according to federal funds, deep racial and ethnic disparities in health and well-being are still the norm in the U.S. today — its research found that blacks and American Indians/Alaska Natives lived on average shorter than whites and were more likely to die from, for example, treatable disease and many chronic health diseases are at higher risk. On another front, American Addiction Center said blue-collar workers had high rates of alcohol and drug abuse. Unfortunately, the Covid-19 pandemic has widened this gap. The past two years have exacerbated already serious health care access and equity issues.
While many healthcare companies are already using AI for functions such as machine learning explainability that the healthcare industry needs for compliance purposes, AI-based healthcare solutions also have the potential to make healthcare more affordable and accessible , thereby helping to improve equity in healthcare. With new machine learning and artificial intelligence technologies, patient data and medical records can be used in unique ways to continuously improve patient outcomes and increase access for all. Here are four examples:
Eliminate bias in diagnosis and treatment
In recent years, healthcare providers have turned their attention to the social determinants of health and their impact on health outcomes. This development has drawn attention to racial and socioeconomic factors that play a role in how people receive health care. The truth is that there is bias – even if it’s implicit. Augmenting existing human-based practices with AI allows healthcare providers to not only improve operations but also eliminate bias. For example, AI-assisted decision support systems can be used for unbiased second opinions to review any important missing data points in a diagnosis or treatment plan.
Increase vaccine equity
A key application of AI in healthcare today is natural language processing (NLP) for vaccines. By pulling information from social media, aggregating it into user-defined groups, and presenting key insights about population sentiment in dashboards, organizations can improve their understanding of the public’s perception of infections and vaccines. They can then use this understanding to develop tailored educational efforts and increase vaccination rates.
Involve patients of diverse backgrounds in their healthcare plans
One of the longstanding racial disparities in health care is that minorities return less frequently for follow-up appointments. AI and remote patient monitoring can be powerful tools that give providers insight into the day-to-day factors that affect patient health. Advanced algorithms can process large datasets, including clinical and socioeconomic information, to provide a holistic view of an individual, and AI can suggest which approaches work best, not only to activate patients, but to keep them engaged. With the ability to collect data from patient devices and more, AI and patient monitoring provide additional data sources to improve the patient experience, including prime-time engagements—such as attending key follow-up appointments.
Avoid Opioid Abuse
Many blue-collar jobs are physically demanding and involve a lot of physical labor that can lead to workplace injuries, causing these workers to sometimes resort to drugs and alcohol for stress and pain. As we know from the dire headlines surrounding the opioid crisis, some people can become addicted to painkillers originally prescribed by doctors. But now technology is helping alleviate that problem. AI can help clinicians identify patients with opioid use disorder and high risk of overdose. By using data from patient electronic medical records to predict risk levels, AI can safely and effectively guide clinicians in choosing who to prescribe opioids.
These examples omit the possibilities of artificial intelligence in healthcare. There are more possibilities.
Photo: Undefined Undefined, Getty Images
