North America leads the race in healthcare cloud computing with a 51% revenue of the global market, which is expected to reach over $201.1 billion by 2032. In the wake of a pandemic that shifted the medical sphere to focus more on remote approaches and digital alternatives, the impact of the cloud has become even deeper as private healthcare enters a new era.
What Drives Healthcare to the Cloud?
The private sector is unmistakably driven by profit, which is one of the biggest factors driving the massive inclination toward the cloud. Despite being an investment in new technology (at least by the medical industry’s standards) it is a move that ends up being more cost-effective in the long run as it eliminates many on-premise costs, improves security, and provides more scalability.
It essentially drives up productivity by streamlining healthcare processes while simultaneously cutting down on unnecessary corners. As such, major healthcare organizations have already taken to adopting it to improve business. In turn, it actually helps patient outcomes as it allows better response times, quick reaction to changes, enhanced resource management, and minimized disruption.
In Fast Company’s breakdown of healthcare figures taking on the cloud, standouts include Prospect Medical Holdings’ cloud-based HR and payroll systems, Mayo Clinic’s Oracle Fusion Cloud Application for employee and supply chain support, and Northwell Health’s analytics and data warehousing for remedying patient-staff deficits.
The State of Telemedicine
Cloud advancement is not simply a concept that carries potential for the future. It already has a proactive progression most felt in today’s telemedicine industry. More than a tool for internal staffing and processes, the cloud also creates a more efficient and secure way to store patient records. It also enables real-time data sharing and allows scalable infrastructure to allow remote consultations.
Aside from steady growth due to general digitalization, telemedicine saw a sharp incline in adoption after COVID-19 spread globally. Even developing countries across the Asia-Pacific reason saw a boom, with several countries expected to surpass 70% in telehealth adoption by 2024. The only major factors stunting the growth of telehealth, as noted by the National Institutes of Health, are social determinant causes such as income, education level, race, and insurance type.
This calls for the need to create solutions that are more accessible and close the gap created by these “potential inequities”. In response to these issues, the private healthcare sector is using existing tech resources to improve telemedicine.
This is why we see many major providers try MongoDB to advance machine learning, store large volumes of patient data, secure transactions that may be from various geographical tags, and integrate other healthcare applications. On the patient’s end, prescriptions, ordering medication, getting medical documents, and getting remote consultations become possible in one digital suite.
Diagnostics, Treatment, and Artificial Intelligence
Despite large strides for tech advancement in healthcare, there are still more use cases for the cloud that are seeing buzz and potential applications. As we’ve delved into before with ‘How is Technology Advancing Healthcare?’, health technology is developing at breakneck speed with surgical automation, machine learning, and AI algorithms for basic symptom tracking and patient administration.
Artificial intelligence is a major turning point for diagnostics and treatment, with the cloud facilitating its use across locations and throughout the span of extended treatment plans. Ultimately, the cloud enables artificial intelligence to access and contribute to patient data in a secure manner that is safe from data loss or unauthorized access. It also makes collaboration with humans and other AI models easier since data is not limited to hardware. Finally, the scalability of the cloud makes AI integration more promising because systems can make efficient readings from a centralized platform that is not limited to small amounts of healthcare data.
Eventually, diagnostics and treatment for patients will become not only more efficient (and, in turn, more profitable) but also allow for greater outcomes and care.
