# Cleaning Quality Control Management of Medical Equipment in Hospital Disinfection Supply Room Based on Smart Medicine

Authors: Meixia Wu; Qing Wang; Zhuolin Cheng
Journal: Computational Intelligence and Neuroscience
 (2022)

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## Abstract

With the continuous improvement of medical level, the demand for medical devices increases year by year, and it is necessary to track the quality and safety of medical devices. Establishing the cleaning quality control management of medical devices can not only reduce medical accidents and inhibit the spread of counterfeit or substandard medical devices but also help enterprises find the source of problems, determine the flow of the same batch of products, and warn relevant enterprises to take measures after the occurrence of problem products, and ultimately ensure the rights and interests of consumers. This study aims to study the cleaning quality control management of medical equipment in the hospital disinfection supply room based on smart medical care and proposes related concepts of smart medical care, as well as related theories of Internet of Things technology and medical equipment tracking system and related concepts of medical equipment cleaning. In this study, by comparing the cleaning compliance rates of the two groups of medical devices through smart medical care, it can be seen that 100% of the research group applying program-based management is significantly higher than 76.6% of the conventional management path. There was statistical significance in the data comparison between groups (P<0.05). Therefore, programmatic management is more targeted than conventional management paths.


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## Body

## 1. Introduction

Clinical gadgets allude to the instruments, gear, instruments, in vitro demonstrative reagents, alignments, materials, and other comparable or related articles straightforwardly or by implication utilized for the human body, and it likewise includes the PC programming required. It requires very high stability and a wide variety of products. Due to the demand of more than one billion people, and due to the explosive growth of the demand for medical devices, so many medical devices are produced by mass production. However, due to the lack of strict cleaning of medical devices, it also makes it more and more difficult to manage medical devices and causes some harm to the human body. Smart medical treatment is an effective attempt to get rid of the current medical dilemma by relying on the continuous development of information technology and combined with the new medical reform scheme. It is an important part of providing medical and health security for the masses and will also become an important basis for building a harmonious medical system in the future. Based on this, this study tries to build a management study on the cleaning and quality control of medical devices.With the large use of medical devices and complex varieties, it will be impossible to use manual use process tracking and supervision. Only with the help of modern technology, the whole process and seamless management of medical equipment can be realized. Medical device management is to carry out comprehensive supervision in every link of clinical application of medical devices, but now, there are few problems of research on medical devices and lack of systematic device management. There are few professional papers and works on this, let mention the number of books on medical devices, equipment, and related management knowledge at the same time. The safety problem of medical devices has reached the point of urgent solution. Automatic identification of one of the core technologies of the Internet of Things brings opportunities to solve these problems.The innovations of this study are as follows: (1) the research on the cleaning quality control management of medical equipment in the hospital disinfection supply room based on smart medical treatment is innovative and practical; (2) it is beneficial to protect the health and safety of the people. (3) It has very important theoretical significance and practical value.


## 2. Related Work

With the advancement of social economy, savvy clinical consideration has been progressively applied in numerous clinical fields, and numerous researchers have explored it. With the exacerbation of populace maturing, different lower furthest point loss of motion brought about by different infections regularly happens, and individuals’ interest for lower limit care and recovery is developing. Geng et al. consolidated wise clinical innovation and lower limit kinematics model and proposed to lay out a lower furthest point joint consideration and restoration framework in light of canny clinical treatment. This showed that the framework was planned with logical restoration activity and simple to work and can be utilized for recovery preparation subsequent to further development of wearing solace [1]. Wang et al. proposed a green range asset distribution system in view of the Hungarian strategy. To check the exhibition of the proposed calculation, he likewise performed framework-level Monte Carlo recreations, which showed the positive presentation of the proposed calculation over customary avaricious calculations [2]. To assist individuals with picking a reasonable clinical coordinator, Wang proposed an issue with the versatile contracting region strike wolf bundle streamlining calculation utilizing an irregular pursuit methodology (ORRSS-WPOA) [3]. Li et al. examined the application field of 5G correspondence innovation in the counteraction and control of the 2019 Covid illness (COVID-19) scourge and laid out a 5G shrewd clinical benefit framework for the anticipation and control of the new Covid pneumonia in China [4]. Wu et al. depended on information from 8920 patients with nonlittle cell cellular breakdown in the lungs gathered from various clinical frameworks in three medical clinics in China. In light of the savvy clinical framework, based on the keen clinical framework, a convolutional brain organization (CNNSAD)-based helper finding model for nonlittle cell cellular breakdown in the lungs was developed [5]. Yan and Zhang predominantly talked about the liver assurance system and retention advancement innovation of silibinin in light of wise clinical examination [6]. Liu et al.’s examination on keen clinical consideration as another application innovation of the Internet of Things (IoT) has stood out at home and abroad by advancing clinical informatization, modernization, and intelligence [7]. Zhang fabricated a MIoT stage and exhibited a situation, in which a prepared convolutional brain organization (CNN) model for anticipating cellular breakdown in the lungs muddled by pneumonic embolism can be gone after. In any case, the deficiency of these examinations is that the models built utilizing shrewd clinical consideration are not sufficiently logical and the information should be gotten to the next level.


## 3. Smart Healthcare and Related Methods

### 3.1. Related Concepts of Smart Healthcare

#### 3.1.1. Status Quo of Smart Medical Development

Shrewd clinical consideration alludes to furnishing clients with advantageous and quick clinical benefits through advancements like the Internet of Things, large information, and distributed computing to meet the different requirements of clients in their day-to-day clinical consideration. Clinical and wellbeing administrations are a perplexing complex, including infection counteraction, medical care, sickness conclusion and therapy, medical procedure, recovery, and subject logical examination. The intervention of smart medical care will bring huge opportunities and challenges to the medical and health industry [8, 9]. Smart healthcare connects information related to medical construction in an intelligent and perceptible way to create an intelligent healthcare ecosystem [10–12]. Users can not only meet medical needs through smart medical care but also enjoy health prevention services. Smart medical-related pictures are shown in Figure 1.Figure 1
Smart healthcare.
(a)(b)The conceptual diagram of smart medical care is shown in Figure2. Smart healthcare has the following characteristics: (1) interconnected; (2) collaborative; (3) preventive; (4) popular; (5) innovative; (6) reliable.Figure 2
Conceptual diagram of smart healthcare.


#### 3.1.2. The Goal of Building a Smart Medical System

The brilliant clinical framework built in this study utilizes a versatile terminal to gather the physiological data of the human body, and the gathered physiological data will be communicated to the shrewd clinical stockpiling and handling terminal through the remote organization in the briefest time by the terminal framework [13, 14]. The capacity and handling framework module will understand the constant stockpiling of the client’s physiological data input from every terminal. Simultaneously, the brilliant clinical framework likewise shows the physiological data of the human body on time, so that specialists can see the physiological observing data of the concerned client progressively. The overall system functional structure is shown in Figure 3.Figure 3
Functional framework diagram of smart medical system based on portable terminal.The information transmission and data storing module generally comprehends the continuous transmission of the information assembled by the adaptable terminal to the limit end of the insightful clinical structure. Considering that coronary sickness is very fragile to protect time, the time delay between information grouping, far-off transmission, and data accumulating ought to be seen as in the arrangement of information transmission and data storing limit modules. At the same time, to simplify it for the diagnosing expert to make heads or tails of the continuous situation of the patient more, the indispensably visual video transmission work is turned on when basic, and the truly visual video is shipped off the terminal of the astute clinical end system through the distant transmission module [15]. This module sends the data gathered by the versatile terminal to the data stockpiling and brilliant clinical handling terminal as quickly as time permits, which is more helpful for the acknowledgment of the well-being observing of the human body. The savvy clinical handling is utilized to understand the ongoing showcase of the information gathered by the versatile terminal and send the physiological data of the human body to the applicable diagnosing doctors through the brilliant clinical framework. This allows doctors to obtain real-time information of patients as soon as possible and at the same time can quickly make diagnosis information, which is conducive to realizing timely assistance to patients.


#### 3.1.3. Architecture of Smart Medical System

According to the goal of building a smart medical system based on portable terminals, the overall system framework constructed in this study is shown in Figure4.Figure 4
Structure diagram of smart medical system based on portable terminal.The smart medical system based on portable terminals utilizes the convenience of modern smart terminals and combines the new physiological signal acquisition sensors to upload the user’s physiological information in real time. Once the system has more in-depth requirements (such as when the user’s physiological signals show signs of danger), the portable terminal will enable the video acquisition and transmission function and transmit the user’s real-time video information to the rear smart medical diagnosis center, which is convenient for doctors to make a quick diagnosis [16, 17]. In order to realize the real-time transmission and storage of user information, the system designs an information transmission and storage scheme based on GPRS, Internet, socket, multithreading, and other technologies. The solution focuses on ensuring that the user’s physiological information can be transmitted, stored, and diagnosed in real time. This better ensures that in the event of an emergency, the smart medical diagnosis center can obtain the user’s information more quickly, laying a technical foundation for the quickest first aid measures [18].From the above analysis, it can be seen that there are many modules that need to be constructed for the construction of a smart medical system. This study will implement some modules in the smart medical system, and these modules include portable terminal information collection and processing, information transmission, data center port monitoring, data real-time storage, and data dynamic realization modules. These modules build a small smart medical system, complete an overall process from data collection, transmission, and processing, and build a verification platform for the smart medical system, which lays a necessary foundation for the subsequent in-depth research on the smart medical system.


#### 3.1.4. Realization Module

The previous section expounds on the overall system framework of smart medical care constructed in this study [19]. Based on this framework, this study completes a small smart medical verification platform system. The modules of the work completed in this study are shown in Figure 5. It lays an important foundation for verifying the rationality of the smart medical system and for the later research and development of smart cognition.Figure 5
Module diagram of the smart medical system implemented in this study.The main control program of the portable terminal is mainly used to complete the logic control and data flow of the mobile terminal. In this module, the monitoring of the data collection port is implemented after running the portable terminal. After the data buffer of the data acquisition port acquires the data, it will acquire the data through the data bus. Then, it calls the 3G communication module to connect to the portable terminal data center. After the block connecting the link is released, the 3G communication module will be called and the collected data will be uploaded.In the smart medical system, in order to collect the physiological information of the user into the system, a mobile terminal is needed, so each user has a mobile phone terminal connected to the data center in real time. Considering that various terminals often collect human physiological information, the amount of data increases sharply with the increase of mobile phone terminals. Therefore, the data centers need to establish multithreaded monitoring threads to send the data uploaded by various portable terminals [20].Meanwhile, the user physiological information data uploaded to the data center must also be stored in the database in time. Considering the many tasks to be processed during the system execution, the resources occupied by the system are limited to each portable terminal monitoring unit. Therefore, each monitoring unit must keep the physiological information data in the database in the cache as soon as possible.At the same time, the data center is also the intermediary of the smart medical system and the portable terminal to control the command transmission. When the smart medical system needs to send instructions to the portable terminal. For example, when a user has an emergency and needs to transfer the user’s GPS information and video information to the data center, the data center needs to transmit the control command to the portable terminal, so that the portable terminal opens the GPS and other information collection and transmission functions.The data dynamic display module is used to dynamically draw the real-time collected user physiological information dynamically to the display terminal to achieve a quick diagnosis. Considering the problems of information transmission and data storage, it is necessary to constantly extract the physiological information of the required monitoring users from the data center and draw it to the display terminal by using dynamic display technology.The above-described portable terminal, data center, and dynamic data display functions are the main contents of the research and design in this study. Through the design and implementation of the above functions, the real-time collection, transmission, storage, and display of remote data in the intelligent medical system are completed [21]. A smart medical verification system based on portable terminals has been built, laying a good foundation for the subsequent in-depth research and development of smart medical system.


### 3.2. Theories Related to IoT Technology and Medical Device Tracking System

#### 3.2.1. The Basic Composition of the Internet of Things

The Internet of Things is a data-oriented application network with functions such as information perception, data processing, data backhaul, and decision support. In a broad sense, the Internet of Things can achieve 4 As, that is, anyone (Anybody), anytime (Anytime), place (Anywhere), using the network to exchange information with anything (Anything), it is a future development vision. In a narrow sense, as long as the items are connected by sensors, the network formed belongs to the category of the Internet of Things. At the core of the IoT definition, there are three main characteristics: addressable, controllable, and communicable.Sensor networks, information service systems, etc. constitute the hardware platform of the Internet of Things, as shown in Figure6. Software and hardware are closely related. The two cannot be separated and independent. Different types of IoT will have different uses, resulting in different performance in software.Figure 6
Schematic diagram of IoT hardware platform.


#### 3.2.2. Internet of Things System Framework

The Internet of Things is a new type of network that emerges after combining some emerging perception technologies and wireless communication technologies. It is an extension of the Internet and computer networks. The variety of information technologies involved in the Internet of Things has gradually evolved into an aggregated system. The principal portion of the IoT reference model can be isolated into four layers: application layer, business/application support layer, network layer, and gadget layer. In addition, it has cross-laminate capability and safety capabilities.


#### 3.2.3. The Basic Framework of the Hospital Internet of Things

IoT needs to leverage a range of existing or evolving advanced technologies. In order to connect physical objects and virtual objects to provide better services, a simple generalization of the IoT reference model is made [22], as shown in Figure 7.Figure 7
Basic framework of hospital IoT.The Internet of Things is a new mode of communication where objects in the virtual extended world and the physical world are interconnected. It can turn virtual world objects into reality by running a large number of applications and services, so it has no small challenges. IoT involves different knowledge domains such as ubiquitous computing, network communication, object recognition, and special data processing.


### 3.3. Data Mining Technology Based on Classification

#### 3.3.1. Basic Concepts of Classification Analysis

The K-nearest neighbor (KNN) method is the simplest classification algorithm. Classification is a data mining technique that is used to map the data in the data set to a certain category according to the characteristics of the existing data set [23, 24].


#### 3.3.2. Classification Model and Evaluation Index

To build a classification model, the classifier must first be trained using a reliable dataset of a certain size as a training set. By analyzing the characteristics of the training set, a unique and accurate judgment description is found for each class to classify the subsequent test data.


#### 3.3.3. Classical Classification Algorithm

(1) Nearest Neighbor Algorithm. The K-nearest neighbor classification algorithm is the simplest classification algorithm. K-nearest neighbor literally means that each sample is represented by its K nearest neighbor samples [25]. The core idea is that most of the K samples around the position of the sample in the space with the dimension of the feature value belong to a certain class, and then the sample belongs to this class.The commonly used correlation pairs in the K-nearest neighbor algorithm are as follows:Distance and Included Angle. Let d(X, Y) be the distance between samples X and Y, and the distance function d(X, Y) should satisfy the following conditions:(a)
(1)DAi,Bi=0.If and only if(2)Ai=Bi.(b)
Non-negativity is given by the following equation:(3)DAi,Bi≥0.(c)
Symmetry is given by the following equation:(4)DAi,Bi=DBi,Ai.(d)
Triangular inequality is given by the following equation:(5)DAi,Bi≤DAi,Ak+DAk,Bi.Minkowski distance is given by the following equation:(6)DAi,Bi=Ai−Biq=∑k=1mAik−Ajkq1/q,where(7)q∈1,+∞.Sinceq can take any value from 1 to +∞, the Minkowski distance is a generalization of an infinite number of distance metrics. In particular, when q is 1, it is the Manhattan distance, when q is 2, it is the Euclidean distance, and when q is +∞, it is the Chebyshev distance.Manhattan distance is given by the following equation:(8)DAi,Bi=Ai−Bi=∑k=1mAik−Ajk.Euclidean distance is given by the following equation:(9)DAi,Bi=Ai−Bi2=∑k=1mAik−Ajk21/2.Chebyshev distance is given by the following equation:(10)DAi,Bi=Ai−Bi∞=∑k=1mAik−Ajk∞1/∞.Cosine of Included Angle. Let the included angle between sample Ai,Bi be δAi,Bi and δAi,Bi∈0,180. The cosine of the included angle is given by the following equation:(11)cosδAi,Bi=∑k=1mAikAjk∑k=1mAik2∑k=1mAjk22.The algorithm steps are as follows: (1) the data item to be classified is A, calculate the distance or angle between it and each data object in the training sample set; (2) find the closest distance between the object and the data object in the training set; (3) count the categories of each data object in turn, and find the category that contains the most numbers, that is, the most common subcategory; (4) divide the data to be divided into this category; (5) repeat the above steps until the end of classification data.(2) Decision Tree. A choice tree is a tree structure. A characteristic tree is built from the traits of each example in the preparation set. It is built through and through. The leaf hubs of the tree are the classes utilized for arrangement, and the nonleaf hubs are feature credits, the parts of the tree are choice circumstances Figure 8.Figure 8
Decision tree algorithm.The way in to the choice tree calculation is to choose proper qualities as hubs at each layer and to decide suitable limits for the chose hubs to expand the expectation exactness. Another key is to properly prune the decision tree to thwart overfitting [26]:①
Commonplace Choice Tree ID3 calculation. In the event that a likelihood circulation W1,W2,…Wn is given, how much data conveyed by the dissemination is known as the entropy of the likelihood dispersion. The absolute entropy of the framework is as follows:(12)IW1,W2,…,Wn=−∑i=1nWilog2Wi.Given a preparation setP, where the quantity of test focuses is signified as P, assuming there are t various classes Bii=1,2,…,k and Gi test focuses in class Bi, and Gi/G is utilized to gauge the likelihood that any example has a place with Bi, then, at that point,(13)IG1G,G2G,…,GkG=−∑i=1kGiGlog2GiG.For traitC with l various qualities c1,c2,…,cl, it tends to be utilized to isolate the preparation set G into l subsets. Allowing Gij to be the quantity of tests having a place with Bi in Gij, the entropy (anticipated data) of the subset partitioned by C is as follows:(14)EC=∑i=1kGij+G2j+⋯+GkjGIG1j,G2j,…,Gkj.For a given subsetDj, the data entropy is as follows:(15)IG1j,G2j,…,Gkj=−∑i=1kWijlog2Wij,IGC=IG1G,G2G,…GkG−EC.The main issue in the obtaining of affiliation rules is the colossal measure of information to be dissected. Accordingly, working on the proficiency of the calculation is the most significant. If by some stroke of good luck one affiliation rule calculation is utilized, then there are numerous information to be investigated, and the execution season of the calculation will turn out to be extremely lengthy.②
Choice Tree C4.5 Calculation. The pruning technique took on by the C4.5 calculation in this primer is negative blunder pruning. The standard of this calculation is investigated extensively under. AnticipatingV(t) is how much preparing set cases at focus point t and p(t) is how much misclassified occasions at focus t, A proportion of the misclassification rate is as follows:(16)Ht=GtVt.The coherence amended blunder rate is as follows:(17)H′t=Gt+1/2Vt.In a like manner, the misclassification pace of subtreeTt is as follows:(18)HTt=∑Gi∑Vi,where i takes the leaves of the subtree, so the helped misclassification rate is as follows:(19)H′Tt=∑Gi+1/2∑Vi.Then,(20)H′Tt=∑Gi+VTi/2∑Vi,where VT is the quantity of leaves on the hub.Utilizing the preparation information, subtrees consistently produce less mistake than their comparing hubs. Be that as it may, this is not the situation while utilizing adjusted numbers, since they rely upon the quantity of leaves, in addition to the quantity of mistakes.The standard deviation is calculated as follows:(21)SEu′Ti=u′Tt∗Vt−u′TiVt.Among them, for the node, there are(22)u′t=Gt+12.For subtrees, we have(23)u′Tt=∑Gi+VTtVTt.Accordingly, if the amount of misclassifications after subtree correction is more critical than the amount of misclassifications after center revision, this pruning methodology proposes pruning the subtree. The potential gain of this approach is that a comparable planning set is used for tree improvement and tree pruning, and it is especially speedy considering the way that only one scope is required and each center point is reviewed once.


### 3.4. Quality Management in Medical Device Cleaning Process

#### 3.4.1. Importance of Medical Device Cleaning Process

The cleaning process of medical equipment is an important part of hospital infection management and an important part of hospital medical equipment disinfection management. It plays an important role in improving the quality of medical equipment cleaning. In addition, the quality management of the medical device cleaning process also plays an important role. The whole process requires professional management personnel training, effective cleaning procedures and specifications, and the improvement of hospital disinfection management. In addition, various cleaning links need to be monitored. The supply room also has a lot to do with improving the quality of medical device cleaning. At the same time, in order to improve the cleaning quality of medical equipment, some people need to plan to use medical equipment.


#### 3.4.2. Measures to Improve the Quality of Instrument Cleaning

The method to improve the quality of instrument cleaning is shown in Figure9.Figure 9
Ways to improve the quality of instrument cleaning.


## 3.1. Related Concepts of Smart Healthcare

### 3.1.1. Status Quo of Smart Medical Development

Shrewd clinical consideration alludes to furnishing clients with advantageous and quick clinical benefits through advancements like the Internet of Things, large information, and distributed computing to meet the different requirements of clients in their day-to-day clinical consideration. Clinical and wellbeing administrations are a perplexing complex, including infection counteraction, medical care, sickness conclusion and therapy, medical procedure, recovery, and subject logical examination. The intervention of smart medical care will bring huge opportunities and challenges to the medical and health industry [8, 9]. Smart healthcare connects information related to medical construction in an intelligent and perceptible way to create an intelligent healthcare ecosystem [10–12]. Users can not only meet medical needs through smart medical care but also enjoy health prevention services. Smart medical-related pictures are shown in Figure 1.Figure 1
Smart healthcare.
(a)(b)The conceptual diagram of smart medical care is shown in Figure2. Smart healthcare has the following characteristics: (1) interconnected; (2) collaborative; (3) preventive; (4) popular; (5) innovative; (6) reliable.Figure 2
Conceptual diagram of smart healthcare.


### 3.1.2. The Goal of Building a Smart Medical System

The brilliant clinical framework built in this study utilizes a versatile terminal to gather the physiological data of the human body, and the gathered physiological data will be communicated to the shrewd clinical stockpiling and handling terminal through the remote organization in the briefest time by the terminal framework [13, 14]. The capacity and handling framework module will understand the constant stockpiling of the client’s physiological data input from every terminal. Simultaneously, the brilliant clinical framework likewise shows the physiological data of the human body on time, so that specialists can see the physiological observing data of the concerned client progressively. The overall system functional structure is shown in Figure 3.Figure 3
Functional framework diagram of smart medical system based on portable terminal.The information transmission and data storing module generally comprehends the continuous transmission of the information assembled by the adaptable terminal to the limit end of the insightful clinical structure. Considering that coronary sickness is very fragile to protect time, the time delay between information grouping, far-off transmission, and data accumulating ought to be seen as in the arrangement of information transmission and data storing limit modules. At the same time, to simplify it for the diagnosing expert to make heads or tails of the continuous situation of the patient more, the indispensably visual video transmission work is turned on when basic, and the truly visual video is shipped off the terminal of the astute clinical end system through the distant transmission module [15]. This module sends the data gathered by the versatile terminal to the data stockpiling and brilliant clinical handling terminal as quickly as time permits, which is more helpful for the acknowledgment of the well-being observing of the human body. The savvy clinical handling is utilized to understand the ongoing showcase of the information gathered by the versatile terminal and send the physiological data of the human body to the applicable diagnosing doctors through the brilliant clinical framework. This allows doctors to obtain real-time information of patients as soon as possible and at the same time can quickly make diagnosis information, which is conducive to realizing timely assistance to patients.


### 3.1.3. Architecture of Smart Medical System

According to the goal of building a smart medical system based on portable terminals, the overall system framework constructed in this study is shown in Figure4.Figure 4
Structure diagram of smart medical system based on portable terminal.The smart medical system based on portable terminals utilizes the convenience of modern smart terminals and combines the new physiological signal acquisition sensors to upload the user’s physiological information in real time. Once the system has more in-depth requirements (such as when the user’s physiological signals show signs of danger), the portable terminal will enable the video acquisition and transmission function and transmit the user’s real-time video information to the rear smart medical diagnosis center, which is convenient for doctors to make a quick diagnosis [16, 17]. In order to realize the real-time transmission and storage of user information, the system designs an information transmission and storage scheme based on GPRS, Internet, socket, multithreading, and other technologies. The solution focuses on ensuring that the user’s physiological information can be transmitted, stored, and diagnosed in real time. This better ensures that in the event of an emergency, the smart medical diagnosis center can obtain the user’s information more quickly, laying a technical foundation for the quickest first aid measures [18].From the above analysis, it can be seen that there are many modules that need to be constructed for the construction of a smart medical system. This study will implement some modules in the smart medical system, and these modules include portable terminal information collection and processing, information transmission, data center port monitoring, data real-time storage, and data dynamic realization modules. These modules build a small smart medical system, complete an overall process from data collection, transmission, and processing, and build a verification platform for the smart medical system, which lays a necessary foundation for the subsequent in-depth research on the smart medical system.


### 3.1.4. Realization Module

The previous section expounds on the overall system framework of smart medical care constructed in this study [19]. Based on this framework, this study completes a small smart medical verification platform system. The modules of the work completed in this study are shown in Figure 5. It lays an important foundation for verifying the rationality of the smart medical system and for the later research and development of smart cognition.Figure 5
Module diagram of the smart medical system implemented in this study.The main control program of the portable terminal is mainly used to complete the logic control and data flow of the mobile terminal. In this module, the monitoring of the data collection port is implemented after running the portable terminal. After the data buffer of the data acquisition port acquires the data, it will acquire the data through the data bus. Then, it calls the 3G communication module to connect to the portable terminal data center. After the block connecting the link is released, the 3G communication module will be called and the collected data will be uploaded.In the smart medical system, in order to collect the physiological information of the user into the system, a mobile terminal is needed, so each user has a mobile phone terminal connected to the data center in real time. Considering that various terminals often collect human physiological information, the amount of data increases sharply with the increase of mobile phone terminals. Therefore, the data centers need to establish multithreaded monitoring threads to send the data uploaded by various portable terminals [20].Meanwhile, the user physiological information data uploaded to the data center must also be stored in the database in time. Considering the many tasks to be processed during the system execution, the resources occupied by the system are limited to each portable terminal monitoring unit. Therefore, each monitoring unit must keep the physiological information data in the database in the cache as soon as possible.At the same time, the data center is also the intermediary of the smart medical system and the portable terminal to control the command transmission. When the smart medical system needs to send instructions to the portable terminal. For example, when a user has an emergency and needs to transfer the user’s GPS information and video information to the data center, the data center needs to transmit the control command to the portable terminal, so that the portable terminal opens the GPS and other information collection and transmission functions.The data dynamic display module is used to dynamically draw the real-time collected user physiological information dynamically to the display terminal to achieve a quick diagnosis. Considering the problems of information transmission and data storage, it is necessary to constantly extract the physiological information of the required monitoring users from the data center and draw it to the display terminal by using dynamic display technology.The above-described portable terminal, data center, and dynamic data display functions are the main contents of the research and design in this study. Through the design and implementation of the above functions, the real-time collection, transmission, storage, and display of remote data in the intelligent medical system are completed [21]. A smart medical verification system based on portable terminals has been built, laying a good foundation for the subsequent in-depth research and development of smart medical system.


## 3.1.1. Status Quo of Smart Medical Development

Shrewd clinical consideration alludes to furnishing clients with advantageous and quick clinical benefits through advancements like the Internet of Things, large information, and distributed computing to meet the different requirements of clients in their day-to-day clinical consideration. Clinical and wellbeing administrations are a perplexing complex, including infection counteraction, medical care, sickness conclusion and therapy, medical procedure, recovery, and subject logical examination. The intervention of smart medical care will bring huge opportunities and challenges to the medical and health industry [8, 9]. Smart healthcare connects information related to medical construction in an intelligent and perceptible way to create an intelligent healthcare ecosystem [10–12]. Users can not only meet medical needs through smart medical care but also enjoy health prevention services. Smart medical-related pictures are shown in Figure 1.Figure 1
Smart healthcare.
(a)(b)The conceptual diagram of smart medical care is shown in Figure2. Smart healthcare has the following characteristics: (1) interconnected; (2) collaborative; (3) preventive; (4) popular; (5) innovative; (6) reliable.Figure 2
Conceptual diagram of smart healthcare.


## 3.1.2. The Goal of Building a Smart Medical System

The brilliant clinical framework built in this study utilizes a versatile terminal to gather the physiological data of the human body, and the gathered physiological data will be communicated to the shrewd clinical stockpiling and handling terminal through the remote organization in the briefest time by the terminal framework [13, 14]. The capacity and handling framework module will understand the constant stockpiling of the client’s physiological data input from every terminal. Simultaneously, the brilliant clinical framework likewise shows the physiological data of the human body on time, so that specialists can see the physiological observing data of the concerned client progressively. The overall system functional structure is shown in Figure 3.Figure 3
Functional framework diagram of smart medical system based on portable terminal.The information transmission and data storing module generally comprehends the continuous transmission of the information assembled by the adaptable terminal to the limit end of the insightful clinical structure. Considering that coronary sickness is very fragile to protect time, the time delay between information grouping, far-off transmission, and data accumulating ought to be seen as in the arrangement of information transmission and data storing limit modules. At the same time, to simplify it for the diagnosing expert to make heads or tails of the continuous situation of the patient more, the indispensably visual video transmission work is turned on when basic, and the truly visual video is shipped off the terminal of the astute clinical end system through the distant transmission module [15]. This module sends the data gathered by the versatile terminal to the data stockpiling and brilliant clinical handling terminal as quickly as time permits, which is more helpful for the acknowledgment of the well-being observing of the human body. The savvy clinical handling is utilized to understand the ongoing showcase of the information gathered by the versatile terminal and send the physiological data of the human body to the applicable diagnosing doctors through the brilliant clinical framework. This allows doctors to obtain real-time information of patients as soon as possible and at the same time can quickly make diagnosis information, which is conducive to realizing timely assistance to patients.


## 3.1.3. Architecture of Smart Medical System

According to the goal of building a smart medical system based on portable terminals, the overall system framework constructed in this study is shown in Figure4.Figure 4
Structure diagram of smart medical system based on portable terminal.The smart medical system based on portable terminals utilizes the convenience of modern smart terminals and combines the new physiological signal acquisition sensors to upload the user’s physiological information in real time. Once the system has more in-depth requirements (such as when the user’s physiological signals show signs of danger), the portable terminal will enable the video acquisition and transmission function and transmit the user’s real-time video information to the rear smart medical diagnosis center, which is convenient for doctors to make a quick diagnosis [16, 17]. In order to realize the real-time transmission and storage of user information, the system designs an information transmission and storage scheme based on GPRS, Internet, socket, multithreading, and other technologies. The solution focuses on ensuring that the user’s physiological information can be transmitted, stored, and diagnosed in real time. This better ensures that in the event of an emergency, the smart medical diagnosis center can obtain the user’s information more quickly, laying a technical foundation for the quickest first aid measures [18].From the above analysis, it can be seen that there are many modules that need to be constructed for the construction of a smart medical system. This study will implement some modules in the smart medical system, and these modules include portable terminal information collection and processing, information transmission, data center port monitoring, data real-time storage, and data dynamic realization modules. These modules build a small smart medical system, complete an overall process from data collection, transmission, and processing, and build a verification platform for the smart medical system, which lays a necessary foundation for the subsequent in-depth research on the smart medical system.


## 3.1.4. Realization Module

The previous section expounds on the overall system framework of smart medical care constructed in this study [19]. Based on this framework, this study completes a small smart medical verification platform system. The modules of the work completed in this study are shown in Figure 5. It lays an important foundation for verifying the rationality of the smart medical system and for the later research and development of smart cognition.Figure 5
Module diagram of the smart medical system implemented in this study.The main control program of the portable terminal is mainly used to complete the logic control and data flow of the mobile terminal. In this module, the monitoring of the data collection port is implemented after running the portable terminal. After the data buffer of the data acquisition port acquires the data, it will acquire the data through the data bus. Then, it calls the 3G communication module to connect to the portable terminal data center. After the block connecting the link is released, the 3G communication module will be called and the collected data will be uploaded.In the smart medical system, in order to collect the physiological information of the user into the system, a mobile terminal is needed, so each user has a mobile phone terminal connected to the data center in real time. Considering that various terminals often collect human physiological information, the amount of data increases sharply with the increase of mobile phone terminals. Therefore, the data centers need to establish multithreaded monitoring threads to send the data uploaded by various portable terminals [20].Meanwhile, the user physiological information data uploaded to the data center must also be stored in the database in time. Considering the many tasks to be processed during the system execution, the resources occupied by the system are limited to each portable terminal monitoring unit. Therefore, each monitoring unit must keep the physiological information data in the database in the cache as soon as possible.At the same time, the data center is also the intermediary of the smart medical system and the portable terminal to control the command transmission. When the smart medical system needs to send instructions to the portable terminal. For example, when a user has an emergency and needs to transfer the user’s GPS information and video information to the data center, the data center needs to transmit the control command to the portable terminal, so that the portable terminal opens the GPS and other information collection and transmission functions.The data dynamic display module is used to dynamically draw the real-time collected user physiological information dynamically to the display terminal to achieve a quick diagnosis. Considering the problems of information transmission and data storage, it is necessary to constantly extract the physiological information of the required monitoring users from the data center and draw it to the display terminal by using dynamic display technology.The above-described portable terminal, data center, and dynamic data display functions are the main contents of the research and design in this study. Through the design and implementation of the above functions, the real-time collection, transmission, storage, and display of remote data in the intelligent medical system are completed [21]. A smart medical verification system based on portable terminals has been built, laying a good foundation for the subsequent in-depth research and development of smart medical system.


## 3.2. Theories Related to IoT Technology and Medical Device Tracking System

### 3.2.1. The Basic Composition of the Internet of Things

The Internet of Things is a data-oriented application network with functions such as information perception, data processing, data backhaul, and decision support. In a broad sense, the Internet of Things can achieve 4 As, that is, anyone (Anybody), anytime (Anytime), place (Anywhere), using the network to exchange information with anything (Anything), it is a future development vision. In a narrow sense, as long as the items are connected by sensors, the network formed belongs to the category of the Internet of Things. At the core of the IoT definition, there are three main characteristics: addressable, controllable, and communicable.Sensor networks, information service systems, etc. constitute the hardware platform of the Internet of Things, as shown in Figure6. Software and hardware are closely related. The two cannot be separated and independent. Different types of IoT will have different uses, resulting in different performance in software.Figure 6
Schematic diagram of IoT hardware platform.


### 3.2.2. Internet of Things System Framework

The Internet of Things is a new type of network that emerges after combining some emerging perception technologies and wireless communication technologies. It is an extension of the Internet and computer networks. The variety of information technologies involved in the Internet of Things has gradually evolved into an aggregated system. The principal portion of the IoT reference model can be isolated into four layers: application layer, business/application support layer, network layer, and gadget layer. In addition, it has cross-laminate capability and safety capabilities.


### 3.2.3. The Basic Framework of the Hospital Internet of Things

IoT needs to leverage a range of existing or evolving advanced technologies. In order to connect physical objects and virtual objects to provide better services, a simple generalization of the IoT reference model is made [22], as shown in Figure 7.Figure 7
Basic framework of hospital IoT.The Internet of Things is a new mode of communication where objects in the virtual extended world and the physical world are interconnected. It can turn virtual world objects into reality by running a large number of applications and services, so it has no small challenges. IoT involves different knowledge domains such as ubiquitous computing, network communication, object recognition, and special data processing.


## 3.2.1. The Basic Composition of the Internet of Things

The Internet of Things is a data-oriented application network with functions such as information perception, data processing, data backhaul, and decision support. In a broad sense, the Internet of Things can achieve 4 As, that is, anyone (Anybody), anytime (Anytime), place (Anywhere), using the network to exchange information with anything (Anything), it is a future development vision. In a narrow sense, as long as the items are connected by sensors, the network formed belongs to the category of the Internet of Things. At the core of the IoT definition, there are three main characteristics: addressable, controllable, and communicable.Sensor networks, information service systems, etc. constitute the hardware platform of the Internet of Things, as shown in Figure6. Software and hardware are closely related. The two cannot be separated and independent. Different types of IoT will have different uses, resulting in different performance in software.Figure 6
Schematic diagram of IoT hardware platform.


## 3.2.2. Internet of Things System Framework

The Internet of Things is a new type of network that emerges after combining some emerging perception technologies and wireless communication technologies. It is an extension of the Internet and computer networks. The variety of information technologies involved in the Internet of Things has gradually evolved into an aggregated system. The principal portion of the IoT reference model can be isolated into four layers: application layer, business/application support layer, network layer, and gadget layer. In addition, it has cross-laminate capability and safety capabilities.


## 3.2.3. The Basic Framework of the Hospital Internet of Things

IoT needs to leverage a range of existing or evolving advanced technologies. In order to connect physical objects and virtual objects to provide better services, a simple generalization of the IoT reference model is made [22], as shown in Figure 7.Figure 7
Basic framework of hospital IoT.The Internet of Things is a new mode of communication where objects in the virtual extended world and the physical world are interconnected. It can turn virtual world objects into reality by running a large number of applications and services, so it has no small challenges. IoT involves different knowledge domains such as ubiquitous computing, network communication, object recognition, and special data processing.


## 3.3. Data Mining Technology Based on Classification

### 3.3.1. Basic Concepts of Classification Analysis

The K-nearest neighbor (KNN) method is the simplest classification algorithm. Classification is a data mining technique that is used to map the data in the data set to a certain category according to the characteristics of the existing data set [23, 24].


### 3.3.2. Classification Model and Evaluation Index

To build a classification model, the classifier must first be trained using a reliable dataset of a certain size as a training set. By analyzing the characteristics of the training set, a unique and accurate judgment description is found for each class to classify the subsequent test data.


### 3.3.3. Classical Classification Algorithm

(1) Nearest Neighbor Algorithm. The K-nearest neighbor classification algorithm is the simplest classification algorithm. K-nearest neighbor literally means that each sample is represented by its K nearest neighbor samples [25]. The core idea is that most of the K samples around the position of the sample in the space with the dimension of the feature value belong to a certain class, and then the sample belongs to this class.The commonly used correlation pairs in the K-nearest neighbor algorithm are as follows:Distance and Included Angle. Let d(X, Y) be the distance between samples X and Y, and the distance function d(X, Y) should satisfy the following conditions:(a)
(1)DAi,Bi=0.If and only if(2)Ai=Bi.(b)
Non-negativity is given by the following equation:(3)DAi,Bi≥0.(c)
Symmetry is given by the following equation:(4)DAi,Bi=DBi,Ai.(d)
Triangular inequality is given by the following equation:(5)DAi,Bi≤DAi,Ak+DAk,Bi.Minkowski distance is given by the following equation:(6)DAi,Bi=Ai−Biq=∑k=1mAik−Ajkq1/q,where(7)q∈1,+∞.Sinceq can take any value from 1 to +∞, the Minkowski distance is a generalization of an infinite number of distance metrics. In particular, when q is 1, it is the Manhattan distance, when q is 2, it is the Euclidean distance, and when q is +∞, it is the Chebyshev distance.Manhattan distance is given by the following equation:(8)DAi,Bi=Ai−Bi=∑k=1mAik−Ajk.Euclidean distance is given by the following equation:(9)DAi,Bi=Ai−Bi2=∑k=1mAik−Ajk21/2.Chebyshev distance is given by the following equation:(10)DAi,Bi=Ai−Bi∞=∑k=1mAik−Ajk∞1/∞.Cosine of Included Angle. Let the included angle between sample Ai,Bi be δAi,Bi and δAi,Bi∈0,180. The cosine of the included angle is given by the following equation:(11)cosδAi,Bi=∑k=1mAikAjk∑k=1mAik2∑k=1mAjk22.The algorithm steps are as follows: (1) the data item to be classified is A, calculate the distance or angle between it and each data object in the training sample set; (2) find the closest distance between the object and the data object in the training set; (3) count the categories of each data object in turn, and find the category that contains the most numbers, that is, the most common subcategory; (4) divide the data to be divided into this category; (5) repeat the above steps until the end of classification data.(2) Decision Tree. A choice tree is a tree structure. A characteristic tree is built from the traits of each example in the preparation set. It is built through and through. The leaf hubs of the tree are the classes utilized for arrangement, and the nonleaf hubs are feature credits, the parts of the tree are choice circumstances Figure 8.Figure 8
Decision tree algorithm.The way in to the choice tree calculation is to choose proper qualities as hubs at each layer and to decide suitable limits for the chose hubs to expand the expectation exactness. Another key is to properly prune the decision tree to thwart overfitting [26]:①
Commonplace Choice Tree ID3 calculation. In the event that a likelihood circulation W1,W2,…Wn is given, how much data conveyed by the dissemination is known as the entropy of the likelihood dispersion. The absolute entropy of the framework is as follows:(12)IW1,W2,…,Wn=−∑i=1nWilog2Wi.Given a preparation setP, where the quantity of test focuses is signified as P, assuming there are t various classes Bii=1,2,…,k and Gi test focuses in class Bi, and Gi/G is utilized to gauge the likelihood that any example has a place with Bi, then, at that point,(13)IG1G,G2G,…,GkG=−∑i=1kGiGlog2GiG.For traitC with l various qualities c1,c2,…,cl, it tends to be utilized to isolate the preparation set G into l subsets. Allowing Gij to be the quantity of tests having a place with Bi in Gij, the entropy (anticipated data) of the subset partitioned by C is as follows:(14)EC=∑i=1kGij+G2j+⋯+GkjGIG1j,G2j,…,Gkj.For a given subsetDj, the data entropy is as follows:(15)IG1j,G2j,…,Gkj=−∑i=1kWijlog2Wij,IGC=IG1G,G2G,…GkG−EC.The main issue in the obtaining of affiliation rules is the colossal measure of information to be dissected. Accordingly, working on the proficiency of the calculation is the most significant. If by some stroke of good luck one affiliation rule calculation is utilized, then there are numerous information to be investigated, and the execution season of the calculation will turn out to be extremely lengthy.②
Choice Tree C4.5 Calculation. The pruning technique took on by the C4.5 calculation in this primer is negative blunder pruning. The standard of this calculation is investigated extensively under. AnticipatingV(t) is how much preparing set cases at focus point t and p(t) is how much misclassified occasions at focus t, A proportion of the misclassification rate is as follows:(16)Ht=GtVt.The coherence amended blunder rate is as follows:(17)H′t=Gt+1/2Vt.In a like manner, the misclassification pace of subtreeTt is as follows:(18)HTt=∑Gi∑Vi,where i takes the leaves of the subtree, so the helped misclassification rate is as follows:(19)H′Tt=∑Gi+1/2∑Vi.Then,(20)H′Tt=∑Gi+VTi/2∑Vi,where VT is the quantity of leaves on the hub.Utilizing the preparation information, subtrees consistently produce less mistake than their comparing hubs. Be that as it may, this is not the situation while utilizing adjusted numbers, since they rely upon the quantity of leaves, in addition to the quantity of mistakes.The standard deviation is calculated as follows:(21)SEu′Ti=u′Tt∗Vt−u′TiVt.Among them, for the node, there are(22)u′t=Gt+12.For subtrees, we have(23)u′Tt=∑Gi+VTtVTt.Accordingly, if the amount of misclassifications after subtree correction is more critical than the amount of misclassifications after center revision, this pruning methodology proposes pruning the subtree. The potential gain of this approach is that a comparable planning set is used for tree improvement and tree pruning, and it is especially speedy considering the way that only one scope is required and each center point is reviewed once.


## 3.3.1. Basic Concepts of Classification Analysis

The K-nearest neighbor (KNN) method is the simplest classification algorithm. Classification is a data mining technique that is used to map the data in the data set to a certain category according to the characteristics of the existing data set [23, 24].


## 3.3.2. Classification Model and Evaluation Index

To build a classification model, the classifier must first be trained using a reliable dataset of a certain size as a training set. By analyzing the characteristics of the training set, a unique and accurate judgment description is found for each class to classify the subsequent test data.


## 3.3.3. Classical Classification Algorithm

(1) Nearest Neighbor Algorithm. The K-nearest neighbor classification algorithm is the simplest classification algorithm. K-nearest neighbor literally means that each sample is represented by its K nearest neighbor samples [25]. The core idea is that most of the K samples around the position of the sample in the space with the dimension of the feature value belong to a certain class, and then the sample belongs to this class.The commonly used correlation pairs in the K-nearest neighbor algorithm are as follows:Distance and Included Angle. Let d(X, Y) be the distance between samples X and Y, and the distance function d(X, Y) should satisfy the following conditions:(a)
(1)DAi,Bi=0.If and only if(2)Ai=Bi.(b)
Non-negativity is given by the following equation:(3)DAi,Bi≥0.(c)
Symmetry is given by the following equation:(4)DAi,Bi=DBi,Ai.(d)
Triangular inequality is given by the following equation:(5)DAi,Bi≤DAi,Ak+DAk,Bi.Minkowski distance is given by the following equation:(6)DAi,Bi=Ai−Biq=∑k=1mAik−Ajkq1/q,where(7)q∈1,+∞.Sinceq can take any value from 1 to +∞, the Minkowski distance is a generalization of an infinite number of distance metrics. In particular, when q is 1, it is the Manhattan distance, when q is 2, it is the Euclidean distance, and when q is +∞, it is the Chebyshev distance.Manhattan distance is given by the following equation:(8)DAi,Bi=Ai−Bi=∑k=1mAik−Ajk.Euclidean distance is given by the following equation:(9)DAi,Bi=Ai−Bi2=∑k=1mAik−Ajk21/2.Chebyshev distance is given by the following equation:(10)DAi,Bi=Ai−Bi∞=∑k=1mAik−Ajk∞1/∞.Cosine of Included Angle. Let the included angle between sample Ai,Bi be δAi,Bi and δAi,Bi∈0,180. The cosine of the included angle is given by the following equation:(11)cosδAi,Bi=∑k=1mAikAjk∑k=1mAik2∑k=1mAjk22.The algorithm steps are as follows: (1) the data item to be classified is A, calculate the distance or angle between it and each data object in the training sample set; (2) find the closest distance between the object and the data object in the training set; (3) count the categories of each data object in turn, and find the category that contains the most numbers, that is, the most common subcategory; (4) divide the data to be divided into this category; (5) repeat the above steps until the end of classification data.(2) Decision Tree. A choice tree is a tree structure. A characteristic tree is built from the traits of each example in the preparation set. It is built through and through. The leaf hubs of the tree are the classes utilized for arrangement, and the nonleaf hubs are feature credits, the parts of the tree are choice circumstances Figure 8.Figure 8
Decision tree algorithm.The way in to the choice tree calculation is to choose proper qualities as hubs at each layer and to decide suitable limits for the chose hubs to expand the expectation exactness. Another key is to properly prune the decision tree to thwart overfitting [26]:①
Commonplace Choice Tree ID3 calculation. In the event that a likelihood circulation W1,W2,…Wn is given, how much data conveyed by the dissemination is known as the entropy of the likelihood dispersion. The absolute entropy of the framework is as follows:(12)IW1,W2,…,Wn=−∑i=1nWilog2Wi.Given a preparation setP, where the quantity of test focuses is signified as P, assuming there are t various classes Bii=1,2,…,k and Gi test focuses in class Bi, and Gi/G is utilized to gauge the likelihood that any example has a place with Bi, then, at that point,(13)IG1G,G2G,…,GkG=−∑i=1kGiGlog2GiG.For traitC with l various qualities c1,c2,…,cl, it tends to be utilized to isolate the preparation set G into l subsets. Allowing Gij to be the quantity of tests having a place with Bi in Gij, the entropy (anticipated data) of the subset partitioned by C is as follows:(14)EC=∑i=1kGij+G2j+⋯+GkjGIG1j,G2j,…,Gkj.For a given subsetDj, the data entropy is as follows:(15)IG1j,G2j,…,Gkj=−∑i=1kWijlog2Wij,IGC=IG1G,G2G,…GkG−EC.The main issue in the obtaining of affiliation rules is the colossal measure of information to be dissected. Accordingly, working on the proficiency of the calculation is the most significant. If by some stroke of good luck one affiliation rule calculation is utilized, then there are numerous information to be investigated, and the execution season of the calculation will turn out to be extremely lengthy.②
Choice Tree C4.5 Calculation. The pruning technique took on by the C4.5 calculation in this primer is negative blunder pruning. The standard of this calculation is investigated extensively under. AnticipatingV(t) is how much preparing set cases at focus point t and p(t) is how much misclassified occasions at focus t, A proportion of the misclassification rate is as follows:(16)Ht=GtVt.The coherence amended blunder rate is as follows:(17)H′t=Gt+1/2Vt.In a like manner, the misclassification pace of subtreeTt is as follows:(18)HTt=∑Gi∑Vi,where i takes the leaves of the subtree, so the helped misclassification rate is as follows:(19)H′Tt=∑Gi+1/2∑Vi.Then,(20)H′Tt=∑Gi+VTi/2∑Vi,where VT is the quantity of leaves on the hub.Utilizing the preparation information, subtrees consistently produce less mistake than their comparing hubs. Be that as it may, this is not the situation while utilizing adjusted numbers, since they rely upon the quantity of leaves, in addition to the quantity of mistakes.The standard deviation is calculated as follows:(21)SEu′Ti=u′Tt∗Vt−u′TiVt.Among them, for the node, there are(22)u′t=Gt+12.For subtrees, we have(23)u′Tt=∑Gi+VTtVTt.Accordingly, if the amount of misclassifications after subtree correction is more critical than the amount of misclassifications after center revision, this pruning methodology proposes pruning the subtree. The potential gain of this approach is that a comparable planning set is used for tree improvement and tree pruning, and it is especially speedy considering the way that only one scope is required and each center point is reviewed once.


## 3.4. Quality Management in Medical Device Cleaning Process

### 3.4.1. Importance of Medical Device Cleaning Process

The cleaning process of medical equipment is an important part of hospital infection management and an important part of hospital medical equipment disinfection management. It plays an important role in improving the quality of medical equipment cleaning. In addition, the quality management of the medical device cleaning process also plays an important role. The whole process requires professional management personnel training, effective cleaning procedures and specifications, and the improvement of hospital disinfection management. In addition, various cleaning links need to be monitored. The supply room also has a lot to do with improving the quality of medical device cleaning. At the same time, in order to improve the cleaning quality of medical equipment, some people need to plan to use medical equipment.


### 3.4.2. Measures to Improve the Quality of Instrument Cleaning

The method to improve the quality of instrument cleaning is shown in Figure9.Figure 9
Ways to improve the quality of instrument cleaning.


## 3.4.1. Importance of Medical Device Cleaning Process

The cleaning process of medical equipment is an important part of hospital infection management and an important part of hospital medical equipment disinfection management. It plays an important role in improving the quality of medical equipment cleaning. In addition, the quality management of the medical device cleaning process also plays an important role. The whole process requires professional management personnel training, effective cleaning procedures and specifications, and the improvement of hospital disinfection management. In addition, various cleaning links need to be monitored. The supply room also has a lot to do with improving the quality of medical device cleaning. At the same time, in order to improve the cleaning quality of medical equipment, some people need to plan to use medical equipment.


## 3.4.2. Measures to Improve the Quality of Instrument Cleaning

The method to improve the quality of instrument cleaning is shown in Figure9.Figure 9
Ways to improve the quality of instrument cleaning.


## 4. Experiment of Cleaning Quality Control Management of Medical Equipment in Hospital Disinfection Supply Room of Smart Medical Care

A hospital set up a separate cleaning and disinfection room in the operating room and put the used medical equipment into the cleaning machine for unified cleaning in time, so as to avoid secondary pollution of the hospital environment caused by the medical equipment during the transfer process, and the medical equipment cannot be cleaned in time The sterilized medical equipment is temporarily stored in the multienzyme cleaning agent to keep the medical equipment moist and prevent the coagulation of attached pollutants such as blood and body fluids. During the cleaning process, it is more scientific and reasonable to grasp the concentration, temperature, and soaking time of the cleaning agent. Generally, the Lanso multienzyme cleaning agent and water are prepared into a standby cleaning agent according to the concentration ratio of 1 : 200, and the water temperature is 25–30°C.


### 4.1. Current Status of Cleaning of Medical Equipment in the Disinfection Supply Room

Through this research and investigation, it is found that the cleaning of medical equipment in the disinfection supply room follows the scientific processing principles in many aspects. The cleaning failure rate of medical equipment in the disinfection supply room of a hospital generally showed a downward trend, but there were still some problems, as listed in Table1.Table 1
Qualification rate of medical device cleaning.
Device typeCleaning qualification rate201720182019First aid equipment97.6599.7599.75Surgical instruments98.6698.5198.51Oral instruments98.5898.9798.97Disposable instrument sterilizer97.1298.1698.16Lower exhaust first aid sterilization kit98.5499.8299.82Disinfectant container99.5899.7899.72From January 2017 to December 2019, the top three problems with the medical devices in the nosocomial infection evaluation are as follows: expired sterile items, incomplete disinfection of equipment, and failure to make sterilization packs as required.


### 4.2. Cleaning Compliance Rate of Programmed Management and Conventional Management Paths

About 650 pieces of medical equipment are selected in the disinfection supply room of a hospital and are divided into two groups according to the principle of random allocation by computer, namely, the research group and the reference group, each with 300 pieces of medical equipment. The main instruments are as follows: vascular forceps, tissue scissors, and forceps, as well as curved discs, oval forceps, retractors, vices, rib punches, and needle-holding forceps. There are 20 staff in the department.Looking at the cleaning consistence paces of the two gatherings of clinical gadgets, 99.38% of the examination bunch was altogether higher than 96.92% of the reference bunch. The information between the gatherings was looked at, and the thing that matters was genuinely critical (P<0.05), as listed in Table 2.Table 2
Cleaning compliance rate of programmed management and conventional management paths (n, %).
GroupnCleaning up to standardProportion (%)Research group32532399.38%Reference group32531596.92%X25.4422P<0.05


### 4.3. Satisfaction Survey Results of Programmatic Management and Conventional Management Paths

Contrasting the clinical staff’s fulfillment and the cleaning of clinical gadgets, the examination bunch was 100% essentially higher than the reference gathering’s 76.6%. The information between the gatherings was looked at, and the thing that matters was genuinely critical (P<0.05), as listed in Table 3.Table 3
Satisfaction survey results for programmatic management and conventional management paths [n (%)].
GroupnPerfect contentmentRelative satisfactionDissatisfiedSatisfaction (%)Research group6036240100%Reference group6026201476.6%X27.9245P<0.05It can be seen from Table3 and Figure 10 that in the research group applying program-based management, the cleaning compliance rate of 99.3% is significantly higher than the 96.7% of the reference group using the conventional management path. There was statistical significance in the data comparison between groups (P<0.05). From the results of medical staff’s satisfaction with the cleaning of medical devices, the 100% research group applying program-based management was significantly higher than 76.6% of the conventional management path. There was statistical significance in the data comparison between groups (P<0.05), and the program management was more targeted than the conventional management path.Figure 10
Satisfaction with programmatic management and conventional management paths. (a) Study group satisfaction. (b) Satisfaction of the reference group.
(a)(b)


## 4.1. Current Status of Cleaning of Medical Equipment in the Disinfection Supply Room

Through this research and investigation, it is found that the cleaning of medical equipment in the disinfection supply room follows the scientific processing principles in many aspects. The cleaning failure rate of medical equipment in the disinfection supply room of a hospital generally showed a downward trend, but there were still some problems, as listed in Table1.Table 1
Qualification rate of medical device cleaning.
Device typeCleaning qualification rate201720182019First aid equipment97.6599.7599.75Surgical instruments98.6698.5198.51Oral instruments98.5898.9798.97Disposable instrument sterilizer97.1298.1698.16Lower exhaust first aid sterilization kit98.5499.8299.82Disinfectant container99.5899.7899.72From January 2017 to December 2019, the top three problems with the medical devices in the nosocomial infection evaluation are as follows: expired sterile items, incomplete disinfection of equipment, and failure to make sterilization packs as required.


## 4.2. Cleaning Compliance Rate of Programmed Management and Conventional Management Paths

About 650 pieces of medical equipment are selected in the disinfection supply room of a hospital and are divided into two groups according to the principle of random allocation by computer, namely, the research group and the reference group, each with 300 pieces of medical equipment. The main instruments are as follows: vascular forceps, tissue scissors, and forceps, as well as curved discs, oval forceps, retractors, vices, rib punches, and needle-holding forceps. There are 20 staff in the department.Looking at the cleaning consistence paces of the two gatherings of clinical gadgets, 99.38% of the examination bunch was altogether higher than 96.92% of the reference bunch. The information between the gatherings was looked at, and the thing that matters was genuinely critical (P<0.05), as listed in Table 2.Table 2
Cleaning compliance rate of programmed management and conventional management paths (n, %).
GroupnCleaning up to standardProportion (%)Research group32532399.38%Reference group32531596.92%X25.4422P<0.05


## 4.3. Satisfaction Survey Results of Programmatic Management and Conventional Management Paths

Contrasting the clinical staff’s fulfillment and the cleaning of clinical gadgets, the examination bunch was 100% essentially higher than the reference gathering’s 76.6%. The information between the gatherings was looked at, and the thing that matters was genuinely critical (P<0.05), as listed in Table 3.Table 3
Satisfaction survey results for programmatic management and conventional management paths [n (%)].
GroupnPerfect contentmentRelative satisfactionDissatisfiedSatisfaction (%)Research group6036240100%Reference group6026201476.6%X27.9245P<0.05It can be seen from Table3 and Figure 10 that in the research group applying program-based management, the cleaning compliance rate of 99.3% is significantly higher than the 96.7% of the reference group using the conventional management path. There was statistical significance in the data comparison between groups (P<0.05). From the results of medical staff’s satisfaction with the cleaning of medical devices, the 100% research group applying program-based management was significantly higher than 76.6% of the conventional management path. There was statistical significance in the data comparison between groups (P<0.05), and the program management was more targeted than the conventional management path.Figure 10
Satisfaction with programmatic management and conventional management paths. (a) Study group satisfaction. (b) Satisfaction of the reference group.
(a)(b)


## 5. Discussion

Once the smart medical system is in operation, it is conceivable that most of the contradictions existing in the field of doctors and patients can be resolved. For example, in the current difficult problem of seeing a doctor, the vast majority of users will no longer see a doctor through the hospital, but through the smart medical system, where you and doctors can carry out pathological diagnosis and analysis at your convenience. This will greatly reduce the work pressure of the hospital and make it better to put it into medical work. There can also be a smart medical system to provide solutions for the phenomenon of unbalanced medical levels. Using this system, more routine pathologies can be performed within the system by general physicians. The system is more accurate because it can provide routine pathology solutions.For intractable diseases, more experienced and technical experts can be systematically arranged to balance the needs of doctors and patients. The smart medical system is an important means to resolve the conflict between doctors and patients, because the system stores a large amount of physiological information and treatment process information. Therefore, it can be seen that the adoption of the smart medical system will be very helpful to solve most of the current medical conflicts and provide better medical services for the people.


## 6. Conclusion

The development of modern technology has laid the foundation for a better life for people, and smart medical care is currently using the Internet of Things technology and real-time signal processing to provide people with ubiquitous and ubiquitous medical services. The new form of smart medical care is officially one of the ways to solve the current difficulties such as difficulty in seeing a doctor, low hospital efficiency, and unbalanced medical resources. In short, the cleaning quality management of medical equipment in the hospital disinfection supplies room can greatly improve the cleaning quality. Therefore, the hospital should strengthen the cleaning quality management to ensure the safety of the equipment. Considering the advantages of program management, it can also be used for reference and application in clinical diagnosis and treatment.



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*Source: 4380735-2022-08-05.xml*