Smart technology is when devices use the internet, artificial intelligence (AI), the cloud and other modern functionalities. A smart city aims to promote economic growth and optimize city functions using data analysis and smart technologies. Cities play an essential role in ensuring the wellbeing and health of residents. They are developing healthcare ecosystems that diagnose and treat illnesses and injuries and use digital technology to support prevention and early intervention. Advances in technology are making a difference throughout healthcare, with many new systems being used to optimize patient care, such as predictive analytics, telemedicine, contact tracing apps and more. Healthcare leaders play an essential role in ensuring that smart technology is successfully implemented in organizations.
A smart city uses information and communication technology (ICT) to provide better government services, share information with the public, and improve operational efficiency. Smart cities have sensors collecting data. The data is analyzed, insights are communicated to decision makers, and solutions are created. Operations and asset management are optimized, and the quality of life for residents is improved. Healthcare access and quality are considerably higher in urban areas than among remote and rural populations. Smart cities that are digitally connected and data-driven can make healthcare smarter when data and systems are combined across health and other services. Smart cities can ensure health equity by providing healthcare to all and addressing the environmental, economic and social factors affecting residents’ wellbeing and health. Many cities are making investments to ensure quality remote treatment, diagnosis and telemedicine services. They have made digital health service delivery a new priority.
Most COVID-19 cases were in cities, and the pandemic demonstrated that people’s wellbeing and health are connected to their communities. The pandemic brought unprecedented challenges, and the need for technology became apparent. Some cities dealt with the pandemic more easily than others as they already had digital systems in place. Since the pandemic, city leaders have been implementing digital systems to improve community care and health equity and remove barriers to healthcare. Developing smart healthcare involves access to data, health system navigation and health literacy. Digitalization was a crucial factor in cities’ response to the pandemic, with tools used to measure risk and advise on confinement and social distancing. The pandemic resulted in rapid digital transformation and made the development of smart cities possible. Many cities implemented digital platforms to enable communication with residents.
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Implementation Of Smart Technology In Healthcare:
Contact Tracing Apps
During the COVID-19 pandemic, public health officials tried reducing transmission rates using contact tracing apps. Contact tracing identified infected individuals and notified anyone who may have caught the disease. Infected individuals and their contacts were asked to quarantine and get tested.
Contact tracing may mean lower transmission rates because people at risk are identified and notified.
Contact tracing apps were used for the first time in response to COVID-19. Contact tracing can be facilitated by technology, such as apps that can be used on cellphones. There are challenges to using this method, including privacy concerns and adoption rates.
There are currently two main approaches. One is based on the Global Positioning System (GPS) – the app tracks where someone goes, so if they catch COVID-19 or another infectious disease, it will show where they have been. After this, a more traditional approach is used with manual contact tracing. The second approach is based on Bluetooth – the app sends a signal from someone’s phone to another phone that is also running the app. The phones store the signal. If neither person catches the disease, those signals are dormant. However, if one person gets the disease, they can notify the app, which can notify all the phones that received the signal.
It is currently unknown how many people are using contact tracing apps. It can take time for people to use new technology. The Bluetooth apps do not track locations or have any identity information, but some people have privacy concerns about having their location tracked on the GPS app. Manual contact tracing is very slow, whereas the apps provide fast responses and identify more people with whom the person has had contact. Developers are likely to continue working on these apps and incorporate more features that public health authorities want. Policymakers may agree that apps can be interoperable and used between jurisdictions. They may find ways to encourage the public to use these apps, including clarifying privacy concerns and strengthening privacy protection.
Contact tracing apps are still very new, and more work is needed to make them more accessible. There are groups of people who have less technology experience and vulnerable groups who do not use smartphones. This presents challenges that need to be addressed, but the speed and effectiveness of these apps could potentially transform contact tracing.
Telemedicine
Telemedicine provides healthcare services remotely, allowing those living in rural or remote areas to access quality care. Smart hospitals use telemedicine to monitor patients remotely and give them access to remote specialist medical care. Telemedicine is used for consultations and initial diagnosis, remote patient monitoring and medical education for health professionals. Providers deliver individual treatment plans and prevent hospital admission or readmission. Fewer patients in hospital means reduced costs and an improved service. Access to healthcare can be improved, particularly for people living in rural or underserved areas. There is no need to travel for the appointment, which is convenient for patients. Telemedicine improves communication and collaboration among healthcare providers, delivers care smoothly and efficiently, and protects against medical errors.
The three kinds of telemedicine are remote patient monitoring, store and forward, and interactive medicine. Remote patient monitoring allows clinicians to communicate with patients and record health information, whereas interactive medicine involves patients and physicians connecting through video calls. Store-and-forward telemedicine sends medical images and reports directly to the practitioner, alleviating the need for physicians to meet patients in person. Smart hospitals that use telemedicine and virtual care technologies can provide quality treatment throughout all aspects of care. Monitoring patient health can improve chronic condition management, reduce the spread of infectious diseases and reduce hospital readmissions. Telemedicine has been used with patients who have chronic diseases that are affected by diet. Interventions include regular communication with health professionals to support patients in adopting healthier dietary lifestyles.
Telemedicine tools have become more accessible and affordable, and healthcare organizations can treat patients who live far away. Telemedicine is being applied to new types of medical care, and healthcare organizations are embracing new practices to improve health outcomes. Patients can access preventive care and emergency care that improves outcomes. Patients using telemedicine can avoid spreading infections and be kept safe from exposure.
Data Analysis
Data analysis can be utilized in many aspects of patient care and operations management. It can identify ways to improve healthcare and find the most effective treatments. Data analysis is expected to seriously impact different areas of care, including early disease detection and personalized patient care. Data analysis uses a clinical and molecular data library that provides a clear clinical context for healthcare professionals working with cancer patients. The data includes lab reports, cancer research, radiology images, clinical notes and pathology, and allows for individualized treatment. Machine learning models identify biomarkers on mammogram screening that indicate the risk of a patient developing breast cancer.
Data analysis in clinical settings can improve scheduling and staffing, reduce patient waiting times, and offer more choice when making appointments. Analysis of patient-generated data, social factors and lab results can reduce the risk of long-term illness, improving patient outcomes and reducing healthcare costs. The benefits of data analysis in healthcare include supporting clinical decisions from doctors and other healthcare professionals and more efficient healthcare provision with lower costs. Healthcare providers apply a systematic outlook to improve patient outcomes and implement improvements to healthcare processes. The analysis of patient data contributes to fewer errors, reduced readmission rates and more effective identification of high-risk people.
Electronic health records (EHRs) provide the most patient data and were established to improve treatment efficiency and patient care. The data can deliver insights into the improvement of care. The analysis can identify patterns of disease and provide warnings to doctors. Doctors and nurses can use analysis to recognize the most successful treatments and adapt their practices accordingly. EHR data can guard against medication errors; the spreading of disease can be identified; and prevention and treatment plans can be put in place.
Predictive Analytics
Modern healthcare solutions use data analytics to improve health outcomes. Predictive models and data-driven insights allow healthcare organizations to foresee patient needs, identify potential problems, and recognize health trends more effectively. Analytics enables healthcare providers to predict health outcomes and assign resources accordingly, meaning that care is improved and cost-effective. Analytics considers the patient’s medical history and gene profile and individualizes treatment. Early interventions can reduce readmissions, and the prediction of resource needs improves operational efficiency.
Predictive analytics is changing patient care, bringing an understanding of potential outcomes and current challenges. Data mining techniques and machine learning enable healthcare providers to identify risk factors and potential problems, improving patient care. Predictive modeling can considerably affect intensive care, emergency care and surgery, where decisive actions make a difference in patient outcomes. Predictive analytics can forecast the likelihood of trends, the spread of disease and various health conditions. Healthcare providers are able to make informed decisions about treatments and how to personalize them for patients. Analytics can identify patients at risk and make problems less likely through interventions. Hospitals are able to identify high-risk patients and organize necessary resources, and physicians can make quick and accurate diagnoses.
Analytics can identify patterns and warn that a patient requires an emergency room (ER) visit. Nurses can respond by providing the necessary care and making the ER visit unnecessary, which is better for the patient and reduces the demands on the ER. Predictive analytics provides useful information to staff in the intensive care unit, where timely interventions can save patient lives. Predictive algorithms monitor and analyze patients’ vital signs and recognize needed interventions. Analytics can also recognize warning signs for patients in a general ward, alerting staff to the need for the rapid response team. Predictive analytics is a useful tool in healthcare, improving patient outcomes and safety.
Healthcare Leaders
Healthcare leaders can support the implementation of smart technology in their organizations and ensure that staff are committed to using new systems. Leaders can communicate their vision and share how smart healthcare can reduce inefficiencies and waste and improve the safety and quality of patient care. Leaders must work to get the whole organization behind a new digital culture. The success of smart healthcare relies on the organization’s capability to develop a digital culture. The culture, people and processes need to support the building of digital services. Leaders must align the digital vision with employees’ behaviors and values. With a collaborative approach, the organization can move toward adopting smart healthcare.
Smart healthcare involves a continuous process that requires collaboration between leaders and staff. Ongoing communication ensures that problems are quickly identified and solutions are applied. Leaders can develop new programs that enable staff to provide quality care and management to reduce care costs. Leaders must ensure that staff are trained and educated to work effectively with smart technologies. Staff must be trained to use smart technology and provide more efficient diagnoses and treatment. Investment in training will benefit organizations with better data management and reduced costs. Training staff to use smart devices and systems can boost productivity, reduce medical errors, enhance patient care and improve the patient experience.
Smart Healthcare
Smart cities are using data analysis and technologies to optimize city functions. They are developing healthcare ecosystems that use digital technology to ensure that residents receive quality care. The COVID-19 pandemic resulted in a rapid increase in the use of technology, and advances in digital services have been seen in many industries. There are numerous facets to digital healthcare, and some of the functions include telemedicine, data analysis, predictive analytics and contact tracing apps. The advantages of smart healthcare include early disease detection, personalized patient care, reduced readmission rates and the identification of high-risk people. Healthcare leaders play an essential role in the successful implementation and use of smart technology.
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