AI and digital health: the driving forces behind the next healthcare revolution

Digital health and artificial intelligence (AI) are two of the most recent hot topics that people both inside and outside of the healthcare industry have been discussing.
For many years, technology has been at the heart of the healthcare revolution. The evolution of the internet, mobile networks, smart devices, and other technologies have significantly altered the process of providing patient care. People no longer have to wait for hours for 15-minute doctor consultations.

Doctor consultations are now as simple as a phone call. Patients can now consult with doctors from the comfort of their own homes. This is just one example of how technology has changed healthcare. Digital health and artificial intelligence (AI) are two of the most recent hot topics that people both inside and outside of the healthcare industry have been discussing. This article examines how artificial intelligence and digital health are fueling the next healthcare revolution while redefining healthcare delivery.

What exactly is digital health?
Digital health is a multidisciplinary concept that employs communication and information technologies to assist healthcare systems in providing affordable, high-quality care. Healthcare institutions can also become more efficient and sustainable with the help of digital health. Real-time examples of digital health include telehealth, mhealth, and wearable devices used to monitor patient status.

AI stands for Artificial Intelligence
AI is one of the most significant breakthrough technologies that is altering our daily lives, from avoiding traffic to online shopping to hospital experiences. While we are already seeing AI-induced changes in our lives, such as personalised movie or music recommendations and voice-controlled personal assistants like Alexa and Siri, let us take a deeper look into how AI and digital health are transforming the healthcare industry and patient care.

Through automation, AI can make it easier to detect invalid claims and accelerate the pace of claim-assessment, processing, approval, and payment.

How artificial intelligence and digital health are transforming healthcare

1. Improved workflow scheduling and prioritisation of cases
   Workflow management and case prioritisation are critical in the healthcare industry because a patient’s life is on the line. The sooner a diagnosis is made, the sooner treatment can begin. AI and machine learning algorithms can help with workflow optimization, case prioritisation, and patient flow management. Using AI and ML algorithms, healthcare professionals can navigate hundreds of medical records and identify critical and non-critical cases in seconds. This will allow physicians and radiologists to prioritise critical cases and design workflows and patient flows accordingly.
2. Rapid drug discovery It can take years, if not decades, to develop an appropriate drug for an illness. Chickenpox, for example, was discovered in the 1950s. However, it took nearly four decades to find the right vaccine for the illness. Drugs for contagious diseases can be discovered and synthesised in months, if not days, thanks to AI. The recent COVID-19 pandemic is a real-time example of how AI can accelerate drug discovery. With the assistance of AI, a relevant vaccine was developed and distributed globally almost a year after the COVID-19 outbreak.
3. Analysis and reporting of quantitative imaging Have you ever received different diagnoses for the same problem from different doctors? If you answered yes, you may have wondered which of the diagnoses is correct. The reason for such disparities in diagnosis among doctors is primarily due to subjective analysis and reporting. Almost all medical images are studied subjectively – based on the radiologist’s or physician’s personal opinions, point of view, and interpretations – which has frequently resulted in diagnostic errors and unnecessary/incorrect treatment. Only quantitative imaging analysis and objective reporting can overcome the shortcomings of subjective analysis and reporting.The process of measuring all the elements in a medical image and comparing them to anatomical values to identify deformities and determine the severity of illness is known as quantitative imaging analysis. Objective reports are generated from quantitative imaging analysis and contain detailed information about every element of the scanned body part, including measurements. However, performing quantitative imaging analysis and producing objective reports takes time, which is why most health centres are unable to do so. However, AI can assist health care facilities in performing quantitative imaging analysis in a timely and accurate manner.
4. Robotic surgery and virtual nursing assistant When compared to traditional techniques, robot-assisted surgery enabled by AI can assist surgeons in performing complex procedures with greater precision, flexibility, and control. Robot-assisted surgery is gaining popularity in the medical field, and the market for robotic surgery is expected to exceed $7 billion by 2025. AI-powered robots, like robot-assisted surgery, can serve as virtual assistants to provide 24/7 support for chronic conditions, monitor patient status, check medication intake, and schedule doctor’s appointments, just like a nurse practitioner.
5. Detection of Fraud AI can assist in ensuring the security of highly sensitive patient data, which is at the heart of providing secure and personalised patient care. Furthermore, AI can automate the process of detecting invalid claims and accelerating the pace of claim-assessment, processing, approval, and payment.
6. Sixth, precision medicine Precision medicine, also known as personalised medicine, is a medical model in which healthcare is tailored to a person’s genetics, lifestyle, and environment. Precision medicine is diametrically opposed to the one-drug-fits-all medical model. Numerous studies and experiments have been conducted to better understand AI’s potential in precision medicine. In the majority of cases, AI has been able to classify and solve precision medicine problems such as disease detection and prediction, treatment optimization, and so on. Most healthcare providers and professionals believe that AI will advance precision medicine by improving accuracy and prediction in patient outcomes. They also believe that AI can help make precision medicine more affordable and accessible to people from rural areas.

To summarise
AI and digital health are beneficial not only to patients but also to providers. Many stakeholders and industry leaders believe that the digital health and AI market is expanding and has a high ROI potential. According to one study, AI adoption could save US healthcare providers nearly USD 150 billion by 2025. Not only that, but with medical imaging data expected to double in the next decade, AI will be the only solution to deal with the healthcare data explosion.

According to studies, the increasing volume of data will drive the growth of AI in healthcare. Indeed, many health-care organisations have begun to embrace AI applications not only in patient-facing clinical processes, but also in diagnostic workflows and tasks involving medical images. According to a KPMG survey, 89% of respondents believe AI is already improving system efficiency.

Many health tech companies are shifting their focus away from cancer diagnosis and toward developing AI algorithms for other health issues such as chronic neck and back pain. Synapsica, for example, is a leading AI health tech company that has developed AI tools for spine problems and injuries. Radiologists can perform quantitative imaging analysis and generate objective reports in minutes using Synapsica’s AI tools, Spindle and SpindleX. The healthcare industry is one of those that undergoes transformation almost every decade. The current healthcare industry is very different from what it was a decade ago, and it will be very different in the next decade. And artificial intelligence and digital health will be the primary drivers of the next healthcare revolution.