It’s no secret that there are a multitude of issues when it comes to ensuring equitable and fair access to quality treatment within the healthcare...
What impact can AI and data analytics have on neonatal services?
Last week, we looked at the many ways in which the power of artificial intelligence and data analytics can be harnessed to combat ageism in healthcare – but what about the other end of the scale? In today’s blog post, we’re exploring how healthcare providers can use this innovative new technology to improve neonatal services, both pre and post-delivery.
One of the key barriers to quality healthcare provision is location, with many studies claiming that those living in economically deprived or rural areas face poorer access to these essential services. Although the vast majority of indications and conditions are affected by this lack of accessible treatment, those requiring neonatal services are one of the most severely impacted groups – something of particular concern when we consider the fact that newborns are a highly vulnerable demographic.
There’s still a long way to go in terms of ensuring total health equity across the board, but we’re currently witnessing number of positive improvements in the neonatal sector. These measures are very much scalable across a variety of indications – meaning that those experiencing other conditions requiring medical attention could benefit from adopting these policies and structures.
For example, telehealth and remote patient monitoring is an obvious step in promoting healthcare equity. Remote consultation is convenient for those living in rural areas or regions with few healthcare providers, or those who experience difficulty finding reliable transport to an appropriate medical center – something of particular importance when it comes to pregnancy. Aside from the practical benefits offered by such telehealth services, there’s a growing body of evidence to suggest that their use helps patients engage more successfully in self-management and care plan adherence, resulting in a reduced cost of care not only for the healthcare providers, but ultimately for the individuals themselves in the long term.
By leveraging these advances in data-driven technology, healthcare providers are taking a proactive approach to the current state of affairs - reducing costs, increasing access to quality treatment, optimizing clinical staff efficiency whilst simultaneously addressing the issue of clinical staff shortages, boosting caregiver connectivity and involvement in care, lowering the number of hospital-related infections and the risk of COVID-19 spread, expanding referral opportunities and improving patient retention - ultimately making the relationship between patients, caregivers and healthcare providers that much better and more effective.
In addition to this, AI and data analytics can be used in a variety of innovative ways post-pregnancy – especially for premature births. It’s no secret that preterm infants are one of the most fragile and vulnerable patient demographics, and are uniquely susceptible for injury or infection immediately after birth, with neonatal sepsis being one of the more serious conditions this group is at higher risk of developing. This is where AI and data analytics step in. Using data derived from vital signs monitoring, analysts might be able to determine whether or not this information suggests that a newborn might at risk of developing certain complications based on signal analysis.
Although it’s still a relatively recent advancement, this technology solution offers a unique opportunity to automate and modernize the diagnosis process, using current and historical data in step with data modeling capabilities and a variety of artificial intelligence techniques. Current research in this area claims to be able to identify preterm infants at risk of sepsis up to several hours before standard protocols for monitoring and testing were able to do so. By predicting whether or not a newborn is heading towards a sepsis diagnosis, data analytics is able to trigger an evaluation protocol indicating a need for immediate medical attention – potentially saving the lives of countless infants across the globe, particularly those in low or middle-income regions where this disease is prevalent.
Existing systems of care recognize that support for this delicate patient population has a variety of unique challenges that don’t necessarily apply to other demographics, with a growing number of neonatal healthcare providers adopting AI and data analytics tools into their care policies. Preterm infants in particular require special attention when it comes to ensuring their vitals fall within narrow ranges of normal and safe values, as the risk of injury or infection is greatly increased when a newborn falls outside of these margins. Fortunately, AI tools and algorithms are helping healthcare providers to monitor their patients continually, minimizing the overall risk of these neonatal problems even having an opportunity to make themselves known.
There’s a world of possibility when it comes to using data analytics and AI to improve the current state of neonatal care, not just for new mothers and newborns themselves, but also for the healthcare sector as a whole. From the intricacies of pregnancy itself to post-birth monitoring, there are myriad ways in which the widespread adoption of these technologies is changing the face of neonatal support.