.

[0117] like Figure 4 As shown, the resident data processing device also includes: a health record update module 36, which is used to obtain the newly added basic information of the target resident and determine whether there is a corresponding target resident identification for the target resident basic information; if there is a target resident identification, the resident health record corresponding to the target resident identification is updated based on the target resident basic information; if there is no target resident identification, a new resident health record and resident identification are added based on the target resident basic information.

[0118] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the resident data processing system described above can refer to the corresponding process in the aforementioned embodiment of the resident data processing method, and will not be repeated here.

[0119] Embodiment 4:

[0120] The embodiment of the present invention also provides an electronic device for executing the above-mentioned resident data processing method; see Figure 5 A structural schematic diagram of an electronic device is shown, which includes a memory 100 and a processor 101, wherein the memory 100 is used to store one or more computer instructions, and the one or more computer instructions are executed by the processor 101 to implement the above-mentioned method for processing resident data.

[0121] Further, Figure 5 The electronic device shown further includes a bus 102 and a communication interface 103 , and the processor 101 , the communication interface 103 and the memory 100 are connected via the bus 102 .

[0122] The memory 100 may include a high-speed random access memory (RAM), and may also include a non-volatile memory, such as at least one disk storage. The communication connection between the system network element and at least one other network element is realized through at least one communication interface 103 (which may be wired or wireless), and the Internet, wide area network, local area network, metropolitan area network, etc. may be used. The bus 102 may be an ISA bus, a PCI bus, or an EISA bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5 Only one bidirectional arrow is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0123] The processor 101 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit or software instructions in the processor 101. The above processor 101 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present invention can be implemented or executed. The general processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in conjunction with the embodiments of the present invention can be directly embodied as a hardware decoding processor for execution, or a combination of hardware and software modules in the decoding processor for execution. The software module may be located in a storage medium mature in the art, such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory 100, and the processor 101 reads the information in the memory 100 and completes the steps of the method of the above embodiment in combination with its hardware.

[0124] An embodiment of the present invention also provides a computer-readable storage medium, which stores computer-executable instructions. When the computer-executable instructions are called and executed by a processor, the computer-executable instructions prompt the processor to implement the above-mentioned method for processing resident data. The specific implementation can be found in the method embodiment, which will not be repeated here.

[0125] The computer program product of the method and apparatus for processing resident data provided in the embodiments of the present invention includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the methods in the previous method embodiments. The specific implementation can be found in the method embodiments, which will not be repeated here.

[0126] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the system and / or device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0127] In addition, in the description of the embodiments of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0128] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0129] In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", and "third" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance.

[0130] Finally, it should be noted that the above-described embodiments are only specific implementations of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The protection scope of the present invention is not limited thereto. Although the present invention is described in detail with reference to the above-mentioned embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-mentioned embodiments within the technical scope disclosed by the present invention, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A method for processing resident data, characterized in that: The method comprises: Obtaining resident data from a plurality of domains and injecting the resident data into a summary table; Performing data cleaning on the resident data in the summary table; Performing matching calculations on the resident data in the summary table, and dividing the resident data in the summary table into a plurality of groups; The resident data of each group are integrated to generate corresponding resident health records and resident identifications; wherein different groups have different corresponding resident identifications.

2. The method according to claim 1, characterized in that The multiple domains include: basic information of residents registered in the hospital, and basic information of residents registered in the public health system; The resident data includes at least one of the following: diagnosis and treatment file data, door-to-door service data, health examination data, family doctor contract data, self-service equipment file data or institution shared data.

3. The method according to claim 1, characterized in that The step of cleaning the resident data in the summary table includes at least one of the following: Deduplication of resident data in the summary table; Standardizing the resident data in the summary table; Process missing values ​​for the resident data in the summary table; Performing outlier processing on the resident data in the summary table; Perform a data consistency check on the resident data in the summary table.

4. The method according to claim 1, characterized in that: The resident data of each group correspond to the same residents, and the resident data of different groups correspond to different residents; The step of performing matching calculation on the resident data in the summary table comprises: A matching calculation is performed on the resident data in the summary table based on a designated field; wherein the designated field includes at least one of the following: identity information, natural information, address information or biometric information.

5. The method according to claim 4, characterized in that The step of dividing the resident data in the summary table into a plurality of groups comprises: If information of a designated field of the first resident data is identical to information of a designated field of the second resident data, the first resident data and the second resident data are classified into the same group.

6. The method according to claim 4, characterized in that The step of dividing the resident data in the summary table into a plurality of groups comprises: Determining similarity between the first resident data and the second resident data based on information in a plurality of designated fields; If the similarity is greater than a preset first threshold, classifying the first resident data and the second resident data into the same group; If the similarity is less than or equal to a preset second threshold, the first resident data and the second resident data are not classified into the same group; wherein the first threshold is greater than the second threshold; If the similarity is less than or equal to the first threshold and the similarity is greater than the second threshold, it is manually determined whether to classify the first resident data and the second resident data into the same group.

7. The method according to claim 1, characterized in that The step of integrating the resident data of each group to generate corresponding resident health records and resident identifications includes: Generate a resident health file based on the resident data of each group; wherein the data of the resident health file is the latest resident data; A resident identification is generated for the resident health record.

8. The method according to any one of claims 1 to 7, characterized in that: After the step of integrating the resident data of each group to generate corresponding resident health records and resident identifications, the method further includes: Conduct resident business in medical institutions or public health institutions based on the resident identification.

9. The method according to any one of claims 1 to 7, characterized in that: After the step of integrating the resident data of each group to generate corresponding resident health records and resident identifications, the method further includes: Obtain the newly added basic information of the target resident, and determine whether the basic information of the target resident has a corresponding target resident identifier; If the target resident identifier exists, updating the resident health record corresponding to the target resident identifier based on the target resident basic information; If the target resident identification does not exist, a new resident health record and resident identification are added based on the target resident basic information.

10. A resident data processing device, characterized in that: The device comprises: A data acquisition module, used to acquire resident data from multiple domains and inject the resident data into a summary table; A data cleaning module, used for cleaning the resident data in the summary table; A data matching calculation module, used for performing matching calculation on the resident data in the summary table, and dividing the resident data in the summary table into multiple groups; The data integration module is used to integrate the resident data of each group to generate corresponding resident health records and resident identifications; wherein different groups have different corresponding resident identifications.

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