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Devices to Improve Healthcare Service Delivery

Introduction

Healthcare providers are facing challenges while delivering quality care following the COVID-19 pandemic. The medical staff and affiliated workers experience physical and psychological pressure in diagnosing, assessing, providing treatment, and tracing patients’ recovery processes. Therefore, the report provides a proposal and development of IoT-based devices to improve practices in healthcare service delivery to manage COVID-19-related issues. It describes various challenges affecting current healthcare practices following the review of real-world case studies.

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The challenges are likely to be resolved with the implementation of the IoT solution, which implies the use of a specific application that adopts GPS, Bluetooth, and Wi-Fi to track patients’ data, trace their recovery process, and broadcast the movement of vaccinated and unvaccinated people.

The potential challenges that the healthcare sector faces include difficulties following the inconvenience and inefficient delivery of blood, vaccines, serum, birth control, and other supplies to rural areas. However, patients in rural areas who require immediate medical attention are likely to receive inadequate quality care, which is a risk of an increased mortality rate following COVID-19 effects and related containment measures. Therefore, healthcare IoT-enabled drones are essential tools to enhance the delivery of medical supplies and improve the public’s well-being. The other challenge associated with the COVID-19 pandemic is the limited number of beds and inadequate information about the available beds to accommodate hospitalized patients. Healthcare facilities need to place IoT sensors on the beds for easy identification of available beds, thus enhancing visualization of hospital capacity. The technological tool, IoT, will help the hospital stakeholders and the local authority to prepare and provide necessary resources and beds to manage patients.

COVID-19 has led to strict measures, including lockdowns that limit patients’ accessibility to healthcare services. Healthcare providers face problems with tracking and monitoring patients for appointments and registering new victims to sustain remote treatments. IoT-enabled devices will help physicians and nurses to measure patients’ data and identify and respond to emergency situations (Javaid and Khan, 2021). Hence, this paper provides a diagram illustrating the application’s design and architecture following the process from the developer to the user process and government regulation. The implementation process will follow the repository, registration, and profile creation to achieve its validity use.

Digital technologies have extensive impacts on various activities in the modern world. The internet of things involves using mechanical and digital devices appropriate in computing and transmitting data in a given network by applying human level. Therefore, IoT-enabled devices result in increased patient engagement and satisfaction; hence, they are essential for reducing hospital stay days and healthcare costs, minimizing readmissions, and improving treatment outcomes. Thus, it is appropriate to adopt and implement IoT by redefining the space of devices and people interaction to transform the healthcare industry and enhance healthcare delivery solutions.

Background

COVID-19 Pandemic has dramatically impacted human lives in various ways. Its emergence has led to changes in healthcare sectors, technology context, education, and business institutions. The adjustments and changes in doing things have impacted the economy. According to Nasajpour et al. (2020), COVID-19 occurrence is the most significant public health crisis due to the increased mortality rates and infected persons. The disease causes illnesses from 1-14 days after getting in contact with an infected person. The challenge is that an asymptomatic patient can also transmit the COVID-19 virus. Therefore, early identification and isolation of such patients are vital to combating and reducing the increased spread of the virus. The other concern is that the disease takes 6 to 41 days to recover from its underlying conditions. Therefore, researchers and healthcare providers are trying to understand the appropriate ways and techniques to follow to reduce the COVID-19 spreading rate. Healthcare workers in many countries remain in-person to become involved in treating and screening these conditions.

In contrast, healthcare and frontline workers had to face all these patients daily with the risk of forestalling more patients from coming into the hospital at any time. An excessive workload and inadequate personal protective equipment are required to support healthcare workers in completing their treatment, thus overcoming COVID-19-related challenges (Felice et al., 2020). Unfortunately, many hospitals lack enough beds, and even medical support, such as that requiring oxygen supplementation, is going to be reduced, and death rates could continue to rise. Within the timing and magnitude of the epidemic peak, there is a need for an immediate determination of the minimum healthcare capacity essential for care delivery.

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The increased rate of COVID-19 transmission can result in a significant burden across the United States as it becomes heterogeneous. The challenging aspect, in this case, is the adequacy of gathered information and accuracy in determining the epidemic peak season. The healthcare providers and researchers need to select and balance the system capacity and the quality of care for a certain number of patients to enhance recovery outcomes and minimize the spread of this virus. However, the challenge of obtaining adequate and accurate data on emerging outbreaks such as COVID-19 is due to the limited and unreliable information about the incidence; hence, it becomes challenging to provide accurate predictions of the epidemic peak. The other concern is to research and understand the effects of rapidly changing mitigating efforts in reducing the COVID-19 virus spread (Miller et al., 2020). Hence, testing standards and measures variability at the county level and inadequate serological data cause difficulties in mitigating the risks of COVID-19 spread.

Predicting the disease peak focusing on intensity and time is essential to provide solutions and monitor the mitigating process. Describing the season of an epidemic helps prepare for a positive response and minimize the disease burden. However, other estimates of disease burden’s regional footprint offer critical information, thus influencing resource distribution (Miller et al., 2020). Therefore, the healthcare sector needs to identify the hospital’s capacity to accommodate a given number of patients with reported acute and chronic infections at the county level to facilitate quality care delivery. This will help the area measure the degree of disease burden and capabilities to solve the problem.

Adequate resources for healthcare practices are vital for enhancing recovery outcomes and minimizing the spread of infectious diseases. Studies show limited resources on aspects of infectious disease outbreak, whereby COVID-19 is among the contagious illness that causes heterogeneity disease burden. This is because county-level authorities and healthcare providers face challenges in deciding whether patients are suitable for invasive treatments. The challenge is to identify the virulent level of an infectious disease and the significant resources required (Miller et al., 2020). Therefore, healthcare providers have adequate knowledge of the degree of contagious disease and its peak compared to the general public; hence, it becomes difficult to regulate the condition and available resources.

Healthcare providers also face difficulties while providing services during the pandemic. The outbreaks resulted in increased workloads among healthcare workers and issues such as the fear of adopting new and frequently changing protocols, using personal protective equipment, the fear of contagion for families and themselves, and saving the lives of very sick patients. Frontline workers are likely to experience adverse physical and psychological dangers following possible experience adverse physical and psychological risks following caring for COVID-19-infected patients. Studies show that most healthcare professionals acquire signs of post-traumatic stress disorder after handling deteriorating patients (Rossi et al., 2020). Hence, providing adequate resources during COVID-19 diagnosis, assessment, and treatment will help improve the well-being and safety of healthcare providers and increase the quality of care delivery.

Healthcare sectors are trying to eliminate the use of the traditional approach to mitigate the Pandemic risks since they are costly, time-consuming, and inefficient. Studies show that IoT is appropriate for managing issues related to COVID-19. In the present day, physicians can use technological devices in the treatment phases, such as diagnosis, isolation, and after recovery, through tracking, control, and review of processes to solve COVID-19-related challenges (Nasajpour et al., 2020). In addition, there are multiple applications, such as Life360, Google Maps, or Glimpse, that help people track their family members and relatives. At the same time, they are inefficient due to people’s inability to mitigate the risk of infection by themselves as they do not include health screening and tracking on the basis of COVID-19 – thus, a potential solution should combine all these functions.

Solution

Therefore, technology is essential in the fight against the pandemic. The government needs to provide funds to help stop the spread of the virus (Vargo et al., 2021). Healthcare providers must use the opportunities provided by improvised means due to their high efficiency (Goldschmidt, 2020). By registering in the application, a person only agrees to provide the application with data about his location and indicates his status. There can be several statuses: vaccinated or unvaccinated and the presence of antibodies. The application on the map broadcasts shows the movement of such people and alerts every healthy and vaccinated people about the possible proximity of an infected or unvaccinated person.

The application will be a set of the maximum simple registration interface and profile, with the ability to edit the status. In addition, the application will display a map of the area showing the movements of also registered people. First, people will be able to more competently and consciously observe social distance as a necessary limitation to stop the spread of the Pandemic (Ting et al., 2020). Secondly, this application will be at hand for everyone, and each person will more carefully choose places to visit. Displaying unvaccinated people is necessary because large gatherings of unvaccinated groups pose a more significant share of the risk of infection than a similar population of vaccinated people (Shahcheraghi et al., 2021).

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Given that new strains of viruses are spreading rapidly, this application can mitigate the spread risk (Torjesen, 2021). Users should understand that this application must be cross-platform and work on all possible mobile operating systems. The application developers manually regulated and set its modes only for specific situations. For example, a physician is responsible for confirming diagnosis, recovery, and vaccine availability in particular medical institutions to avoid misinformation through this application. Users will set the mode for symptoms of a cold or infection and the absence of a vaccine. For each of these regimes affixed in medical institutions, a given state establishes a specific validity period. Another advantage of this application is that reports of possible symptoms can be sent through it, drawing the attention of healthcare professionals to newly discovered cases. As a result, the application will help organize more thoughtful work at many system levels— (describe enabling tech).

Finally, this application’s architecture and design features are presented below in Figures 1 and 2, respectively. Different countries comprise similar prototypes, but most were not localized nor had any functional features (Nasaipour et al., 2020). For storing data, it is possible to use classical relational databases since the specifics of the problem satisfy the need for strength, atomicity, and data isolation. View entities, if this application is developed according to the model-view-controller scheme, it has only three different windows: registration view, profile view, and map view. The models are users themselves, and the global distribution of the application, and the division of geographic objects into maps can also be presented as models form. The controller in this situation will serve as a control center and display models in the map view windows. As a result, this application is almost entirely devoid of any complex functions, except the classic editing, creation, and deletion at the stage of registration and profile editing.

IoT Table List.
IoT Component Hardware Software Enabling Technologies
Smartphone Devices: iPhone 5 or later
Samsung Galaxy S7 or later
OS: Android 7.0 or later
iOS 13.4 or later
Screen orientation: portrait
Cloud storage system, use of geographic maps

Prototype architecture and design

Prototype architecture and design

Prototype architecture and design

Implementation

According to the process of development of the prototype, a logic app was broken down into each of the steps. Throughout every development, each stage allows the prototype to monitor while subsequently I also implemented another app called Azure map. After the monitor process, it was able to detect only the geo-location whenever there are many people in the place as every device is wireless and connected to the internet and therefore it will be helpful for the people to use the app and there will require a reduction of people as shown in the solution.

Evaluation

The application’s performance evaluation will involve the correctness of profile data display, the test of the validator, the calculation of the systematic error in the presentation of models on the map, and the resistance of the database to atypical queries. It will require four tests on a different data set, taken from user testers and implemented through additional unit testing systems. Users should understand that the application does not collect users’ data: they indicate only their status and permission to display their geo-location. The prototype has overcome the problem of the experiment, which is easily testing the application. Henceforth, one should transfer data to the cloud for analysis. Through research, the maps would pinpoint which areas are not supposed to go and which areas are safe.

Conclusion

Countries throughout the world have implemented digital technologies to aid in understanding, tracking, and reducing COVID-19 infections. Furthermore, several technological apps such as GPS and Bluetooth devices are still researched following data protection and privacy since they can cause more false positives. The Internet of things has been around for decades. It solved many healthcare solutions and lifestyles other than those IoT devices that people have already invented, such as wearable devices, except for the COVID-19 situation.

The current contact tracing technologies have several limitations. The virus is still growing in many nations since there is no reliable methodology for predicting COVID-19 clusters, so no effective viral containment techniques exist. In this paper, we discussed a novel IoT application that may be used for contact tracking and predicting the epidemic peak of COVID-19. The report shows that technology applications provide solutions as they are tested and experimented with.

The device helps healthcare workers feel at ease since this application would allow people to test themselves whether they have the virus or not, even with their vaccination on it with these checks. The data collected would be sent to the cloud for analysis and allow the Health Organization to see which area is unsafe or not. Therefore, the Health Organization would post a map whereby people could see the location of safe gatherings or hazardous gatherings. Big data received from phone applications are delivered and stored in cloud computing servers for future forecasts and risk prediction. Healthcare providers should access this data to spot clustering and take appropriate measures to control the problem better. In a future health crisis, the proposed instrument might be applicable in tracing patients’ contacts and surveillance. As a result, if the application did not work for everyone, I recommend that it should be improved as more functionality can still be programmed and used for tackling COVID-19 and other health issues.

Reference List

Felice, C. et al. (2020) ‘Impact of COVID-19 outbreak on healthcare workers in Italy: results from a national survey, Journal of Community Health, 45(4), pp.675-683. Web.

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Goldschmidt, K. (2020) ‘The COVID-19 pandemic: technology use to support the wellbeing of children’, Journal of Pediatric Nursing, 53, p.88. Web.

Javaid, M. and Khan, I. H. (2021) ‘Internet of Things (IoT) enabled healthcare helps to take the challenges of COVID-19 pandemic’, Journal of Oral Biology and Craniofacial Research, 11(2), pp.209-214. Web.

Miller, I.F. et al. (2020) ‘Disease and healthcare burden of COVID-19 in the United States’, Nature Medicine, 26(8), pp.1212-1217. Web.

Nasajpour, M. et al. (2020) Internet of Things for current COVID-19 and future pandemics: an exploratory study’, Journal of Healthcare Informatics Research, pp.1-40. Web.

Rossi, R. et al. (2020) ‘Mental health outcomes among healthcare workers and the general population during the COVID-19 in Italy’, Frontiers in Psychology, 11. Web.

Shahcheraghi, S.H. et al. (2021) ‘An overview of vaccine development for COVID-19’, Therapeutic Delivery, 12(3), pp.235-244. Web.

Ting, D. S. W. et al. (2020) ‘Digital technology and COVID-19’, Nature Medicine, 26(4), pp.459-461. Web.

Torjesen, I. (2021) ‘Covid-19: Omicron may be more transmissible than other variants and partly resistant to existing vaccines, scientists fear’. Web.

Vargo, D. et al. (2021) ‘Digital technology use during COVID‐19 pandemic: a rapid review’, Human Behavior and Emerging Technologies, 3(1), pp.13-24. Web.

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