Hospital multidisciplinary consultation intelligent management system based on big data

Abstract

The invention discloses a hospital multidisciplinary consultation intelligent management system based on big data, and relates to the technical field of medical record management. An information acquisition unit is arranged for acquiring medical record information of a target patient and selecting and extracting multi-party equipment information of the target patient; an information sharing unit is arranged to generate dimensional basic information of a target patient in real time according to 16 four-bit binary numbers, and medical record information of the target patient is converted according to the dimensional basic information. The generated dimensional basic information of the target patient is obtained by firstly extracting and screening out system features of the four-bit binary numbers; the corresponding three-dimensional conversion coordinates are constructed according to the number of the system features, and then the associated conversion sequence is obtained based on the three-dimensional conversion coordinates, so that on one hand, the confidentiality and security of the medical record information transmission process are enhanced; and on the other hand, the method gets rid of dependence on the secret key, and the problems of unsafe factors and high maintenance cost possibly occurring when the secret key is used are avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of medical record management, and in particular to a hospital multidisciplinary consultation intelligent management system based on big data.

[0002] In today's digital age, data is growing explosively, and all fields are experiencing a big data revolution. Big data is not only reflected in the huge amount of data, but also in the diversification of data types (such as structured, semi-structured and unstructured data) and the acceleration of data generation and processing speed. In many industries such as medicine, finance, transportation, and industrial manufacturing, these massive data contain rich value and can provide key support for decision-making. For example, in the medical field, by analyzing the medical records, genetic data, and medical imaging data of a large number of patients, potential patterns and trends of diseases can be discovered, which is helpful for early diagnosis and precise treatment of diseases. However, the effective use of these big data faces many technical challenges, including data storage, data processing capabilities, data analysis algorithms, and data security.

[0003] A notable feature of the development of modern science and technology is the cross-integration of multiple disciplines. Different disciplines penetrate and promote each other, resulting in many new research directions and application fields. Taking the medical field as an example, multidisciplinary consultation (MDT) has become the core model for the diagnosis and treatment of complex diseases.

[0004] In the process of multidisciplinary consultation, it is essential to transmit the patient's medical record information to the doctor's equipment in the corresponding hospital. The medical record information covers the patient's basic personal information, detailed medical history, various examination results (such as imaging examinations, laboratory tests, etc.), diagnosis opinions, treatment records and other rich content. This information plays a decisive role in helping doctors fully understand the patient's condition, make accurate diagnoses and formulate reasonable treatment plans.

[0005] In order to ensure the security of medical records during transmission, the existing technology usually adopts key encryption. However, this method is obviously unreliable and there is a risk of the key being cracked. In a complex network environment, hackers and lawless elements constantly try various attack methods. As a conventional encryption method, the key may be stolen or cracked through network attacks, malware, etc. Once the key is cracked, the patient's medical records will be exposed on the network without protection, and the patient's privacy will be seriously violated. It may also lead to medical disputes and legal issues.

[0006] In order to solve the above problems, the present invention proposes a solution. Summary of the invention

[0007] The purpose of the present invention is to provide a hospital multidisciplinary consultation intelligent management system based on big data, in order to solve the problems raised in the above background technology;

[0008] The purpose of the present invention can be achieved through the following technical solutions:

[0009] The hospital multidisciplinary consultation intelligent management system based on big data includes:

[0010] An information collection unit is used to obtain the medical record information of the target patient uploaded by the administrator of the target hospital and display the device sharing information of all doctors in the hospital cooperating with the target hospital to the administrator, and extract and generate the multi-party device information of the target patient from all the displayed device sharing information;

[0011] The information sharing unit is used to first generate the dimensional basic information of the target patient in real time according to the preset real-time generation rules after receiving the medical record information and multi-party device information of the target patient, and then generate the shared processing data of the target patient in combination with the medical record information according to the preset conversion generation rules.

[0012] Furthermore, one piece of device sharing information corresponds to one doctor, and the device sharing information includes the corresponding doctor's name, professional field, and device address;

[0013] The manager selects the device sharing information of all doctors who pre-share the medical record information, extracts the corresponding device addresses, and generates multi-party device information of the target patient based on all the extracted device addresses.

[0014] Furthermore, the instant generation rules of the target patient's dimensional basic information are as follows:

[0015] S11: Mark the four-bit binary numbers of 0 to 15 as A0, A1, ..., A15 in ascending order;

[0016] S12: extracting and screening a number of base features of the four-digit binary number A0 from the four-digit binary number A0 according to a preset extraction and screening rule;

[0017] S13: extracting and screening a number of binary features of the four-digit binary numbers A1, A2, ..., A15 from the four-digit binary numbers A1, A2, ..., A15 in sequence according to S12;

[0018] S14: generating a three-dimensional coordinate of the four-bit binary number A0 according to a plurality of binary features of the four-bit binary number A0 and a preset conversion generation rule;

[0019] S15: Calculate and obtain the three-dimensional coordinates of the four-bit binary numbers A1, A2, ..., A15 in sequence according to S14;

[0020] The dimensional basic information of the target patient is generated according to the three-dimensional coordinates of the four-bit binary numbers A0, A1, ..., A15 generated by the conversion.

[0021] Furthermore, it also includes a multi-party consultation terminal, which includes a plurality of consultation units, one consultation unit corresponds to a device address, and after the corresponding consultation unit receives the transmitted shared processing data of the target patient, it restores the shared processing data of the target patient to obtain the medical record information of the target patient and displays the medical record information.

[0022] Beneficial effects of the present invention:

[0023] (1) The present invention sets an information collection unit for acquiring the medical record information of the target patient and extracting the multi-party device information of the target patient, sets an information sharing unit for instantly generating the dimensional basic information of the target patient according to 16 four-bit binary numbers, converts the medical record information of the target patient according to the dimensional basic information to obtain shared processing data, and transmits the shared processing data. During this process, the dimensional basic information is instantly generated and instantly destroyed after the transmission is completed. This mechanism of instant generation and instant destruction not only avoids the potential security risks caused by the long-term storage of information, but also greatly reduces the risk of illegal acquisition and use of information, further ensuring the security of the medical record information of the target patient;

[0024] (2) The dimensional basic information of the target patient generated by the present invention is to first extract and filter out the base features of the four-bit binary number, and then construct the corresponding three-dimensional conversion coordinates according to the number of base features. Then, based on the three-dimensional conversion coordinates, several groups of conversion arrays obtained by converting the medical record data are processed. Specifically, the decimal numbers of the two adjacent conversion arrays are compared, and then according to the size comparison results and combined with the three-dimensional conversion coordinates, different calculation methods are used to determine the associated horizontal axis, vertical axis and height axis of the two adjacent conversion arrays, and finally obtain the associated conversion sequence. In this way, on the one hand, it is ensured that the medical record information exists in a form that seems conventional but is encrypted in an unconventional way during the transmission process, making it not only difficult to be detected during the transmission process, but also difficult to be cracked, further enhancing the confidentiality and security of the medical record information transmission process; on the other hand, this method gets rid of the dependence on keys, avoids the unsafe factors and high maintenance costs that may arise when using keys, and provides a new and reliable solution for the secure transmission of medical record information. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The present invention will be further described below in conjunction with the accompanying drawings.

[0026] Figure 1 It is a system block diagram of the present invention. DETAILED DESCRIPTION

[0027] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only 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.

[0028] like Figure 1 As shown in the figure, the hospital multidisciplinary consultation intelligent management system based on big data includes a consultation information management and control terminal and a multi-party consultation terminal;

[0029] A consultation information management and control terminal is used to safely manage the relevant information of the target patient, and the consultation information management and control terminal includes an information collection unit and an information sharing unit;

[0030] The information collection unit pre-stores device sharing information of doctors in several hospitals cooperating with the target hospital, one device sharing information corresponds to one doctor, and the device sharing information includes the name of the doctor to whom the device belongs, the professional field, and the device address, wherein the device refers to the electronic device equipped by the corresponding hospital for the doctor to work. In this embodiment, the electronic device equipped by the hospital for the doctor to work is a desktop computer, and one device address refers to the IP address of the corresponding electronic device;

[0031] After the information collection unit obtains the medical record information of the target patient uploaded by the administrator of the target hospital, it reads the device sharing information of all doctors stored therein and displays it to the administrator of the target hospital for review and selection;

[0032] In this embodiment, the administrator selects the doctor with whom the medical record information is pre-shared by clicking on the displayed doctor's name and professional field;

[0033] The administrator of the target hospital selects the device sharing information of all doctors who pre-share the medical record information and extracts the corresponding device addresses, generates the multi-party device information of the target patient according to all the extracted device addresses, and transmits the medical record information of the target patient and the multi-party device information together to the information sharing unit;

[0034] After receiving the transmitted medical record information of the target patient and the multi-party device information, the information sharing unit first generates the dimensional basic information of the target patient in real time according to the preset real-time generation rules. The generation rules are as follows:

[0035] S11: Mark the four-bit binary numbers of 0 to 15 as A0, A1, ..., A15 in ascending order;

[0036] S12: extracting and filtering out several base features of the four-digit binary number A0 from the four-digit binary number A0 according to a preset extraction and filtering rule, wherein the extraction and filtering rule is as follows:

[0037] SS11: Label all characters that make up the four-bit binary number A0 as B0, B1, B2, and B3 in order from left to right;

[0038] SS12: concatenate characters B0 and B1 in the order of B0 and B1 to obtain a combined string C0, concatenate characters B1 and B2 in the order of B1 and B2 to obtain a combined string C1, and concatenate characters B2 and B3 in the order of B2 and B3 to obtain a combined string C2;

[0039] SS13: sequentially add the combination strings C0, C1, and C2 into an empty list to obtain a feature list of the four-bit binary number A0, remove duplicates from the feature list, and sequentially extract several combination strings contained in the feature list after removal of duplicates from left to right, and recalibrate all the extracted combination strings as base features of the four-bit binary number A0;

[0040] S13: extracting and screening a number of binary features of the four-digit binary numbers A1, A2, ..., A15 from the four-digit binary numbers A1, A2, ..., A15 in sequence according to S12;

[0041] S14: Generate the three-dimensional coordinates of the four-bit binary number A0 according to a preset conversion generation rule based on several base characteristics of the four-bit binary number A0. The conversion generation rule is as follows:

[0042] SS21: Obtain the total number D1 of the base features of the four-bit binary number A0. If D1=1, determine the decimal number E1 of the base features of the four-bit binary number A0. If E1=0, determine that the base horizontal axis, base vertical axis, and base high axis of the four-bit binary number A0 are all 0, expressed as (0,0,0). If E1=1, determine that the base horizontal axis of the four-bit binary number A0 is 0, determine that the base vertical axis and base high axis of the four-bit binary number A0 are both 1, expressed as (0,1,1).

[0043] SS22: If D1=2, the base horizontal axis of the four-bit binary number A0 is determined to be 1, and all base features of the extracted four-bit binary number A0 are marked as E1 and E2 in the order of extraction;

[0044] According to the base characteristics E1 and E2, the base vertical axis and base high axis of the four-bit binary number A0 are determined, which are expressed as (1, F1, F2), where F1 is the decimal number of the base characteristic E1, and F2 is the decimal number of the base characteristic E2;

[0045] SS23: If D1=3, all the base features of the extracted four-bit binary number A0 are marked as E1, E2, and E3 in the order of extraction;

[0046] According to the base features E1, E2, and E3, the base horizontal axis, base vertical axis, and base high axis of the four-digit binary number A0 are determined, which are expressed as (F1, F2, F3), where F1 is the decimal number of the base feature E1, F2 is the decimal number of the base feature E2, and F3 is the decimal number of the base feature E3;

[0047] S15: Calculate and obtain the three-dimensional coordinates of the four-bit binary numbers A1, A2, ..., A15 in sequence according to S14;

[0048] The dimensional basic information of the target patient is generated according to the three-dimensional coordinates of the four-bit binary numbers A0, A1, ..., A15 generated by the conversion. After the dimensional basic information of the target patient is generated, the information sharing unit converts and generates the shared processing data of the target patient according to the preset conversion generation rules. The conversion generation rules are as follows:

[0049] S21: performing binary conversion on the medical record information, and recalibrating the binary data obtained after the conversion into medical record binary data;

[0050] S22: from left to right, taking every four characters in the medical record binary data as a group of conversion arrays to obtain a plurality of groups of conversion arrays, and marking all the groups of conversion arrays as G1, G2, ..., Gg, g≥1 from left to right according to the position of each group of conversion arrays in the medical record binary data;

[0051] S23: Traversing the dimensional basic data, obtaining the three-dimensional base coordinates of the four-bit binary number that is consistent with the conversion array G1, and using the three-dimensional base coordinates as the three-dimensional conversion coordinates H1 of the conversion array G1, wherein consistent means that all characters constituting the four-bit binary number and all characters constituting the conversion array are consistent in content and order;

[0052] S24: according to S23, the three-dimensional transformation coordinates H2, H3, ..., Hg of the transformation arrays G2, G3, ..., Gg are obtained in sequence;

[0053] S25: Calculate and obtain the associated conversion sequence of the conversion arrays G1 and G2 according to the preset calculation rules. The calculation rules are as follows:

[0054] SS31: Compare the decimal numbers in the conversion arrays G1 and G2:

[0055] If the decimal number of the conversion array G1 is greater than or equal to the decimal number of the conversion array G2, the associated horizontal axis K1 of the conversion arrays G1 and G2 is calculated using the formula K1=I1×J1, the associated vertical axis K2 of the conversion arrays G1 and G2 is calculated using the formula K2=I2×J2, and the associated vertical axis K3 of the conversion arrays G1 and G2 is calculated using the formula K3=I3×J3;

[0056] If the decimal number of the conversion array G1 is less than the decimal number of the conversion array G2, the associated horizontal axis K1 of the conversion arrays G1 and G2 is calculated using the formula K1=I2×J3-I3×J2, the associated vertical axis K2 of the conversion arrays G1 and G2 is calculated using the formula K2=I3×J1-I 1×J3, and the associated vertical axis K3 of the conversion arrays G1 and G2 is calculated using the formula K3=I 1×J2-I2×J1, wherein the three-dimensional conversion coordinates of the conversion array G1 are expressed as (I 1, I2, I3), and the three-dimensional conversion coordinates of the conversion array G2 are expressed as (J1, J2, J3);

[0057] SS32: in the order of the associated horizontal axis, the associated vertical axis, and the associated high axis, the associated horizontal axis K1, the associated vertical axis K2, and the associated high axis K3 of the conversion arrays G1 and G2 are concatenated to obtain a three-dimensional conversion array of the conversion arrays G1 and G2, and the three-dimensional conversion array is binary converted to obtain an associated conversion sequence of the conversion arrays G1 and G2;

[0058] S26: according to S25, the associated conversion sequences of the conversion arrays G2 and G3, G3 and G4, ..., Gg-1 and Gg are calculated in sequence, all the associated conversion sequences are spliced ​​in the calculated order to obtain the shared processing data of the target patient, and the shared processing data is transmitted to the multi-party consultation terminal;

[0059] The multi-party consultation terminal is used for doctors in the hospital to receive and view the medical record information of the target patient. The multi-party consultation terminal includes a plurality of consultation units. One consultation unit corresponds to one device address. After receiving the transmitted shared processing data of the target patient, the corresponding consultation unit restores the shared processing data of the target patient to obtain the medical record information of the target patient and displays the medical record information.

[0060] It should be noted here that, in transmitting the shared processing data of the target patient, the shared processing data of the target patient can be accurately transmitted to the corresponding consultation unit according to the multi-party device information of the target patient;

[0061] After the multi-party consultation terminal receives the transmitted shared processing data of the target patient, the information sharing unit destroys the generated dimensional basic information of the target patient;

[0062] In the description of the specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0063] The above contents are merely examples and explanations of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the invention or exceed the scope defined by the claims, they shall all fall within the protection scope of the present invention.

[0064] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. The intelligent management system for multidisciplinary consultation in hospitals based on big data is characterized by: include: An information collection unit is used to obtain the medical record information of the target patient uploaded by the administrator of the target hospital and display the device sharing information of all doctors in the hospital cooperating with the target hospital to the administrator, and extract and generate the multi-party device information of the target patient from all the displayed device sharing information; The information sharing unit is used to first generate the dimensional basic information of the target patient in real time according to the preset real-time generation rules after receiving the medical record information and multi-party device information of the target patient, and then generate the shared processing data of the target patient in combination with the medical record information according to the preset conversion generation rules.

2. The big data-based hospital multidisciplinary consultation intelligent management system according to claim 1 is characterized in that: Each piece of device sharing information corresponds to one doctor, and the device sharing information includes the name of the corresponding doctor, professional field, and device address; The manager selects the device sharing information of all doctors who pre-share the medical record information, extracts the corresponding device addresses, and generates multi-party device information of the target patient based on all the extracted device addresses.

3. The hospital multidisciplinary consultation intelligent management system based on big data according to claim 1 is characterized in that: The instant generation rules of the target patient's dimensional basic information are as follows: S11: Mark the four-bit binary numbers of 0 to 15 as A0, A1, ..., A15 in ascending order; S12: extracting and screening a number of base features of the four-digit binary number A0 from the four-digit binary number A0 according to a preset extraction and screening rule; S13: extracting and screening a number of binary features of the four-digit binary numbers A1, A2, ..., A15 from the four-digit binary numbers A1, A2, ..., A15 in sequence according to S12; S14: generating a three-dimensional coordinate of the four-bit binary number A0 according to a plurality of binary features of the four-bit binary number A0 and a preset conversion generation rule; S15: Calculate and obtain the three-dimensional coordinates of the four-bit binary numbers A1, A2, ..., A15 in sequence according to S14; The dimensional basic information of the target patient is generated according to the three-dimensional coordinates of the four-bit binary numbers A0, A1, ..., A15 generated by the conversion.

4. The big data-based hospital multidisciplinary consultation intelligent management system according to claim 3 is characterized in that: S12, the extraction and screening rules for screening out several base features of the four-bit binary number A0 are as follows: SS11: Label all characters that make up the four-bit binary number A0 as B0, B1, B2, and B3 in order from left to right; SS12: concatenate characters B0 and B1 in the order of B0 and B1 to obtain a combined string C0, concatenate characters B1 and B2 in the order of B1 and B2 to obtain a combined string C1, and concatenate characters B2 and B3 in the order of B2 and B3 to obtain a combined string C2; SS13: Add the combination strings C0, C1, and C2 into an empty list in sequence to obtain a feature list of the four-digit binary number A0, deduplicate the feature list, and extract several combination strings contained in the deduplicated feature list in sequence from left to right, and recalibrate all the extracted combination strings as base features of the four-digit binary number A0.

5. The hospital multidisciplinary consultation intelligent management system based on big data according to claim 3 is characterized in that: S14, the conversion and generation rule of the three-dimensional coordinates of the four-bit binary number A0 is as follows: SS21: Obtain the total number D1 of the base features of the four-bit binary number A0. If D1=1, determine the decimal number E1 of the base features of the four-bit binary number A0. If E1=0, determine that the base horizontal axis, base vertical axis, and base high axis of the four-bit binary number A0 are all 0, expressed as (0,0,0). If E1=1, determine that the base horizontal axis of the four-bit binary number A0 is 0, determine that the base vertical axis and base high axis of the four-bit binary number A0 are both 1, expressed as (0,1,1). SS22: If D1=2, the base horizontal axis of the four-bit binary number A0 is determined to be 1, and all base features of the extracted four-bit binary number A0 are marked as E1 and E2 in the order of extraction; According to the base characteristics E1 and E2, the base vertical axis and base high axis of the four-bit binary number A0 are determined, which are expressed as (1, F1, F2), where F1 is the decimal number of the base characteristic E1, and F2 is the decimal number of the base characteristic E2; SS23: If D1=3, all the base features of the extracted four-bit binary number A0 are marked as E1, E2, and E3 in the order of extraction; According to the base features E1, E2, and E3, the base horizontal axis, base vertical axis, and base high axis of the four-digit binary number A0 are determined, which are expressed as (F1, F2, F3), where F1 is the decimal number of the base feature E1, F2 is the decimal number of the base feature E2, and F3 is the decimal number of the base feature E3.

6. The big data-based hospital multidisciplinary consultation intelligent management system according to claim 3 is characterized in that: The conversion generation rules for generating the shared processing data of the target patient are as follows: S21: performing binary conversion on the medical record information, and recalibrating the binary data obtained after the conversion into medical record binary data; S22: from left to right, taking every four characters in the medical record binary data as a group of conversion arrays to obtain a plurality of groups of conversion arrays, and marking all the groups of conversion arrays as G1, G2, ..., Gg, g≥1 from left to right according to the position of each group of conversion arrays in the medical record binary data; S23: traverse the dimensional basic data to obtain the three-dimensional coordinates of the four-bit binary numbers that are consistent with the conversion array G1, and use the three-dimensional coordinates as the three-dimensional conversion coordinates H1 of the conversion array G1; S24: according to S23, the three-dimensional transformation coordinates H2, H3, ..., Hg of the transformation arrays G2, G3, ..., Gg are obtained in sequence; S25: Calculate and obtain the associated conversion sequence of the conversion arrays G1 and G2 according to a preset calculation rule; S26: According to S25, the associated conversion sequences of the conversion arrays G2 and G3, G3 and G4, ..., Gg-1 and Gg are calculated in sequence, and all the associated conversion sequences are spliced ​​in the calculated order to obtain the shared processing data of the target patient.

7. The big data-based hospital multidisciplinary consultation intelligent management system according to claim 6 is characterized in that: S25, the calculation rule for obtaining the associated conversion sequence of the conversion arrays G1 and G2 is as follows: SS31: Compare the decimal numbers in the conversion arrays G1 and G2: If the decimal number of the conversion array G1 is greater than or equal to the decimal number of the conversion array G2, the formula K1=I1×J1 is used to calculate and obtain the associated horizontal axis K1 of the conversion arrays G1 and G2. Similarly, the associated vertical axis K2 and the associated height axis K3 of the conversion arrays G1 and G2 can be obtained in sequence. If the decimal number of the conversion array G1 is less than the decimal number of the conversion array G2, the associated horizontal axis K1 of the conversion arrays G1 and G2 is calculated using the formula K1=I2×J3-I3×J2, the associated vertical axis K2 of the conversion arrays G1 and G2 is calculated using the formula K2=I3×J1-I 1×J3, and the associated vertical axis K3 of the conversion arrays G1 and G2 is calculated using the formula K3=I 1×J2-I2×J1, wherein the three-dimensional conversion coordinates of the conversion array G1 are expressed as (I1, I2, I3), and the three-dimensional conversion coordinates of the conversion array G2 are expressed as (J1, J2, J3); SS32: In the order of the associated horizontal axis, the associated vertical axis, and the associated high axis, the associated horizontal axis K1, the associated vertical axis K2, and the associated high axis K3 of the transformation arrays G1 and G2 are spliced ​​to obtain a three-dimensional transformation array of the transformation arrays G1 and G2, and the three-dimensional transformation array is binary-converted to obtain an associated transformation sequence of the transformation arrays G1 and G2.

8. The big data-based hospital multidisciplinary consultation intelligent management system according to claim 2 is characterized in that: It also includes a multi-party consultation terminal, which includes a plurality of consultation units. One consultation unit corresponds to a device address. After the corresponding consultation unit receives the transmitted shared processing data of the target patient, it restores the shared processing data of the target patient to obtain the medical record information of the target patient and displays the medical record information.

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