Interviews & Features

For more than 4,000 years, humans have been keeping medical records. Everything from examinations, treatment plans, outcomes, and follow-ups have been charted on papyrus, tablets, and ancient books. In more modern times, paper charts have been the gold standard till they were replaced with electronic health records (EHRs) in 2011. These records have served individually to care for individual patients and aggregately to inform decisions system wide.

As artificial intelligence (AI) has become more advanced in recent years, technologists and healthcare professionals have noticed many opportunities for AI-based tools to improve the healthcare industry.

Not all medical devices talk to each other or to a particular EHR system, making it difficult for healthcare providers to access and analyze patient data leading to gaps in patient care and missed opportunities to improve outcomes. The lack of interoperability is a major challenge in integrating medical devices with electronic health records, and any potential solutions must address IT and OT security issues to ensure patient health records are secure, not only for privacy reasons but also HIPAA requires it.

Bias in medicine is pervasive and results in systematic errors or prejudices that can influence medical decisions, research outcomes, and patient care. These biases, conscious or unconscious, can be towards race, gender, socioeconomic status, or personal beliefs of healthcare providers. While healthcare providers can be made aware of their bias and develop techniques to combat it, bias in medical technology can only be addressed by changing the hardware or software.

Modern healthcare runs on data. In 2018, the healthcare industry generated approximately 30 percent of the world’s data volume. That share has likely only increased in recent years, with the growing adoption of wearable tech, remote patient monitoring, and electronic health records. But raw data is only as valuable as the insights one can derive from it.

Health data is at the core of modern healthcare, from in-person visits to cutting-edge virtual care. It is collected, stored, and shared in ever greater quantities. But that data is only as powerful as its ability to be matched to the right patient. An incomplete or inaccurate record can be more dangerous than no record at all.

Video game enthusiasts have long enjoyed escaping reality to roam simulated worlds and alternate universes, from prehistoric jungles to sci-fi fantasy lands. However, the two-dimensional nature of video games has always been a glass ceiling, blocking the complete suspension of disbelief that gamers seek.

Healthcare cybersecurity is multifaceted, encompassing numerous physical and digital systems and key employee roles. From a physical standpoint, healthcare cybersecurity systems can include security cameras, computer hardware, access control systems, and biometric authentication devices.

AI-powered tech could make healthcare more affordable, equitable, effective, and accessible. This isn’t just hype: preliminary research suggests wider AI adoption could lead to a 5 to 10 percent savings on US healthcare spending annually, translating to roughly $200 million to $360 billion per year (NBER 2023). The potential is massive.

Administrative costs account for up to a quarter of all US health expenditures, with billing coding costs being one of the top drivers (JAMA 2021). Staffing shortages and coding complexity have worsened matters. But major breakthroughs in automating aspects of the medical coding process may point toward a long-term solution. Already, some provider organizations have implemented autonomous coding in high-volume outpatient specialties such as radiology, pathology, emergency medicine, urgent care, and primary care.