Learning Objectives
By the end of this section, you will be able to:
- Define telemedicine
- Define artificial intelligence
- Explain how AI and telemedicine impact patient care
- Identify the challenges of integrating AI into telemedicine
- Describe the role of technology in nursing education
- Discuss the nurse’s role in the evolution of telemedicine and AI
Imagine the convenience of connecting with your health-care provider through a video call during your lunch break at work, eliminating the need to take time off to seek medical care. What was once a futuristic idea has now become a reality with telemedicine. While telemedicine is not a new concept, recent advancements in technology—especially in the wake of the COVID-19 pandemic—have propelled its use, solidifying its place in modern health care. Embracing the power of artificial intelligence (AI) further enhances telemedicine’s capabilities and creates endless possibilities for future developments. As nurses, it is important to be well-informed about the potential challenges posed by AI-based telemedicine and recognize the integral role we play in its evolution and successful implementation for safe and effective patient care.
The discipline of informatics, the science of information, plays a pivotal role in harnessing these technological advancements within health-care organizations. By incorporating informatics into their operational strategies, health-care providers can streamline workflows, enhance data-driven decision-making, and improve overall efficiency in delivering patient care. The Institute of Medicine’s Healthy People 2030 objectives further emphasize the importance of health information technology for achieving enhanced access and effectiveness in health-care services, creating a strong impetus for health-care organizations to embrace technological innovations (National Academies of Sciences, Engineering, & Medicine, 2021). Due to all these factors, the total value of the health-care information technology market is projected to surpass $707 billion by 2032 (Acumen Research and Consulting, 2023).
As technology continues to transform the health-care landscape, it is critical for nurses to adapt effectively, understanding and embracing the uses and impact of health informatics and information technologies within their practice. High-tech devices are developed and implemented to improve patient care, but they will never replace the importance of human touch and compassion. Consequently, nurses must play a role in the digital evolution of health care, as they leverage new technologies to optimize workflows and achieve better patient health outcomes. In brief, nurses who stay abreast of technological advancements are best positioned to foster an environment of continuous improvement and patient-centered care.
What Is Telemedicine?
The remote diagnosis and treatment of patients by means of telecommunications technology is called telemedicine. Sometimes referred to as telehealth, telemedicine allows health care to be delivered from a distance using technologies such as computers, cameras, tablets, smartphones, videoconferencing, wireless communications, and the internet. Telemedicine may be used to provide care for a variety of situations, such as:
- postsurgical follow-up
- prescription management
- treatment of skin conditions
- delivery of lab or test results
- online counseling
- physical and occupational therapy
- remote monitoring of chronic or reoccurring conditions and urgent care issues
Clinical Safety and Procedures (QSEN)
Telemedicine for Stroke Assessment and Care
John, a sixty-year-old man, has a history of hypertension and is at risk for stroke. His health-care provider has equipped him with a telemedicine kit that includes a tablet, a high-resolution camera, and a connected blood pressure monitor. The telemedicine platform is designed to facilitate regular check-ins and immediate assessments in case of potential stroke symptoms.
- Remote monitoring: John uses the telemedicine kit at home to measure his blood pressure regularly. The data is transmitted securely to his health-care provider, who monitors trends and adjusts his medication as needed. Additionally, the tablet is equipped with an application that guides John through simple neurological assessments, such as checking for facial droop, arm weakness, and slurred speech.
- Regular telehealth check-ins: Every few weeks, John has scheduled video calls with his neurologist through the telemedicine platform. During these check-ins, the neurologist assesses John’s overall neurological function using standardized stroke scales, such as the National Institutes of Health Stroke Scale (NIHSS).
During the video call, the neurologist guides John through specific tasks to assess his neurological status, such as asking him to lift both arms, smile to check for facial symmetry, and articulate specific phrases. The neurologist scores each task based on the standardized scale, providing an objective measure of John’s neurological health. - Emergency assessment: One day, John experiences sudden weakness on one side of his body and difficulty speaking. Recognizing these potential stroke symptoms, John activates the emergency feature on his telemedicine platform. The neurologist is immediately notified and conducts a live video assessment.
Using the tablet’s camera, the neurologist observes John’s physical symptoms in real time. The neurologist guides John through additional assessments to evaluate the severity of the symptoms. Based on the findings and the NIHSS scores, the neurologist determines that it’s a potential stroke and activates the emergency response team. - Timely intervention: Emergency medical services are dispatched to John’s location, and he is taken to the nearest stroke center for immediate intervention. The early detection through telemedicine enables a faster response, potentially reducing the long-term impact of the stroke.
This example demonstrates how telemedicine, combined with stroke scale assessments, can be a powerful tool for continuous monitoring, early detection, and timely intervention in cases of stroke, ultimately improving patient outcomes.
While the delivery of virtual health care continues to increase in popularity and frequency, it may not be appropriate for all situations. For example, conditions that require the provider to physically assess the patient or perform diagnostic testing still require a face-to-face visit. Emergencies such as severe trauma, acute chest pain, or sudden neurological deficits demand immediate in-person evaluation to ensure timely and accurate treatment. Additionally, complex cases where multiple specialists need to collaborate or where nuanced physical examinations are crucial may also necessitate traditional office visits.
Clinical Judgment Measurement Model
Take Action: Determining Appropriateness of Telemedicine Visits
While working the triage phone line, a nurse at a hospital receives a call from a patient reporting they woke up with their “eye crusted shut.” The nurse asks the patient a series of follow-up questions, such as if the eye is red, if there is a foreign object in the eye, and if one eye or both eyes are affected (recognizing cues). From the patient’s answers, the nurse determines there are no foreign objects in the eye, only the right eye is affected, and the eye is red. The nurse then analyzes the cues and suspects the patient may have conjunctivitis, or pink eye (prioritize hypotheses). The nurse determines the patient needs to be scheduled to see a provider to receive medical treatment (generate solutions). Recognizing that pink eye is contagious, the nurse determines it would be better to schedule a telemedicine visit. The nurse confirms the patient has access to the internet and a mobile phone or computer, explains how the telemedicine visit will work, and schedules the appointment for later that day (take action).
Telemedicine allows for two-way telecommunications (Figure 37.2). The patient may be asked to supply the provider with their weight, vital signs, laboratory values, and symptoms. Additional documentation, such as images and medical records, may also be uploaded by the patient to ensure the provider has all information needed to accurately diagnose the problem. On the other hand, the provider may supply the patient with notifications or reminders related to their health, detailed instructions for home care, and encouragement for continuing with their treatment plan.
Utilizing telemedicine offers several benefits. It makes health care more accessible and affordable. Patients can conveniently access care from their current location, eliminating the need to travel, take time off work, or arrange childcare, thereby reducing associated costs. Additionally, telemedicine provides enhanced access to specialized providers, regardless of geographical constraints, while also minimizing wait times for appointments, lowering exposure to potential health risks, and increasing patient engagement and adherence to treatment (Vicente et al., 2022). For instance, patients can avoid exposure to contagious diseases such as influenza or COVID-19 by opting for virtual consultations instead of sitting in crowded waiting rooms. Research has shown that patients who participate in telemedicine visits experience lower hospitalization rates (Campion et al., 2023; Pande et al., 2015; Peters et al., 2021).
Cultural Context
Cultural Considerations of Telemedicine
Cultural considerations in telemedicine are crucial for providing effective and patient-centered care to individuals from diverse cultural backgrounds. When implementing telemedicine services, health-care providers should keep in mind the following variables:
- Language and communication: Language barriers can hinder effective communication between health-care providers and patients. Telemedicine platforms should support multiple languages and use interpreters when necessary. When communicating with English as a Second Language (ESL) patients, it’s important to use clear and straightforward language to ensure understanding. Avoiding slang can help facilitate effective communication.
- Cultural beliefs and practices: Each culture may have unique beliefs and practices related to health, illness, and treatment. Health-care providers must be culturally sensitive and respectful of these beliefs, as they can influence a patient’s willingness to engage in telemedicine and adhere to treatment plans.
- Privacy and confidentiality: In some cultures, discussing personal health matters openly may be considered taboo. Providers must ensure that telemedicine consultations are conducted in a private and secure environment to respect patients’ cultural norms and maintain confidentiality.
- Access to technology: Cultural factors can influence a patient’s access to technology and willingness to use telemedicine services. Providers should be aware of potential disparities and work to ensure equitable access to telehealth services for all patients.
- Body language and nonverbal cues: In telemedicine, the inability to fully observe a patient’s body language and nonverbal cues can pose challenges. Cultural differences in nonverbal communication, such as eye contact, should be considered, and providers should be sensitive to these nuances during virtual consultations.
- Family and community involvement: In some cultures, family and community members play a significant role in health-care decision-making. Providers should be open to involving family members in telehealth consultations if the patient desires and consents to it.
- Religious observances: Religious practices may impact a patient’s availability for telemedicine appointments. Many religious traditions observe specific days or times for worship, rituals, or rest, which could conflict with standard telemedicine appointment schedules. For instance, in Islam, Muslims are required to pray five times a day at prescribed times. These prayer times could coincide with potential telemedicine appointments, making it challenging for patients to be available without interruption. Providers should be accommodating and flexible with scheduling to respect patients’ religious observances.
- Health literacy: Cultural factors can influence a patient’s health literacy level, affecting their understanding of medical information and treatment plans. Providers should use clear and simple language and patient education materials that are culturally appropriate.
By integrating these cultural considerations into telemedicine practices, health-care providers can ensure care is inclusive, respectful, and effective in meeting the diverse needs of their patients. This approach fosters trust, improves patient engagement, and leads to better health outcomes for individuals from different cultural backgrounds.
Influence of COVID-19 on Telemedicine
Because telemedicine limits the physical contact required to provide care, the prevalence of virtual care rapidly increased with the onset of the COVID-19 pandemic in 2020. Within the first three months of the pandemic, telemedicine encounters increased by 766 percent, from 0.3 percent to 23.6 percent of all encounters (Shaver, 2022). The widespread adoption of telemedicine played a crucial role in reducing disease transmission, facilitating triage care, ensuring uninterrupted access to health-care services, and safeguarding the well-being of patients, providers, and the entire community (Shaver, 2022).
Telemedicine not only enabled safer health-care delivery during the pandemic—it also played a pivotal role in driving progressive changes in reimbursement policies. Some of these policies were temporary, but others became permanent. For example, the federal government expanded coverage for reimbursable services, allowed reimbursement for care received at the patient’s home, and expanded the number of providers eligible to provide telemedicine (Department of Health and Human Services [DHHS], n.d.). There has also been a rise in research studies providing evidence to support the use and effectiveness of telemedicine, which should further encourage policy changes as health care settles into a new “normal” postpandemic (Campion et al., 2023; Pande et al., 2015; Peters et al., 2021; Snoswell et al., 2023).
Link to Learning
The U.S. Department of Health and Human Services (HHS) provides telehealth policy resources for health-care providers and organizations.
Artificial Intelligence
Encompassing computer science and comprehensive data sets, artificial intelligence (AI) focuses on leveraging technology to address and solve complex problems, enabling machines to perform tasks that typically require human intelligence. AI analyzes data by using algorithms and models that recognize patterns in data to emulate how humans learn, a process known as machine learning. AI has the potential to increase the efficiency, accuracy, and speed at which health care is delivered. While there are benefits to AI, potential challenges include data privacy concerns, risk of error, and the inability of AI to demonstrate wisdom or compassion—both of which are essential to the delivery of health care. As such, AI is not intended to replace the provider. Rather, AI is intended to complement the provider so care can be delivered more efficiently, allowing providers more time to spend with their patients.
Common applications of AI in telemedicine include practices relevant to telemonitoring, patient care, and chronic disease management. AI-powered chatbots and virtual assistants can interact with patients to gather information about symptoms, provide initial assessments, and offer guidance on health-care queries. AI is used to analyze medical images—such as x-rays, MRIs, and CT scans—to aid in the detection and diagnosis of conditions. Wearable devices equipped with AI algorithms can analyze physiological data such as heart rate, blood pressure, and glucose levels, providing real-time insights to health-care providers and triggering alerts for potential issues.
Telemonitoring and Patient Care
The practice of monitoring aspects of a patient’s health from a remote location is called telemonitoring. It allows data such as heart rate, blood pressure, oxygen saturation, weight, and blood sugar levels to be entered or transferred into a portal that can be accessed by the provider. Telemonitoring has proven to be effective at monitoring both acute and chronic conditions. Research has shown telemonitoring to be particularly useful in improving patient outcomes for heart failure, stroke, COPD, asthma, and hypertension (Noah et al., 2018). By closely monitoring these data, providers can identify changes in a patient’s condition more quickly and alter the plan of care accordingly. In addition, telemonitoring reduces the patient’s travel time, frequency of visits, costs associated with seeking care, and risk of infection; it also frees up medical providers to attend to patient needs that cannot be monitored remotely.
Patient data management systems (PDMSs) are comprehensive software solutions designed to manage and organize patient-related data within health-care facilities. PDMSs automatically retrieve data from bedside medical equipment, such as vital sign machines, ventilators, and intravenous (IV) pumps. The integration of PDMSs and telemonitoring creates a more comprehensive and seamless health-care management approach. Patient data collected through telemonitoring devices can be directly fed into the PDMS, providing health-care providers with a holistic view of the patient’s health status. This integration promotes data-driven decision-making, enhances care coordination, and supports more personalized and proactive health-care interventions. Benefits of PDMSs include their integration with clinical decision support systems that enhance clinical decision-making, decreasing charting time, increasing time to spend with the provider, reducing medical errors, and improving clinical outcomes.
Patient Diagnosis
AI can also be used to assist providers in identifying and diagnosing diseases with increased accuracy, speed, and efficiency (Figure 37.3). AI can use stored medical images from x-rays, MRIs, ultrasounds, and CT scans to analyze subsequent images, for example. AI can also use patient data such as imaging, vital signs, demographics, medical history, and laboratory results to predict accurate diagnoses that may be used to support provider decision-making. While AI may be used to help providers make more informed patient care decisions and reduce the likelihood of misdiagnosis, it should not be used in solitude to diagnose a patient. AI can generate predictions; however, it is the responsibility of the health-care provider to apply their clinical judgment and expertise to accurately interpret the predictions and arrive at a diagnosis.
Clinical Judgment Measurement Model
Prioritizing Hypotheses: Using AI for Patient Diagnosis
Scenario: A patient named Emily presents with a persistent cough and shortness of breath. Her primary care provider orders a chest x-ray to investigate potential pulmonary conditions.
In the hospital’s diagnostic workflow, an advanced AI system designed for pulmonary imaging analysis is seamlessly integrated. Trained on a diverse data set, the AI algorithm excels at identifying nuanced patterns and abnormalities related to respiratory health. Emily’s chest x-ray undergoes meticulous analysis by the AI algorithm, which examines the image for indications of nodules, infiltrates, or other respiratory anomalies. The AI system generates a comprehensive report highlighting regions of interest and providing an assessment of potential conditions based on recognized patterns in the x-ray.
The AI-generated report is made available to the attending radiologist, who collaborates with the AI system in a synergistic approach. The radiologist, leveraging their clinical expertise, conducts a thorough analysis, considering both the AI insights and their own observations, and determines Emily has pneumonia. This scenario showcases the collaborative and complementary role of AI in pulmonary imaging, illustrating how technology supports health-care professionals in providing precise and timely diagnoses for better patient care.
Patient Treatment Plans
AI provides models for searching medical data to assist with the development of patient treatment plans. By collecting and analyzing data, computers can formulate treatment recommendations based on the patient’s diagnosis, health history, risk factors, and medical condition. While trial and error have historically guided some treatment plans, AI offers valuable insights into identifying the most beneficial treatment plan for the patient right from the beginning.
AI can be utilized to deliver individualized treatment for patients, tailoring medical interventions to meet their unique needs and conditions. AI chatbots, for instance, can be used to provide customized, real-time recommendations to patients according to the patient’s symptoms. Additionally, AI can be employed to provide patient education. By storing patient data, including medical history and preferences, these AI-powered technologies can effectively provide patient-centered care.
Robots
Robots are becoming increasingly integrated within treatment. For example, robots can be used to complete simple, repetitive tasks such as taking a patient’s vital signs and assisting with hygiene. Utilizing robots to complete these tasks reduces human workload and provides the nurse more time to focus on other, more complex duties. Robots can also be used to assist with mobility, provide medication reminders, and engage patients in opportunities for social interaction. They may also be used to help deliver medication, collect labs, and disinfect equipment. Artificial intelligence coupled with these robotic supports can produce powerful outcomes in data analysis and, in some cases, with diagnosis or alerts.
Additionally, robots can be used to perform surgical procedures. For example, the da Vinci Surgical System is a robotic surgical platform used for various procedures, including prostatectomies, hysterectomies, and colorectal surgeries (Figure 37.4). It consists of robotic arms controlled by a console, providing the surgeon with enhanced dexterity and precision. Used in spine surgery, the Mazor X and Renaissance systems assist surgeons in the placement of spinal implants with high precision. These robots enhance accuracy and reduce the risk of complications. In fact, surgical procedures are the most widely used application of robotics within health care due to the volume of procedures that can be conducted in comparison to the volume achieved by humans (D’Souza et al., 2019). AI is increasingly being incorporated into these systems to provide feedback after each surgery, potentially helping the surgeon improve their performance and improve the robotic products.
Link to Learning
Explore how robots are being used by nurses at Cedars-Sinai.
Patient Engagement
The field of study and application that focuses on the use of information and communication technologies to empower individuals in managing their health and health care is called consumer health informatics. It involves the integration of technology, information, and communication tools to provide consumers (patients or individuals) with access to health information, support self-care, and facilitate communication with health-care providers. Consumer health informatics encompasses topics such as health literacy, consumer education, personal health records, and patient engagement and empowerment. Consumer health informatics addresses these areas by analyzing consumers’ information needs, exploring methods to deliver accessible information, and implementing measures to cater to these needs. This includes integrating consumer preferences into health information systems and meeting the growing demands for internet-based health information.
Chronic Disease Management
AI technologies have the potential to bridge the gap between rising health-care costs and the increasing burden of chronic diseases, leading to reduced mortality rates. Algorithms offer the capability to identify individuals with an elevated risk of developing chronic diseases, predict the progression of existing conditions, and utilize health records to anticipate patient outcomes. Incorporating AI into chronic disease management holds the potential to lower costs, enhance outcomes, optimize resource utilization, expand access to care, improve quality of life, and alleviate the burden on the health-care system. It can also create personalized treatment plans based on each patient’s individual needs, provide the right treatment at the right time, reduce the risks of complications and disease progression, and reduce side effects of unnecessary treatments.
AI telemonitoring may also prove beneficial to the treatment of chronic medical conditions. AI algorithms can analyze patient data in real time and produce alerts for abnormal readings or patterns, aiding in the detection of changes to a patient’s health status and facilitating early interventions. Patterns can be identified to determine the effectiveness of a treatment plan and recommend adjustments as needed. Using real-time data, providers can then tailor the treatment plan to meet the individual needs of the patient, identify early warning signs, and provide personalized feedback.
Challenges with Telemedicine and AI
While telemedicine is associated with many benefits, there are also some notable challenges to be aware of. For example, telemedicine can be used to improve access to care, but providers must take caution not to inadvertently create or reinforce health disparities: preventable differences in the ability of socially disadvantaged populations to achieve optimal health. In particular, older adults, minorities, and those with lower socioeconomic status may not always have the necessary technologies, including internet access, needed for telemedicine. It is essential for providers to explore strategies for ensuring that patients who lack these key resources can still access telemedicine and to consider alternative approaches that reduce barriers to care for individuals who cannot access telemedicine.
Even when patients can access the internet and other necessary technologies, telemedicine adds a layer of complexity that may be difficult for some to understand. Patient education will be necessary prior to initiating telemedicine care. For this education to be effective, health-care professionals will need to receive training on how to use the technology and navigate potential challenges that may occur.
Link to Learning
The U.S. Department of Health and Human Services (HHS) maintains Telehealth.HHS.gov, a great resource to help patients make and prepare for a telemedicine visit.
Telemedicine can also pose challenges when a provider is unfamiliar with the patient’s medical history or unable to easily communicate with the patient’s other providers. This may result in fragmented care, with each provider knowing only the conditions and prescribed medications that are directly relevant to their expertise. Additionally, some health conditions may not be suitable for virtual care, necessitating in-person provider visits and potentially duplicating care efforts.
Another significant challenge associated with the integration of AI and telemedicine is the potential for dehumanization in health-care interactions. As technology plays a larger role, there is a risk of diminishing the human touch and empathy traditionally associated with health care. Patients may feel a sense of detachment when engaging with AI-driven systems or virtual consultations, impacting the quality of the patient-provider relationship. Striking a balance between technological efficiency and the human aspects of care is essential to ensure that patients feel supported, heard, and cared for throughout their health-care journey. Addressing issues related to trust, communication, and emotional support is crucial to mitigate the dehumanizing effects of advancing technology in health-care delivery. Other challenges include legal, ethical, data security, and privacy issues, warranting careful consideration in telemedicine implementations.
Legal and Ethical Issues with AI Use
Use of AI within telemedicine does not come without legal and ethical issues that must be considered. Laws and regulations are needed to ensure AI systems are transparent and their decision-making can be explained. AI technologies must prove to be fair, accurate, and nondiscriminatory. Regulations must also be in place to guide liability and clarify who is responsible for the decisions made by AI. Additional legal considerations include defining boundaries for AI use and developing international governance to maintain consistency across borders.
The most prevalent ethical concerns linked to the utilization of AI involve obtaining informed consent for data usage, ensuring algorithmic fairness, removing bias, and understanding the role of human judgment in AI-driven decisions. (Gerke et al., 2020). Although data is essential for effective machine learning, the critical issue is whether each patient must consent for their health information to be included in the data collection. Before permitting AI to use stored data from medical records to create algorithms, providers should have satisfactory answers to the following questions: Who owns an individual’s health-care records? With whom will health information be shared? Is the patient’s consent necessary to share their data? According to the Health Insurance Portability and Accountability Act (HIPAA), the patient owns their health-care records and must give consent for them to be shared.
Effective use of AI must also acknowledge the potential for bias. AI bias occurs because humans select the data used to develop the AI algorithms and are responsible for the decision-making process through which the algorithms are applied. AI systems are trained with data that reflect bias and often are not representative of diverse populations. Biased data leads to biases in the patterns identified and the recommendations provided. Addressing bias in AI-powered telemedicine requires a multidimensional approach. Diverse teams, accurate data, and extensive testing are needed to ensure accurate AI algorithms are developed without bias.
The role of human judgment in AI-driven decisions is crucial and multifaceted. While artificial intelligence systems are capable of data processing, pattern recognition, and decision-making, they lack the capacity to demonstrate the understanding, empathy, and wisdom that humans possess. Human validation is necessary to interpret and determine the accuracy of AI recommendations. Human judgment is also necessary to adapt AI-driven decisions to specific situations and consider factors that AI cannot capture. AI-powered glucose monitoring systems, for instance, may provide insights for diabetes management; however, endocrinologists must use their clinical judgment to interpret these trends, consider lifestyle factors, and make recommendations for insulin adjustments or other interventions. AI algorithms may also analyze data to predict patient deterioration; however, nurses and providers must draw on their judgment, interpret these predictions, assess the broader clinical picture, and make decisions regarding treatment adjustments or interventions. Ultimately, humans are responsible for the provisions of health care and will be held liable for actions and decisions taken, regardless of whether they are based on AI recommendations.
Data Security and Privacy
Data security protects personal information from unauthorized access. By adequately securing data, providers ensure it is accurate, reliable, and available to authorized users when they need it. While the delivery of all health care requires participants to follow HIPAA laws, telemedicine adds a layer of complexity to data security and privacy. Because cybercriminal attacks are a major concern when sensitive personal health information is shared, telemedicine requires a secure platform that meets HIPAA compliance (DHHS, n.d.). Additional technological factors that impact data security include the potential hacking of virtual visits and the use of cellular data or public Wi-Fi that is not secure (Houser et al., 2023).
Due to the data security risks involved, federal regulations are in place to guide organizations in implementing strategies to keep patient data secure. Strong network security features, controlled access rights, and encryption are strategies used to deliver HIPAA-compliant telemedicine. Other strategies include using secured websites that feature the “lock” icon in the address bar, requiring passwords for virtual visits, keeping antivirus software up-to-date, and avoiding public Wi-Fi and shared devices. Nurses must be knowledgeable of the data security policies established by their health-care agency and implement measures to ensure compliance with these policies.
Privacy is a human right; therefore, all individuals have the right to keep their personal information private. Data privacy involves properly handling, processing, storing, and using personal information. Furthermore, additional environmental factors outside the provider’s control may affect a virtual care session. For example, the lack of privacy—whether real or perceived—may decrease the likelihood that patients will share sensitive health information with the provider. It may also expose details of the patient’s living conditions. Though unauthorized exposure violates a patient’s privacy, it is often beneficial for the provider to gain a better understanding of the environmental factors affecting the patient’s health. With the patient’s consent, the provider may conduct a home safety assessment.
To safeguard patient privacy during telemedicine visits, patients should be educated to seek out a private setting, wear headphones, and be mindful of their surroundings before initiating the virtual visit. Privacy standards should be incorporated into the agency’s policies, procedures, and workflows. Staff and providers should receive patient privacy training that is directed toward the specific use of telemedicine.
AI, Technology, and Nursing Education
AI and related technological advancements have drastically changed how education is delivered. In particular, they have played instrumental roles in the use of simulations utilizing augmented and virtual reality. Using AI algorithms, education can provide personalized training experiences that are customized to the learner’s needs. AI also allows educators to collect and analyze data to identify areas of opportunity within the curriculum, such as an increased focus on remote learning.
Simulation
Simulation plays a crucial role in nursing education because it helps nurses to practice skills in safe, controlled replications of clinical scenarios. AI has enhanced the capabilities of simulation, including the ability to present a variety of patient profiles that allow the learner to practice providing comprehensive care to a more diverse population (Figure 37.5). For example, it allows the inclusion of psychosocial dynamics, introducing patient variability that better prepares learners for real-life situations and clinical encounters. Additionally, the automation of scenarios enables them to progress independently, relieving instructors of system management responsibilities. This autonomy allows instructors to focus their attention on observing and assessing students’ interactions during the simulation.
Augmented Reality/Virtual Reality
The technology of augmented reality (AR) superimposes a computer-generated environment onto the real world to create an interactive experience for the user. In contrast, virtual reality (VR) integrates hardware (a headset) and software (the VR platform) to create an immersive, simulated environment; typically, the user is represented by an interactive avatar, a digital representation of an individual created within a virtual environment. AI algorithms play a pivotal role in enabling avatars to respond and clinical variations to unfold as virtual scenarios progress. These algorithms also facilitate voice recognition within the virtual environment, allowing avatars to recognize user commands and respond appropriately. AI also allows three-dimensional (3D) scenes to be created by a single photo, provides motion tracking data, and collects, stores, and analyzes user-specific data as individuals navigate the scenario.
Benefits of incorporating AI into AR and VR include an improved user interaction and user experience, as well as the possibility of augmenting human intelligence and reducing educational costs. AI algorithms in AR/VR systems can analyze individual learning patterns and preferences. By tailoring content and experiences to the specific needs of each learner, personalized learning enhances comprehension and knowledge retention, optimizing the educational process. If a learner demonstrates mastery in a particular area, the system can advance to more challenging material, promoting efficient learning. AI-driven assessments in AR/VR environments provide immediate and detailed feedback to learners, allow individuals to identify and rectify mistakes promptly, and enable remote learning opportunities to make education more accessible. Students can engage in immersive learning experiences without the need for extensive physical infrastructure, lowering expenses related to building and maintaining educational facilities.
The Nurse’s Role
Technology has instrumentally changed health care and the way in which care is provided. Nurses are responsible for learning, integrating, and supporting the evolution of technology within health care. This responsibility brings both benefits and challenges.
Emerging technologies have the potential to make the nurse’s workload more manageable. Electronic health records and digital records improve accessibility, accuracy, and clarity of documentation. Technology may also reduce the nurse’s risk of error and liability by automating tasks with precision and speed. The integration of additional technology leads to improved communication capabilities, facilitating real-time interactions that have the potential to enhance care coordination and minimize delays in providing health-care services. As technologies improve patient care and allow it to be provided in rural and remote areas, the health of the patient may improve, thereby reducing the number of patient visits and overall workload of the nurse.
As new and innovative technologies emerge, nurses must engage in continuous learning to stay updated on the latest techniques for providing care. Each new technology requires training, the establishment of new workflows, and patient education. The constant state of change can be overwhelming and take a toll on nurses, possibly leading to resistance toward adopting new technologies and eventually to burnout. While the role of the nurse may shift with the advancement of technology, the nurse will continue to be essential to the processes of coordinating patient care, developing trusting relationships with patients, and adapting to new technologies that allow us to provide the best care for our patients. The nurse’s role will retain its essential qualities of wisdom, clinical judgment, and compassion—qualities that cannot be replaced by technology.