Can artificial intelligence help fulfill our ethical obligation to long-term care residents? – Marketplace


Charles E. Binkley, M.D., FACS

Nursing homes and long-term care (LTC) facilities throughout the country have reported significant clusters of SARS-CoV-2 infection, often with high associated mortality among the residents infected.  The recent COVID-19 outbreak has raised questions about the need for improved infectious disease prevention measures, earlier infection detection and coordinated management of infectious diseases in nursing homes and LTC facilities.

As a result of the pandemic, it is likely that LTC facilities will come under greater scrutiny by federal and state agencies, as well as families and prospective residents. Novel solutions to address the problem of infectious outbreaks in LTC facilities are ethically necessary not just for the well being of residents, but also to restore public trust and satisfy the high likelihood of increased oversight. Artificial intelligence (AI) offers one of the best solutions to reduce the threat that infectious diseases pose to LTC facilities and their residents.

AI has numerous applications in public health and medicine including earlier disease detection, more precise diagnosis, and personalized treatments. The AI system algorithms adapt as new information is received, essentially “learning” through a combination of inputs and outputs. AI is currently being used by hospitals for earlier and more precise identification of COVID-19 patients. 

In order to understand how AI can be effective against infectious diseases in nursing homes, one must look at the factors that make nursing home residents particularly vulnerable. These can be divided into resident factors, employee factors, and operational factors. LTC facility residents are often older, have more chronic medical problems, and live in close proximity to each other. These factors make residents more vulnerable to infections and the severity of the infection greater. LTC facility staff can introduce infectious agents to residents from the community as well as within the facility, from an infected to a noninfected resident. As is the case with COVID-19, transmission can occur from an infected resident before the resident shows symptoms. Finally, delays in identifying, isolating and medically managing potentially infectious residents can lead to the spread of infection, even before the resident is showing signs and symptoms. Besides staff, visitors such as family members, volunteers and clergy can unwittingly introduce infections from the community into the nursing home.

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So,
how can AI address these issues?

  1. Screening of visitors and staff for infection: AI can assess potential visitors and staff for risk of infection. This process would be completely automated, and AI algorithms would decide whether the person’s risk of infection was prohibitive. As noted previously, some infections can be contagious before the individual harboring the infection shows symptoms. Using a combination of screening questions, biometrics and vital signs, AI systems are able to predict infections 48 hours before symptoms appear.
  2. Early detection of infection in residents: A key factor in any infection prevention and control process is the early identification and isolation, or cohorting, of infectious individuals. As noted previously, AI has the potential to predict infections well before symptoms manifest themselves.  Applying this to a LTC facility population could remarkably reduce the transmission risk of both community- and facility-acquired infections. AI could be particularly valuable for residents who may not be able to recognize early signs of infection because of cognitive impairment. 
  3. Telemedicine to allow remote assessments and standardized management: Symptomatic residents often have to be transported to an emergency room for evaluation. Telemedicine allows a clinician to make an assessment and potentially initiate treatment without having the resident transported outside the facility. AI could also provide an algorithm, tailored specifically to nursing home residents, which would assist clinicians in accurate and early diagnosis, testing and treatment. 
  4. Assurance of compliance with hand hygiene and PPE: One of the most common means through which infections are spread in healthcare settings is by staff from an infected to a noninfected person. The most basic way of preventing this is hand hygiene (washing or sanitizing gel) between all resident contacts. Despite the simplicity of this intervention, it is one of the most ignored opportunities to improve healthcare quality and patient safety. Another common means of staff mediated transmission of infections is failure to properly utilize personal protective equipment between resident encounters, especially when going from an infected resident to a noninfected resident. AI offers systems to foster compliance with both hand hygiene and PPE.
  5. Companionship: LTC facility residents who are isolated and unable to have visitors are at high risk for depression, anxiety, delirium and other mental health issues. AI systems that offer companionship have the potential to provide for residents who are isolated and unable to have contact with their families and friends.
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While no system will completely eliminate the risk of infection among at risk LTC facility residents, partnering with advanced technology such as AI has the best chance of helping facilities fulfill their ethical duty to protect this vulnerable population and also restore public trust and respond to increased oversight. Relying solely on human factors to prevent, detect and manage infections in LTC facilities has failed.  Let us take the hard lessons of this pandemic to heart, leverage technology, and assure the best possible infection prevention and quality in our LTC facilities.

Charles E. Binkley, M.D., FACS, is a surgeon, healthcare quality consultant, bioethicist, and principal and founder of ProNobis Health.



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