CN112786167A

CN112786167A - Statistical method and device for times of operation cases applying antibacterial drugs based on MapReduce and big data

Info

Publication number: CN112786167A
Application number: CN202011311715.0A
Authority: CN
Inventors: 林�建; 霍瑞; 陈春平
Original assignee: Hangzhou Xinglin Information Technology Co ltd
Current assignee: Hangzhou Xinglin Information Technology Co ltd
Priority date: 2020-11-20
Filing date: 2020-11-20
Publication date: 2021-05-11
Anticipated expiration: 2040-11-20
Also published as: CN112786167B

Abstract

The invention provides a statistical method and a statistical device for times of operation cases applying antibacterial drugs based on MapReduce and big data, which are based on a MapReduce framework and utilize the parallel computing capability of machines under a distributed system to divide the times of cases of millions and tens of millions of inpatients which exceed the memory and storage limit of a server into tens of millions and hundreds of millions of small tasks for calculating the times of cases of hospital infection with multi-drug-resistant bacteria, execute the small tasks on a plurality of machines simultaneously, and generate a final result by summarizing intermediate output results of the small tasks. The invention can carry out massive parallel calculation on large data containing million, million and hundred million levels of inpatients according to provincial and urban areas, hospital grades, hospital beds, synthesis and specialization, public and civil calibers and the like.

Description

Statistical method and device for times of operation cases applying antibacterial drugs based on MapReduce and big data

Technical Field

The invention belongs to the technical field of antibacterial drug management, and particularly relates to a method and a device for counting the times of operation cases applying antibacterial drugs based on MapReduce and big data, in particular to the counting of the times of operation cases applying antibacterial drugs preventively in class I incision operations of inpatients, and the method and the device are particularly suitable for scenes that the data volume of patients to be processed far exceeds the storage capacity (magnetic disc) and the computing capacity (memory and CPU) of one server and the tasks cannot be split and distributed manually.

Background

The invention and application of the antibacterial drug bring convenience for human beings to treat a plurality of serious bacterial infectious diseases, and effectively reduce the death rate of various infectious diseases. The application of the antibacterial agent needs to be reasonably selected according to different infectious diseases.

For hospitalized patients, nosocomial infections are divided into two categories: one is exogenous infection, also called cross-infection, which refers to infection that a patient or a worker receives in a hospital through daily diagnosis and treatment activities, contact between the patient and the patient or from a polluted environment, such as infection occurring at a surgical site; the other is endogenous infection, also called self infection, which is the infection caused by the disturbance of normal flora in vivo, the activation of potential pathogenic bacteria in vivo, the displacement of resident microorganisms originally existing in the body cavity or body surface of a patient and the like in the process of receiving diagnosis and treatment because the resistance of the patient is reduced due to diseases. Surgery on hospitalized patients is a common cause of infection in patients. The harm caused by the surgical infection of the patient is very large, so that in the actual diagnosis and treatment process, antibacterial drugs are usually applied to the surgical patient in a preventive manner, and the surgical related infection is avoided.

However, the phenomenon of abuse of antibacterial drugs often occurs in clinic, so that pathogenic bacteria generate drug resistance to the antibacterial drugs, and the curing difficulty of bacterial infectious diseases is increased. Therefore, the antibacterial drugs should be used reasonably from the beginning of clinical practice, and abuse of the antibacterial drugs is firmly stopped. Therefore, the statistics of the number of the operation cases applying the antibacterial drugs has important significance for the management of the antibacterial drugs, and can provide important guidance for the treatment of the subsequent complications of the operation.

Therefore, how to realize the statistics of the number of the operation cases using the antibacterial drugs, especially the statistics of the number of the operation cases using the preventive drugs when the inpatients perform the class I incision surgery, becomes a problem to be solved in the field.

The operation cases of applying the antibacterial drugs are relatively easy to calculate in one medical institution, the number of people discharged from one common medical institution such as a third-class medical institution is about fifty thousand every year, and the state or provincial-class tap hospital has hundreds of thousands of people. The calculation of the key indexes is complex under the condition of large data of millions, billions and billions of inpatients of hundreds and thousands of medical institutions in provincial regions or nationwide ranges, 2749 third-level hospitals in the China in 2019, 9687 second-level hospitals in 2019 and 17487 thousands of inpatients in public hospitals, and the original result of one-time statistical analysis needs to be calculated in the last year.

Therefore, how to develop standardization, normalization and homogenization hospital infection monitoring in hundreds of hospitals and thousands of hospitals in one area and realize the frequency of operation examples applying antibacterial agents in a specified time period under the condition of big data of inpatients becomes the most urgent problem to be solved for developing the regional information monitoring platform.

Disclosure of Invention

The invention aims to provide a statistical method, a device, equipment and a storage medium for applying the times of operation cases of antibacterial drugs based on MapReduce and big data aiming at the defects of the prior art. The operation example frequency of the antibacterial agent is high in practicability, the operation example frequency can be accurately counted according to the needs of a user, and effective guidance can be provided for treatment and management of the antibacterial agent of the inpatient. Meanwhile, the problem of complex manual operation case frequency counting processing is avoided by automatically counting the operation case frequency.

In order to achieve the purpose, the invention adopts the following technical scheme:

the statistical method of the times of the operation cases applying the antibacterial drugs based on MapReduce and big data comprises the following steps:

s1, acquiring hospitalization process information A of the patient, and acquiring the hospitalization time and the discharge time of the patient based on the hospitalization process information, wherein the hospitalization time and the discharge time are jointly used as parameters g.MC2;

s2, acquiring operation information G of the patient, and acquiring operation information G (a) _ Y occurring in the current hospitalization period and operation information G (a) _ N occurring in the non-current hospitalization period in the operation information G based on the parameter g.MC2;

s3, judging whether the operation information G (a) Y has operation records, if yes, executing a step S3, and if not, outputting 0 operation example times of preventive application of antibacterial agents in the type I incision operation;

s4, acquiring the operation starting time and the operation ending time based on the operation information G (a) _ Y, and taking the operation starting time and the operation ending time as perioperative parameters g.QA4. optimal of the operation;

s5, receiving statistical time, an operating department, incision grade, operation classification, an operating doctor, an anesthesia mode, operation duration, ASA grading, an operation name, a healing grade, an operation position, NNIS grading, phase-selective emergency call, an operating room, operation times, an antibacterial drug grade and a drug administration mode selected by a user, and determining an authority department of the user according to identity information of the user;

s6, acquiring operation information G (S) Y meeting the statistical time, the operation department, the incision grade, the operation classification, the operation doctor, the anesthesia mode, the operation duration, the ASA score, the operation name, the healing grade, the operation position, the NNIS score, the phase-selective emergency call, the operation room, the operation times and the limitation of the authority department based on the operation information G (a) Y;

s7, judging whether the operation information G (S) -Y contains operation records, if yes, executing step S8, and if not, outputting 0 operation example times of preventive application of antibacterial agents in the type I incision operation;

s8, collecting an antibacterial medication record F, dividing the antibacterial medication order record F into an antibacterial medication record F (a) Y used during patient hospitalization and an antibacterial medication record F (a) N not used during patient hospitalization based on the parameter g.mc2;

s9, obtaining an antibacterial drug record F (d) Y in the antibacterial drug record F (a) Y, wherein the antibacterial drug record F (d) Y aims to prevent and meet the antibacterial drug grade and the administration mode limitation;

s10, judging whether the antibacterial drug record F (d) Y contains antibacterial drug information, if yes, executing step S11, and if not, outputting 0 times of operation cases of preventive application of antibacterial drugs in the type I incision operation;

s11, acquiring the order starting time and the order ending time based on the antibacterial drug record F (d) _ Y, and using the order starting time and the order ending time as the parameter g.THW of the starting and ending time period list of the order;

s12, dividing the operation information G (S) _ Y into operation information G (t) _ Y using antibacterial drugs in the perioperative period and operation information G (t) _ N not using antibacterial drugs in the perioperative period based on the parameter g.THW and the parameter g.QA4. optimal;

s13, outputting the operation example times of preventive application of the antibacterial drugs in the type I incision operation based on the number recorded in the operation information G (t) _ Y.

Further, the hospitalization process information comprises a patient case number, an admission department, admission time, an discharge department and discharge time; the operation information comprises a patient case number, an operation department, operation categories, an operating doctor, an anesthesia mode, an operation name, operation starting time, operation ending time, incision, healing grade, ASA, phase-selective emergency call, operation position, NNIS score, an operation room and operation times; the antibacterial drug records comprise patient case numbers, advice departments, antibacterial drug names, starting times, ending times, antibacterial drug grades, drug administration modes, drug purposes, advice doctors and advice doctor grades.

Further, the step S6 includes:

s61, according to the operation information G (a) _ Y and the statistical time, filtering to obtain the operation information G (b) _ Y in the statistical time range, and filtering the operation information G (b) _ N which is not in the statistical time range;

s62, according to the operation information G (b) _ Y and the authority department information, filtering to obtain the operation information G (c) _ Y in the authority range, and filtering the operation information G (c) _ N out of the authority range;

s63, according to the operation information G (c) _ Y and the selected operation department, filtering to obtain the operation information G (d) _ Y in the range of the selected operation department, and filtering out the operation information G (d) _ N which is not in the range;

s64, according to the operation information G (d) _ Y, filtering to obtain the operation information G (e) _ Y with the incision grade selected by the user as the I-type incision, and filtering the operation information G (e) _ N which is not in the selection range;

s65, according to the operation information G (e) _ Y and the selected operation classification, filtering to obtain the operation information G (f) _ Y in the selected operation classification range, and filtering out the operation information G (f) _ N not in the selected range;

s66, according to the operation information G (f) _ Y and the selected operation doctor, filtering to obtain operation information G (g) _ Y in the range of the selected operation doctor, and filtering operation information G (g) _ N out of the range;

s67, according to the operation information G (g) _ Y and the selected anesthesia mode, filtering to obtain operation information G (h) _ Y in the selected anesthesia mode range, and filtering operation information G (h) _ N out of the selected range;

s68, according to the operation information G (h) Y and the selected operation duration information, filtering to obtain operation information G (i) Y in the selected operation duration range, and filtering operation information G (i) N out of the selected range;

s69, according to the operation information G (i) _ Y and the selected ASA score, filtering to obtain operation information G (j) _ Y in the selected ASA score range, and filtering operation information G (j) _ N out of the selected range;

s610, filtering the operation information G (k) Y in the selected operation name range according to the operation information G (j) Y and the selected operation name, and filtering the operation information G (k) N out of the selected range;

s611, according to the operation information G (k) _ Y and the selected healing grade, filtering to obtain the operation information G (m) _ Y in the selected healing grade range and filtering the operation information G (m) _ N out of the selected range;

s612, filtering the operation information G (N) Y in the selected operation position range according to the operation information G (m) Y and the selected operation position information, and filtering the operation information G (N) N out of the selected range;

s613, according to the operation information G (N) _ Y and the selected NNIS score, filtering to obtain operation information G (p) _ Y in the selected NNIS score range, and filtering operation information G (p) _ N which is not in the selection range;

s614, filtering the operation information G (q) Y in the selected period selection emergency range according to the operation information G (p) Y and the selected period selection emergency information, and filtering the operation information G (q) N which is not in the selected range;

s615, according to the operation information G (q) _ Y and the selected operation room, filtering to obtain the operation information G (r) _ Y in the selected operation room range, and filtering out the operation information G (r) _ N out of the selected range;

s616, according to the operation information G (r) _ Y and the selected operation times, filtering to obtain the operation information G (S) _ Y in the selected operation time range, and filtering out the operation information G (S) _ N which is not in the selected range.

Further, the step S9 includes:

s91, dividing the antibacterial record F (a) Y into an antibacterial medical order F (b) Y for preventive medication and an antibacterial medical order F (b) N for non-preventive medication based on whether the medication purpose is preventive or not;

s92, dividing the antibacterial drug record F (b) Y into an antibacterial drug record F (c) Y consistent with the antibacterial drug administration mode selected by the user and an antibacterial drug record F (c) N inconsistent with the antibacterial drug administration mode selection based on the administration mode;

s93, dividing the antibacterial medicine records F (c) _ Y into antibacterial medicine records F (d) _ Y which are consistent with the antibacterial medicine grade selected by the user and antibacterial medicine records F (d) _ N which are not consistent with the antibacterial medicine grade selection based on the antibacterial medicine grade.

The invention also provides a statistical device for the number of operation cases applying the antibacterial drugs based on MapReduce and big data, which comprises the following steps:

the system comprises a first acquisition unit, a second acquisition unit and a third acquisition unit, wherein the first acquisition unit is used for acquiring hospitalization process information A of a patient, and acquiring the hospitalization time and the discharge time of the patient based on the hospitalization process information, and the hospitalization time and the discharge time are jointly used as a parameter g.MC2;

the first division unit of the operation information is used for acquiring operation information G of a patient, and acquiring operation information G (a) Y occurring in the current hospitalization period and operation information G (a) N occurring in the non-current hospitalization period in the operation information G based on the parameter g.MC2;

a first judging unit, configured to judge whether a surgical record exists in the surgical information g (a) _ Y, if yes, execute step S3, and if not, output 0 surgical example number of preventive application of an antibacterial agent in a type I incision surgery;

a second acquisition unit for acquiring the operation start time and the operation end time based on the operation information G (a) _ Y, and taking the operation start time and the operation end time as perioperative parameters g.QA4. optimal of the operation;

the third acquisition unit is used for receiving the statistical time, the operating department, the incision grade, the operation classification, the operating doctor, the anesthesia mode, the operation duration, the ASA score, the operation name, the healing grade, the operation position, the NNIS score, the phase-selective emergency call, the operating room, the operation times, the antibacterial medicine grade and the drug administration mode selected by the user, and determining the authority department of the user according to the identity information of the user;

the operation information dividing unit is used for acquiring operation information G(s) Y meeting the statistical time, the operation department, the incision grade, the operation classification, the operation doctor, the anesthesia mode, the operation duration, the ASA score, the operation name, the healing grade, the operation position, the NNIS score, the phase-selective emergency call, the operation room, the operation times and the limitation of the authority department based on the operation information G (a) Y;

a second determination unit, configured to determine whether a surgical record exists in the surgical information g (S) _ Y, if yes, execute step S8, and if not, output 0 surgical example number of preventive applications of antibacterial agents in the type I incision surgery;

an antibacterial drug record first dividing unit for acquiring an antibacterial drug record F, and dividing the antibacterial drug order record F into an antibacterial drug record F (a) used during the hospitalization of the patient and an antibacterial drug record F (a) used not during the hospitalization of the patient based on the parameter g.MC2;

the antibacterial drug record dividing unit is used for acquiring an antibacterial drug record F (d) Y in the antibacterial drug record F (a) Y, wherein the antibacterial drug record F (d) Y aims at preventing and meeting the antibacterial drug grade and administration mode limitations;

the third judging unit is used for judging whether the antibacterial drug information exists in the antibacterial drug record F (d) _ Y, if so, the fourth collecting unit is called, and if not, the operation example frequency of preventive application of the antibacterial drug in the type I incision operation is output to be 0;

the fourth acquisition unit is used for acquiring the medical order starting time and the medical order ending time based on the antibacterial drug record F (d) _ Y, and the medical order starting time and the medical order ending time are jointly used as the parameter g.THW of the starting and ending time period list of the medical order;

the fifth division unit of the antibacterial medicine record is used for dividing the operation information G(s) _ Y into operation information G (t) _ Y using the antibacterial medicine in the perioperative period and operation information G (t) _ N not using the antibacterial medicine in the perioperative period based on the parameter g.THW and the parameter g.QA4. optimal;

and the output unit is used for outputting the operation example times of preventive application of the antibacterial drugs in the type I incision operation based on the number recorded in the operation information G (t) _ Y.

Further, the operation information dividing unit includes:

the second operation information dividing unit is used for filtering operation information G (b) Y in the statistical time range according to the operation information G (a) Y and the statistical time, and filtering operation information G (b) N out of the statistical time range;

the operation information third dividing unit is used for filtering the operation information G (c) Y in the authority range according to the operation information G (b) Y and the authority department information, and filtering the operation information G (c) N out of the authority range;

the operation information fourth dividing unit is used for filtering operation information G (d) Y in the range of the selected operation department according to the operation information G (c) Y and the selected operation department, and filtering operation information G (d) N not in the range;

the operation information fifth dividing unit is used for filtering operation information G (e) Y of the I-type incision at the incision grade selected by the user according to the operation information G (d) Y and filtering operation information G (e) N not in the selection range;

the operation information sixth dividing unit is used for filtering operation information G (f) Y in the selected operation classification range according to the operation information G (e) Y and the selected operation classification, and filtering operation information G (f) N not in the selected operation classification range;

the operation information seventh dividing unit is used for filtering operation information G (g) Y in the range of the selected operating doctor and filtering operation information G (g) N out of the range according to the operation information G (f) Y and the selected operating doctor;

the operation information eighth dividing unit is used for filtering the operation information G (h) Y in the selected anesthesia mode range according to the operation information G (g) Y and the selected anesthesia mode, and filtering the operation information G (h) N out of the selected range;

the operation information ninth dividing unit is used for filtering the operation information G (i) Y in the selected operation duration range according to the operation information G (h) Y and the selected operation duration information, and filtering the operation information G (i) N which is not in the selected range;

the operation information tenth dividing unit is used for filtering operation information G (j) Y in the selected ASA scoring range according to the operation information G (i) Y and the selected ASA scoring, and filtering operation information G (j) N not in the selected range;

the operation information eleventh dividing unit is used for filtering the operation information G (k) Y in the selected operation name range according to the operation information G (j) Y and the selected operation name, and filtering the operation information G (k) N which is not in the selected range;

the operation information twelfth dividing unit is used for filtering the operation information G (m) Y in the selected healing grade range and filtering the operation information G (m) N out of the selected healing grade range according to the operation information G (k) Y and the selected healing grade;

the operation information thirteenth dividing unit is used for filtering the operation information G (N) Y in the selected operation position range according to the operation information G (m) Y and the selected operation position information, and filtering the operation information G (N) N out of the selected range;

the operation information fourteenth dividing unit is used for filtering operation information G (p) Y in the selected NNIS scoring range according to the operation information G (N) Y and the selected NNIS score, and filtering operation information G (p) N not in the selected NNIS scoring range;

the fifteenth surgical information dividing unit is used for filtering the surgical information G (q) Y in the selected phase selection emergency range according to the surgical information G (p) Y and the selected phase selection emergency information, and filtering the surgical information G (q) N out of the selected range;

the operation information sixteenth dividing unit is used for filtering the operation information G (r) Y in the selected operation room range according to the operation information G (q) Y and the selected operation room, and filtering the operation information G (r) N out of the selected range;

and the operation information seventeenth dividing unit is used for filtering the operation information G(s) Y in the selected operation frequency range according to the operation information G (r) Y and the selected operation frequency and filtering the operation information G(s) N out of the selected range.

Further, the antibacterial agent record dividing unit includes:

the second antibacterial record dividing unit is used for dividing the antibacterial record F (a) Y into an antibacterial medical order F (b) Y for preventive medication and an antibacterial medical order F (b) N for non-preventive medication based on whether the medication purpose is preventive or not;

the antibacterial drug record third dividing unit is used for dividing the antibacterial drug record F (b) _ Y into an antibacterial drug record F (c) _ Y which is consistent with the antibacterial drug administration mode selected by the user and an antibacterial drug record F (c) _ N which is not consistent with the antibacterial drug administration mode selection on the basis of the administration mode;

and the antibacterial medicine record fourth dividing unit is used for dividing the antibacterial medicine record F (c) _ Y into an antibacterial medicine record F (d) _ Y which is consistent with the grade of the antibacterial medicine selected by the user and an antibacterial medicine record F (d) _ N which is not consistent with the grade selection of the antibacterial medicine based on the grade of the antibacterial medicine.

The invention also provides computer equipment which is characterized by comprising a memory and a processor, wherein the memory is stored with a computer program, and the processor realizes the statistical method of the times of the operation cases applying the antibacterial drugs when executing the computer program.

The invention also provides a storage medium, which is characterized in that the storage medium stores a computer program, and the computer program can realize the statistical method of the times of the operation cases applying the antibacterial drugs when being executed by a processor.

The invention describes a specific implementation mode of statistics of the times of operation cases applying antibacterial drugs in detail, and determines the times of I-type incision surgery and preventive application of antibacterial drug operation cases of inpatients according to the authority department of a user by using hospitalization process information, antibacterial drug medical advice records, operation information, selected statistical time, an operation department, incision grades, operation classification, an operating doctor, an anesthesia mode, operation duration, ASA (acrylonitrile styrene acrylate copolymer) scores, operation names, healing grades, operation positions, NNIS (network connection information) scores, phase-selective emergency treatment, an operation room, operation times, antibacterial drug grades and a drug administration mode according to identity information of the user. The operation example frequency of the application of the antibacterial agent counted by the invention is strong in practicability, the operation example frequency can be accurately counted according to the needs of users, and effective guidance can be provided for the treatment and management of the antibacterial agent of inpatients. Meanwhile, the problem that the manual operation case frequency counting is complex is solved by automatically counting the operation case frequency.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on the drawings without creative efforts.

Fig. 1 is a schematic flow chart of a statistical method for the number of times of surgery cases using antibacterial agents based on MapReduce and big data according to an embodiment of the present invention;

fig. 2 is a schematic block diagram of each unit of a statistical device for the number of times of surgery cases applying antibacterial drugs based on MapReduce and big data, provided by an embodiment of the invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

It will be understood that the terms "comprises" and "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

The invention is further described with reference to the following drawings and specific examples, which are not intended to be limiting.

It is also to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the specification of the present invention and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.

It should be further understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

In the following examples, X (y) type specification:

x represents a data set of a certain type;

y represents a serial number used for distinguishing a front data set and a rear data set of the same type of data in different logic units;

x (y) represents a data set under different logical units for a certain type of data;

y represents a coincidence condition;

n represents nonconforming;

the embodiment provides a statistical method for the number of times of an operation example applying an antibacterial drug based on MapReduce and big data, and the statistical method is applied to a server, for example, a cloud server. The server obtains data for the hospital. Hospital data is processed. As shown in fig. 1, the statistical method of the number of the operation cases to which the antibacterial agent is applied includes the following steps S1 to S13:

the number of cases of preventive application of antibacterial agents in the type I incision surgery is the number of cases of type I incision surgery and preventive drug use in hospitalized patients. Determining that surgical patients who prophylactically apply antibacterial drugs in class I incision surgery need to meet: 1. the patients were hospitalized at the same time, and the time of admission and discharge of the patients was within the statistical time range. That is, the time period formed by the admission time and the discharge time of the patient is crossed with the statistical time; 2. Patients underwent type I incision surgery during hospitalization and had prophylactic use of antibacterial drugs during perioperative periods. The corresponding condition is that the perioperative period of the operation and the medication time period of preventive medication are crossed; 3. the condition of the selection of the user is satisfied.

The hospitalization process information is used for integrally recording the hospitalization process of the patient, and specifically comprises the patient case number, the hospital admission department, the hospital admission time, the hospital discharge department and the hospital discharge time. The method firstly acquires the hospitalization process information A of the patient, and further acquires the relevant information of the fields of the admission time and the discharge time, which are taken as the parameter g.MC2 together.

For example, hospitalization procedure information a is:

patient's case number	Admission department	Time of admission	Discharge department	Time of discharge
					123456(1)	Neurology department	2019-01-01 00:00:12	Rehabilitation department	2019-01-12 03:00:12

And (3) outputting: MC2 with a value of [ 2019-01-0100: 00:12,2019-01-1203: 00:12]

the operation information is used for recording the specific conditions of the operation performed by the patient, including the patient case number, the operating department, the operation category, the operator, the anesthesia mode, the operation name, the operation starting time, the operation ending time, the incision, the healing grade, the ASA, the phase-selective emergency call, the operation position, the NNIS score, the operating room and the operation times. In order to solve the problem of operation record information of wrong time which does not occur in the period of the current hospitalization, the invention firstly screens the collected operation information G, and selects the operation information G (a) _ Y which is performed in the time range of the patient's admission and discharge, namely the operation information G (a) _ Y which occurs in the period of the current hospitalization. Specifically, the invention filters out the operation information G (a) and N which does not occur during the current hospitalization period based on the comparison between the field of ' operation start time ' and ' operation end time ' in the operation information and the parameter g.MC2 of the hospitalization and discharge time, and obtains the operation information G (a) and Y which are performed in the time range of the patient's hospitalization and discharge.

For example, the collected surgical information G is:

for g.MC2 above [ 2019-01-0100: 00:12,2019-01-1203: 00:12], the corresponding G (a) _ Y is:

g (a) _ N is:

s3, judging whether the operation information G (a) Y has operation records, if yes, executing step S3, and if not, outputting 0 operation example frequency of preventive application antibacterial drugs in the type I incision operation.

Specifically, the invention judges according to the operation information G (a) _ Y, if the patient has records after the steps, the operation is continued downwards, if the patient has no records, the operation is ended, and the result 0 is output.

For example, for g (a) _ Y described above, two records are included, so execution of step S3 is continued.

the perioperative parameters are determined based on the operative information G (a) Y, and preparation is made for obtaining the intersection operative information in the perioperative period and the medical advice time range subsequently. The perioperative period is a whole process around the operation, starting from the decision of the patient to receive the operation treatment, and going to the basic recovery, including a period of time before, during and after the operation, and specifically, from the time of determining the operation treatment until the treatment related to the operation is substantially ended. In the present invention, the perioperative time is determined from one day before the operation start time to one day after the operation end time.

For example, for the above-mentioned surgical information g (a) _ Y, perioperative parameters g.qa4.operid, values are [ 2019-01-0608: 00:00,2019-01-0808: 30:00] and [ 2019-01-0809: 00:00,2019-01-1009: 30:00 ].

S5, receiving statistical time selected by a user, an operating department, an incision grade, an operation classification, an operating doctor, an anesthesia mode, an operation duration, an ASA score, an operation name, a healing grade, an operation position, an NNIS score, a phase-selective emergency call, an operating room, operation times, an antibacterial medicine grade and a drug administration mode, and determining an authority department of the user according to identity information of the user;

the invention is used for automatically counting the times of operation cases for preventively applying antibacterial drugs in the type I incision operation, so that a user is required to select a corresponding time period, namely the user selects corresponding counting time, and the type I incision operation patients discharged from the hospital within the counting time are counted and searched. In addition, for the type I incision surgery patient, the user usually manages the example times aiming at a specific surgery department, so that the invention also sets a corresponding surgery department besides counting the time. In addition, aiming at specific operations, the user can also select the operation name, operation classification, an operating doctor, an anesthesia mode, operation duration, ASA score, incision grade, healing grade, operation position, NNIS score, phase-selective emergency treatment, an operating room and operation times, so that the accurate statistics and monitoring of the times of the patient cases of hand type I incision operations are realized. In addition, the invention screens the record information related to the antibacterial drugs, so that the grade and the administration mode of the antibacterial drugs can be set according to the antibacterial drugs.

The hospital data has corresponding privacy, so that the statistics and management of the hospital data in the invention require a user to acquire corresponding data authority. The data authority of the user is related to the corresponding identity information, so that the invention determines the authority department of the user according to the identity information of the operating user, and counts and monitors the number of the patient cases of the type I incision operation on the data in the authority department.

in an embodiment of the present invention, the step S6 may include steps S61-S616, referring to fig. 2, where the step S6 is selected according to the statistical time, the operating department, the incision grade, the surgical classification, the surgeon, the anesthesia mode, the surgical duration, the ASA score, the surgical name, the healing grade, the surgical location, the NNIS score, the phase-selective emergency call, the operating room, the number of operations, and the authority department.

the method comprises the steps of firstly screening operation information G (a) _ Y occurring in the period of hospitalization on the basis of statistical time, specifically, acquiring a field of 'operation starting time' in the operation information G (a) _ Y occurring in the period of hospitalization, judging whether the 'operation starting time' in an operation record occurring in the period of hospitalization currently belongs to the range of statistical time period, if so, adding the operation record into the operation information G (b) _ Y in the statistical time period, and otherwise, adding the operation record into the operation information G (b) _ N which is not in the statistical time range.

For the above G (a) _ Y, the statistical time is [ 2019-01-0600: 00:00,2019-01-2023: 59:59], then G (b) _ Y is:

g (b) _ N is:

s62, according to the operation information G (b) _ Y and the authority department information, filtering to obtain the operation information G (c) _ Y in the authority range, and filtering the operation information G (c) _ N out of the authority range

Because the authority of each user is different, the invention screens the operation information G (b) _ Y based on the authority department, so that the data operated by the user is adaptive to the corresponding authority. And comparing the 'surgical department' field in the operation information with the authority department, and judging whether the 'surgical department' field belongs to the scope of the authority department. The operation information g (c) _ Y is operation information in departments that belong to the authority range managed by the user, and the operation information g (c) _ N is operation information in departments that do not belong to the authority range managed by the user.

For example, for the above g (b) _ Y, when the right department is all departments, g (c) _ Y is:

g (c) _ N is:

s63, according to the operation information G (c) _ Y and the selected operation department, filtering to obtain the operation information G (d) _ Y in the range of the selected operation department, filtering out the operation information G (d) _ N not in the range

In the invention, the number of times of the patient cases of the operation is monitored based on a specific operating room, and a user can manage the number of times of the patient cases of the operation aiming at the specific operating room, so that the operation information G (c) _ Y is screened based on the selected operating room, the counted and screened data is adaptive to the operating room selected by the user independently, and the user can select corresponding data according to the requirement to count the number of times of the patient cases of the operation from the specific operating room. And comparing the 'operating room' field in the operation information with the selected operating room, and judging whether the 'operating room' field belongs to the range of the selected operating room.

For example, for all departments selected by the user, g (c) _ Y and g (d) _ Y described above are:

g (d) N is:

the invention can manage the number of times of the patient cases of the operation aiming at the I-type incision so as to determine the operation condition of the I-type grade incision. Therefore, the invention screens the operation information G (d) _ Y based on the I-class grade incision, so that the statistical and screened data are adaptive to the I-class grade incision selected by the user, the user can select the corresponding data according to the requirement, and the times of the I-class grade incision operation in the patient are counted.

For example, for the above-mentioned G (d) _ Y, if the incision is a type I incision, G (e) _ Y is:

g (e) N is:

s65, according to the operation information G (e) _ Y and the selected operation classification, filtering to obtain operation information G (f) _ Y in the selected operation classification range, and filtering operation information G (f) _ N out of the selected range;

the operation classification is a set of operations with certain rules, for example, the operation classification is hernia operation, and the classification includes inguinal hernia recovery, laparoscopic hernia repair, hernia high ligation, and the like. Therefore, the invention screens the operation information G (e) Y based on the selected operation classification, so that the statistical and screened data is adaptive to the operation classification selected by the user, the user can select the corresponding data as required, and the patient case frequency of the specific operation classification is counted.

For example, the user does not limit the surgical category, and g (e) _ Y, g (f) _ Y is the same as g (e) _ Y, and g (f) _ N is null, as described above.

the invention can manage the number of times of operating patients aiming at specific operating doctors so as to determine the occurrence condition of the infection of the operating part executed by a designated doctor. Therefore, the invention screens the operation information G (f) Y based on the selected operation doctor, so that the statistical and screened data are adaptive to the operation doctor selected by the user independently, the user can select the corresponding data according to the requirement, and the times of the patient cases of the operation of the specific operation doctor are counted.

For example, the user is not restricted to the surgeon, and g (f) _ Y, g (g) _ Y is the same as g (f) _ Y, and g (g) _ N is null, as described above.

the invention can manage the number of times of operating patient cases aiming at a specific anesthesia mode so as to determine the occurrence condition of the surgical site infection of a designated anesthesia mode. Therefore, the invention screens the operation information G (g) _ Y based on the selected anesthesia mode, so that the statistical and screened data are adaptive to the anesthesia mode selected by the user independently, the user can select the corresponding data according to the requirement, and the times of the patient cases operated under the specific anesthesia mode are counted.

For example, the user is not restricted to the anesthesia mode, and G (g) _ Y, G (h) _ Y and G (g) _ Y are the same, and G (h) _ N is empty.

the user can manage the number of times of the surgical patient according to specific surgical time so as to determine the surgical conditions of different surgical time. Therefore, the invention screens the operation information G (h) Y based on the selected operation duration, so that the statistical and screened data are adaptive to the operation duration selected by the user independently, the user can select the corresponding data according to the requirement, and the times of the patient cases of the operation under the specific operation duration are counted.

For example, the user does not limit the operation time length, and for g (h) _ Y described above, g (i) _ Y is the same as g (h) _ Y, and g (i) _ N is null.

the ASA score is a system for classifying patients' physical condition and surgical risk by the American Society of Anesthesiologists (ASA). The ASA rating is based on the patient's physical condition and rules for classifying surgical risks, with higher ASA and higher mortality. According to the invention, a user can manage the number of times of the surgery patient cases according to the specific ASA scores so as to determine the surgery conditions with different ASA scores. Therefore, the operation information G (i) _ Y is screened based on the selected ASA scores, so that the statistical and screening data are adaptive to the ASA scores selected by the user, the user can select corresponding data according to needs, and the times of the patient cases of the operation corresponding to the ASA scores are counted.

For example, the user does not limit the ASA score, and for g (i) _ Y described above, g (j) _ Y is the same as g (i) _ Y, and g (j) _ N is null.

in the actual monitoring, the user needs to monitor the information of the number of the cases of the surgical patients with different surgical names, and the adaptation is carried out through the step. Therefore, the invention screens the operation information G (j) _ Y based on the selected operation name, so that the counted and screened data is adaptive to the operation name selected by the user independently, and the user can select the corresponding data as required and count the patient case frequency of the specific operation name. And comparing the 'operation name' field in the operation information with the selected operation name, and judging whether the 'operation name' field belongs to the range of the selected operation name.

For example, the user does not limit the operation name, and for g (j) _ Y described above, g (k) _ Y is the same as g (j) _ Y, and g (k) _ N is null.

the user of the invention can manage the times of the surgical patient cases aiming at the specific healing grade so as to determine the surgical conditions of different healing grades. Therefore, the invention screens the operation information G (k) Y based on the selected healing grade, so that the counted and screened data is adaptive to the healing grade selected by the user, the user can select corresponding data according to the requirement, and the patient case frequency of the operation with the specific healing grade is counted.

For example, the user does not limit the level of healing, and for g (k) Y described above, g (m) Y is the same as g (k) Y, and g (m) N is empty.

the invention can manage the number of times of operating patients aiming at specific operation positions so as to determine the operation conditions of different operation positions. The operation positions are divided into superficial incision, deep incision and organ lacuna. Therefore, the invention screens the operation information G (m) Y based on the selected operation position, so that the counted and screened data is adaptive to the operation position selected by the user, the user can select the corresponding data according to the requirement, and the patient case frequency in the operation of the specific operation position is counted.

For example, the user does not restrict the surgical site, and g (m) _ Y, g (N) _ Y is the same as g (m) _ Y, and g (N) _ N is null, as described above.

the general "operational risk stratification" method of the international medical quality index system is to divide the operation into four grades, i.e., the NNIS0 grade, the NNIS1 grade, the NNIS2 grade and the NNIS3 grade, according to the "operational risk stratification criteria (NNIS)" in the United states of America' Hospital infection monitoring Manual. The user can manage the times of the surgical patient cases according to different NNIS scores so as to determine the surgical conditions of the different NNIS scores. Therefore, the invention screens the operation information G (n) _ Y based on the selected NNIS scores, so that the statistical and screened data are adaptive to the NNIS scores selected by the user independently, the user can select corresponding data as required, and the times of patient cases of specific NNIS scoring operations are counted.

For example, the user does not limit the NNIS score, and for G (N) _ Y described above, G (p) _ Y is the same as G (N) _ Y, and G (p) _ N is null.

the invention can manage the times of the surgical patient cases aiming at different surgical types (phase selection emergency treatment) so as to determine the surgical situation of the phase selection emergency treatment. Therefore, the invention screens the operation information G (p) Y based on the selected phase-selective emergency treatment, so that the statistical and screening data are adaptive to the phase-selective emergency treatment selected by the user, the user can select the corresponding data according to the requirement, and the times of the patient cases of the specific phase-selective emergency treatment operation are counted.

For example, the user is not limited to phase selection emergency treatment, and g (p) _ Y, g (q) _ Y is the same as g (p) _ Y, and g (q) _ N is null.

the invention can manage the times of the surgical patient cases aiming at the specific operating room so as to determine the surgical conditions of different operating rooms. Therefore, the invention screens the operation information G (q) _ Y based on the selected operation room, so that the statistical and screened data are adaptive to the operation room selected by the user, the user can select the corresponding data according to the requirement, and the times of the patient cases operating in the specific operation room are counted.

For example, the user does not limit the operating room, and g (q) _ Y, g (r) _ Y is the same as g (q) _ Y, and g (r) _ N is empty, as described above.

S616, according to the operation information G (r) _ Y and the selected operation times, filtering to obtain operation information G (S) _ Y in the selected operation time range, and filtering operation information G (S) _ N out of the selected range;

the invention can manage the number of times of the surgical patient according to the specific number of times of the surgery so as to determine the surgery conditions of different surgery times. Therefore, the invention screens the operation information G (r) _ Y based on the selected operation times, so that the counted and screened data is adaptive to the operation times selected by the user independently, the user can select the corresponding data according to the needs, and the times of the patient cases in the operation with the specific operation times are counted.

For example, the user does not limit the number of operations, and g (r) _ Y, g(s) _ Y and g (r) _ Y are the same, and g(s) _ N is null.

S7, judging whether the operation information G (S) _ Y has operation records, if yes, executing step S8, and if not, outputting 0 operation example frequency of preventive application antibacterial drugs in the type I incision operation.

Specifically, the invention judges according to the operation information G(s) _ Y, if the patient has records after the steps, the operation is continued to be carried out downwards, if the patient has no records, the operation is ended, and the result 0 is output.

For example, for g (S) _ Y described above, two records are included, so execution of step S8 is continued.

the antibacterial drug record F is used for recording the advice information of the doctor on each patient, and specifically comprises the patient case number, the advice department, the antibacterial drug name, the starting time, the ending time, the antibacterial drug grade, the drug administration mode, the drug purpose, the doctor and the doctor level. Patients who use antibacterial drugs in a normal observation period should have the start time and the end time of the antibacterial drug order record within the hospitalization time range of the patients, so the invention screens obviously wrong data according to the parameter g.MC2. Specifically, the invention filters out the antibacterial drug records F (a) and N which are not used during the patient's hospital stay period based on the comparison between the fields of' start time 'and' end time 'in the antibacterial drug order records and the parameter g.MC2 of the hospital entrance and discharge time, and obtains the antibacterial drug records F (a) and Y which are used during the patient's hospital stay period by the 'start time' and 'end time'.

For example, antibacterial drug record F is:

patient's case number

Prescribing department

Name of antibacterial drug

Starting time

End time

Mode of administration

Purpose of medication

123456(1)

Neurology department

Cefuroxime

2019-01-03 08:00:00

2019-01-07 08:30:00

Is administered orally

Prevention of

123456(1)

Neurology department

Cefuroxime

2019-01-02 08:00:00

2019-01-02 08:30:00

Is pumped into

Treatment of

For g.mc2 above, f (a) _ Y is:

patient's case number

Prescribing department

Name of antibacterial drug

Starting time

End time

Mode of administration

Purpose of medication

123456(1)

Neurology department

Cefuroxime

2019-01-03 08:00:00

2019-01-07 08:30:00

Is administered orally

Prevention of

123456(1)

Neurology department

Cefuroxime

2019-01-02 08:00:00

2019-01-02 08:30:00

Is pumped into

Treatment of

F (a) N is:

patient's case number

Prescribing department

Name of antibacterial drug

Starting time

End time

Mode of administration

Purpose of medication

in an embodiment of the present invention, referring to fig. 1, the step S9 may include steps S91 to S93.

S91, dividing the antibacterial drug record F (a) Y into an antibacterial drug order F (b) Y for preventive medication and an antibacterial drug order F (b) N for non-preventive medication based on whether the medication purpose is preventive or not;

the record of the antibacterial agent for non-prophylactic purposes does not require monitoring of this indicator. Therefore, the invention screens the antibacterial drug record F (a) _ Y based on the 'purpose of administration' field in the antibacterial drug record. When the field of the purpose of medication is 'prevention', the record belongs to the antibacterial record F (b) _ Y, otherwise, the record belongs to the antibacterial record F (b) _ N.

For F (a) _ Y, F (b) _ Y mentioned above:

patient's case number

Prescribing department

Name of antibacterial drug

Starting time

End time

Mode of administration

Purpose of medication

123456(1)

Neurology department

Cefuroxime

2019-01-03 08:00:00

2019-01-06 08:30:00

Is administered orally

Prevention of

F(b)_N：

Patient's case number

Prescribing department

Name of antibacterial drug

Starting time

End time

Mode of administration

Purpose of medication

123456(1)

Neurology department

Cefuroxime

2019-01-02 08:00:00

2019-01-02 08:30:00

Is pumped into

Treatment of

S92, dividing the antibacterial drug record F (b) Y into an antibacterial drug record F (c) Y consistent with the administration mode of the antibacterial drug selected by the user and an antibacterial drug record F (c) N inconsistent with the selection of the antibacterial drug administration mode based on the administration mode;

the invention screens the antibacterial drug records F (b) Y based on the 'administration mode' field in the antibacterial drug records. When the 'administration mode' field is consistent with the administration mode selected by the user, the field belongs to the antibacterial drug record F (c) _ Y, otherwise, the field belongs to the antibacterial drug record F (c) _ N.

For example, when the mode of administration of the antibacterial agent is selected to be oral administration, for f (b) Y described above, f (c) Y is:

patient's case number

Prescribing department

Name of antibacterial drug

Starting time

End time

Mode of administration

Purpose of medication

123456(1)

Neurology department

Cefuroxime

2019-01-03 08:00:00

2019-01-07 08:30:00

Is administered orally

Prevention of

F(c)_N：

Patient's case number

Prescribing department

Name of antibacterial drug

Starting time

End time

Mode of administration

Purpose of medication

123456(1)

Neurology department

Cefuroxime

2019-01-02 08:00:00

2019-01-02 08:30:00

Is pumped into

Treatment of

S93, dividing the antibacterial drug record F (c) _ Y into an antibacterial drug record F (d) _ Y which is consistent with the antibacterial drug grade selected by the user and an antibacterial drug record F (d) _ N which is not consistent with the antibacterial drug grade selection based on the antibacterial drug grade;

the invention screens the antibacterial drug record F (c) Y based on the antibacterial drug grade field in the antibacterial drug record. When the antibacterial medicine grade field is consistent with the antibacterial medicine grade selected by the user, the antibacterial medicine record F (d) Y belongs to, otherwise, the antibacterial medicine record F (d) N belongs to.

For example, when no grade of antimicrobial is selected, F (c) _ Y, F (d) _ Y, and F (c) _ Y are the same as described above, and F (d) _ N is empty.

S10, judging whether the antibacterial drug record F (d) Y contains antibacterial drug information, if yes, executing step S11, and if not, outputting 0 operation example times of preventive application of the antibacterial drug in the type I incision operation.

Specifically, the invention judges according to the antibacterial drug record F (d) _ Y, if the patient has records after the steps, the operation is continued downwards, if the patient has no records, the operation is ended, and the result is 0.

For example, for f (d) _ Y described above, one record is included, so execution of step S11 is continued.

the invention determines the parameter g.thw of the start-stop time period list of the order based on the antibacterial drug record f (d) _ Y. Thw is a parameter list consisting of the order start time and the order end time. Specifically, the fields of the start time and the end time in the antibacterial drug record f (d) _ Y are obtained, and for each medical order, the corresponding parameter g.thw is generated as [ start time and end time ].

For F (d) Y mentioned above, g.THW is [ 2019-01-0308: 00:00,2019-01-0708: 30:00 ].

S12, dividing the operation information G (S) Y into operation information G (t) Y using antibacterial drugs in the perioperative period and operation information G (t) N not using antibacterial drugs in the perioperative period based on the parameter g.THW and the parameter g.QA4. optimal;

specifically, the parameter g.THW and the parameter g.QA4. optimal are compared, whether the parameter g.THW and the parameter g.QA4. optimal are crossed or not is judged, if the parameter g.THW and the parameter g.QA4. optimal are crossed, the operation information G (t) is Y for using the antibacterial drugs in the perioperative period, otherwise, the operation information G (t) is N for not using the antibacterial drugs in the perioperative period, and the operation records of which the perioperative period and the advice start-stop period are not crossed are filtered.

For the above-mentioned operation information g(s) _ Y, parameter g.thw, parameter g.qa4. optimal, g (t) _ Y is:

g (t) _ N is:

The operation information g (t) _ Y obtained by the above-mentioned processing is the operation record of the hospitalized patient for the type I incision operation and the use of the preventive medicine. And if the record in the operation information G (t) _ Y is null, 0 is output, and if the record is not null, the operation example number of preventive application of the antibacterial agent in the corresponding type I incision operation is output. When a specific operation record needs to be output, G (t) _ Y is output.

Since the operation information g (t) _ Y includes one record, the number of operation cases for prophylactic application of the antibacterial agent in the type I incision operation is 1.

Fig. 2 is a schematic block diagram of a device for counting the number of surgical cases applying antibacterial drugs based on MapReduce and big data according to an embodiment of the present invention. As shown in fig. 2, the present invention also provides a statistical apparatus for the number of times of surgical examples applying antibacterial agents based on MapReduce and big data, corresponding to the statistical method for the number of times of surgical examples applying antibacterial agents. The statistical device for the number of times of the procedure using the antibacterial agent includes a unit for performing the statistical method for the number of times of the procedure using the antibacterial agent, and the device may be configured in a server. Specifically, referring to fig. 2, the device for counting the number of surgical cases using an antibacterial agent includes a first collecting unit, a first surgical information dividing unit, a first judging unit, a second collecting unit, a third collecting unit, a surgical information dividing unit, a second judging unit, a first antibacterial agent record dividing unit, a second antibacterial agent record dividing unit, a third judging unit, a fourth collecting unit, a fifth antibacterial agent record dividing unit, and an output unit.

The system comprises a first acquisition unit, a second acquisition unit and a third acquisition unit, wherein the first acquisition unit is used for acquiring hospitalization process information A of a patient, and acquiring the hospitalization time and the discharge time of the patient based on the hospitalization process information, and the hospitalization time and the discharge time are jointly used as a parameter g.MC2; the first division unit of the operation information is used for acquiring operation information G of a patient, and acquiring operation information G (a) Y occurring in the current hospitalization period and operation information G (a) N occurring in the non-current hospitalization period in the operation information G based on the parameter g.MC2; the first judging unit is used for judging whether the surgical record exists in the surgical information G (a) Y, if so, the second collecting unit is called, and if not, the operation example frequency of preventive application of antibacterial drugs in the type I incision surgery is output to be 0; the second acquisition unit acquires the operation starting time and the operation ending time based on the operation information G (a) _ Y and takes the operation starting time and the operation ending time as perioperative parameters g.QA4. optimal of the operation; the third acquisition unit is used for receiving statistical time, an operating department, incision grades, operation classifications, an operating doctor, anesthesia modes, operation duration, ASA scores, operation names, healing grades, operation positions, NNIS scores, phase-selective emergency calls, operating rooms, operation times, antibacterial drug grades and drug administration modes selected by a user, and determining the authority department of the user according to the identity information of the user; the operation information dividing unit is used for acquiring operation information G(s) Y meeting the limitation of the statistical time, the operation department, the incision grade, the operation classification, the operation doctor, the anesthesia mode, the operation duration, the ASA score, the operation name, the healing grade, the operation position, the NNIS score, the phase-selective emergency call, the operation room, the operation times and the authority department based on the operation information G (a) Y; the second judging unit is used for judging whether the operation record exists in the operation information G(s) _ Y or not, if so, the first division unit is called to record the antibacterial drug, and if not, the operation example frequency of preventive application of the antibacterial drug in the I-type incision operation is output to be 0; an antibacterial drug record first dividing unit for acquiring an antibacterial drug record F, and dividing the antibacterial drug order record F into an antibacterial drug record F (a) Y used during the hospitalization of the patient and an antibacterial drug record F (a) N not used during the hospitalization of the patient based on the parameter g.MC2; the antibacterial drug record dividing unit is used for acquiring an antibacterial drug record F (d) Y in the antibacterial drug record F (a) Y, wherein the antibacterial drug record F (d) Y aims at preventing and meeting the antibacterial drug grade and administration mode limitations; the third judging unit is used for judging whether the antibacterial drug information exists in the antibacterial drug record F (d) _ Y, if so, the fourth collecting unit is called, and if not, the operation example frequency of preventive application of the antibacterial drug in the type I incision operation is output to be 0; the fourth acquisition unit is used for acquiring the medical order starting time and the medical order ending time based on the antibacterial drug record F (d) _ Y, and the medical order starting time and the medical order ending time are jointly used as the parameter g.THW of the starting and ending time period list of the medical order; the fifth division unit for recording the antibacterial drugs is used for dividing the operation information G(s) _ Y into operation information G (t) _ Y using the antibacterial drugs in the perioperative period and operation information G (t) _ N not using the antibacterial drugs in the perioperative period based on the parameter g.THW and the parameter g.QA4. optimal; and the output unit is used for outputting the operation example times of preventive application of the antibacterial drugs in the type I incision operation based on the number recorded in the operation information G (t) _ Y.

In one embodiment, the surgical information dividing unit includes a second dividing unit to a seventeenth dividing unit of the surgical information.

In one embodiment, the antimicrobial record dividing unit includes an antimicrobial record second dividing unit, an antimicrobial record third dividing unit, and an antimicrobial record fourth dividing unit.

An antibacterial record second dividing unit configured to divide the antibacterial record f (a) _ Y into an antibacterial medical order f (b) _ Y for preventive medication and an antibacterial medical order f (b) _ N for non-preventive medication, based on whether the medication purpose is preventive or not;

and the antibacterial medicine record fourth dividing unit is used for dividing the antibacterial medicine record F (c) _ Y into an antibacterial medicine record F (d) _ Y which is consistent with the antibacterial medicine grade selected by the user and an antibacterial medicine record F (d) _ N which is not consistent with the antibacterial medicine grade selection based on the antibacterial medicine grade.

It should be noted that, as can be clearly understood by those skilled in the art, the statistics device for the number of times of the operation example using the antibacterial agent and the specific implementation process of each unit may refer to the corresponding description in the foregoing method embodiment, and for convenience and brevity of description, no further description is provided herein.

The above-mentioned statistical means for the number of times of the procedure using the antibacterial agent may be implemented in the form of a computer program, which may be run on a computer device.

The computer device may be a server, wherein the server may be an independent server or a server cluster composed of a plurality of servers.

The computer device includes a processor, a memory, and a network interface connected by a system bus, where the memory may include a non-volatile storage medium and an internal memory.

The non-volatile storage medium may store an operating system and a computer program. The computer program includes program instructions that, when executed, cause a processor to perform a statistical method of a number of surgical cases in which an antimicrobial drug is applied.

The processor is used to provide computational and control capabilities to support the operation of the overall computer device.

The internal memory provides an environment for execution of a computer program on a non-volatile storage medium, which when executed by the processor, causes the processor to perform a count of a number of instances of surgery to which an antimicrobial drug has been applied.

The network interface is used for network communication with other devices. Those skilled in the art will appreciate that the above-described computer device configurations are merely part of the configurations associated with the present application and do not constitute limitations on the computer devices to which the present application may be applied, and that a particular computer device may include more or less components than those shown in the figures, or may combine certain components, or have a different arrangement of components.

Wherein the processor is configured to run a computer program stored in the memory, the program implementing the method for counting the number of surgical cases to which the antibacterial agent is applied according to the first embodiment.

It should be understood that in the embodiments of the present Application, the Processor may be a Central Processing Unit (CPU), and the Processor may also be other general purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, and the like. Wherein a general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

It will be understood by those skilled in the art that all or part of the processes of the method for implementing the above embodiments may be implemented by a computer program instructing the relevant hardware. The computer program includes program instructions, and the computer program may be stored in a storage medium, which is a computer-readable storage medium. The program instructions are executed by at least one processor in the computer system to implement the flow steps of the embodiments of the method described above.

The invention also provides a storage medium. The storage medium may be a computer-readable storage medium. The storage medium stores a computer program, wherein the computer program, when executed by the processor, causes the processor to perform a statistical method for the number of times of surgical examples using an antibacterial agent according to one embodiment.

The storage medium may be a usb disk, a removable hard disk, a Read-Only Memory (ROM), a magnetic disk, or an optical disk, which can store various computer readable storage media.

Those of ordinary skill in the art will appreciate that the elements and algorithm steps of the examples described in connection with the embodiments disclosed herein may be embodied in electronic hardware, computer software, or combinations of both, and that the components and steps of the examples have been described in a functional general in the foregoing description for the purpose of illustrating clearly the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.

In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative. For example, the division of each unit is only one logic function division, and there may be another division manner in actual implementation. For example, various elements or components may be combined or may be integrated into another system, or some features may be omitted, or not implemented.

The steps in the method of the embodiment of the invention can be sequentially adjusted, combined and deleted according to actual needs. The units in the device of the embodiment of the invention can be merged, divided and deleted according to actual needs. In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling a computer device (which may be a personal computer, a terminal, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention.

It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. The statistical method of the times of the operation cases applying the antibacterial drugs based on MapReduce and big data is characterized by comprising the following steps:

s6, acquiring operation information G (S) _ Y meeting the statistical time, the operation department, the incision grade, the operation classification, the operation doctor, the anesthesia mode, the operation duration, the ASA score, the operation name, the healing grade, the operation position, the NNIS score, the phase-selective emergency call, the operation room, the operation times and the limitation of the authority department based on the operation information G (a) _ Y;

s9, obtaining an antibacterial drug record F (d) Y in the antibacterial drug record F (a) Y, wherein the antibacterial drug record F (d) Y aims to prevent and meet the antibacterial drug grade and administration mode limitations;

s10, judging whether the antibacterial drug record F (d) Y contains antibacterial drug information, if yes, executing step S11, and if not, outputting 0 times of operation examples of preventive application of antibacterial drugs in the type I incision operation;

2. The statistical method of claim 1, wherein the hospitalization procedure information includes patient case number, hospital admission department, hospital admission time, hospital discharge department, hospital discharge time; the operation information comprises a patient case number, an operation department, operation categories, an operating doctor, an anesthesia mode, an operation name, operation starting time, operation ending time, an incision, a healing grade, ASA, phase-selective emergency call, an operation position, NNIS scores, an operation room and operation times; the antibacterial drug records comprise patient case numbers, advice departments, antibacterial drug names, starting times, ending times, antibacterial drug grades, drug administration modes, drug purposes, advice doctors and advice doctor grades.

3. The statistical method according to claim 2, wherein the step S6 includes:

s616, according to the operation information G (r) _ Y and the selected operation times, filtering to obtain the operation information G (S) _ Y in the selected operation time selection range, and filtering out the operation information G (S) _ N which is not in the selected range.

4. The statistical method according to claim 2, wherein the step S9 includes:

5. Statistics device based on operation example number of using antibiotic medicine of MapReduce and big data, characterized by includes:

a first judging unit, configured to judge whether a surgical record exists in the surgical information g (a) _ Y, if yes, execute step S3, and if not, output a number of procedure cases for prophylactic application of an antibacterial agent in a type I incision surgery as 0;

a second determination unit, configured to determine whether a surgical record exists in the surgical information g (S) _ Y, if yes, execute step S8, and if not, output a number of procedure cases for prophylactic application of an antibacterial agent in a type I incision surgery as 0;

6. The statistical apparatus of claim 5, wherein the hospitalization procedure information comprises patient case number, hospital admission department, hospital admission time, hospital discharge department, hospital discharge time; the operation information comprises a patient case number, an operation department, operation categories, an operating doctor, an anesthesia mode, an operation name, operation starting time, operation ending time, an incision, a healing grade, ASA, phase-selective emergency call, an operation position, NNIS scores, an operation room and operation times; the antibacterial drug records comprise patient case numbers, advice departments, antibacterial drug names, starting times, ending times, antibacterial drug grades, drug administration modes, drug purposes, advice doctors and advice doctor grades.

7. The statistical apparatus according to claim 6, wherein the surgery information dividing unit includes:

the second surgical information dividing unit is used for filtering the surgical information G (b) Y in the statistical time range according to the surgical information G (a) Y and the statistical time, and filtering the surgical information G (b) N out of the statistical time range;

the operation information third dividing unit is used for filtering operation information G (c) Y in the authority range and filtering operation information G (c) N out of the authority range according to the operation information G (b) Y and the authority department information;

the operation information fifth dividing unit is used for filtering operation information G (e) Y of the I-type incision at the incision grade selected by the user according to the operation information G (d) Y and filtering operation information G (e) N which is not in the selection range;

the operation information ninth dividing unit is used for filtering the operation information G (i) Y in the selected operation duration range according to the operation information G (h) Y and the selected operation duration information, and filtering the operation information G (i) N out of the selected range;

the operation information fourteenth dividing unit is used for filtering operation information G (p) Y in the selected NNIS score range according to the operation information G (N) Y and the selected NNIS score, and filtering operation information G (p) N not in the selected NNIS score range;

and the operation information seventeenth dividing unit is used for filtering the operation information G(s) _ Y in the selected operation frequency range according to the operation information G (r) _ Y and the selected operation frequency and filtering the operation information G(s) _ N which is not in the selected range.

8. The statistical device according to claim 6, wherein the antibacterial agent record division unit comprises:

the antibacterial drug record third dividing unit is used for dividing the antibacterial drug record F (b) _ Y into an antibacterial drug record F (c) _ Y which is consistent with the antibacterial drug administration mode selected by the user and an antibacterial drug record F (c) _ N which is not consistent with the antibacterial drug administration mode selected by the user on the basis of the administration mode;

and the antibacterial medicine record fourth dividing unit is used for dividing the antibacterial medicine record F (c) _ Y into an antibacterial medicine record F (d) _ Y with the grade consistent with the grade of the antibacterial medicine selected by the user and an antibacterial medicine record F (d) _ N without the grade selection of the antibacterial medicine based on the grade of the antibacterial medicine.

9. A computer arrangement, characterized in that the arrangement comprises a memory having stored thereon a computer program and a processor implementing the method according to any of claims 1-4 when executing the computer program.

10. A storage medium, characterized in that the storage medium stores a computer program which, when executed by a processor, implements the method according to any one of claims 1 to 4.