Dr. Anita Gupta is a C-Suite Healthcare Executive Leader, Board Member and Physician-PharmD at Johns Hopkins School of Medicine. New data shows that the future of health innovation will need to be equitable. As a physician innovation representative to the AMA Physician Innovation Network, I recently attended the HLTH 2022 meeting. There, I learned that 19% of digital tools are inaccessible by Americans with disabilities. Moreover, health disparities amount to over $90 billion a year in excess of medical costs and 24% of the lowest income bracket in America does not have access to a smart phone.

Remote patient monitoring is now a key application in medical spaces where cameras and AI are revolutionizing the delivery of care. This article will thus discuss how the two technologies work together to make life easier for patients and caregivers. The adoption of artificial intelligence is on the rise across all sectors. Though current AI cannot compete with the cognitive ability of the human brain, it has already started to dominate when it comes to performing mundane as well as intelligent tasks – and the medical field is not an exception to this. It has been captivating to see new and emerging applications and use cases where AI works in harmony with other technologies to enhance human experiences.

Big data in healthcare refers to the massive amount of information created by adopting modern technologies that collect patients' medical records and are used for managing hospital performance. It can be used for a variety of purposes, from curing individual patients to predicting and preventing epidemics and cutting costs. This healthcare technology trend is transforming healthcare as we know it today. The biggest medical systems in the future are going to use devices that will monitor patients' well-being and help medical experts provide high-quality care. Global big data in the healthcare market is expected to reach $34.27 billion by 2022 at a CAGR of 22.07%.

The coronavirus pandemic expedited the digital transformation underway in healthcare, and patients and providers alike saw benefits to the new tech and virtual solutions. Telehealth appointments, remote patient monitoring services, and amended insurance offerings were able to extend quality care to consumers at a quicker and less-expensive rate. But incumbent healthcare institutions should keep an eye out for big tech companies encroaching on their space, as companies including Alphabet, Amazon, Apple, and Microsoft try to sway consumers from traditional healthcare players through consumer-first, tech-focused approaches. Below, we run through the trends and transformations taking place within the healthcare ecosystem, and outline what traditional health players can do to stay ahead of big tech competitors. While the healthcare industry was slow-moving when it came to digital solutions, COVID-19 upended the entire health ecosystem, including insurance, healthcare delivery, and pharmaceutical spaces.

The earliest clinical decision support systems date back to the 1960s, when pharmacists used automated technology to check patient allergies, research dosages, and check for drug-to-drug interactions.(1) Now, according to recent estimates, up to 74 percent of healthcare provider organizations use clinical decision support (CDS) technology.(2) These systems harness the power of artificial intelligence (AI) to help provide clinicians, staff members, patients, and others with person-specific health information. In New Jersey, a CDS system known as Clover Assistant is taking hold as an invaluable resource for physicians--the platform provides clinicians with patient-specific information that is relevant to the visit, as well as providing actionable insights to help improve long-term outcomes and guide preventative care.(3) But there is still the problem of fragmentation. Stuart Long, CEO of InfoBionic, a leading digital cardiac health company, says, "CDS systems are great for helping physicians arrive at appropriate and timely clinical decisions regarding many aspects of patient care.

Digital health technology is playing a critical role in the Covid-19 public health crisis by helping support patient-provider connection across the care continuum. Since the pandemic started back in March, clinicians have seen many patients with potential symptoms looking for care. It's an uncertain and scary time, especially for those who are at risk and may be infected; but, hospitals and health systems are continuing to implement new processes to help patients and their families receive personalized care in real-time. The healthcare industry overall is looking to technology to help engage patients and their families to take a more active role in their own healthcare. Let's take a closer look at the top three technologies that will continue to play a major role in fighting this pandemic, as the industry prepares for a potential second wave.

PredictMedix (PMED.CN) has been a stock garnering a lot of attention throughout this Covid pandemic. Our team and esteemed writers have covered the company extensively, and the fundamental information which I will summarize, can be read on our latest article here. In terms of a technical approach, the analysis is mine. Looking at the daily chart of PMED, we can clearly see the higher lows and higher highs in an uptrend. On its run from breaking resistance way back at 0.195, we formed two higher lows on the road to the all important 1.00 zone.

Predictive analytics, artificial intelligence, machine learning, personalization, consumer-centric services, enhanced security and telehealth all will affect the delivery and business of healthcare in big ways in 2020, according to five health IT experts from GetWellNetwork, a digital health company that focuses on the patient experience and patient engagement. Healthcare IT News interviewed the CEO, CSO, CISO, CTO and vice president of strategy at GetWellNetwork to get their perspectives on where health IT is headed this year. Their answers ran the gamut, and are good indicators for where healthcare provider organization CIOs and other provider IT leaders need to keep their eyes on. In 2020, predictive guidance will enhance patient workflows, leading clinicians to increasingly deliver the right modality of treatment, adjust treatment recommendations as needed and triage patients to the right location throughout their care journey, whether it is the ER, urgent care or an at-home video consultation, said Robin Cavanaugh, chief technology officer at GetWellNetwork. "Additionally, predictive analytics will guide patient care by suggesting additional healthcare services that similar patients have utilized, augmenting treatment protocols with healthy living suggestions and curating information to resources that may be helpful after treatment," he added.

The smartphone has paved the way for direct-to-consumer (DTC) marketing, driving refinements in marketing tools and redefining consumer expectations. Consumers increasingly value experience over product, and have come to expect personalized, targeted experiences radically shifting the focus of the business marketplace. The healthcare landscape is no exception to this shift: it is increasingly driven by the needs and desires of patients Thanks to the rise of high-deductible health plans and premiums, patients are shouldering a greater portion of healthcare costs than ever before. This increase has positioned patients as consumers at the center of operational changes across the healthcare marketplace. First of all, health tools are not about "cutting out the middle man"--instead they are about reinforcing and improving the relationship between patient and provider that is fundamental to care.

Deep learning's pre-eminence to the enterprise today is significant for two reasons. It represents the ultimate expression of machine learning's advanced capabilities and, as such, has become virtually synonymous with artificial intelligence because of its progressive learning prowess. Deep learning is at the core of the most intricate AI capabilities including speech recognition, image and video recognition, speech generation and aspects of robotics. In considering the massive influx of unstructured data besieging enterprises such as healthcare organizations, the ascending interest in AI, and the pivotal context with which deep learning purveys nearly any use case, it's clear 2018 is the year this technology's utility will finally supersede classic machine learning's. "Traditional machine learning is more like statistics," indico CEO Tom Wilde reflected.