Dental operation solution support system and method

Abstract

The dental operation solution support system and method according to the embodiment aims to provide a system that provides and supports solutions related to dental operation in general, such as education, qualification guarantee, and operation support related to ultra-thin dental prosthetic treatment. In addition, in an embodiment, the system evaluates the marketability of member hospitals that have joined the system and provides consulting information for operational solutions and optimal management. In addition, in an embodiment, by reflecting the marketability of member hospitals in the evaluation, appropriate customized solutions are provided, and in order to prevent damage to brand value, items such as lease agreements, interior design drawings, on-site inspections, and membership review forms are analyzed, and not only simple operational solutions but also consulting for building an optimal management environment are provided.

Description

[Technical Field]

[0001] The present disclosure relates to a dental operations solution support system and method, and relates to a system for providing and supporting overall solutions for dental operations. [Background technology]

[0002] Unless otherwise stated herein, the material described in this section is not prior art to the claims of this application and is not admitted to be prior art by inclusion in this section.

[0003] To successfully operate a dental clinic after opening, attention must be paid to many aspects, including patient management, medical skill development, and hospital management. Among these, improving the medical skills of dentists is the most important factor in hospital management. However, there is currently no platform that provides specialized training that is closely tied to clinical practice for dentists before and after opening a clinic, and manages dentists based on their course completion and whether or not they have completed each course.

[0004] Furthermore, there is no system that analyzes detailed hospital information to provide accurate consulting information for hospital management and supports various services necessary for hospital management within a network. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Korean Patent Registration No. 10-2572400 [Patent Document 2] Korean Patent Registration No. 10-1587924 Summary of the Invention [Problem to be solved by the invention]

[0006] The dental operation solution support system and method according to the embodiment aims to provide a system that provides and supports solutions related to dental operation in general, such as education, qualification guarantee, and operation support related to ultra-thin dental prosthetic treatment.

[0007] In addition, in an embodiment, the marketability of member hospitals that have joined the system is evaluated, and consulting information for operational solutions and optimal management is provided.

[0008] In addition, in some embodiments, appropriate customized solutions are provided by reflecting the marketability of member hospitals in the evaluation, and in order to prevent damage to brand value, items such as lease agreements, interior design drawings, on-site inspections, and membership review forms are analyzed, and not only simple operational solutions but also consulting services for building an optimal management environment are provided. [Means for solving the problem]

[0009] The dental management solution support system according to the embodiment includes a member terminal provided at each hospital registered as a member, an administrator terminal that provides input and output to the administrator, and a main server that manages the hospitals. The main server includes a collection unit that collects promotion review information for each member, including whether or not the member has completed academy education, the number of treatments, and the number of consents from existing members, a grade calculation unit that calculates the grade of the member based on the collected promotion review information and determines whether or not to promote the member, and a grade assignment unit that assigns and stores the calculated grade to the member.

[0010] In an embodiment, the main server includes a solution provider that provides dental management solutions including educational content, qualification assurance, and management support related to ultra-thin dental prosthetic treatment.

[0011] In an embodiment, the solution providing department analyzes items of hospital documents including lease agreements, interior design drawings, on-site inspections, and membership review forms, and provides consulting information to create an optimal business environment based on the analysis results. [Effects of the Invention]

[0012] The above-described dental management solution support system and method provides efficient management by operating member hospitals by grade, and enhances expertise and generates profits by providing differentiated solutions as members' grades increase.

[0013] In addition, depending on the embodiment, it is possible to provide communities divided by access rights and provide appropriate information based on the position and personality of members, thereby improving operational efficiency and promoting friendship by forming a circle of empathy.

[0014] In addition, in the embodiment, when supporting an operational solution, security is enhanced by setting a disclosure level for each material provided.

[0015] It should be understood that the effects of the present invention are not limited to the above effects, but include all effects that can be inferred from the configuration of the invention described in the detailed description of the present invention or the claims. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a diagram showing the configuration of a dental operation solution support system according to an embodiment. [Figure 2] FIG. 2 is a block diagram of a main server according to the embodiment. [Figure 3] FIG. 2 is a diagram illustrating a configuration of an instruction set stored in a memory according to an embodiment. [Figure 4] FIG. 10 is a diagram showing types and standards of grades according to an embodiment. [Figure 5] FIG. 2 is a diagram showing a system participation application form according to the embodiment. [Figure 6] FIG. 10 is a diagram showing a membership screening form according to the embodiment. [Figure 7] FIG. 10 is a diagram illustrating a data processing process of a main server according to an embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0017] Hereinafter, the embodiments disclosed herein will be described in detail with reference to the accompanying drawings. Regardless of the reference numerals in the drawings, identical or similar components will be designated by the same reference numerals, and redundant descriptions thereof will be omitted. The suffixes "module" and "section" used in the following description are used solely for the convenience of drafting the specification and do not have any distinct meanings or functions. Furthermore, when describing the embodiments disclosed herein, if a detailed description of related publicly known technology is deemed to obscure the gist of the embodiments disclosed herein, such a detailed description will be omitted. Furthermore, the accompanying drawings are intended to facilitate understanding of the embodiments disclosed herein, and should not be construed as limiting the technical ideas disclosed herein, but should be understood to include all modifications, equivalents, and alternatives within the spirit and technical scope of the present invention.

[0018] Terms including ordinal numbers such as first, second, etc. may be used to describe various components, but the components are not limited by the terms. The terms are used only to distinguish one component from another.

[0019] When a component is referred to as being "coupled" or "connected" to another component, it should be understood that the component may be directly coupled or connected to the other component, but that there may also be other components between them. On the other hand, when a component is referred to as being "directly coupled" or "directly connected" to another component, it should be understood that there are no other components between them.

[0020] It is to be understood that in this application, the use of terms such as "comprises" or "having" is intended to specify the presence of features, numbers, steps, operations, components, parts, or combinations thereof described herein, but does not preclude the possible presence or addition of one or more other features, numbers, steps, operations, components, parts, or combinations thereof.

[0021] In this specification, the term "module" includes a unit realized by hardware, a unit realized by software, and a unit realized by using both hardware and software. Furthermore, one unit may be realized by using two or more pieces of hardware, and two or more units may be realized by one piece of hardware.

[0022] In this specification, some of the operations or functions described as being performed by a terminal, apparatus, or device may instead be performed by a server connected to the corresponding terminal, apparatus, or device. Similarly, some of the operations or functions described as being performed by a server may instead be performed by a terminal, apparatus, or device connected to the corresponding server.

[0023] The present invention will now be described in detail with reference to the accompanying drawings.

[0024] FIG. 1 is a diagram showing the configuration of a dental operation solution support system according to an embodiment.

[0025] Referring to FIG. 1, the dental operation solution support system according to the embodiment may be configured to include a member terminal 300, an administrator terminal 200, and a main server 100.

[0026] The member terminal 300 is a terminal of each hospital registered as a member who has subscribed to the dental operation solution support system. In an embodiment, the member terminal 300 may include not only a terminal provided in the hospital, but also terminals of doctors who operate the hospital and hospital personnel. The administrator terminal 200 is a system administrator terminal, and in an embodiment, the administrator can input information, check member information, manage members registered in the system, and manage the system via an interface output to the administrator terminal 200.

[0027] In an embodiment, at least one of the terminals 200 and 300 may be realized as a computer that can connect to a remote server or terminal via a network. Here, the computer may include, for example, a notebook, desktop, or laptop equipped with a navigation system and a web browser. In this case, at least one of the terminals 200 and 300 may be realized as a terminal that can connect to a remote server or terminal via a network. At least one of the terminals 200, 300 may include, for example, any kind of handheld-based wireless communication device, such as a navigation system, a Personal Communication System (PCS), a Global System for Mobile communications (GSM), a Personal Digital Cellular (PDC), a Personal Handyphone System (PHS), a Personal Digital Assistant (PDA), an International Mobile Telecommunication (IMT)-2000, a Code Division Multiple Access (CDMA)-2000, a W-Code Division Multiple Access (W-CDMA), a Wireless Broadband Internet (Wibro) terminal, a smartphone, a smartpad, or a tablet PC, as a wireless communication device that ensures portability and mobility.

[0028] The main server 100 manages members and hospitals that have joined the system. For example, the main server 100 provides and supports a system that offers solutions related to overall dental management, such as education, qualification assurance, and management support for ultra-thin dental prosthetic treatment. The main server 100 also evaluates the marketability of member hospitals that have joined the system and provides management solutions and consulting information for optimal management. In an embodiment, the main server 100 provides appropriate customized solutions by reflecting the marketability of member hospitals in the evaluation. In addition, to prevent damage to brand value, the main server 100 analyzes items such as lease agreements, interior design drawings, on-site inspections, and membership screening forms, and provides not only simple management solutions but also consulting for building an optimal management environment.

[0029] FIG. 2 is a block diagram of a main server according to the embodiment.

[0030] In an embodiment, a server is a computing system that provides services to other computers or devices in a computer network or stores and manages data. The main server 100 receives requests from other computers or devices called clients and provides responses or data to the requests. The configuration of the main server 100 shown in Figure 2 is merely a simplified example.

[0031] The communication unit 110 can be configured regardless of the communication mode, such as wired or wireless, and can be configured using various communication networks, such as a short-range communication network (PAN: Personal Area Network) or a long-range communication network (WAN: Wide Area Network). The communication unit 110 can also operate based on the well-known World Wide Web (WWW) and can use wireless transmission technologies used for short-range communication, such as infrared data association (IrDA) and Bluetooth (registered trademark). For example, the communication unit 110 can be responsible for transmitting and receiving data necessary to execute a technique according to an embodiment of the present disclosure.

[0032] The memory 120 may refer to any type of storage medium. For example, the memory 120 may include at least one of the following types of storage media: a flash memory type, a hard disk type, a multimedia card micro type, a card-type memory (e.g., SD or XD memory), a random access memory (RAM), a static random access memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, and an optical disk. Such memory 120 may constitute the database shown in FIG. 1.

[0033] The memory 120 can store at least one instruction that can be executed by the processor 130. The memory 120 can also store any type of information generated or determined by the processor 130 and any type of information received by the main server 100. For example, the memory 120 stores RM data and RM protocols by a user, as will be described later. The memory 120 also stores various types of modules, instruction sets, and models.

[0034] The processor 130 may perform technical features according to embodiments of the present disclosure, which will be described later, by executing at least one instruction stored in the memory 120. In one embodiment, the processor 130 may be configured with at least one core, and may include a processor for data analysis and / or processing, such as a central processing unit (CPU) of a computer device, a general purpose graphics processing unit (GPGPU), or a tensor processing unit (TPU).

[0035] FIG. 3 is a diagram showing the configuration of an instruction set stored in a memory according to the embodiment.

[0036] 3, an instruction set according to an embodiment may be configured to include a collection unit 121, a grade calculation unit 122, a grade assignment unit 123, a solution provision unit 124, and a community generation unit 125. The term "unit" used herein should be interpreted to include software, hardware, or a combination thereof, depending on the context in which the term is used. For example, software may be machine language, firmware, embedded code, and application software. As another example, hardware may be a circuit, a processor, a computer, an integrated circuit, an integrated circuit core, a sensor, a Micro-Electro-Mechanical System (MEMS), a passive device, or a combination thereof.

[0037] The collection unit 121 collects member information and promotion review information from the member terminal 300. In an embodiment, the member information may include, but is not limited to, detailed information about a member who has joined the system, such as the location, size, and year of opening of the hospital. In an embodiment, the member information may be collected through a membership review form. The promotion review information may include, but is not limited to, information necessary for a member's promotion review, such as whether or not each member has completed academy education, the number of treatments, and the number of consents from existing members.

[0038] Furthermore, the collection unit 121 collects learning data for an analytical model for analyzing the detailed hospital information. In an embodiment, the detailed hospital information may include lease agreements, interior design drawings, on-site inspections, membership screening forms, etc., as information necessary for generating hospital evaluations and consulting information. In an embodiment, the analytical model analyzes each item included in the detailed hospital information, and is capable of generating evaluation results and consulting information according to the analysis results.

[0039] The grade calculation unit 122 calculates the grade of the corresponding member based on the input information. In an embodiment, the grade calculation unit 122 calculates the grade of the member based on the collected member information, including whether or not each member has completed training, the number of treatments, and the number of consents from existing members. In an embodiment, the grade calculation unit 122 calculates different grades depending on the number of treatments and completed training courses included in the member information, and grants a grade only if more than half of the existing members consent.

[0040] In an embodiment, the grade calculation unit 122 grants an LMD qualification and an opportunity to observe treatments performed at the clinic when a member completes the basic course. Also, if the number of requests exceeds a certain number, the member can complete the in-depth course through an interview and majority consent. After the in-depth course, the member is judged whether to be promoted to a member through case presentations, interviews, and majority consent. After that, the member is granted an MMD qualification and the basic conditions for MMC, which allows staff to observe treatments.

[0041] Hereinafter, the grade and the function of the grade calculation unit 122 according to the embodiment will be described in more detail with reference to FIG.

[0042] FIG. 4 is a diagram showing types and standards of grades according to the embodiment.

[0043] Referring to FIG. 4, grades according to an embodiment may include LMD (License Of MINISH Dentistry), MMD (Member Of MINISH Dentistry), CMD (Chief Of MINISH Dentistry), and MMD (MINISH Member's Doctor) grades.

[0044] Anyone with a medical license can obtain the LMD (License of MINISH Dentistry) grade and take the MINISH Academy Basic Course (which provides basic kits such as a MINISH Bur Kit, Polishing Kit, and Bonding Kit). Doctors who complete the course are awarded an LMD certificate. LMDs are required to pay laboratory fees and can request laboratory work on a certain number of MINISH items (e.g., 20 pieces, or approximately three orders). The benefits listed above can be received within one year of completing the academy, and a fixed laboratory fee is charged per piece. If necessary, materials, equipment, and personnel can be dispatched from the headquarters, and opportunities for observation tours of the headquarters are also offered. This is only available to those with an LMD; dental staff are not permitted to participate.

[0045] The MMD (Member of MINISH Dentistry) rank is one rank higher than the LMD, and if the number of MINISH technician requests exceeds 20, one must become an MMD to request additional technicians. In some cases, an interview with the MINISH committee is required, and promotion to MMD is only possible with the consent of a majority of CMDs / DMDs / MAs / MDs, as well as participation in an annual symposium and community. Also, after becoming an MMD, one will be eligible to open an MMC.

[0046] The CMD (Chief of MINISH Dentistry) grade is a higher grade than the MMD, and MMDs can be promoted to CMD by presenting cases at regularly held seminars. Promotion to CMD requires an interview with the MINISH Committee and the consent of a majority of DMDs / MAs. In some cases, promotion to CMD qualifies one to open an MMC Premium program.

[0047] The grade assignment unit 123 assigns the calculated grade to the corresponding member and stores it. In addition, the grade assignment unit 123 sets and stores detailed information required for grade maintenance and registration, such as benefits for each grade, initial registration fee, and monthly maintenance fee. In addition, in an embodiment, the grade assignment unit 123 sets hospital support services to be provided when the initial registration fee and monthly maintenance fee are paid. In an embodiment, the hospital support services to be provided may include a MINISH business license acquisition fee, a brand management fee, a MINISH design plan, a designated hospital sign, consultation supplies, and regular visits.

[0048] The solution provider 124 provides dental management solutions. In an embodiment, the dental management solutions may include solutions that can be provided as a basic solution when subscribing to the system and consulting information generated by analyzing hospital data.

[0049] In an embodiment, the solutions that can be provided primarily include dental operations solutions that include educational content, qualification assurance, and operations support for ultra-thin dental prosthetic treatments.

[0050] In an embodiment, the solution providing unit 124 analyzes items of hospital documents, including lease agreements, interior design drawings, on-site inspections, and membership screening forms, and provides consulting information for building an optimal business environment based on the analysis results. In an embodiment, the solution providing unit 124 may analyze items of hospital documents using stored analysis models. In an embodiment, the analysis models may include an image analysis model, a video analysis model, and a text analysis model, and may generate consulting information using a generative artificial intelligence model based on the analysis results of the hospital documents.

[0051] In addition, in an embodiment, the solution providing unit 124 can evaluate a hospital that has applied for membership by quantitatively and qualitatively analyzing the membership screening form shown in FIG. 6. In an embodiment, the quantitative analysis is a method of adding up preset scores for each item and evaluating the hospital based on the total score. For example, the solution providing unit 124 can provide preset consulting information depending on the range of the total score. Note that in an embodiment, the membership screening form may be scored, and membership may be approved only if the score is above a certain level.

[0052] Qualitative analysis is a method of analyzing the text and images written in the evaluation form and providing consulting information according to the analysis results. In an embodiment, the solution providing unit 124 can analyze the text and images included in the evaluation form through a text analysis model and an image analysis model, and generate consulting information based on the analysis results obtained by the generative artificial intelligence.

[0053] As used herein, a model may refer to a network function, an artificial neural network, and / or any form of computer program that operates based on a neural network. As used herein, the terms model, neural network, network function, and neural network may be used interchangeably. A neural network is a network in which one or more nodes are connected to each other via one or more links, forming a relationship between an input node and an output node. The characteristics of a neural network may be determined by the number of nodes and links in the neural network, the relationship between the nodes and links, and the weight values ​​assigned to each link. A neural network may be composed of a set of one or more nodes. A subset of the nodes that make up a neural network may constitute a layer.

[0054] A deep neural network (DNN) may refer to a neural network that includes multiple hidden layers in addition to an input layer and an output layer. Deep neural networks may include convolutional neural networks (CNNs), recurrent neural networks (RNNs), autoencoders, generative adversarial networks (GANs), restricted Boltzmann machines (RBMs), deep belief networks (DBNs), Q-networks, U-networks, Siamese networks, generative adversarial networks (GANs), and transformers. The above descriptions of deep neural networks are merely examples, and the present invention is not limited thereto.

[0055] A neural network can be trained using at least one of supervised learning, unsupervised learning, semi-supervised learning, self-supervised learning, or reinforcement learning. Training a neural network can be a process of applying knowledge to the neural network to cause it to perform a particular operation.

[0056] Neural networks can be trained to minimize output errors. Training a neural network involves repeatedly inputting training data into the neural network, calculating the error between the neural network's output and the target for the training data, and backpropagating the neural network's error from the output layer to the input layer in a direction that reduces the error, thereby updating the weights of each node in the neural network. In supervised learning, labeled data with a correct answer can be used for each training data, while in unsupervised learning, unlabeled data can be used for each training data. The amount of change in the connection weights of each node to be updated may be determined according to a learning rate. The neural network calculation for input data and backpropagation of the error can constitute a learning cycle (epoch). The learning rate may be applied differently depending on the number of iterations of the neural network's learning cycle. In addition, methods such as increasing the amount of training data, regularization, dropout (deactivating some nodes), and batch normalization layers may be applied to prevent overfitting.

[0057] In one embodiment, the model may borrow at least a portion of a Transformer. The Transformer may be composed of an encoder that encodes embedded data and a decoder that decodes the encoded data. The Transformer may have a structure that receives a stream of data and outputs a stream of data of a different type through encoding and decoding steps. In one embodiment, the stream of data may be transformed into a format that the Transformer can operate on. The process of transforming the stream of data into a format that the Transformer can operate on may include an embedding process. Expressions such as data token, embedding vector, and embedding token may refer to embedded data in a format that the Transformer can process.

[0058] In order for the Transformer to encode and decode a series of data, the encoder and decoder in the Transformer may be processed using an attention algorithm. The attention algorithm may refer to an algorithm that calculates the similarity of one or more keys for a given query, reflects the similarity in values ​​corresponding to each key, and then weights the values ​​reflecting the similarity to calculate an attention value.

[0059] Depending on how the query, key, and value are set, various types of attention algorithms can be classified. For example, if the query, key, and value are all set to the same value and attention is calculated, this may refer to a self-attention algorithm. If the dimension of the embedding vector is reduced to process a series of input data in parallel, and attention is calculated by calculating a separate attention head for each divided embedding vector, this may refer to a multi-head attention algorithm.

[0060] In one embodiment, a Transformer may be composed of modules that perform multiple multi-head self-attention algorithms or multi-head encoder-decoder algorithms. In one embodiment, a Transformer may include additional components other than attention algorithms, such as embedding, normalization, softmax, etc. Methods for configuring a Transformer using attention algorithms may include those disclosed in Vaswani et al., Attention Is All You Need, 2017 NIPS, which is incorporated herein by reference.

[0061] A Transformer can be applied to various data domains, such as embedded natural language, segmented image data, or audio waveforms, to transform a series of input data into a series of output data. To transform data having various data domains into a series of data that can be input to the Transformer, the Transformer can embed the data. The Transformer may process additional data that represents relative positional or phase relationships between the series of input data. Alternatively, the Transformer may further incorporate vectors that represent relative positional or phase relationships between the input data into the series of input data before embedding the series of input data.

[0062] In one embodiment, the relative positional relationship between a series of input data may include, but is not limited to, the order of words in a natural language sentence, the relative positions of each segmented image, the time order of segmented audio waveforms, etc. The process of adding information representing the relative positional or phase relationship between a series of input data is also called positional encoding. In one embodiment, the model may include, but is not limited to, at least one of a Recurrent Neural Network (RNN), a Long Short Term Memory (LSTM) network, a Deep Neural Network (DNN), a Convolutional Neural Network (CNN), and a Bidirectional Recurrent Deep Neural Network (BRDNN).

[0063] In one embodiment, the model may be a model trained by a transfer learning method, where transfer learning refers to a learning method in which a large amount of unlabeled training data is pre-trained in a semi-supervised or self-supervised manner to obtain a pre-trained model for a first task, and the pre-trained model is fine-tuned to be suitable for a second task and then trained on labeled training data in a supervised manner to achieve a target model.

[0064] 3, in an embodiment, the solution providing unit 124 analyzes the lease agreement using an analytical model to generate consulting information. In an embodiment, the solution providing unit 124 analyzes the hospital lease agreement to evaluate the lease terms, rent, contract period, etc., and determine whether adjustments to the lease terms or rent are necessary.

[0065] The solution providing unit 124 also analyzes interior design drawings. In an embodiment, the solution providing unit 124 analyzes the hospital's interior design drawings to evaluate space utilization, environmental composition, patient and medical staff movement routes, etc. This allows the solution providing unit 124 to check whether the environment is efficiently configured and derive improvement measures.

[0066] In addition, in an embodiment, the solution providing unit 124 visits the actual hospital site, collects on-site inspection information by directly investigating the state and operation of the facility, identifies problems with the facility and areas requiring improvement, and is able to derive solutions.

[0067] In addition, the solution providing unit 124 analyzes the hospital's admission examination form to grasp information on the patient's admission and treatment process, and then derives measures to improve service quality through the patient's experience and evaluation of medical services.

[0068] In an embodiment, the solution providing unit 124 provides consulting information based on the analysis results of the described hospital data. In an embodiment, the solution providing unit 124 synthesizes the analysis results of the hospital data and generates an optimal plan for building the hospital's management environment using a generative artificial intelligence model. This may include, for example, facility improvement proposals, strategies for improving patient service quality, cost reduction measures, etc.

[0069] The community generation unit 125 generates a community where members can converse and share information according to the educational courses and positions they have completed.

[0070] In an embodiment, the community generating unit 125 may separately generate communities with different access rights according to the educational courses and positions of each member. For example, the community generating unit 125 may separately generate an overall community, a representative community, a department head community, an initial setup community, and a website creation community.

[0071] In one embodiment, the overall community is a community of clinic directors who have completed the academy's basic course, and is a community that shares information related to the hospital, posts uploaded to SNS, new MMC contract information, internal and external events, dental materials and equipment purchasing information such as dental malls, etc.

[0072] The Representative Community is a community for representative directors of dental clinics that have signed MMC contracts, and it shares information related to the hospital, posts uploaded to social media, new MMC contracts, and other announcements related to MINISH operations. It also shares information about MMC management meetings and symposiums, and is a community for continuous communication with directors who have joined MMC.

[0073] The Department Director (Non-Physician) Community is a community for dental department directors who have signed MMC contracts. It shares hospital-related information, posts uploaded to social media, materials useful for hospital management and consultations, announcements related to management, and answers to inquiries about medical treatment, and provides conversation tools for continuous communication with participating department directors.

[0074] The initial setup community is a community made up of dental clinic directors, department heads, and medical business teams who have signed MMC contracts, and is a community that assists with the initial setup for MINISH operation and provides materials necessary for system operation.

[0075] The website production community is a community of dental directors and department heads who have signed an MMC contract, website production companies employed by MMC, and medical business teams, and provides materials necessary for website production and management, and answers inquiries regarding website production materials.

[0076] In an embodiment, each community provides setup items categorized according to publication grade. In an embodiment, the setup items may include physical items and electronic files.

[0077] In an embodiment, the disclosure level may be subdivided into a disclosure level, an in-clinic disclosure level (no external disclosure), a non-disclosure level, etc. Specifically, the disclosure level information includes model promotional materials, before-and-after photos of ultra-thin dental prostheses, logo materials, etc., while the in-clinic disclosure level includes materials that typically involve portrait rights issues, such as promotional videos and before-and-after photos of ultra-thin dental prostheses. In addition, the non-disclosure level includes materials that typically include operational know-how, such as the MINISH Guidebook (MINISH operation guide), content guide (content operation and usage guide), and other MMC (other member) materials.

[0078] The dental management solution support system and method according to the embodiment determines whether a candidate has completed the basic course, whether they hold an LMD qualification upon completion, and whether they have observed treatments performed at the clinic, and then determines whether they have completed the in-depth course. Upon completion of the in-depth course, if the number of requests exceeds the standard number, promotion can be determined through an interview and majority consent. Promotion to CMD is then determined through case presentations, interviews, and majority consent. After that, the candidate can receive the benefits of the MMC basic requirements, including MMD qualification and the ability for staff to observe treatments.

[0079] In one embodiment, once the MMD qualification is granted, the patient can receive Doctor MINISH products on an irregular basis, including the initial registration fee, monthly maintenance fees - MINISH business license acquisition fees, brand management fees, MINISH design proposals, designated hospital signage, consultation supplies, and regular business trips.

[0080] In addition, in an embodiment, to join as a member, a membership application form, business registration certificate, medical institution opening declaration certificate, medical license, lease agreement (or copy), and interior design drawings can be submitted as hospital documents, and consulting information based on document analysis can be received.

[0081] In addition, in an embodiment, on-site inspections of the director, department head, interviews, etc. can be conducted, and inspection information can be collected and analyzed. In addition, the final decision on whether to accept or promote a member can be made based on the results of the committee's inspection based on the membership inspection form.

[0082] Once membership is confirmed, the member's device will sign an electronic contract to create the contract. In addition, members who join the system can continuously receive various operational guidance, such as invitations to KakaoTalk group chat rooms, provision of MINISH setup items, provision of interior reference materials upon request, cooperation upon request, hospital visits and staff training, and branch office visits and staff training.

[0083] The dental management solution support method according to the embodiment will be described below in order. The operation (function) of the dental management solution support method according to the embodiment is essentially the same as the function of the system, so the description overlapping with that in FIGS. 1 to 6 will be omitted.

[0084] FIG. 7 is a diagram showing a data processing process of the main server according to the embodiment.

[0085] Referring to FIG. 8, in step S100, the main server collects promotion screening information, including whether the member has completed academy training, the number of treatments, and the number of consents from existing members. In step S200, the main server calculates the member's grade based on the information entered. In step S300, the main server assigns and stores the calculated grade to the member. In step S400, the system provides a dental management solution, including educational content, qualification guarantees, and management support for ultra-thin dental prosthetic treatment. In one embodiment, step S400 analyzes hospital documents, including lease agreements, interior design drawings, on-site inspections, and membership screening forms, and provides consulting information for building an optimal management environment based on the analysis results.

[0086] The above-described dental management solution support system and method operate member hospitals by grade to provide efficient management, and provide differentiated solutions as members' grades increase, thereby enhancing expertise and generating profits.

[0087] In addition, depending on the embodiment, it is possible to provide communities divided by access rights and provide appropriate information based on the position and personality of members, thereby improving operational efficiency and promoting friendship by forming a circle of empathy.

[0088] In addition, in the embodiment, security is enhanced by setting a disclosure level for each document provided when supporting the management solution.

[0089] The disclosed content is merely an example, and various modifications can be made by a person skilled in the art without departing from the spirit of the claims, so the scope of protection of the disclosed content is not limited to the specific embodiments described above.

Claims

1. A member terminal provided at each hospital registered as a member; an administrator terminal that provides input and output to an administrator; a main server that manages the hospital; The main server A collection department that collects promotion review information for each member, including whether they have completed academy education, the number of treatments, and the number of consents from existing members; a rank calculation unit that calculates the rank of the member based on the collected promotion examination information and determines whether to promote the member; A dental management solution support system including a grade assignment unit that assigns and stores the calculated grade to the corresponding member.

2. The main server The dental operation solution support system according to claim 1, further comprising a solution providing unit that provides dental operation solutions including educational content, qualification guarantee, and operation support related to ultra-thin dental prosthetic treatment.

3. The solution providing department The dental management solution support system described in claim 2 is characterized by analyzing items of hospital documents including lease agreements, interior design drawings, on-site inspections, and membership review forms, and providing consulting information to create an optimal management environment based on the analysis results.

4. The main server The dental management solution support system according to claim 1, further comprising a community generation unit that generates a community for conversation and information sharing according to the educational courses and positions completed by each member.

5. The grade calculation unit The dental management solution support system of claim 1, characterized in that evaluation factors including whether or not the educational content has been completed, the size of the hospital, sales, the number of digital devices owned, whether or not the hospital has an in-house laboratory, and the length of membership are extracted from the membership review form, and the extracted evaluation factors are analyzed to calculate the grade of each member.

6. The solution providing department The dental management solution support system of claim 3, characterized in that it determines whether or not to approve a hospital for membership through a quantitative analysis of the membership evaluation form, and generates consulting information by qualitatively analyzing the membership evaluation form of the hospital that has been approved for membership.

7. (A) collecting member information including whether or not the member has completed academy education, the number of treatments, and the number of consents from existing members on a main server; (B) calculating the rank of the member based on the information input to the main server; (C) assigning the calculated grade to the member in the main server and storing the grade; (D) providing a dental management solution including educational content, qualification guarantee, and management support for ultra-thin dental prosthetic treatment; The step (D) A dental management solution support method that analyzes items in hospital documents, including lease agreements, interior design drawings, on-site inspections, and membership screening forms, and provides consulting information to create the optimal management environment based on the analysis results.

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