A review of advanced technologies available to improve the healthcare performance during COVID-19 pandemic

Information technology (IT) has enabled the initiation of an innovative healthcare system. An innovative healthcare system integrates new technologies such as cloud computing, the internet of things, and artificial intelligence (AI), to transform the healthcare to be more efficient, more convenient and more personalized. This review aims to identify the key technologies that will help to support an innovative healthcare system. A case study approach was used in this research analysis to enable a researcher to closely analyze the data in a particular context. It presents a case study of the coronavirus (COVID-19) as a means of exploring the use of advanced technologies in an innovative healthcare system to help address a worldwide health crisis. An innovative healthcare system can help to promote better patient self-management, reduce costs, relieve staff pressures, help with resource and knowledge management, and improve the patient experience. An innovative healthcare system can reduce the expense and time for research, and increase the overall efficacy of the research. Overall, this research identifies how innovative technologies can improve the performance of the healthcare system. Advanced technologies can assist with pandemic control and can help in the recognition of the virus, clinical treatment, medical protection, intelligent diagnosis, and outbreak analysis. The review provides an analysis of the future prospects of an innovative healthcare system.


Introduction
A health information system is an integrated system that includes people, processes, and technology to support healthcare services [1]. Using IT technologies in healthcare businesses can improve medical procedures, enhance decision-making processes, and ease information transmission [2]. The increasing adoption of IT and biotechnology by healthcare professionals has enabled changes to a more client-centred model and a more preventative healthcare paradigm [3,4]. Technology can help better meet the individual needs of clients, thereby enhancing their medical and health service experience and representing the future direction of medicine [5].
COVID-19 is an acute respiratory infection caused by the novel coronavirus SARS-CoV-2, which has produced a global healthcare disaster unprecedented in modern history [6]. The World Health Organization (WHO) declared COVID-19 a Public Health Emergency of International Concern (PHEIC) on January 30, 2020. Later, less than 12 weeks after the first case was diagnosed in Wuhan, China, WHO declared COVID-19 a pandemic [7]. Since the first case was reported in December 2019 (i.e., as of July 25th, 2021), approximately 192 million illnesses and more than 4.1 million deaths have been confirmed globally [8].
In the current COVID-19 environment, various countries use a variety of digital tools to promote public health activities. Several new technologies, such as mobile applications, robots, Artificial Intelligence (AI), drones, and other social media platforms, have been found to be helpful in healthcare (contact tracing, monitoring, thermal screening, sanitation, locomotion, and clinical conditions), logistics, surveillance, and awareness measures [9].
There is a need for further development and resolution of the challenges that are outlined below [3]. The emerging innovative healthcare system is seen as lacking guidance and appropriate documentation [10], resulting in a perceived lack of goal clarity and resource wastage [11]. A lack of uniform standards across regions and medical institutions has also been identified [12]. Improvement in data security is seen to be required [13]. Data sharing and communication are perceived to be limited by data size and complexity [14]. Platform and device compatibility problems have been noted [3,15]. There is perceived to be a lack of relevant legal protections from the patient's perspective [3,16]. Users have difficulty using some of the new technology, some of the technology is still at the experimental stage, and some of it is capital intensive to maintain and upgrade [3].
In response to these issues, there is interest in further technology development and information analysis capacity [17]. Establishment of a unified technical standard for device and platform compatibility has been perceived as essential [3,18].
This review begins with a presentation of the innovative healthcare system. It identifies related technologies that have been used in the healthcare system. The review then presents a case study based on the health issues related to COVID-19 to explore the current operation of the innovative healthcare system and identifies a number of different advanced technologies that have been used in the COVID-19 pandemic, and concludes by examining this system's future prospects.

The main concept of the innovative healthcare system
The innovative healthcare system arose from IBM's "Smart Planet" concept, which was introduced in 2009 [3,19]. This concept represented an intelligent sensor infrastructure able to perceive and transmit information through the IoT, via information processing that utilized supercomputers and cloud computing [20]. Such processing was seen to be capable of coordinating social systems and integrating them in order to achieve a more dynamic refined management of human society [3]. The innovative healthcare system is a technology infused system, including wearable devices, IoT and mobile internet technology to: access information dynamically; connect people, material and institutions; and intelligently manage and respond to ecosystems within the system [21]. The innovate healthcare system is designed to promote interaction between the stakeholders in the healthcare field and to facilitate rational resource allocation, because it is an evolved and technologically developed information system [22].

Key technologies in the innovative healthcare system
The innovative healthcare system is an organic whole made up of multiple participants including: doctors, patients, and medical researches. It has a number of dimensions including: diagnosis, disease treatment, prevention and monitoring, health decision making, hospital management and medical research [3]. Its technological base is broad and varied, including: IoT, mobile internet, cloud computing, AI and biotechnology [21].All of these technologies are extensively utilized by various participants and in all dimensions of the innovative healthcare system [23].
Patients benefit by being able to wear devices that enable constant monitoring of their health, by obtaining medical assistance through virtual assistants and by utilizing remote services and mobile medical platforms [24]. Doctors benefit from an improved diagnostic system, due to more intelligent clinical decision making [25]. They are better able to manage medical information as well through a more integrated information platform, which includes laboratory information management systems, visual interactive archiving and communication systems and electronic digital medical record keeping management systems [26]. More precise surgery is possible through the use of surgical robots and mixed reality technologies [17]. The hospital system gains the benefit of radio frequency identification (RFID) to better manage personnel, materials and the medical supply chain, aided by integrated management platforms, which enhance information collection and decision making [27,28]. Medical research institutions are aided by technologies related to machine learning applied to their research, for example to address drug screening or subject selection [26,27]. Some of the more substantive types of technologies which are embedded in the innovative healthcare system include:

Internet of Things (IoT)
There are numerous definitions of the IoT, but it can be defined as a network of devices communicating with one another via machine to machine (M2M) connections, allowing for improved data collection and exchange [29][30][31]. The IoT is considered as a crucial driver for increased automation across a wide range of businesses, as well as for the collection of large amounts of data [32]. In the context of health care, IoT refers to any device that can collect healthrelated data from individuals, such as computing devices, mobile phones, smart bands, wearables, digital medications, implantable surgical devices, or other portable devices that can measure health data and connect to the internet [33].
The IoT has become a focus of research directed at identifying how it may be able to assist in alleviating health care pressures [29,31,34]. A significant component of this research has been directed at how IoT may aid monitoring of patients with specific conditions such as diabetes [35] or Parkinson's disease [36]. IoT has the potential to aid patient rehabilitation, by constant patient monitoring [29,37,38].
The IoT' potential is characterized as a growing field of research in healthcare. These advancements present an excellent potential for health-care systems to proactively predict health issues and to diagnose, treat, and monitor patients both in and out of the hospital (Kelly et al., 2020). As health systems employ technology-enabled health services to create flexible models of care, a growing number of traditional health service delivery practices will be supplemented or replaced by IoT [39,40]. The deployment of IoT in health care, on the other hand, will rely on a clear and rigorous code of practice for data management, privacy, confidentiality, and cybersecurity in relation to the supply and use of IoT devices in healthcare [38].

Cloud Computing
The term "cloud computing" refers to the ability to have constant and convenient network access to a shared pool of configurable computer resources, such as networks and servers, with immediate processing and minimal contact or management [13,41]. Cloud computing has rapid elasticity and offers ubiquitous access to health resources [42,43]. It is seen to offer fast data management and easy access to data, together with cost and labour savings as well as enhancing data sharing security [43,44]. Data transmission through wireless technology aligns cloud computing with the innovative health system, especially in the areas of EMR, EHR and telemedicine especially in the context of a disaster, for the purposes of prescription transmission and patient medication and status management [45]. Cloud computing, like most other technologies related to the innovative health system, faces challenges, in particular privacy protection and data security [43], with the need to comply with recent legislation such as HIPAA, HITECH, and GLBA [46]. Technology for addressing these issues may include biometric authentication methods such as fingerprint recognition and palm vein scanning [44,47,48].

Artificial Intelligence (AI)
Early on, the healthcare sector was considered as one of the most promising AI application sectors. Since the twenty-first century, researchers have proposed and implemented numerous AI-based healthcare decision support systems [49]. Many elements of patient care, as well as administrative operations inside provider, payer, and pharmaceutical organizations, have the potential to be transformed by these AI systems.
AI is a collection of technologies, not a single one. The majority of these technologies are immediately applicable to the subject of healthcare, although the exact processes and tasks they assist differ greatly. Machine learning -neural networks and deep learning; natural language processing; rule-based expert systems; physical robots and robotic process automation are some of the most important AI technologies in healthcare [49][50][51].
AI is already available in consumer electronics, such as Amazon's Alexa and Apple's Siri. AI software technology varies from credit card fraud detection to NASA's payload scheduling procedures and NASDAQ's insider trading monitoring [52]. AI is the imitation of human cognition by a machine [53] and recent interest in the application of AI is driven by machine learning technological advances such as computer algorithm data learning without human direction [54,55].
There is an expectation and desire that AI may enable better diagnostic observation, helping in finding selected areas faster, enable the development of advanced medications, and more personalized medication [56]. AI-powered technologies are predicted to outperform humans in surgery by 2053 [57]. Innovated healthcare can be expected to improve personalized clinical management [58].

Research Method (Case study)
In this research investigation, a case study approach was employed to allow a researcher to precisely examine the data in a specific setting. In most cases, a case study approach selects a specific geographical region or a relatively small number of people as the subjects of study. Case studies, in their true form, investigate and explore current reallife trends through a careful contextual examination of a small range of occurrences or circumstances and their relationships. According to [59], the case study research technique is defined as "an empirical investigation into a current phenomenon inside its real-life setting; when the boundaries between phenomenon and context are not readily visible; and when many sources of information are utilized".
There are various types of case studies [59][60][61]. According to Yin [59], exploratory, descriptive, and explanatory case studies are the three types of case studies. The first, exploratory case studies, are designed to investigate any phenomena in the data that piques the researcher's curiosity. The second type is descriptive case studies, which are designed to describe natural occurrences that occur within the data in question, such as what different tactics a reader employs and how the reader employs them. The third category is explanatory case studies, which closely investigate the data at both a surface and a deep level to explain the occurrences in the data. This research review employed the first type of case study, which is utilized to investigate any phenomenon in the data that piques the researcher's curiosity (explanatory case study). COVID-19 is the case study for this research evaluation.

Case study of COVID-19
Several coronaviruses can infect humans, including the globally endemic human coronaviruses HCoV-229E, HCoV-NL63, HCoV-HKU1 and HCoV-OC43, which cause mild respiratory disease, and the zoonotic Middle East respiratory syndrome coronavirus (MERS-CoV) and the severe acute respiratory syndrome coronavirus (SARS-CoV), which cause severe respiratory disease [62]. In December 2019, a cluster of individuals in Wuhan, China, were diagnosed with a new coronavirus [62]. The virus was first termed 2019 novel coronavirus (2019-nCoV), however, the International Committee on Taxonomy of Viruses (ICTV) has recently renamed it SARS-CoV-2 [63]. This virus has the potential to cause the coronavirus illness 2019 (COVID-19). The WHO labelled the COVID-19 outbreak a global health emergency on January 30, 2020 [64,65]. The WHO proclaimed COVID-19 a global pandemic on March 11, 2020, the first such classification since H1N1 influenza was declared a pandemic in 2009 [66].
COVID-19 has spread rapidly. During the 2002 SARS pandemic, it took more than a year to decode the virus's genome; but, thanks to modern technologies, the COVID-19 (coronavirus) genome was found within a month. China and other countries are utilizing innovative technologies to overcome the issues of COVID-19 [67].

Data collection stages
The works of Watson and Ali et al., are referred as guidelines for this current review method [68,69]. The review is sequenced vide a specific protocol and process that is initiated to identify, select and assess the literature, based on the parameter, of relevance. The article is aimed to make the review process highly efficient [70], replicable, objective, candid, unbiased and with rigor [71]. Derived from the works of Kitchenham and Charters [72] and Ali, Shrestha, Soar and Wamba [68], AlAhmad, Kahtan, Alzoubi, Ali and Jaradat [73], Al-Ahmad, Kahtan, Hujainah and Jalab [74], Ali, Ally and Dwivedi [75], the review is sequenced as a two-stage process: Planning and execution stage. The explanation of the two processes follows next.
Planning stage: This phase characterizes the identification of requirements of the review. In spite of studies on how technologies improve the healthcare performance during COVID 19 pandemic, the academic literature pertaining to the topic and its review has been under-developed. Thus, the paper shall contribute to a detailed analysis of the existent knowledge in research and practice. Secondly, at the planning stage, research questions were identified; core amongst which was: How advanced technologies improve the healthcare performance during COVID-19 pandemic? Thus, the review aims to answer this research question.
Third, the criterion for selection of source was set, with specific strategies and techniques. Herein an integrated search strategy was embraced to include search engine -automated search, on different online sources and inclusion of manual review of assorted publications [76]. For this case study, many different online sources have been chosen. Moreover, a strategic filtering of tools was materialized to limit and mine the requisite research results, for each of the chosen sources [77]. The broad manual review was sequenced as reading through the title and abstract of each chosen source [76]; followed by systematic reading of the assorted content of these chosen sources, to exclude the extraneous [68,73,74].
Execution stage: At this stage, strategies of the planning phase were extended to filter sources of relevance for the sake of this topic. The main method, applied in our study were: 1) identifying the search terms and words as an everevolving process; which though began with using unique -technical terms, recognised in the area [78]; 2) online sources filtering tools were used in order to enhance the relevance of search results; feature of temporal restriction was used [79]; 3) Subsequent to which, results were manually checked with focal on title and abstract, to ensure their relevance [80]; 4) Filtered sources from the previous step, were thoroughly analysed (read for full text article) for relevant knowledge, information, theory and like, on the area of research topic [81].

Discussion
Many facets of life have changed as a result of the technological revolution. In 2019, 67 percent of the global population held mobile devices, 65 percent of which were smartphones [82]. 204 billion applications were downloaded in 2019 [83], about 3.8 billion people actively used social media as of January 2020 [84]. As a result, advanced technology can help with pandemic containment by assisting with virus recognition, clinical treatment, medical protection, intelligent diagnosis, and outbreak analysis [85]. Various Chinese regional governments used Kingsoft Clouds to distribute and authorize medical supplies like face masks, disinfectants, and detection devices. The intelligent temperature measurement and analysis system in Beijing employs AI and infrared imaging of congested places such as airports and train stations. A real-time surveillance and alarm device is being used in the Haidian region to identify and track people with fever. An online coronavirus infection medical platform, created by the local government and around 11 technology companies including AliHealth, Baidu and JD Health, will more easily categorize questions from the public, link targeted doctors and provide fast responses. The platform has attracted more than 4,600 doctors since it was introduced on February 1st 2021 [86]. On February 5th, the Beijing government released around 10 different policies aimed at speeding up the implementation of scientific and technological research applications that will help deter and monitor the spread of the disease. The major aim, according to Xu Qiang, Director of the Beijing Science and Technology Commission, was to satisfy and meet the urgent demand for speedy diagnostic tests, a vaccination, intelligent body temperature assessment, and online medical consultations [86]. The innovative healthcare system gathers data from wearables and smart devices [87]. These gadgets have the potential to provide patients with continuous objective monitoring. A constant stream of data on characteristics like gait measurements can offer clinicians with a better knowledge of a patient's health that was previously unavailable in the controlled, potentially biased clinic setting [87]. The data is then uploaded to the cloud over a network, and the results are analysed using big data algorithms to provide real-time feedback on the projected consequences of customers utilizing the short messaging service [88]. These types of measurements can be more effective for the healthcare system [89]. Thus, enabling improvements in clinical care and patient self-care and assisting in the development of national healthcare policies to best manage COVID-19. Some of the advanced technologies for dealing with COVID-19 include: Colour Coding: The Chinese government has partnered with technology companies including Alibaba and Tencent to create a colour-coded health rating system to check a large number of people on a daily basis [90]. The smartphone application was first introduced in the city of Hangzhou and used in cooperation with Alibaba. This application provides three colour options (green, yellow, or red) which depend on people's physical movements and medical history [91]. In Shenzhen a similar mobile application was created by Tencent [90].
The shading code and colors indicate if an individual should be excluded or permitted in public areas. Citizens are obligated to participate and sign in using mobile wallet tech system such as Alibaba's AliPay. By utilizing the specific QR code at train and bus stations, and workplaces, only citizens with the green shading colour would be permitted in public areas. There are many checkpoints in the most popular areas, where the code and the person's body temperature are tested. These checkpoints are used in 200 Chinese towns, and are expected to be expanded nationally [67].
Colour-coding has been utilized in a variety of circumstances, including assessing the efficacy of antenatal care [92]. Colour-coded stratification for ordering radiological tests to reduce the amount of tests ordered (red, amber, and green tests can be allowed by a consultant, registrar/consultant, and interns/residents, respectively) [93]. Uniform hospital colour codes for communicating various emergency situations to hospital employees without frightening patients [94]. to increase the safety of several infants [95], anesthetic medicines that are Colour-coded to prevent inadvertent syringe swapping, as well as intravenous Colour-coded cannulas [96], Colour-coded wristbands for identifying certain signals such as allergies [97], periodontal instruments [98]; for sensitization sessions on electrocardiograms [99]; radiological examinations and other dye-based tests [100]. To summarize, colour coding in healthcare offers enormous potential to enable the delivery of quality assured services, particularly in low-resource situations. Nonetheless, there is an urgent need to widely deploy this method in order to broaden its range of benefits to both patients and healthcare professionals.
Robotics: Robots are being used for sterilization, delivery of medicines and food, and checking for indications of COVID-19 [86]. Robots often provide diagnoses with the use of thermal imaging. Shenzhen Company Multicopter uses robots to transport medical samples [90]. OrionStar intelligent robots are presently working in Peking University's Shougang Hospital to give patient support, react to enquiries, and conduct remote diagnosis and treatment. Robots can assist in the distribution of laboratory test results and medication, reducing the stress on medical staff and reducing human-to-human contact [67,86].
The use of robotics and automation in healthcare and related fields is growing by the day [101,102]. The International Federation of Robots (IFR) expects an increasing trend in medical robot demand in the following years, with a 9.1 billion USD market estimated by the end of 2022 [102]. Robots not only assist physicians and medical personnel in performing complex and precise jobs, but they also reduce their workload, enhancing the overall efficiency of healthcare institutions [103].
As seen in the Chinese outbreak, effective COVID-19 management can drastically minimize the number of infected patients and casualties. Because it has now become a worldwide concern, technologically advanced countries can assist others by providing support equipment and robotic infrastructure to ensure a successful conclusion in treating this disease. This brief assessment demonstrates that the implementation of medical robotics has considerably improved the safety and quality of health management systems when compared to manual methods as a result of healthcare digitalization [102]. Medical robots are solely classified using application-based categories to meet every aspect of hospital services, from cleaning robots to extremely advanced surgical robots. There are numerous opportunities in the design and operation of medical robots, including a cyber-physical system (CPS), power management using optimized algorithms and renewable sources, fault tolerant control, and dependable architectures for reliable and safe operation within healthcare facilities.
Big Data and Facial Recognition: Control panels (dashboards) can be created to help track the virus continuously by using Big Data [24,90,104]. In all major Chinese cities, facial recognition and temperature measuring devices are being used. AI firms, including China's SenseTime and Hanwang Technology, claim to have developed sophisticated facial recognition systems that can distinguish people even while they are hidden. Smartphone and web applications can assist in following people and determining whether they have come into contact with an infected person [67].
Numerous stakeholders have explored ways to apply facial recognition into healthcare as the facial recognition market has evolved [24]. Machine learning has been used to discover genetic disorders based on facial dimensions using massive data sets developed for study [104]. This same technology is also used to track patients over time in order to detect minor changes caused by age, discomfort, and mood. One group has used facial recognition to validate patients before to surgery, while another has used it to identify an individual patient's likelihood of having problematic airway [67]. Because of the sensitivity of facial recognition, research has demonstrated that it is even more sensitive than physician judgement, raising the prospect of employing facial recognition to improve clinical decision making. However, facial recognition is most typically employed for human identification and security. Facial recognition has the ability to improve the efficiency and security of our healthcare systems, from identifying patients accessing PHI to monitoring workers for access to restricted parts of the hospital [105].
Artificial Intelligence: Data mining and statistical algorithms, are helping medical professionals and researchers to better describe particular types of diseases [86]. Baidu, the Chinese internet company, has made its unique algorithm (Lineatrfold) accessible. In contrast to other viruses like Ebola, HIV and Influenza, Covid-19 can be transmitted much more quickly because of its single-strand RNA. AI helps in determining the structure of the virus [24]. The Baidu Company built software to help to scan large populations and detect a change in the temperature of a person. These applications are currently being used at Qinghe railway station in Beijing to identify travelers who might be a survivor of this virus. This program identifies up to 200 individuals per second without disturbing the traveler [24,67]).
The application of AI in detecting infectious diseases is tremendously valuable in the medical sector and has the potential to revolutionize healthcare procedures [86]. Integrating AI into imaging operations and other medical processes has attracted a lot of attention in the healthcare industry [55]. Machine-learning (ML) prototypes can examine medical photos to diagnose illness in the early stages. To complete the mission, such prototypes are driven by big data and deep learning algorithms [56,106]. Pathology, ophthalmology, radiography, and dermatology are some of the potential applications for image-based learning [107]. The prevention of diseases like COVID-19 is heavily reliant on screening people through pathogenic testing, which is a time-consuming operation, and hence precision is essential [55]. In a study, the author implemented a medical identification approach for COVID-19 based on radiographic abnormalities in computerized tomography (CT) scans, achieving 85.2 percent accuracy in the testing and validation stage [107].
ML can help medical personnel by evaluating and organizing massive amounts of patient data recorded in digitized medical records [56,106]. Furthermore, ML is used in a variety of medical applications, such as diagnosing patients with severe problems who require intensive care unit (ICU) facilities immediately, identifying early indicators of diseases, comprehending the patient's respiratory state by studying chest X-rays, and so on. As a result, AI and machine learning increase the performance of the identification and prediction processes, as well as how administrative decisions are made in the medical sector [107]. In the context of the COVID-19 pandemic, the aforementioned technologies have already considerably benefited medical personnel dealing with the problem [106,108].
Autonomous Vehicles: Autonomous vehicles can be used for transporting essential items such as drugs and groceries [86]. Apollo, one of the automated vehicle groups of Baidu, has developed the Neolix autonomous vehicle to deliver supplies and food to emergency health facilities in Beijing. Baidu Apollo has made its micro-car kits and automated vehicle software available at no cost to companies who are working on the virus and its impacts. Idriverplus, a Chinese self-driving company that focuses on autonomous road cleaning cars has contributed towards the organizations that are working to combat the spread of the virus. Its vehicles are being utilized to sterilize medical clinics [86].
In the World Economic Forum's newly released report, "The Future of the Last-Mile Ecosystem," we predicted that e-commerce delivery demand would result in 36% more delivery cars in inner cities by 2030 [109]. The COVID-19 crisis has resulted in a massive increase in demand, as people all over the world are self-isolating, quarantining, or working from home for extended periods of time, causing a surge in the demand for food, groceries, household items, and even medical supplies to be delivered to the homes of millions of people [86]. This rising demand has already put a strain on many suppliers' existing supply chains and delivery infrastructures. It also increases the danger of infection to delivery drivers and improves their ability to spread the sickness. This pressing threat of exposure, as well as the pressure on present delivery services, could be mitigated by automated delivery trucks [109].
Social Media: Increases in connectivity and access to data allow health authorities to monitor epidemic transmission more quickly and provide alerts to the public [88]. Facebook has created maps displaying population density, demographics, and travel habits, thus enabling scientists to pick the areas to deliver medicines or how to cure illness [85]. Therefore, Facebook, YouTube, Google, Twitter and other several social networks are collaborating to try to recognize and remove misinformation regarding COVID-19, and referring people to the WHO's credible reports [86].
People are using social media more than usual in the aftermath of the COVID-19 outbreak because they rely on news sources from online sites to find health information for themselves and their loved ones [110,111]. During the ongoing COVID-19 pandemic, the use of social media platforms has been a welcome reprieve in the health disaster and worldwide crisis [112]. Social media platforms have made it simple to find health information, empowering people to assess health risks and handle global health challenges [113,114]. In reaction to a global public health crisis, social media users often create and disseminate health information available from local and international sources. Meanwhile, health professionals and governments have begun to use social media platforms to contain and manage the negative impacts of a health crisis [115].
Scholars conducted numerous studies to explore how the public finds, generates, and communicates health information through internet sources during a health emergency situation, according to the available literature [116][117][118]. Earlier studies in this area of health crisis focused primarily on user channel selection [119]. They discovered that in both health crisis events and normal circumstances, consumers tended to depend more on traditional media for health information [120]. People seeking health information utilize smartphones and social media more than conventional media in the emergence of a health crisis [115,121]. Table 1 summarize the main results on how these technologies improved the healthcare performance during COVID-19 pandemic. Improve process efficacy and accuracy by using the computerized system in classification and categorization, which improves health service quality.

Robotics
Can be used to assist medical practitioners in complex and precise operations, which improve the safety and quality of health service quality.

Recognition
Using big data in machine learning and facial recognition will help medical decision making especially in diagnosing and tracking patients, which improves the performance and security of the health service quality at the minimum cost.

Artificial Intelligence
AI using ML and Data mining enables medical practitioners and researchers to infer disease characteristics which will help in diagnosing illness in the early stages.

Autonomous Vehicles
It can be used to deliver food, supplies, drugs, and medical personnel while at the same time controlling the infection. Medium

Social Media
Collecting data and improving awareness about certain medical situations is much easier and more efficient using social media. Low

Conclusion
The COVID-19 pandemic is still ongoing, and it is too soon to adequately assess the importance of sophisticated technologies in pandemic response. Although sophisticated technology provides tools to aid in pandemic response, they do not provide an immediate answer. An innovative healthcare system can help to promote better patient selfmanagement, reduce costs, relieve staff pressures, help with resource and knowledge management, and improve the patient experience. An innovative healthcare system can reduce the expense and time for research, and can increase the overall efficacy of the research. An innovative healthcare system can strengthen the current state of medical resource disparity, accelerate medical policy, and encourage the adoption of preventive strategies and reduce the social medical costs. From the COVID-19 case study, we can identify the main advanced technologies that play significant roles in improving the performance of the healthcare system. These technologies include; colour coding, social media, autonomous vehicles, AI, big data, facial recognition, and robotics. However, to expand alongside the emerging area of mobile and innovative healthcare, the COVID-19 epidemic necessitates not only data sharing but also rigorous evaluation and ethical guidelines with community participation. Building public trust requires robust communication strategies across all creative platforms, as well as demonstrating a commitment to proportional privacy.