AI and Electronic Health Records in Modern Healthcare

Introduction to Artificial Intelligence in Healthcare

Artificial intelligence (AI) is the science and art of developing machines that simulate human intelligence. AI is frequently used for routine tasks that would normally involve human skills, such as visual perception, speech recognition, and decision-making. Apple's Siri application is a widely recognized example of commonly used AI technology. AI is particularly useful in the medical field, as it has allowed for better patient monitoring combined with more efficient utilization of resources. One way it has accomplished this is by replacing human beings in certain applications. For example, a technical application of AI is in radiology and imaging, where computers can be used to read imaging reports, eliminating the risk of human error and allowing diagnosis before a human doctor could detect abnormalities (AAAI, 2013).

However, applications like that one could be accomplished through traditional programming that may or may not fall under the rubric of AI. For most people, the concept of AI incorporates more than mirroring human intellect; it also seeks to replicate some of the emotional processes involved in human thought. It is in this replication of emotion that AI may offer its most promising medical advances.

AI Applications in Skilled Nursing and Assisted Living

One of the clinical settings where AI may be most useful is the nursing home or assisted living environment (AAAI, 2013). AI can be used to monitor people, especially those with cognitive impairment, to provide them with as much independence as possible. Simple applications include tools that automatically cut off kitchen appliances, irons, and other potentially dangerous features, thereby helping to facilitate independence — which is critical even for people living in assisted living or skilled nursing environments. More sophisticated tools using AI monitor the health condition of seniors, alerting healthcare providers when vital signs indicate a need for intervention. These are well-established uses of AI in the skilled nursing and assisted living environment.

One of the most critical components of care for the aging population is the maintenance of mental health. Loneliness is a significant challenge for those who have moved away from their traditional homes and into skilled nursing or assisted living facilities. These moves often occur after the death of a spouse and involve leaving behind friends, family, and routine activities. Depending on the availability of skilled care in certain communities, relocation may also require people to become displaced from their home communities. Families may face difficult decisions about appropriate placement, sometimes choosing facilities that are farther away in order to achieve a higher standard of patient care. All of these factors can contribute to feelings of isolation and depression, and AI can be used to help alleviate some of those negative effects.

Robotic Companionship and Mental Health Benefits

The use of AI toys to alleviate loneliness in nursing homes and skilled living facilities has already seen some success. For some time, the use of therapy dogs to elevate patient mood has been an accepted course of treatment for many elderly patients. However, challenges such as allergies and hygiene concerns can prohibit the use of therapy dogs for some individuals. The use of electronic robotic pets has been shown to offer many of the same benefits as live therapy animals for these patients. According to one professor of geriatric medicine, "The most surprising thing is they work almost equally well in terms of alleviating loneliness and causing residents to form attachments" (as cited in Science Daily, 2008). In other words, electronic dogs can serve as a genuine substitute for live canine companionship.

Moreover, the benefit of electronic pets extends beyond mere companionship. For example, the use of an AI robotic seal named Paro with nursing home patients suffering from dementia showed not only an alleviation of loneliness but also a general calming effect. Some patients developed strong relationships with the pet, acting almost like surrogate parents or grandparents in their treatment of it. Most notably, the affection was not dependent on the toy's interaction with the patient, but lingered even after the toy powered off (Harmon, 2010). Furthermore, while critics suggest that robots would be limiting in such an environment, anecdotal evidence indicates that they actually stimulate human interaction (Harmon, 2010). The patients also benefited from the companionship despite knowing the animal was not actually alive.

Electronic Health Records and Ethical Considerations

In addition, Furbys are relatively inexpensive, making them accessible to residents across all income levels. This is in sharp contrast to Paro, which carries a price tag of approximately $6,000. The lower cost of the Furby could make wide adoption in skilled nursing facilities far more practical, allowing more residents to benefit from AI-assisted companionship without significant financial burden.

Electronic medical records are currently widely used by medical professionals and insurers to share medical information. As healthcare providers become increasingly dependent on electronic technology, the need for electronic health records (EHRs) will only grow. From a provider standpoint, electronic records help ensure appropriate care by giving all healthcare providers access to a patient's complete health history. This can alert providers to potential medication interactions, flag pre-existing conditions, and identify other potential healthcare concerns. The innovations introduced by the HITECH Act were expected not only to improve the quality and coordination of healthcare, but also to save $20 billion in health information technology infrastructure and generate additional savings throughout the healthcare sector (Committee on Ways and Means, 2009). The central ethical issue that arises with this increased access to medical information is that data could be used in ways that are prejudicial to the patient, particularly in the identification of pre-existing medical conditions.

The scenario discussed here relates to electronic medical records, pre-existing conditions, and health insurance eligibility. The Affordable Care Act (ACA) prohibits health insurance plans from refusing to cover people or charging more because of pre-existing health conditions (U.S. Centers for Medicare & Medicaid Services, 2013). Ostensibly, this would reduce concerns about maintaining a consolidated repository of patient information. However, the scenario remains relevant given ongoing political support for repealing the ACA, in whole or in part.