Today, we see healthcare leaders refocusing on several new and existing priorities, from addressing staff shortages, to extending care delivery, to leveraging big data and predictive analytics, as they navigate new realities in care delivery. Added to this is the rising expectations of patients, evolving with rapid changes in technologies. Hence, in 2023, there lies an enormous scope for emerging technologies to fully transform and advance the health-tech market in India.
More than ever, a digital connection between patients and caregivers is necessary to complete the last mile in healthcare. SaaS (Software as a Service) is crucial to this improved accessibility. An advanced extension of the cloud, it makes data easily accessible, permitting caregivers to take immediate action, share information, produce data, and analyse it in real- time with a nearly instantaneous response time. This will enable hospitals to have a thorough understanding of each patient's medical background, allowing them to improve their care for patients and achieve better results.
Artificial intelligence (AI) can completely transform e-health solutions by providing insights into the possibility for speedier, less expensive, and patient-specific therapies. According to PwC's Global Digital IQ Survey, AI and internet of things (IoT) are the most disruptive technologies in the healthcare sector. AI algorithms are used in conjunction with more IoT devices than smartphones to digitally collect data and transform it into actionable results. Thanks to AI- driven analytics, tools, and technology, healthcare providers of the future will be able to choose the optimal course of action for each patient with the aid of more effective, accurate, and substantial intervention.
As India gears up to rollout 5G, the healthcare industry has the greatest potential to be transformed by this technology. The dedicated network slices with assured throughput, high-speed, and nearly no latency promise to enable cutting-edge services like live, real-time health monitoring, telemedicine, and remote surgery. When combined with human assistance, technology and 5G connectivity have the potential to improve public services, release resource constraints, and potentially save lives.
Over time, key concerns such as robotic rehabilitation, precision medicine, remote care for emergencies, and many more will develop and benefit with 5G technology.
Modern healthcare firms rely heavily on cloud-based technology as it offers cutting-edge choices for automation, cost reduction, and security. Moreover, we must be aware that the use, archiving, and sharing of medical data have undergone a significant change because of cloud computing in healthcare. Additionally, it offers personalisation in care plans to enhance outcomes and assists in the discovery of new customer outreach channels.
As more people take control of their health, adopting wearable healthcare technologies is one of the trends that is revolutionising the healthcare sector. Mobile sensor data for quick implementation, IoT devices can provide remote diagnostics and health monitoring. A new Internet of Medical Things (IoMT), developed using the Internet of Things and telemedicine, will be essential for tracking and avoiding ailments. Healthcare administrators will need to know how to integrate these technologies into their companies as people become more tech-savvy and health wearables become more widespread.
Standards for computing power, data processing, and data security are advancing and getting better. Although healthcare modernization is already under way, health informatics (HI) will continue to flourish, due to the advancements in standards, technology, and the acceptance of patient information rights.
Experts in health data analytics who can monitor and analyse health informatics data are becoming more and more valuable to population health management initiatives used by healthcare systems to monitor and enhance the health of people with chronic conditions like diabetes, hypertension, and obesity. Health informaticians are increasingly using technology like machine learning to undertake predictive analytics about the likelihood that diseases will affect both individuals and broader patient populations, as well as about the prognosis for therapy.