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Senior living and the use of artificial intelligence for infection prevention and control

By Rhonda DeMeno | August 30, 2023

AI algorithms and their applications will require further study to evaluate the impact on resident care and organizational efficiencies.

Senior living communities are still in the process of recovering from COVID-19, one of several global pandemics since the 1918 Spanish flu pandemic. Based on the rapid spread of COVID-19, a study from the world economic forum estimates that the probability of novel disease outbreaks will likely triple in the next few decades.

While COVID-19 exposed many vulnerabilities for senior living, it also provided an opportunity for operators to reset infection control priorities and adopt practices to create a more robust approach to infection control and mitigation plans. As the senior living industry moves forward from the pandemic, now is the perfect time to review pandemic preparedness plans’ readiness for future pandemics or infectious disease outbreak crises.

In the future, we are going to see more complex epidemics. COVID-19 is a symptom of the drivers we will live with throughout the 21st century. Sir Jeremy Farrar, Director Wellcome Trust.

In the future, we are going to see more complex epidemics. COVID-19 is a symptom of the drivers we will live with throughout the 21st century.”

Sir Jeremy Farrar | Director Wellcome Trust

Because senior living communities are susceptible to infectious outbreaks, they must continue with adherence to the basic principles of infection control. Many of the traditional IPC precautions used during the COVID-19 outbreak, such as masking, social distancing, manual surveillance, symptom monitoring, testing and using PPE, were effective for stopping the virus from spreading. However, in retrospect, traditional surveillance required much time, staff and medical supplies and was often exhausted and not easily monitored. In looking to the future, improved pandemic preparedness will be critical in navigating pandemic threats. Technology and artificial intelligence applications may become integral to a community’s infection prevention and control program (IPC).

Since the pandemic, there has been a heightened awareness of innovation and technologies emerging in healthcare. There are AI applications to assist communities in their overall infection prevention and control plans.

How technology and AI can assist in infection prevention

COVID-19 transformed healthcare delivery in many ways. Sensor-based technologies have provided opportunities for resident virtual assessments and changed caregivers’ approach to deliver and monitor resident care. Mobile health technologies and other sensor-based technologies, when placed in the community and used in combination with staff, have added an extra layer of monitoring for residents in their assisted living or memory care environments.

The advantages of AI for infection prevention and control can be noted in healthcare-associated infection (HAI) surveillance programs. AI can identify infections early and design customized antimicrobial stewardship strategies for residents. AI has the potential to detect transmission events during outbreaks or predict high-risk patients, enabling the development of tailored IPC interventions.

AI provides a broad array of benefits, including predictive analytics, contact tracing, resource allocation, and education and training platforms. AI enhances diagnostics with objective pattern recognition, standardizing diagnosis of infections, and AI facilitates the sharing of information to gain IPC expertise.

AI data mining of laboratory results can be used to predict outbreaks and/or infection events. Next-generation sequencing (NSG) effectively identifies pathogens and identifies antimicrobial resistance (AMR). AI was also used in the development of the COVID-19 vaccine employing data management to address boosters and COVID-19 variants.

AI offers the opportunity to conduct complex analysis and analysis of diverse HAI across a senior living community. Such analyses could aid in predicting residents most at risk of HAI or AMR events and facilitate the timely detection of outbreaks. AI is also used in staff training for hand washing effectiveness and aiding in reporting transmission during outbreaks.

AI risk and challenges

AI tools show promise for improving senior health care by predicting health trajectories, recommending treatments and automating administrative tasks. The rapid evolution of AI presents unlimited opportunities. However, operators must be mindful of challenges and risks associated with the use of AI, such as:

  • Data access. Developers experience difficulties obtaining the high-quality data needed to create effective AI tools.
  • Bias. Limitations and bias in data used to develop AI tools can reduce their safety and effectiveness for different groups of patients, leading to treatment disparities.
  • Scaling and integration. AI tools can be challenging to scale up and integrate into new settings because of differences among communities and resident populations.
  • Socioeconomic inequality. Algorithms may create an opportunity for abuses, such as sparking concerns for job loss because of automation.
  • Limited human integration. AI cannot replace the benefits of human companionship and emotional connection.
  • Lack of transparency. AI tools sometimes lack transparency.
  • Privacy. As more AI systems are developed, large quantities of data will be in the hands of more people and organizations, adding to privacy risks and concerns. Privacy may not be assured for virtual care or AI, and personal health information may be at risk of breach.
  • Uncertainty over liability. The multiplicity of parties involved in developing, deploying and using AI tools is one of several factors that have rendered liability associated with the use of AI tools uncertain.
  • Training. AI works by learning from the data it is fed. The data the systems receive must be accurate. It is important to remember who is inputting the data. Are cultural biases being passed on to the system? If the system is designed poorly, it can misdiagnose.
  • Regulatory and legal challenges. AI is subject to regulatory and legal considerations; compliance with privacy regulations is complex.
  • Data issues and cyber breaches. Data collection and ethics must go hand in hand. Protecting residents from any data leaks is also integral to the safe use of AI in medicine. There should always be full disclosure to residents. They need to be made aware that their information is being used to feed an AI algorithm.
  • History and volume of data. AI requires massive data sets in order to “learn,” thus needing volumes of resident health information for training and validation

Artificial intelligence and risk mitigation

When contracting with an AI provider, senior living operators should consider risk mitigation strategies as follows:  

  • Create policies and procedures for AI-based applications, devices and wearables.
  • Use a multidisciplinary team (including the resident and/or staff member) to review any new products, services or devices being brought into the organization before use.
  • Define clear expectations, goals and objectives with the AI provider.
  • To ensure safety, test the effectiveness of the processes that are using AI through the use of Failure Mode and Effects Analysis.
  • Training checklists should be developed for the care team who will be using the AI applications.
  • Educate the care team on escalation strategies should there be a question regarding the device integrity or when injuries occur.
  • Loop in the organization’s insurance carriers and brokers to review any insurance implications that may arise.
  • Track and trend all device incidents. Ensure that the care team knows the process for reporting such incidents.
  • Build into organizational device management policies the requirements for reporting to the Food & Drug Administration any issues that could have or did result in harm.
  • Privacy laws may not have caught up with the use of AI. Be cautious with AI vendor contracting and insert federal privacy requirements into the agreement.
  • Review AI providers’ security and privacy protocols to ensure adequate safeguards are in place to protect data and comply with privacy laws.
  • Have legal counsel review all AI agreements prior to engagement. Legal should review data governance and access to determine how data is collected, stored and shared.
  • The AI system must be consistently monitored with checks and balances in place to ensure safety.
  • Meet regularly with staff and residents to address application concerns.

Insurance implications

AI regulations are not in place today in the United States, but changes will likely be on the horizon. With those ever-evolving changes, senior living leaders will need to remain vigilant in monitoring AI programs for new regulatory requirements for the industry.

The efficiencies created when using AI may only partially reduce risk a errors resulting in injury may still occur. However, liability will remain with the provider along with new stakeholders, (e.g., software developers), which may now bring forth product liability concerns. Physicians, health systems, senior living organizations and algorithm designers are subject to different, overlapping theories of liability for AI and machine learning (ML) systems.

A senior living organization may face legal actions if errors occurred using the AI technology. If the AI causes harm or violates resident rights, the affected party may choose to file a lawsuit. AI applications, when using algorithms, become part of the diagnostic care team, but an algorithm may lack the decision-making skills to differentiate the underlying reasons for those decisions. Therein lies additional risks. AI can also affect a company’s business income valuation and the coverage limit chosen.

As AI technologies continue to evolve and their use in senior living expands, insurance providers will continue to adapt their coverage. Senior living providers should review their policies to ensure that AI-related risks are adequately covered, and they should consider working with their insurance broker and legal counsel familiar with AI technologies to navigate the potential legal risk and the development of risk mitigation strategies.


Future of AI in senior living

AI applications for senior care services continue to evolve. Understanding the use and applications will require time and research. AI applications can bring significant quality-of-life improvements for seniors and improve community IPC programs.

Advantages for IPC include speed, consistency and the capability of handling infinitely large datasets. However, many challenges and risks remain. In many instances, AI alone will not improve IPC. Often IPC requires cultural and behavioral change.

Senior living may be revolutionizing and paving the way for AI technology and healthcare delivery. AI algorithms and their applications will require further study to evaluate the impact on resident care and organizational efficiencies. While AI may be an evolving solution for fighting pandemics, it will require collaboration with senior living operators and healthcare professionals to validate effective and responsible use of AI applications.


Willis Towers Watson hopes you found the general information provided in this publication informative and helpful. The information contained herein is not intended to constitute legal or other professional advice and should not be relied upon in lieu of consultation with your own legal advisors. In the event you would like more information regarding your insurance coverage, please do not hesitate to reach out to us. In North America, Willis Towers Watson offers insurance products through licensed entities, including Willis Towers Watson Northeast, Inc. (in the United States) and Willis Canada Inc. (in Canada).


Director Clinical Risk Services -Senior Living Center of Excellence

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