Intelligent automation* (IA) is more than a way to revolutionize business and save money—I believe it also has the potential to save lives by the millions and increase healthy life expectancy. Intelligent automation can be applied to medical diagnosis and research to prevent unnecessary deaths. In addition, it provides more equitable access to healthcare worldwide.
*If you’re new to intelligent automation, I recommend you start with my previous UiPath article What You Need to Know About the Age of Intelligent Automation.
Preventing deaths through diagnosis and research
More than 70% of deaths worldwide are caused by chronic non-communicable diseases such as cardiovascular disease, cancer, diabetes, and respiratory illnesses.
An important characteristic of these diseases is that recovery rates are higher the earlier the disease is detected. Leveraging machine learning (ML), IA can save lives by analyzing scans and other medical data (such as blood pressure) to produce quick and reliable diagnoses.
Not surprisingly, ML can process lung or breast scans in minutes or seconds, where a human would take hours. But what’s more remarkable is that it has advantages over doctors when it comes to identifying cancer.
Another common factor among these diseases is the potential to find cures through research. Not only does ML help innovation in medical research (e.g., by simulating the combination of molecules), but it also plays a vital role by automating the documentation and checking of clinical trials, freeing up human researchers for higher-level cognitive tasks, and making the research process quicker and more efficient.
Preventing deaths caused by medical errors
Medical errors are a sad and often overlooked element of modern healthcare. In the United States (U.S.), medical errors cause over 250,000 deaths per year, which is higher than any other single factor except heart disease and cancer.
In 2006, Emily Jerry, a two-year-old recovering from cancer, tragically died after a pharmacy technician gave her 20 times the recommended concentration of intravenous saline solution. Emily’s father wrote, “Medical-care workers are dedicated, caring people, but they are human. And human beings make mistakes.”
IA, in conjunction with human professionals, can double-check prescriptions and identify discrepancies from doctors’ instructions or medical best practices. Automation is never tired nor distracted, so it is not vulnerable to lapses in concentration, which happen to everyone but can have disastrous consequences in healthcare.
IA can also monitor patients’ health in real time. Software robots can alert a nurse or doctor about an emergency based on a patient’s blood pressure, heart rate, or other vital signs. It can even detect patterns that predict heart attacks, strokes, or sepsis in advance, saving lives and freeing up doctors’ and nurses’ time from data collection.
Reducing deaths from preventable causes in developing countries
The global disparity in wealth and resources means that many people in the developing world die of diseases that would be easily preventable in wealthier countries. This is largely due to inadequate access to healthcare. According to the World Health Organization (WHO), there is a global shortage of 4.3 million healthcare professionals.
IA technology can bring healthcare to anyone with access to a smartphone—which is an increasing proportion of people (even in regions that lack other infrastructure and technology). Applications can link patients with doctors remotely, while diagnostic tools can partially take the place of the doctor by diagnosing skin conditions, burns, and chronic wounds based on a digital photo.
Reducing deaths from traffic accidents
Road incidents can cause permanent disabilities or fatalities. Human error is a factor in most road accidents, and there is potential for self-driving cars or IA-assisted driving technology to save lives by reducing or eliminating this factor. Research from the United States (U.S.) Department of Transport estimates 94% of traffic accidents are caused by human error.
Even before fully autonomous self-driving cars become the norm, IA can assist human drivers and help them to drive more safely. Cars can already be augmented with kits that allow them to monitor the driver using an internal camera, detecting when they become drowsy and alerting the driver. Automatic sensors can also be used to augment the human driver’s vision, warning them of unexpected obstacles. Cruise control and assisted parking are common examples of IA technology working together with human drivers to help them drive more safely.
Conclusion
Health organizations that want to start embracing the benefits of IA should start with the most common use cases in their industry:
New patient onboarding and appointment scheduling with the support of automated workflows and cognitive agents
Patient health monitoring, leveraging cameras and sensors in hospital rooms
Medical diagnosis and drug discovery supported by ML
Staffing level prediction and real-time adjustment processes
Automation of invoicing and claims management
Patient experience improvement through real time and 24/7 communication
If you start with these smaller, everyday processes and then build forward from there, you will be able to embrace IA in ways that make your routines and processes easier from the beginning.
Dive deeper: Watch the “AI in Healthcare” session, now available on demand.
Overall, based on my research and expertise, I believe IA technologies could reduce early deaths by 10–30%. Back in 2017, a 20% reduction in the 56 million total annual deaths worldwide would have meant saving 14 million lives every year—the equivalent of the populations of Switzerland and Singapore.
I recently joined Ian Barkin and UiPath to discuss how automation can be used for larger societal impacts. If you missed the first episode of the Automation for Good webinar series, you can catch up with the on-demand recording.
The content of this article is inspired by the Amazon Bestseller book Intelligent Automation.
