Every industry in today’s world has been touched by technological advancements, and healthcare is no different. The healthcare industry has transformed significantly throughout the years, with much of that change owing to technological advancements. When considering all types of digital technology applications in healthcare, there are broadly six categories including telehealth, artificial intelligence and machine learning (AI &ML), augmented and virtual reality, internet of things (IOT), 3D printing, and NGS.
Telehealth has risen to the top of any healthcare provider’s priorities list. This service is becoming one of the most significant business channels for healthcare organisations. This service is in high demand, and technology is well poised to meet it. In countries like India and Africa, health is a major concern. These countries have a large population, and the ratio of healthcare facilities to population is remarkably low. As a result, the only immediate solution is telemedicine, which can bring primary healthcare to every corner of the country.
There are various modules in this telehealth. Video consultations are the most fundamental module we can have. At the very least, consultants can videoconference with a patient in a remote location. The advanced portion of the system is a connector for various medical devices. As a result, it assists us in enabling self-care and lowering the cost of care. In fact, hospitalizations have decreased by over 90%, and the cost of care for these patients has decreased by more than 50%. There is a lot of patient engagement technology associated with tele-health, such as on-line patient appointments, on-line lab/imaging reports, and patient follow-up system.
If we start detailing of the patient engagement system, we can think about Internet of Things (IOT) enabled post care monitoring system. Wearable health monitors have evolved quickly and can now collect real-time, clinically accurate medical data. Paired with well-designed mobile apps, users can view the analysis of their collected data and share it with their healthcare providers. Alerts can also be received in case of irregularities in vital signs such as heart rhythm, which could indicate a serious condition. This technology and the data provided could allow for the timely diagnosis of patients, potentially identifying conditions before they worsen and/or become life-threatening.
Today, clinical trials are challenged to find enough people to participate and, even then, participants are faced with the burden of coming in frequently for tests and monitoring. Many clinical studies can benefit from wearable because they make trial monitoring more accessible. Furthermore, real-time and continuous data obtained for a parameter will almost certainly be more reliable and indicative of reality than a measurement done in a clinical environment on a given day and time.
Digital business in the retail sector is quite matured. The healthcare sector is now enabling the retail pharmacy and homecare businesses by replicating the same application. The use of technology is prevalent across the digital healthcare system. However, this is the current condition of the digital health system. We will now discuss the most advanced state of the digital health system where all of these are either in the R&D stage or have only been partially implemented.
Next Generation Sequencing (NGS) is another important digital technology application in healthcare. As a direct consequence of the introduction of NGS into labs, the numbers of genes associated with causing human inherited disorders have increased. These genetic predispositions can be discovered by sequencing a patient’s genome. As a result, doctors can keep track of their patients before symptoms appear, and essential disease management strategies, such as preventative treatments, can be implemented early.
Gene sequencing can also indicate how people react to different medications. While NGS has been studied in a variety of healthcare contexts, oncology is where it is most advanced. Physicians can sequence tumors in order to match them to targeted medicines that will slow tumor growth. Targeted therapies can significantly improve disease management by reducing the possibility of therapy delays caused by ineffective drugs with potentially unpleasant side effects. Doctors can keep an eye on their patients before symptoms appear.
Last but not least, one of the most intriguing applications in the digital health industry is artificial intelligence and machine learning (AI & ML). AI/ML applications in healthcare are becoming increasingly popular. AI can detect minor anomalies or changes in patterns, which can help in diagnosis, tracking, progression, and treatment response of a disease. This has enormous potential to aid clinical judgments in time-sensitive situations or where expert knowledge is scarce, such as at rural or underfunded medical facilities.
AI is not only being used to assess standard radiological exams that look inside the body, such as x-rays, computerised tomography (CT) scans, and magnetic resonance imaging (MRI), but it can also be used to diagnose disease by analysing the physical appearance of patients. Skin Vision is an app that allows users to perform regular self-skin cancer examinations by analysing images taken with their phone. Facial analysis using AI to detect genetic diseases shows considerable promise for diagnosing patients earlier than traditional methods.
To meet the nation’s demand for health care, it is important to boost the usage of digital healthcare. It includes a number of benefits like access is improved, expenditures are reduced, care is more convenient, and clinician time is saved, to name a few. Hence, more and more digital healthcare solutions are needed to be implemented by providers, payers, and employers.
Shuvankar Pramanick, Dy. CIO, Manipal Health Enterprises Pvt. Ltd
(DISCLAIMER: The views expressed are solely of the author and ETHealthworld does not necessarily subscribe to it. ETHealthworld.com shall not be responsible for any damage caused to any person / organisation directly or indirectly.)