The COVID-19 pandemic has significantly affected older adults, a group that faced increased risks and challenges. As healthcare systems work through the pandemic’s lasting effects, incorporating artificial intelligence (AI) in geriatric care has become crucial for improving patient outcomes and addressing healthcare needs of this population in the United States.
Older adults, especially those in long-term care facilities, represented a large number of COVID-19-related deaths in the United States. This group is vulnerable due to various factors, including multiple health conditions and age-related immune changes. The rapid virus spread created unprecedented challenges for healthcare systems in offering safe and effective care. This situation led to an urgent need for innovative solutions to assist in diagnosing, monitoring, and treating COVID-19 in older adults.
A scoping review that analyzed AI’s role during the pandemic found that these technologies were mainly used for screening, monitoring, diagnosis, and treatment specific to older populations. However, out of 3,228 articles reviewed, only ten met the eligibility criteria, indicating a gap in comprehensive research on AI applications in geriatric COVID-19 care. Most studies concentrated on high-income countries, highlighting the need to extend research to include diverse demographics representing older adults from various socioeconomic and ethnic backgrounds.
AI technologies have been adopted across different areas of healthcare to support geriatric care, especially due to the COVID-19 pandemic. Some notable applications are:
Even with these advancements, research has shown that many current AI models may not be reliable for geriatric care. While studies have indicated moderate to high accuracy, more validation is necessary with larger, more varied datasets. This lack of representation raises ethical concerns about bias and the suitability of AI applications for older adults, particularly in areas with limited research resources.
One of the main findings from the research on AI in geriatric COVID-19 care is the shortage of comprehensive studies focusing on older adults’ specific needs. The findings showed that while AI has potential in patient outcomes, many studies centered around singular AI models that assessed comorbidities without creating more reliable models for broader populations.
Future research should aim to develop AI frameworks that meet the needs of older adults. This includes gathering data that reflects diverse racial and ethnic groups as well as capturing the unique healthcare experiences of older patients across various socio-economic backgrounds. Such an inclusive approach will improve care quality and ensure interventions are effective for different demographic segments.
Streamlining Administrative Processes
AI technology can automate administrative processes in geriatric care settings. This reduces the workload for medical practice administrators and IT managers. Automating tasks such as appointment scheduling and patient follow-ups allows staff to concentrate on direct patient care.
For example, Simbo AI focuses on front-office phone automation, improving communication between patients and healthcare providers. AI-powered answering services ensure that older patients get prompt responses to their inquiries or appointment requests, enhancing their overall experience. This cooperation between AI and human staff can lead to better patient satisfaction and resource management in geriatric care.
Optimizing Communication Channels
AI can analyze call data to identify peak times for patient inquiries or appointment changes. Recognizing these patterns helps practices allocate staff more effectively, enhancing administrative workflow. IT managers can use this information to predict demand, thus improving call center operations and better meeting patient needs.
Improving Data Management
AI enhances data management by streamlining record-keeping and retrieval processes. Electronic health records (EHRs) can be improved with AI algorithms that sort and analyze patient data, ensuring crucial information is readily available for healthcare professionals. This advancement helps coordinate care, especially for geriatric patients with complex medical histories who often interact with multiple specialists.
As AI becomes more integrated into geriatric care, ethical considerations are important. AI systems may perpetuate biases if trained on non-representative datasets. When older adults are underrepresented, AI’s decision-making could negatively affect the quality of their care.
Healthcare organizations should emphasize transparency in AI applications to ensure ethical design and implementation. Training and evaluation processes must include diverse demographic data while addressing potential biases in AI models. By taking a comprehensive approach, administrators can help guarantee that AI solutions truly enhance geriatric care outcomes without increasing disparities.
The movement toward a more integrated AI ecosystem in geriatric care is progressing, indicating potential future growth. As the United States aims for more efficient healthcare delivery models, AI technology is anticipated to play a significant role in addressing the challenges of older adult care.
AI applications can enhance individual health outcomes and improve efficiency for healthcare providers. Automated processes can benefit the healthcare workforce, leading to better resource management and a greater focus on patient care.
As the demand for effective geriatric care grows, practice administrators, owners, and IT managers must stay flexible and informed about AI technology developments. Ongoing education regarding AI advancements, ethical considerations, and research will help healthcare organizations utilize AI responsibly and effectively.
By incorporating AI-driven solutions, organizations such as Simbo AI show the potential benefits of meeting older adults’ healthcare needs. With careful development and a focus on inclusivity, AI’s future in geriatric care could transform service delivery and improve the aging experience in a healthcare system designed for a diverse population.
AI has been implemented in screening, monitoring, diagnosis, and treatment of COVID-19 among older adults, aiming to mitigate the pandemic’s disproportionate impact on this demographic.
The review highlighted research gaps, particularly in dataset representation and the need for more reliable AI models tailored for older adults.
AI models demonstrated moderate to high accuracy, but further validation on larger, more diverse datasets is needed to enhance reliability.
AI applications have promising implications for patient outcomes, healthcare provider efficiency, and overall healthcare system effectiveness in managing older populations.
The scoping review followed the Joanna Briggs Institute and Arksey and O’Malley frameworks, analyzing peer-reviewed publications related to AI in geriatric COVID-19 care.
The review included studies that utilized AI for COVID-19 applications, focusing on outcomes related to patients, healthcare providers, and systems.
Most studies were conducted in high-income countries, with limited demographic representation such as race and gender in the study participants.
Future research should aim to develop comprehensive, reliable AI models using diverse datasets to address the unique healthcare needs of older adults.
Technologies such as telemedicine and AI algorithms have been utilized to enhance older adult care during the COVID-19 pandemic.
AI’s application raises ethical considerations regarding bias and representation, emphasizing the need for careful model training and assessment for older populations.
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