CN115237918A

CN115237918A - Method for designing heterogeneous data index of joint replacement surgery

Info

Publication number: CN115237918A
Application number: CN202210887980.6A
Authority: CN
Inventors: 刘芳德; 江鑫楠; 穆华岭; 施超宇; 李连杰; 刘笑天; 黄琪锋
Original assignee: Hangzhou Huxi Yunbaisheng Technology Co ltd
Current assignee: Hangzhou Huxi Yunbaisheng Technology Co ltd
Priority date: 2022-07-27
Filing date: 2022-07-27
Publication date: 2022-10-25

Abstract

The embodiment of the disclosure provides a method for designing heterogeneous data index of joint replacement surgery, which belongs to the technical field of robot data processing, and comprises the following steps: the data of the system is composed of a partition key PK representing an entity, a sorting key SK representing PK attribute and other data, wherein, a data table is used in a system database to store various different types of data in the operation, and the various different types of data comprise: patient, doctor, prosthesis, operation scheme, operation, effect after operation, etc. The support to massive multi-modal orthopedic surgery data and the high-performance indexing and searching functions are realized. The processing scheme disclosed by the invention can scientifically, objectively and accurately analyze the cause of the medical accident through a big data technology, and has important significance in practical clinical application.

Description

Method for designing heterogeneous data index for joint replacement surgery

Technical Field

The disclosure relates to the technical field of robot data processing, in particular to a method for designing heterogeneous data index of joint replacement surgery.

Background

After orthopaedic joint replacement surgery, the prosthesis may be used in the patient for up to ten years. However, at present, about 25% of prostheses implanted have various adverse events and medical accidents, such as premature aging, prosthesis falling off, abnormal prosthesis sound and the like, so that patients need secondary operations, and heavy burden is caused on the quality of life and medical insurance payment of the patients. Therefore, it is very urgent to analyze the cause of the surgical accident of the prosthesis implantation. However, the complex cause makes the implementation very difficult, and the main reasons include: unreasonable operation scheme, irregular operation, different life habits of patients and the quality problem of the prosthesis. With the advent of surgical navigation and computer-assisted surgery systems, such as surgical robots, it has become possible to record high quality data in detail and efficiently. However, in the current clinical application, a scientific and effective data management and analysis method is still lacked for a large amount of data with different sources and different types, so that the cause of the medical accident can be scientifically, objectively and accurately analyzed. In order to support the analysis of medical accident causes, the data platform faces the following challenges in data governance:

1) Due to the heterogeneity of data, data platforms need to collect a variety of different types of data.

Unlike transactional data, which can be well tabulated, medical data includes a large amount of data that cannot be tabulated, such as medical images (pre-and post-operative CT), prosthesis CAD models, prosthesis placement locations, blood pressure and weight of a patient, and the like. For a platform with complete data, the data types are thousands, and about tens of thousands of markers can be extracted. Because the format and the variety of the data are diversified, different data governance methods are required to be adopted.

2) Due to the chronological nature of the data, the data platform needs to analyze according to the sequence of occurrence of events and to implement interactions between various modalities.

First, because the most prominent analysis method in medical events today is based on evidence-based analysis. For example, patients who used the prosthesis of joint a company and had a prosthesis detachment within three years after the operation were searched. In contrast, the recorded data of the data platform is very important for the time-series relationship of medical events (within three years after operation). Therefore, the database itself must be designed to support timing tracking lookups.

Secondly, in the process of searching medical data, cross-modal searching is usually required. For example, one type of data (prosthesis from Joint A company) is used to find another type of data (patient with post-operative prosthesis detachment). Therefore, the database must also be designed to support cross-modal lookups.

3) Because of the large scale of medical data, a data platform requires clusters of thousands of nodes to complete.

For complete data on orthopaedic joint replacement surgery, each case is of near TB grade, and the annual surgical volume is planned in millions. For such huge amounts of data, the data platform faces huge challenges in data analysis and storage, which requires clusters of thousands of nodes to complete.

Disclosure of Invention

In view of the above, the embodiments of the present disclosure provide a method for designing an index of heterogeneous data in joint replacement surgery to at least partially solve the problems in the prior art.

The embodiment of the disclosure provides a method for designing heterogeneous data index of joint replacement surgery, which comprises the following steps:

all data of the system are composed of a partition key PK representing an entity, a sorting key SK representing PK attribute and other data;

PK is the partition key of the whole table, which is used for identifying the entity; there are 5 entities in the database: a patient, a left leg femoral prosthesis, a right leg femoral prosthesis, a tibial prosthesis, and an operation plan; the partition keys corresponding to the 5 entities are respectively: PAT # PID, IMP # FL # ID, IMP # FR # ID, IMP # T # ID and SUR # UUID; wherein PAT represents patient, PID represents patient ID, IMP # FL represents left leg femoral prosthesis, ID represents model, IMP # FR represents right leg femoral prosthesis, IMP # T represents tibial prosthesis, SUR represents surgical plan, UUID represents unique surgical identification; by means of the design form, the database is flexible, and as the structure of the database expands, the inclusion of expanded entity fields into PK columns is supported, wherein the expanded entity fields comprise data required by doctors, nurses and the like;

SK is the sort key of the whole table, used to identify the attribute; the patient data includes basic information of the patient, associated procedures and associated doctors; the basic information of the patient comprises attributes such as name, birthday, sex, home address and the like, and SK of the basic information is PAT # PID; correlating the surgical records received by the surgical record patient, wherein SK of the surgical records is SUR # UUID; the associated doctor records the information of the main doctor of the patient, and SK of the information is DR #0001, which represents the No. 0001 doctor of the operation; the surgical plan contains a variety of attributes including the surgical affected limb, the attending physician, the patient of the surgery, the preselected prosthesis model, the installed prosthesis model, the preoperative data, the intraoperative data, the postoperative data, the resection plane, the primary registration points, the fine registration points, and the gap balance curve, SK starts with "SUR #", SUR # PRE # LMK # HIPC represents the preoperative femoral center registration, where PRE represents the preoperative data, LMK represents the primary registration; SUR # IN # PLA # AP represents the element point of the anterior cutting plane of the femur during operation, wherein IN represents intraoperative data, and PLA represents the cutting plane; the operation data comprises the model of the replaced prosthesis, the installation position of the replaced prosthesis, each picking of the registration points, the operation effect of various sensors, the calculation result of the surgical robot navigation system, the loading record of the operation scheme and the information 6 types of the successful storage of the operation scheme, wherein SK starts with OP #, OP # CII #0001 represents the operation of the replaced prosthesis model and has the serial number of 0001; SK is expressed through multilayer structure, and redundant items are added, so that fast query can be realized;

other data have a variety of different expressions for extending the partition keys PK to specific needs.

According to a specific implementation manner of the embodiment of the present disclosure, the method further includes:

storing and inquiring by using a key/value pair mode, wherein a primary key uniquely identifies a data tuple in a database, the database uses a partition key PK as the primary key, or a PK and a sequencing key SK are compounded to form the primary key, when the PK can uniquely identify each piece of data, the PK serves as the ID for identifying the tuple, and when different data tuples have the same PK, the SK is introduced as an identifier of auxiliary data, at the moment, the PK + SK is integrally used as the primary key to uniquely identify the data, in the key/value pair design, the primary key is unique in a table, and the structure of the value is flexible and changeable, so that the diversified expression of the relation between the data and the data is met;

the data query comprises two modes of precise query and flexible query.

the precise query is carried out by inputting key values;

when the limiting conditions of accurate query need to be set, setting the limiting conditions for the input key values, and then performing data query through cross-modal secondary accurate query;

when the limiting condition of accurate query does not need to be set, data query is directly carried out through cross-mode secondary accurate query.

when flexible query is carried out, the database is partitioned again through the global secondary index GSI so as to be convenient for query through different partition key values;

when the limiting conditions of flexible query need to be set, setting the limiting conditions for the input query value, and then performing data query through cross-modal secondary accurate query;

when the limit condition of flexible query does not need to be set, data query is directly carried out through cross-modal secondary accurate query

data query is carried out in a precise query or flexible query mode, the precise query obtains the query modes of patient information, operation information and prosthesis information by directly inputting key values (PK, SK), the flexible query carries out query through GSI indexes, and information meeting the conditions is obtained within a given time range;

a GSI (PK: TYPE, SK: TIME) table is designed for flexible query, data can be located according to the query TYPE during query, then data meeting TIME requirements and corresponding conditions can be screened, and an index structure is designed as follows:

GSI PK＝TYPE(string)

GSI SK＝TIME(string)

based on the result obtained by query, when a medical accident and an adverse event occur, the cause of the accident is searched for retrospective analysis, or the association between the occurrence frequency of various medical events and different biomarkers is analyzed, all events meeting the conditions are found through secondary search and first event collection, all found events are grouped and collected according to attributes, and the required information is found through secondary search;

the backtracking analysis is used for searching the cause of the accident when a medical accident and an adverse event occur, and is used for:

whether the operation scheme is reasonable or not can be analyzed according to the scheme before the operation and the motion analysis;

comparing the intraoperative data with preoperative data, analyzing the positioning error of the operation, and mainly analyzing whether the computer-aided navigation system has the positioning error;

the doctor operation level can be analyzed according to the postoperative gap balance curve in the postoperative verification data, the actually measured prosthesis and installation effect and the operation and planning error of the doctor;

according to the rehabilitation record, the patient can see whether the postoperative condition is normal or whether the living habit is changed.

based on the results of the flexible query, an epidemiological analysis is performed for analyzing the correlation between the frequency of occurrence of various medical events and different biomarkers for preparing a defined product and surgical indications, for assessing suitable triage for clinical trials into groups, including frequency of occurrence of adverse events of joint replacement surgery versus body weight.

constructing a data model aiming at the joint replacement surgery heterogeneous data, wherein the data model comprises the following components: a patient information data model, a preoperative data model, an intraoperative data model, a postoperative data model, a prosthesis data model, and an operative record data model;

the patient information data model includes: medical record information, an attending doctor, prosthesis type selection, affected limb selection and default flexion angle;

the preoperative data model includes: preselecting a femur prosthesis, femur model data, a femur primary registration anatomical landmark point, a preselecting tibia prosthesis, tibia model data and a tibia primary registration anatomical landmark point;

the intraoperative data model includes: a femur primary registration anatomical landmark point, a femur fine registration anatomical landmark point, a femur front end tangent plane, a femur rear end tangent plane, a femur far end tangent plane, a femur verification nail, a tibia primary registration anatomical landmark point, a tibia fine registration anatomical landmark point, a tibia tangent plane, a tibia verification nail and an intraoperative gap balance curve;

the post-operative data model comprises: a femur front end cutting plane, a femur rear end cutting plane, a femur far end cutting plane, a femur verification nail, a tibia prosthesis cutting plane, a tibia verification nail and a postoperative gap balance curve;

the prosthesis data model includes: the femoral prosthesis model comprises an anterior end tangent plane normal line, a femoral posterior end tangent plane normal line, an element point coordinate of an anterior end tangent plane, a color, an inner condyle registration point, a three-dimensional prosthesis model, an outer condyle registration point, an element point coordinate of a posterior end tangent plane and a prosthesis model which are contained in a left leg femoral prosthesis model, an anterior end tangent plane normal line, a femoral posterior end tangent plane normal line, an element point coordinate of an anterior end tangent plane, a color, an inner condyle registration point, a three-dimensional prosthesis model, an outer condyle registration point, an element point coordinate of a posterior end tangent plane and a prosthesis model which are contained in a right leg femoral prosthesis model, a tibial bone tangent plane normal line, an element point coordinate of a tibial prosthesis tangent plane, a tibial bone color, a tibial three-dimensional prosthesis model and a tibial prosthesis model which are contained in a tibial prosthesis model;

the surgical procedure record data model includes: unique surgical identifier, time of data generation, type of surgical procedure recorded, pre-operative data record, post-operative data record.

The scheme of the method for designing the index of the heterogeneous data of the joint replacement surgery comprises the following steps of constructing a data model aiming at the heterogeneous data of the joint replacement surgery, wherein the data model comprises the following components: a patient information data model, a preoperative data model, an intraoperative data model, a postoperative data model, a prosthesis data model, and an operative records data model. By the processing scheme, the support to massive multi-modal orthopedic surgery data and the high-performance indexing and searching functions can be realized.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings needed to be used in the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present disclosure, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.

FIG. 1 is a flowchart of a method for designing an index of heterogeneous data in joint replacement surgery according to an embodiment of the present disclosure;

FIG. 2 is a schematic diagram of data association provided by an embodiment of the present disclosure;

fig. 3 is a schematic diagram of a data query method provided by the embodiment of the present disclosure;

FIG. 4 is a schematic illustration of a distal femoral osteotomy provided by an embodiment of the present disclosure;

FIG. 5 is a block diagram representation of a data store provided by embodiments of the present disclosure;

fig. 6 is a schematic view illustrating installation of a laser target of a surgical navigation system according to an embodiment of the present disclosure.

Detailed Description

The embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.

The embodiment of the disclosure provides a method for designing heterogeneous data index of joint replacement surgery. The joint replacement surgery heterogeneous data index design method provided by the embodiment can be executed by a computing device, the computing device can be implemented as software, or implemented as a combination of software and hardware, and the computing device can be integrally arranged in a server, a client and the like.

The method for designing the index of the heterogeneous data of the joint replacement surgery in the embodiment of the disclosure comprises the following steps:

constructing a data model for the joint replacement surgery heterogeneous data, wherein the data model comprises: a patient information data model, a preoperative data model, an intraoperative data model, a postoperative data model, a prosthesis data model, and an operative record data model;

the patient information data model includes: medical record information, an attending physician, prosthesis type selection, affected limb selection and default flexion angle;

the preoperative data model includes: preselecting a femoral prosthesis, femoral model data, a femoral primary registration anatomical landmark point, a preselected tibial prosthesis, tibial model data and a tibial primary registration anatomical landmark point;

the prosthesis data model includes: the femoral prosthesis model of the left leg comprises an anterior tangent plane normal, a femoral posterior tangent plane normal, an element point coordinate of an anterior tangent plane, a color, an internal condyle registration point, a three-dimensional prosthesis model, an external condyle registration point, an element point coordinate of a posterior tangent plane, a prosthesis model, a tibial tangent plane normal, an element point coordinate of a tibial prosthesis tangent plane, a tibial color, a tibial three-dimensional prosthesis model and a tibial prosthesis model;

the surgical procedure record data model includes: a unique surgical identifier, a time at which the data was generated, a type of surgical procedure to be recorded, a pre-operative data record, and a post-operative data record.

The specific structures of the patient information data model, the preoperative data model, the intraoperative data model, the postoperative data model, the prosthesis data model, and the surgical operation record data model are shown in tables 1-6 below.

TABLE 1 patient information data model

TABLE 2 preoperative data model

TABLE 3 intraoperative data model

TABLE 4 postoperative data model

TABLE 5 prosthesis data model

TABLE 6 operation record data model

In addition, referring to fig. 1, the method for designing an index of heterogeneous data in joint replacement surgery in the disclosed embodiment may further include the following steps:

s101, all data of the system are composed of partition keys PK representing entities, sequencing keys SK representing PK attributes and other data;

s102, PK is a partition key of the whole table and is used for identifying the entity; there are 5 entities in the database: a patient, a left leg femoral prosthesis, a right leg femoral prosthesis, a tibial prosthesis, an operative plan; the partition keys corresponding to the 5 kinds of entities are respectively: PAT # PID, IMP # FL # ID, IMP # FR # ID, IMP # T # ID and SUR # UUID; wherein PAT represents the patient, PID represents the patient ID, IMP # FL represents the left leg femoral prosthesis, ID represents the model, IMP # FR represents the right leg femoral prosthesis, IMP # T represents the tibial prosthesis, SUR represents the surgical plan, and UUID represents the unique surgical identifier; by the design form, the database is flexible, and the incorporation of extended entity fields into a PK column is supported as the database structure is extended, wherein the extended fields comprise data required by doctors, nurses and the like;

s103, SK is a sort key of the whole table, and is used for identifying attributes; the patient data includes basic information of the patient, associated procedures and associated doctors; the basic information of the patient comprises attributes such as name, birthday, sex, home address and the like, and SK of the basic information is PAT # PID; correlating the surgical record received by the patient, wherein SK is SUR # UUID; the associated doctor records the information of the main doctor of the patient, and SK of the information is DR #0001 and represents No. 0001 doctor of the operation; the surgical plan contains a plurality of attributes including the surgical affected limb, the attending physician, the patient of the surgery, the preselected prosthesis model, the installed prosthesis model, the preoperative data, the intraoperative data, the postoperative data, the resection plane, the primary registration point, the fine registration point, and the gap balance curve, SK starts with "SUR #", SUR # PRE # LMK # HIPC represents the preoperative femoral center registration, where PRE represents the preoperative data and LMK represents the primary registration; SUR # IN # PLA # AP represents the original point of the resection plane of the front end of the femur during operation, wherein IN represents the data during operation, and PLA represents the resection plane; the operation data comprises the model of the replaced prosthesis, the installation position of the replaced prosthesis, each picking of the registration points, the operation effect of various sensors, the calculation result of the surgical robot navigation system, the loading record of the operation scheme and the information 6 types of the successful storage of the operation scheme, wherein SK starts with OP #, OP # CII #0001 represents the operation of the replaced prosthesis model and has the serial number of 0001; SK is expressed by multilayer structure, and redundant items are added, so that fast query can be realized;

and S104, other data have various expressions and are used for expanding the partition keys PK according to specific requirements.

The method for designing the heterogeneous data index of the joint replacement surgery in the disclosed embodiment further comprises the following steps:

data warehouse design and analysis system

1. Data architecture and index format

1) Description of the design

The system mainly takes a NoSQL unstructured database as a basic framework, supports that each tuple is composed of different fields, further lightens the coupling relation between data, and enhances the expansibility of data attributes, thereby meeting the diversification and flexible access of data and data relations. The search is carried out through the main key during the accurate query, and the flexible query is carried out through the global secondary index, namely the GSI index. The primary keys and GSI index are illustrated as follows:

(1) a main key:

in technical details, the system mainly utilizes a key/value pair mode to store and query, and a primary key in a database uniquely identifies a data tuple. The database can directly use Partition Key (PK) as a simple primary Key, and can also form the primary Key by compounding PK and Sort Key (SK). In particular, when a PK is able to uniquely identify each piece of data, the PK will act as a simple primary key as an ID identifying the tuple. And when different data tuples have the same PK, introducing the SK as the identifier of the auxiliary data, and at the moment, taking the PK + SK as a whole as a main key to uniquely identify the data. The system can efficiently position and accurately inquire the data according to the primary key of the data, so that in the design of the key/value pair of the system, the primary key is unique in the table, and the structure of the value is allowed to be flexible and changeable, thereby satisfying the diversified expression of the relation between the data and the data.

(2) GSI indexing:

when flexible query is performed, the spanned query time is large, and the query type and the query condition are complex. Therefore, GSI tables (PK: TYPE, SK: TIME) are designed for such queries to speed up the query speed. During query, the data is firstly positioned according to the query type, and then the data meeting the time requirement and the corresponding condition is screened. The index structure is designed as follows:

GSI PK＝TYPE(string)

GSI SK＝TIME(string)

2) Data index format

All data in the system consists of Partition Keys (PK), sort Keys (SK), and other data.

①PK：

Is a partition key of the entire table to identify the entity itself; there are 5 entities in the database: a patient, a left leg femoral prosthesis, a right leg femoral prosthesis, a tibial prosthesis, and an operation plan; the partition keys corresponding to the 5 entities are respectively: PAT # PID, IMP # FL # ID, IMP # FR # ID, IMP # T # ID and SUR # UUID; wherein PAT represents the patient, PID represents the patient ID, IMP # FL represents the left leg femoral prosthesis, ID represents the model, IMP # FR represents the right leg femoral prosthesis, IMP # T represents the tibial prosthesis, SUR represents the surgical plan, and UUID represents the unique surgical identifier; by the design form, the database is flexible, and the incorporation of extended entity fields into a PK column is supported as the database structure is extended, wherein the extended fields comprise data required by doctors, nurses and the like;

②SK：

is the sort key of the whole table, used to identify the attribute; the patient data includes basic information of the patient, associated surgery and associated doctors; the basic information of the patient comprises attributes such as name, birthday, gender, family address and the like, and SK of the basic information is PAT # PID; correlating the surgical record received by the patient, wherein SK is SUR # UUID; the associated doctor records the information of the main doctor of the patient, and SK of the information is DR #0001, which represents the No. 0001 doctor of the operation; the surgical plan contains a variety of attributes including the surgical affected limb, the attending physician, the patient of the surgery, the preselected prosthesis model, the installed prosthesis model, the preoperative data, the intraoperative data, the postoperative data, the resection plane, the primary registration points, the fine registration points, and the gap balance curve, SK starts with "SUR #", SUR # PRE # LMK # HIPC represents the preoperative femoral center registration, where PRE represents the preoperative data, LMK represents the primary registration; SUR # IN # PLA # AP represents the original point of the resection plane of the front end of the femur during operation, wherein IN represents the data during operation, and PLA represents the resection plane; the operation data comprises the model of the replaced prosthesis, the installation position of the replaced prosthesis, each picking of the registration points, the operation effect of various sensors, the calculation result of the surgical robot navigation system, the loading record of the operation scheme and the information 6 types of the successful storage of the operation scheme, wherein SK starts with OP #, OP # CII #0001 represents the operation of the replaced prosthesis model and has the serial number of 0001; SK is expressed by multilayer structure, and redundant items are added, so that fast query can be realized;

(3) other data:

has various expressions, and can be expanded according to specific requirements.

3) Design advantages

The NoSQL key/value database is very easy to realize an ultra-large-scale distributed system due to the simple and flexible structural design, supports a flexible data model, and further meets the characteristics of large-capacity storage, high-performance access and high-availability operation.

2. Data index format

1) Description of the design

The data are stored as data tuples, the relation among the data is simulated and stored by adopting a design mode of an adjacent list, and the data of the orthopedic surgery are concentrated in a table for modeling. And a convenient multi-level structure is adopted to arrange the data, the difference of different types of data is extracted, the simplified and efficient data modeling is realized, and in addition, the rapid adjustment can be carried out according to the requirements of hospitals.

2) Orthopedic surgery database format

(1) Patient's health

(2) Surgical data

a. Surgical plan

b. Surgical operation

c. Surgical association data

(3) Prosthesis

3. Data analysis and clinical applications

The invention relates to a method and a system for index design of heterogeneous data of joint replacement surgery, which analyze and search the cause of a prosthesis implantation surgery accident through a big data technology. Because medical data is huge in scale and large in query difficulty, and a general relational database cannot be rapidly and effectively queried, the system develops a distributed-processing orthopedic joint replacement surgery heterogeneous data analysis platform based on NoSQL, provides different query modes for data of different modes, and mainly supports two query modes: precise querying and flexible querying. The accurate query is a query mode for obtaining patient information, operation information, prosthesis information and the like by directly inputting key values (PK, SK). The flexible query refers to query through a GSI index, and can be given a time range to obtain information meeting the requirements. In addition to the above query modes, there is a cross-modal secondary accurate query, that is, a mode of obtaining PK values in other modal domains by querying and further obtaining data of other modal domains, for example, obtaining id of an associated operation from a patient and obtaining operation information of the patient, for example, a prosthesis of the patient falls off, and can obtain all patient information in which the prosthesis of the model is installed within 3 years by the model of the prosthesis installed.

From a clinical perspective, the main applications of the data platform are two major categories, the first category is retrospective analysis, and the second category is epidemiological analysis.

1) Retrospective analysis

The backtracking analysis is mainly used for searching the cause of the accident when a medical accident and an adverse event occur. For example, when a patient has a medical event:

a. whether the operation scheme is reasonable or not can be analyzed according to the scheme before the operation and the motion analysis;

b. comparing the intraoperative data with preoperative data, analyzing the positioning error of the operation, and mainly analyzing whether the computer-aided navigation system has the positioning error;

c. the doctor operation level can be analyzed according to the postoperative gap balance curve in the postoperative verification data, the actually measured prosthesis and installation effect and the operation and planning error of the doctor;

d. according to the rehabilitation record, seeing whether the patient recovers to be normal after the operation or whether the living habit changes;

for this type of application, the analysis function mainly looks for different modality data for the same surgical event, defined as an accurate query in the system.

From a database perspective, the specific query application is illustrated as follows:

(1) patient-related data query

a. All information of the patient with PID 0001 was obtained:

when PK = PAT #0001 is input, all information related to the patient including basic information of the patient, surgical data, a doctor in charge, and the like can be acquired.

b. Obtaining basic information of a patient with PID 0001:

upon entry of PK = PAT #0001, sk = PAT #0001, patient basic information can be obtained.

c. All procedures for patients with PID 0001 were obtained:

input PK = PAT #0001, sk = sur, all surgeries of the patient were acquired, where the data portion is the surgery id.

If a specific operation data needs to be acquired, a secondary cross-modality precision query needs to be performed, and PK = PAT #0001, sk = sur #uuid is input again for acquisition.

d. Obtaining the primary physician of the patient:

PK = PAT #0001, sk = dr, patient attending physician is obtained, where the name is the physician name.

(2) Surgical-related data query

a. All information for a single surgery was acquired:

input PK = SUR # UUID, and all information including patient ID, affected limb (left/right leg), treating doctor, prosthesis selection, surgical plan (before, during, after), surgical operation, and the like, for a single operation can be acquired.

If TYPE = SUR # LMK is further input, all the initial registration point information of the surgical plan (including preoperative, intraoperative, postoperative) can be acquired;

if TYPE = SUR # PLA is further input, all the tangent plane information of the surgical plan (including preoperative, intraoperative, postoperative) can be obtained;

b. obtaining a surgery-associated patient:

inputting PK = SUR # UUID, SK = SUR # PAT, the surgical association patient may be obtained, where the data portion is the patient ID.

If a specific data needs to be acquired, a cross-modality secondary precision query needs to be performed, and PK = PAT # PID is input again to acquire patient data.

c. Obtaining affected limb information:

inputting PK = SUR # UUID and SK = SUR # LEG, the affected limb information can be obtained, wherein the data part is the right LEG/left LEG.

d. Acquiring information of an attending doctor:

inputting PK = SUR # UUID and SK = SUR # DR, the information of the attending doctor can be acquired, wherein the data part is the name of the doctor.

e. Obtaining the femur and tibia false body before operation, and finally installing the femur and tibia false body information:

inputting PK = SUR # UUID, SK = SUR # IMP, obtaining pre-operative femoral and tibial prostheses, and finally fitting the femoral and tibial prostheses, wherein the data portion is the prosthesis ID.

If a specific data needs to be obtained, a secondary cross-modality precision query needs to be performed, and PK = IMP # FR0001 is input again to obtain the specific data of the prosthesis.

f. Acquiring all operation information of the operation:

inputting PK = SUR # UUID and SK = OP, all operations of the operation can be acquired.

g. Acquiring all operation information of a certain type of the operation:

inputting PK = SUR # UUID and SK = OP # CII, and acquiring all operations for replacing the prosthesis model in the operation;

inputting PK = SUR # UUID, SK = OP # CIP, and acquiring all operations for replacing the prosthesis installation site in the current operation;

inputting PK = SUR # UUID and SK = OP # MV, and obtaining all operations of the motion data of the operation;

inputting PK = SUR # UUID and SK = OP # RES, and obtaining all operations of the calculation result of the surgical navigation system;

inputting PK = SUR # UUID, SK = OP # LOAD, and acquiring all operations of the operation loading operation scheme;

inputting PK = SUR # UUID, SK = OP # SAVE, and all operations for storing the calculated operation effect of the operation can be acquired;

h. acquiring preoperative surgical scheme data information in the operation:

inputting PK = SUR # UUID and SK = SUR # PRE, and obtaining the preoperative surgical plan data in the operation.

i. Acquiring operation scheme data information in the operation:

inputting PK = SUR # UUID and SK = SUR # IN, the surgical plan data IN the operation of the operation can be obtained.

j. Acquiring postoperative operation scheme data information in the operation:

inputting PK = SUR # UUID and SK = SUR # AFT, and obtaining postoperative surgical scheme data in the operation.

(3) Prosthesis-related data query

a. All information was obtained for a femoral (right) model 0001 prosthesis:

PK = IMP # FR #0001, and all information of the femoral (right) model 0001 prosthesis including femoral prosthesis model, color, medial-lateral condyle registration points, tangential plane point coordinates, and normal is obtained.

b. All information was obtained for a femoral (left) model 0001 prosthesis:

PK = IMP # FL #0001, and all information of the femoral (right) model 0001 prosthesis including femoral prosthesis model, color, medial and lateral condyle registration points, tangential plane point coordinates, and normal is obtained.

c. All information for the tibia model 0001 prosthesis was obtained:

when PK = IMP # T #0001, all information including the tibial prosthesis model, color, three-dimensional prosthesis model, etc. of the tibial prosthesis model 0001 prosthesis is obtained.

2) Epidemiological analysis

Epidemiological analysis is mainly used to analyze the correlation between the frequency of occurrence of various medical events and different biomarkers. In practical application, the method is mainly used for preparing and defining products and operation indications, collecting appropriate people for clinical trial grouping and the like, such as the relationship between the frequency of adverse events of joint replacement operation and weight and the like. Such applications are implemented in a database in a converged operation, defined in the system as a flexible query.

Generally, through the second search, the first event collection is mainly to find all events meeting the conditions, all found events are grouped and collected according to the attributes, and then the required information is found through the second search.

(1) obtaining surgical data by a physician

a. Input PK = SUR # DR;

b. setting a time range and acquiring operation data in a time period;

c. acquiring operation data of a designated doctor;

d. if a specific data needs to be acquired, performing cross-mode secondary accurate query, and acquiring specific operation data by inputting PK = SUR # UUID.

(2) Obtaining surgical data through a prosthesis

a. Input PK = SUR # IMP;

b. setting a time range and acquiring operation data in a time period;

c. acquiring surgical data specifying the use of femoral (left)/femoral (right)/tibial prosthesis model 1;

d. if a specific data needs to be acquired, performing cross-modal secondary accurate query, and inputting PK = SUR # UUID to acquire specific operation data; by entering PK = SUR # UUID, SK = SUR # PAT, the patient PID can be obtained, followed by PAT # PID to obtain the specific patient data.

(3) Patient data acquisition by a physician

a. Input PK = DR;

b. setting a time range and acquiring patients in a time period;

c. acquiring a patient list of a designated doctor;

d. if specific data of a certain patient needs to be acquired, cross-modal secondary accurate query needs to be performed, and specific patient data can be acquired by inputting PK = PAT # PID.

(4) Checking prostheses according to colour

a. Input PK = IMP # CLR;

b. setting a time range and obtaining the prosthesis in the time period;

c. obtaining a prosthesis of a specified color;

d. and carrying out comparative analysis on the prostheses of the same color, different models and different manufacturers.

(5) Checking the prosthesis according to the model, and comparing the prosthesis among different companies of the same model

a. Input PK = IMP # ID;

b. setting a time range and obtaining the prosthesis in a time period;

c. obtaining a prosthesis of a specified model;

d. comparative analysis of the prosthesis between the same type and different companies was performed.

(6) Screening patients by age

a. Input PK = PAT;

b. setting a time range and acquiring patients in a time period;

c. setting an age group: for example 50 to 59 years old;

d. all patient data were acquired between 50 and 59 years of age.

4. Data expansion

Because the database has strong expandability and has various different expressions, a user can flexibly increase required data according to specific requirements. When data expansion is performed, the data expansion can be realized by adding index data or adding PK entries, and the specific description is as follows:

1) Augmenting index data

For example, if it is desired to add information about the manufacturer of the prosthesis, the following data can be added under the corresponding prosthesis:

for example, postoperative feedback needs to be added after the operation is completed, and the following data can be added under the corresponding operation data:

for example, if a patient needs to be screened by femur length, it can be achieved by adding data of the patient's leg length, specifically adding the following data:

2) Increase of PK term

If necessary, doctors, nurses, etc. can be included in the PK item, and then the data can be queried only by adding the corresponding index. Specific examples are as follows:

(1) the doctor data was added to the PK entry first:

(2) and adding an index:

data acquisition and storage

The system uses the surgical navigation robot to collect data, is used for recording orthopedic surgery data such as NoSQL heterogeneous data storage, instrument data and patient image data secondary storage and the like which are stored in an incremental mode in the surgery, collects various detailed data of the whole process (preoperative, intraoperative and postoperative) of orthopedic joint replacement surgery such as the type of a joint prosthesis, the placement position of the prosthesis, the surgical access and the installation process of the prosthesis and the like which are used by the surgical robot in the surgery process in practical application, and stores the data into a database according to the format defined by the database.

1. Data acquisition

The data acquisition equipment of the system mainly comprises a laser tracker, a laser target, a probe and the like, as shown in figure 6. Laser tracker: the laser scanning device is used for reading the relative positions of the two laser mark rakes in real time; two laser harrows: one on the femoral side of the knee joint and the other on the tibial side of the knee joint; knee plane tool: when the device is used for osteotomy navigation, a doctor is guided to confirm the osteotomy position and the position of an implanted prosthesis; and (3) probe: for acquisition of anatomical landmark points. In actual use, the laser tracker marks anatomical landmark points by capturing the coordinates of the probe relative to the laser target. The laser tracker captures the relative coordinates of the knee plane tool to determine the osteotomy face position, as shown in figure 4.

2. Data storage

Most data can be stored directly in the database, but the surgical instrument data or patient image data related to the business is usually large, and the data exchange speed of the system is greatly influenced if the database is used for storage. Therefore, the invention adopts the secondary storage middleware to store the large files, adopts a mode of recording the change of the file index to replace the frequent reading and writing of the large files, only reads and stores all data when the operation starts and ends, and dynamically loads the changed part through the file index in the operation process. The specific storage flow is shown in fig. 5.

storing and inquiring by using a key/value pair mode, wherein a primary key uniquely identifies a data tuple in a database, the database uses a partition key PK as the primary key, or a PK and a sequencing key SK are compounded to form the primary key, when the PK can uniquely identify each piece of data, the PK serves as the ID for identifying the tuple, and when different data tuples have the same PK, the SK is introduced as an identifier of auxiliary data, at the moment, the PK + SK is integrally used as the primary key to uniquely identify the data, in the key/value pair design, the primary key is unique in a table, and the structure of the value is flexible and changeable, so that the diversified expression of the relation between the data and the data is met; according to a specific implementation manner of the embodiment of the present disclosure, the method further includes:

the data query comprises two modes of precise query and flexible query.

the precise query is carried out by inputting key values;

when the limiting condition of accurate query does not need to be set, data query is directly carried out through cross-modal secondary accurate query.

data query is carried out in a precise query or flexible query mode, the precise query is carried out in a query mode of directly inputting key values (PK, SK) to obtain patient information, operation information and prosthesis information, the flexible query is carried out in a GSI index, and information meeting the conditions is obtained within a given time range;

a GSI (global system interface) table (PK: TYPE, SK: TIME) is designed for flexible query, during query, data can be located according to a query TYPE, then data meeting TIME requirements and corresponding conditions can be screened, and an index structure is designed as follows:

GSI PK＝TYPE(string)

GSI SK＝TIME(string)

based on the result obtained by query, when a medical accident and an adverse event occur, the cause of the accident is searched for to carry out backtracking analysis, or the association between the occurrence frequency of various medical events and different biomarkers is analyzed, all events meeting the conditions are found through secondary search and primary event collection, all found events are grouped and collected according to attributes, and then the required information is found through secondary search;

comparing the intraoperative data with preoperative data to analyze the positioning error of the operation, and mainly analyzing whether a computer-aided navigation system has the positioning error or not;

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The units described in the embodiments of the present disclosure may be implemented by software or hardware. Where the name of a unit does not in some cases constitute a limitation of the unit itself, for example, the first retrieving unit may also be described as a "unit for retrieving at least two internet protocol addresses".

It should be understood that portions of the present disclosure may be implemented in hardware, software, firmware, or a combination thereof.

The above description is only for the specific embodiments of the present disclosure, but the scope of the present disclosure is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present disclosure should be covered within the scope of the present disclosure. Therefore, the protection scope of the present disclosure shall be subject to the protection scope of the claims.

Claims

1. A method for designing heterogeneous data index of joint replacement surgery is characterized by comprising the following steps:

the intraoperative data model includes: the femoral primary registration anatomical landmark point, the femoral precise registration anatomical landmark point, the femoral anterior resection plane, the femoral posterior resection plane, the femoral distal resection plane, the femoral verification nail, the tibial primary registration anatomical landmark point, the tibial precise registration anatomical landmark point, the tibial resection plane, the tibial verification nail and the intraoperative gap balance curve;

2. The method of claim 1, further comprising:

all data of the system consists of a partition key PK representing an entity, a sequencing key SK representing PK attribute and other data;

PK is the partition key of the whole table, which is used for identifying the entity; there are 5 entities in the database: a patient, a left leg femoral prosthesis, a right leg femoral prosthesis, a tibial prosthesis, and an operation plan; the partition keys corresponding to the 5 entities are respectively: PAT # PID, IMP # FL # ID, IMP # FR # ID, IMP # T # ID and SUR # UUID; wherein PAT represents the patient, PID represents the patient ID, IMP # FL represents the left leg femoral prosthesis, ID represents the model, IMP # FR represents the right leg femoral prosthesis, IMP # T represents the tibial prosthesis, SUR represents the surgical plan, and UUID represents the unique surgical identifier; by the design form, the database is flexible, and the incorporation of extended entity fields into a PK column is supported as the database structure is extended, wherein the extended fields comprise data required by doctors, nurses and the like;

SK is the sort key of the whole table, used to identify the attribute; the patient data includes basic information of the patient, associated surgery and associated doctors; the basic information of the patient comprises attributes such as name, birthday, sex, home address and the like, and SK of the basic information is PAT # PID; correlating the surgical records received by the surgical record patient, wherein SK of the surgical records is SUR # UUID; the associated doctor records the information of the main doctor of the patient, and SK of the information is DR #0001 and represents No. 0001 doctor of the operation; the surgical plan contains a plurality of attributes including the surgical affected limb, the attending physician, the patient of the surgery, the preselected prosthesis model, the installed prosthesis model, the preoperative data, the intraoperative data, the postoperative data, the resection plane, the primary registration point, the fine registration point, and the gap balance curve, SK starts with "SUR #", SUR # PRE # LMK # HIPC represents the preoperative femoral center registration, where PRE represents the preoperative data and LMK represents the primary registration; SUR # IN # PLA # AP represents the element point of the anterior cutting plane of the femur during operation, wherein IN represents intraoperative data, and PLA represents the cutting plane; the operation data comprises the model of the replaced prosthesis, the installation position of the replaced prosthesis, each picking of the alignment points, the operation effect of various sensors, the calculation result of the surgical robot navigation system, the loading record of the operation scheme and the information 6 types of the successful storage of the operation scheme, wherein SK begins with 'OP #', OP # CII #0001 represents the operation of the type of the replaced prosthesis and indicates that the serial number is 0001; SK is expressed by multilayer structure, and redundant items are added, so that fast query can be realized;

other data have a variety of different expressions for expanding the partition keys PK according to specific needs.

3. The method of claim 2, further comprising:

the mode of key/value pair is used for storing and inquiring, the primary key in the database is used for uniquely identifying the data tuple, the database uses the partition key PK as the primary key, or the PK and the sequencing key SK are compounded to form the primary key, when the PK can uniquely identify each piece of data, the PK serves as the primary key to serve as the ID for identifying the tuple, and when different data tuples have the same PK, the SK is introduced to serve as the identifier of auxiliary data, at the moment, the PK + SK is integrally used as the primary key to uniquely identify the data, in the design of the key/value pair, the primary key is unique in the table, and the structure of the value is flexible and changeable, so that the diversified expression of the relation between the data and the data is met.

4. The method of claim 3, further comprising:

the data query comprises two modes of precise query and flexible query.

5. The method of claim 4, further comprising:

the precise query is carried out by inputting key values;

6. The method of claim 4, further comprising:

when the limit condition of flexible query needs to be set, after the limit condition is set for the input query value, data query is carried out through cross-modal secondary accurate query;

when the limit condition of flexible query does not need to be set, data query is directly carried out through cross-modal secondary accurate query.

7. The method of claim 4, further comprising:

the data query is carried out in a precise query or flexible query mode, the precise query obtains the query mode of patient information, operation information and prosthesis information by directly inputting key values (PK, SK), the flexible query carries out the query through a GSI index, and the information meeting the conditions is obtained within a given time range.

8. The method of claim 7, further comprising:

GSI PK＝TYPE(string)

GSI SK＝TIME(string)。

9. the method of claim 7, further comprising:

according to the rehabilitation record, the patient can be seen whether the patient recovers to normal after the operation or whether the living habit changes.

10. The method of claim 7, further comprising:

based on the results of the flexible queries, epidemiological analyses were performed for analyzing the association between the frequency of occurrence of various medical events and different biomarkers, for preparing definitions of products and surgical indications, for soliciting appropriate triage for clinical trials into groups, including the relationship between the frequency of occurrence of adverse events of joint replacement surgery and body weight.