Over 800 women died from pregnancy-related complications in 2020 in the United States, and well over half of these deaths were preventable. This isn’t news for professionals who work in this space because maternal deaths in the U.S. outnumber those in most industrialized nations in the west. Maternal outcomes for Black women in the US are even worse. Black mothers die from pregnancy-related complications nearly three times more frequently than white and Hispanic women. Despite efforts to prioritize improved maternal mortality, there’s been very little progress. In fact, maternal mortality actually increased over 18% between 2019 and 2020. Much of this increase is a result of the Covid-19 pandemic. For excess deaths that aren’t attributable to complications from Covid-19, technology may hold the solution. Artificial Intelligence may improve maternal health outcomes in the US Many tech companies focused on developing and implementing AI-driven solutions to healthcare problems in the last few years. These recent advancements in AI give patients and their healthcare providers hope amidst worsening maternal health outcomes in the United States. Some of the newest iterations of AI for healthcare identify pregnant women who are at risk for premature birth and other complications. In doing so, it allows healthcare providers and patient care teams to intervene before it’s too late. As a result, their pregnant patients benefit from health education, as well as medical care and access to social services to lower their risk for negative outcomes. There’s even an element of this technology that leverages the social determinants of health (SDOH). If a pregnant woman has a history of preterm birth or preeclampsia, is struggling to find food, or they can’t get to their appointments because of inadequate transportation, AI helps their healthcare provider understand how those influence maternal and infant health outcomes. This way, healthcare providers can address them early, giving pregnant patients their best chance at positive outcomes. Identifying at-risk pregnant women earlier with AI Traditional methods of care limited healthcare providers’ efforts to identify at-risk pregnant women especially in comparison to what we’ve been able to accomplish with AI and other technology in recent years. Before these advances, OB/GYNs and midwives were tasked with using often incomplete data along with persistence and sheer luck. They did their best to call patients with no guarantee that they would reach them. Many OB/GYNs and midwives did their best, but pregnant moms deserve so much more than that—especially as we face climbing maternal mortality around the world. Now, maternal care providers don’t have to spend long hours rounding up patient data and hoping to catch pregnant patients on the phone. AI has the power to provide all of that data, along with a complete analysis that identifies which patients are at the highest risk. The result? Identifying pregnancies sooner and targeted outreach efforts that prioritize high-risk patients. Healthcare providers who use AI in maternal care can identify over 70% of at-risk moms during the first trimester. This incredible benefit allows these parents to get the care they need from the very beginning of their prenatal journey. Earlier access to care allows for better outcomes and interventions for both mothers and their babies. And AI prepares the folks providing care and doing patient outreach ahead of time so they know exactly how to support each and every patient. Insurance plans are also using this AI to significantly reduce preterm birth disparities for pregnant Black women across the nation. There was a 10% reduction in preterm births and low birth weight among babies whose mothers received care and support leveraging AI tools. This helps avoid lifelong consequences for newborns, including breathing, hearing, and vision issues, developmental delays, and other health complications. The benefits of AI don’t end when a pregnant woman gives birth, though. It continues collecting and analyzing patient data into the fourth trimester, when women are still at risk for life-threatening pregnancy-related complications, like preeclampsia and mental health challenges like postpartum depression or psychosis. Lawmakers are taking maternal mortality to task Tech companies and healthcare providers aren’t the only stakeholders trying to improve maternal mortality rates in the US. It’s become a legislative priority for many folks on Capitol Hill, including President Joe Biden and Vice President Kamala Harris. Together with many federal agencies, they released the White House Blueprint for Addressing the Maternal Health Crisis just last year. This historic effort aims to improve maternal health outcomes by providing more economic and social support to women before, during, and after pregnancy while also prioritizing research and data collection among other key agenda items. Recently, the National Governors Association (NGA) Chair New Jersey Governor Phil Murphy and First Lady Tammy Snyder Murphy hosted a roundtable discussion about efforts to improve birth outcomes and reduce overall maternal and infant mortality and morbidity. One area of focus that Mrs. Murphy highlighted included the significant influence “data holds to transform our national maternal health landscape [ … ] with up-to-date information, we can create policies that are informed by reality. We can direct our strategy to target specific goals. And, most importantly, we can measure our performance and make essential revisions, change direction and learn from our experiences.” Additionally, administrations in states such as Texas and Florida are including maternal health goals in their Medicaid managed care contracts. As the government continues working toward better maternal healthcare, AI and other technology will undoubtedly be a key piece of the puzzle to improve health outcomes and reduce health disparities. Photo: FatCamera, Getty Images

Turning the page on 2022 will be a cause for celebration in the healthcare sector. The past year was one of the worst financial years on record for hospitals, according to Kaufman Hall. New data from the healthcare consulting firm and the American Hospital Association indicates that 53% to 68% of the nation's hospitals will end 2022 in the red. At the same time, hospital employment is down approximately 100,000 from pre-pandemic levels. This is all happening amid a backdrop of growing margin pressures and an aging population.

We live in a time when generation-shaping events and emerging technology have converged at a rapid pace – influencing the way our society communicates and interacts with one another. Nowhere is this more evident than with the rise of digital therapeutics in the field of mental health, as new care models and apps are developed for the treatment of physical and behavioral health conditions such as pain, sleep, anxiety and depression. While it is often presumed that the act of bonding is exclusive to human therapeutic relationships, recent studies have shown that digital therapeutic tools are in fact capable of establishing a comparable therapeutic bond with users. But in the same way that relationships must be nurtured between people, so must the connection between virtual mental health services and their users. As society becomes more open to and reliant on these tools, it is the responsibility of technology companies, especially those tasked with assisting people's mental health, to build and maintain artificial intelligence (AI) and machine learning (ML) models that adapt alongside societal needs.

Healthcare leaders don't need reminding that they face serious nurse shortages. It's a challenge they have faced for years – and it's become a critical concern as record numbers leave their practices due to burnout and exhaustion. The November 2021 Hospital IQ Survey found that a full 90% of nurse respondents were considering resigning to seek new careers. Another disturbing result: 71% of nurses with 15 or more years of experience – an invaluable resource to health systems – said they were on the verge of leaving. The stakes to relieve the stress on nurses have never been higher.

Years after the first cases of Covid-19 were reported in the U.S., the healthcare industry continues to feel the impact. Hospitals and health systems have been on the front lines of the pandemic since day one and still struggle with shortages of skilled clinicians, overworked staff and financial losses. A February 2022 report from the American College of Healthcare Executives found that labor shortages ranked first on the list of community hospital CEOs' top concerns, and a 2022 report by patient safety organization ECRI ranked staff shortages first among the top risks to patient safety. For hospitals and health system executives looking to recruit more clinical staff and retain current staff, they need to embrace and implement modernized technology designed to minimize workloads and allow medical professionals to focus on patient care. The healthcare industry has begun to embrace technology to help solve its staffing strain.

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Powered by AI, ElliQ is a voice-operated robotic care companion designed to foster independence and provide support for older adults. About 1 in 4 adults 65 and older are considered to be socially isolated, putting them at increased risk for a wide range of health conditions, from dementia to heart disease and stroke. Many don't have family and friends who live nearby or visit regularly; and the number of professional caregivers is failing to keep up with demand as the U.S. population ages. Responding to the need, the New York State Office for the Aging announced Wednesday that it is partnering with Intuition Robotics to bring an AI robotic care companion into the homes of 800 older adults as part of the state's efforts to battle social isolation and support aging in place. NYSOFA is working with local offices for the aging and other partners to identify older adults who would most benefit from ElliQ by Intuition Robotics, which the Israeli company describes as first-ever proactive and empathetic AI robotic care companion.

Advanced technologies such as artificial intelligence (AI), machine learning (ML), and natural language processing (NLP) have become a cornerstone of successful modern clinical trials, integrated into many of the technologies enabling the transformation of clinical development. The health and life sciences industry's dramatic leap forward into the digital age in recent years has been a game-changer with innovations and scientific breakthroughs that are improving patient outcomes and population health. Consequently, embracing digital transformation is no longer an option but an industry standard. Let's explore what that truly means for clinical development. Over the years, technology has equipped clinical leaders to successfully reduce costs while accelerating stages of research and development.

The pandemic accelerated the advancement of artificial intelligence (AI) in remote patient care. Physicians are increasingly using digital patient monitoring to better track health data, identify abnormalities, and provide patient-specific treatment -- all without the need for in-person interaction. Additionally, emergency departments are employing remote monitoring solutions to allow some patients to leave the hospital sooner. These transformative technologies are leading to better outcomes for patients and reduced healthcare costs. AI use cases continue to grow in healthcare, as constant learning and training of algorithms results in smarter technology as well as improved patient experiences. Most AI applications in healthcare use "augmented intelligence," which curates the algorithms' output to provide clinicians with direction on "where to look" when they get the analysis.

One of the racial disparities long seen in healthcare lies in minority races returning less frequently for follow-up appointments. AI and remote patient monitoring can be powerful tools to give providers insight into the day-to-day factors impacting a patient's health. Advanced algorithms can process large data sets including clinical and socioeconomic information to give a holistic view of the individual, and AI has the ability to suggest what approaches will work most successfully to not only get patients activated, but keep them engaged. With the ability to collect data from patient devices and more, AI and patient monitoring provide additional data sources to refine the patient experience, including prime times for engagement – such as attending critical follow-up appointments.