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Digital health and AI is one of the hot topics that people within and outside of the healthcare industry have been talking about recently.

Technology has been at the heart of the healthcare revolution for years. The evolution of the internet, mobile networks, smart devices, etc., have significantly changed the process of delivering patient care. Gone are the days when people had to wait for hours for a 15-minute doctor consultation. Today, doctor consultation is just a matter of a phone call. Patients can now have physician consultations from the convenience of their homes. And this is just one example of how much technology has transformed healthcare. Digital health and AI is one of the hot topics that people within and outside of the healthcare industry have been talking about recently. This article discusses how AI and digital health is fuelling the next healthcare revolution while redefining healthcare delivery.

What is digital health?

Digital health is a multidisciplinary concept that uses communication and information technologies to help health systems deliver affordable and good-quality care. Digital health also enables healthcare institutions to be efficient and sustainable. Telehealth, mhealth, and wearable devices used to monitor patient status are some of the real-time examples of digital health.

AI or Artificial Intelligence

AI is one of the greatest breakthrough technologies that is changing our everyday life experiences, right from avoiding traffic and online shopping to hospital experiences. While we are already experiencing AI-induced changes in our lives, like personalized movie or music recommendations, and voice-controlled personal assistants such as Alexa and Siri, let us dive in to understand how AI and digital health is transforming the healthcare industry and patient care.

AI can ease the process of detecting invalid claims and accelerate the pace of claim – assessments, processing, approval, and payment through automation.

How AI and digital health is transforming healthcare

1. Optimized workflow scheduling and case prioritization

Workflow management and case prioritization are highly critical in the healthcare domain, as a patient’s life is at stake. The sooner the diagnosis, the earlier the treatment. AI and ML algorithms can aid in optimizing workflow, prioritizing cases, and managing patient flow. Healthcare professionals can navigate hundreds of medical records and identify critical and non-critical cases within seconds using AI and ML algorithms. This will help physicians and radiologists to focus on critical cases on priority and create workflows and patient flows accordingly. Furthermore, AI can also help in automating time-consuming manual tasks like patient data entry, medical claim scrubbing, etc. AI can also facilitate personalized responses to EHR searches.

2. Quick drug discovery

It takes years, or even decades, to synthesize the appropriate drug for an illness. Chickenpox, for instance, was identified in the 1950s. But it took almost four decades to discover the right vaccine for the illness. With AI, drugs for contagious diseases can be discovered and synthesized within months, if not days. A real-time example of how AI can speed up the drug discovery process is the recent pandemic, COVID-19. Almost within a year of the COVID-19 outburst, a relevant vaccine was developed and distributed across the globe with the help of AI. 

3. Quantitative imaging analysis and reporting

Have you ever got a different diagnosis from different doctors for the same problem? If yes, then you probably might have thought which one of the diagnoses is correct. Such different diagnosis from different doctors is primarily due to subjective analysis and reporting. Almost all medical images are studied in a subjective manner – based on the radiologist or physician’s personal opinions, point of view, and interpretations – and have often led to diagnostic errors and incorrect/unnecessary treatment. The shortcomings of subjective analysis and reporting can be overcome only through quantitative imaging analysis and objective reporting.

Quantitative imaging analysis, as the name suggests, is the process of measuring all the elements in a medical image and comparing it against anatomical values to identify deformities and determine the severity of illness. Reports generated from quantitative imaging analysis are known as objective reports and hold detailed information about every element of the scanned body part, including their measurements. However, performing quantitative imaging analysis and generating objective reports is a time-consuming task, which is why most health centers are unable to perform them. But AI can help health institutions perform quantitative imaging analysis quickly and accurately. 

4. Robot-assisted surgery & Virtual nursing assistant

Robot-assisted surgery enabled by AI can help surgeons to perform complex procedures with increased precision, flexibility, and control as compared to conventional techniques. Robot-assisted surgery is gaining more prominence in healthcare and the market size of robotic surgery is expected to cross $7 billion by 2025. Similar to robot-assisted surgery, AI-powered robots can serve as virtual assistants to provide 24/7 support for chronic conditions, monitor patient status, check medication intake, and schedule doctors’ appointments, just the way a nurse practitioner would do.

5. Fraud detection

AI can help in ensuring the security of patient data, which is highly sensitive and at the heart of providing secured and personalized patient care. Also, AI can ease the process of detecting invalid claims and accelerate the pace of claim – assessments, processing, approval, and payment through automation.

According to a report, AI adoption can help US healthcare providers save nearly USD 150 billion by 2025.

6. Precision medicine

Precision medicine, also known as personalized medicine, is a medical model where healthcare is customized according to the genetics, lifestyle, and environment of a person. Precision medicine is the exact opposite of the one-drug-fits-all medical model. Numerous studies and experiments have been carried out to understand the potential of AI in precision medicine. And in most cases, AI has been able to classify and solve precision medicine problems in aspects like disease detection and prediction, treatment optimization, etc. Most healthcare providers and professionals believe that AI will take precision medicine to the next level and improve the levels of accuracy and prediction in patient outcomes. They also believe that AI can help in making precision medicine affordable and available to people from rural areas.

Summing Up

AI and digital health are not only beneficial for patients but also providers. Many stakeholders and industry leaders posit that the digital health and AI market is growing with a great potential for ROI. According to a report, AI adoption can help US healthcare providers save nearly USD 150 billion by 2025. Not just that, with medical imaging data growing abundantly and projected to double by the next decade, AI will be the only solution to handle the healthcare data explosion.

Studies state that the growth of AI in healthcare will be driven by the increasing volume of data. Matter of fact, numerous health systems have started embracing AI applications not just in patient-facing clinical processes, but also in diagnostic workflows and tasks associated with medical images. According to a KPMG survey, 89% of respondents stated that AI is already enhancing the efficiency of their systems. 

Many health tech firms are moving from cancer diagnosis and focusing on creating AI algorithms for other health issues like chronic neck and back pain. Synapsica, for instance, is a leading AI health tech firm that has successfully built AI tools for spine problems and injuries. Using Synapsica’s AI tools, Spindle and SpindleX, radiologists can perform quantitative imaging analysis and generate objective reports within minutes. The healthcare industry is one of those industries that transform almost every decade. The current healthcare industry is highly different from what it was a decade ago and will be highly different from what it is now in the next decade. And AI and digital health will be the key drivers of the next healthcare revolution.

Composed by: “Dr. Cherian is presently associated with AIIMS, New Delhi. He is leading all medical operations, research and product vision for Artificial Intelligence. He has established many startup teams for pan-India operations.”

InnoHEALTH magazine digital team

Author InnoHEALTH magazine digital team

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