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AI and digital health – the key drivers of the next healthcare revolution

InnoHEALTH magazine digital team — Wed, 24 Aug 2022 10:47:12 +0000

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.”

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AI and Cybersecurity in Digital Healthcare

InnoHEALTH Magazine — Wed, 24 Apr 2019 09:07:46 +0000

All day all round we keep hearing the buzzwords such as Artificial Intelligence (AI), Machine Learning (ML), deep learning cybersecurity, etc. But do we really know what these are? Should we really be bothered and aware of how these can change the healthcare industry? To answer and brainstorm on such questions, the InnovatioCuris team gathered on a beautiful Saturday morning on 6 April 2019 in one of India & premier institutions in Hospital and Health Management, Indian Institute of Health Management Research (IIHMR), Delhi.

The meeting witnessed some very eminent and influential speakers from around the healthcare sector. The former Enforcement Director (ED) Karnal Singh who has investigated many high- profile cases graced the meeting as the Chief Guest.

Innovation is exciting and there are more innovations happening in the private sector, and with increasing technology come increased risks. With the rapidly growing technology, ranging from wireless devices such as mobile phones, tablets, and laptops to smart refrigerators, cars, and even medical devices like pacemakers, etc., it seems that the growing connections around us are difficult to detect. Therefore, the risk that comes together in operating within this brave, new and a connected world is high.

Shri Karnal Singh shared his expert viewpoint on the impact and importance of artificial intelligence, connected healthcare and need for cybersecurity in healthcare. How the digitization of healthcare is important and the rural and urban divide of same. He also insisted on the improvement of infrastructure and facilities available in the rural healthcare industry. In addition, he discussed the gap between the medical industry and government institutions where the research is needed and that we adopt mostly from our partnering and supporting foreign countries and how a change in mindset and adoption of new and improved technology can enhance the Indian healthcare. The future of healthcare is on the Internet and the Internet is vulnerable. Technology is the solution and it will come whether we want it or not. Therefore, the need of the hour is OUR PREPAREDNESS. We should welcome and be prepared for the connected network of healthcare.

An interesting session on the basic concepts of AI was the icing on the cake. It acquainted the participants with AI emphasizing on the fact that one should not get bogged down by the technology. Instead, one should focus on the use cases of it and there lies the innovation.

Often, the terms “digital health” evoke images of smartwatches or apps that can process the health data and can give a readout of parameters like heart rate, blood pressure, etc. That is a part of digital health, to be sure, but today we also focus on a newer aspect called “Precision Health” and the session “Prerequisite and journey of India to offer (precision) healthcare to all: Powered by Digital, Genetics, and AI” offered a far more expansive vision for digital health technologies, genetics and AI.

Precision medicine is an emerging approach of medicine which focuses on the cause of an illness, and not addressing the symptoms alone. Precision medicine may not be very well- known as Personalized Medicine. But they are the same. It takes into consideration individual variability in genes, environment, and lifestyle for each person.

Precision healthcare improves efficiency and accuracy to healthcare treatments. With precision healthcare, doctors can potentially develop targeted and precise treatment and therapies for masses as well as for an individual. This can improve patient treatment to large populations in countries like ours.

It’s based on evidence and data which comes from a series of medical tests on a patient. Thus, the data is its most important aspect. Very soon, along with genome sequencing and health sensors data coupled with the growing amount of Big Data, patient data will create large data sets of valuable information which can be used for more tailored treatments. But as an individual, a physician is not equipped to manually analyze these newly available data sets, which is where the advanced technologies such as AI come into picture.

The challenge that the clinicians see in the adoption of AI is the gap between the technical person and a clinician in regard to understanding the implementation of “normal reference values”. For example: If the normal value of hemoglobin for a person staying at planes (say Delhi NCR) is 13.5, the value 17.5 is perfectly normal at Ladakh. Is that incorporated in the AI system? Something that works in the USA might not work in India. The doctor or a clinician will have a great role to play in case of developing the AI as he/she can only give the correct inputs for the training sets.

With the new wave of digitization, medical records have seen a paradigm shift in the healthcare industry. As a result, the healthcare industry is witnessing an increase in the absolute volume of data in terms of complexity, diversity, and timeliness. Since the healthcare experts look for every possible way to lower the costs while improving the care process, delivery and management, and so is the aim of InnovatioCuris (IC), big data emerges as a persuasive solution with a promise to transform the healthcare industry. This paradigm shift from reactive to proactive healthcare may result in an overall reduction in healthcare costs and gradually may lead to economic growth. The above-stated and many more discussion points were there that became the part of the very interactive and interesting second session on “Mitigating data security and privacy challenges for digital healthcare in India”.

Data transmission is also an important aspect of implementing technology and safeguarding it. The Digital Information Security in Healthcare Act (DISHA) is one such step taken by the Indian Government in the long journey to securing the healthcare data of patients in India.

One of the biggest challenges is the lack of availability of data in a democratic manner and it’s all in silos in short data interoperability is a huge challenge. The major concerns that the clinicians have at the moment regarding the implementation of DISHA act are that it says that no court shall entertain any complaint unless made by the Central Government or central data authority, state data authority or the person affected and there would be times when PIL (public interest litigation) is there on the data security as well. The challenges will always pertain but what we need to do is to have trust in the law and protection by it. Major challenges regarding data security or cybersecurity, in hospitals or the clinical establishments, is that we do not have implemented laws that may protect our data. With the hope that they are definitely going to come, we can only stay prepared with our changed mindsets.

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DocsApp RECEIVED ISO CERTIFICATIONS

InnoHEALTH Magazine — Fri, 29 Dec 2017 05:30:08 +0000

DocsApp
The First Online Healthcare Service Provider to Bag ISO Certifications

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DocsApp, a mobile app that connects patients to specialist doctors via chat or call in less than 30 mins, has received three International Organization Standardization (ISO) certifications from Euro American Joint Accreditation. The certifications garnered are, ISO 9001:2015 for quality management system, ISO 27001:2013 for information security management system and ISO 10002:2014 for quality management, customer satisfaction and complaints handling. These certifications are valid for three years in all 163 Euro-American countries and are issued as per the latest norms of standardization. Whilemany offline healthcare services such as hospitals and service providers have got ISO 9001:2015 and 27001:2013 certifications. This is for the first time that an online healthcare service provider has received ISO certifications. DocsApp is commitment towards bringing superlative and convenient diagnostic services virtually.

Over the years, DocsApp has taken several measures to ensure the safety and security of all the medical records of patients with the help of advanced technology and management procedures. Customer satisfaction and complaints resolution management certification boosts the trust of the customers in it further.

The ISO norms remain same for online and offline processes. The certification process works to identify and implement corrective actions to eliminate non conformance to the quality management standard. For the online processes, quality management, customer satisfaction and complaints handling becomes very important. All these certifications will definitely enhance DocsApp’s solid reputation in the market and further consolidate its position as the go-to app for all healthcare services.

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Read all the issues of InnoHEALTH magazine:
InnoHEALTH Volume 1 Issue 1 (July to September 2016) – https://goo.gl/iWAwN2
InnoHEALTH Volume 1 Issue 2 (October to December 2016) – https://goo.gl/4GGMJz
InnoHEALTH Volume 2 Issue 1 (January to March 2017) – https://goo.gl/DEyKnw
InnoHEALTH Volume 2 Issue 2 (April to June 2017) – https://goo.gl/Nv3eev
InnoHEALTH Volume 2 Issue 3 (July to September 2017) – https://goo.gl/MCVjd6
InnoHEALTH Volume 2 Issue 4 (October to December 2017) – http://amzn.to/2B2UMLw

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