The Impact of AI in Transforming Healthcare Organizations

1. The Impact of AI in Transforming Healthcare Organizations

2. The Impact of AI in Transforming Healthcare Organizations Today, on a day in January 2030, it is very cold, and the flu disease is at its peak. Similar to a decade ago, clinics and doctor’s offices were overflowing with sick people waiting to be seen and get treated; today the patients move easily through the systems to get treated by the doctors.  So, what’s the difference now? With the immense pressure on global healthcare systems and a lack of skilled medical professionals to care for the rapidly growing and ageing populations, and the breakthroughs in powerful technology enablers such as data science and Artificial Intelligence, connected care has become a reality.  Networked hospitals connected careAlong with predictive care, a new innovation in the delivery of such care has emerged. A hospital in 2030 is no longer a single large structure that treats a variety of diseases; instead, it focuses on the critically ill and highly complex procedures, while less urgent cases are monitored and treated through smaller hubs and spokes, such as retail clinics, same-day surgery centers, specialist treatment clinics, and even people’s homes.  All of these locations are linked by a uniform digital infrastructure. To maintain track of supply and demand across the network, centralized command centers analyses clinical and geographic data in real time. This network can eliminate bottlenecks in the system and ensure that patients and healthcare professionals are sent to where they can best be cared for or where they are most required, in addition to using AI to spot those in danger of deterioration.

3. The Impact of AI in Transforming Healthcare Organizations Challenges of AI in healthcareA successful AI solution requires a vast amount of patient data to train and optimize the performance of the algorithms. In healthcare, gaining access to these databases creates a variety of issues:  The future outlook for AIHybrid models, in which clinical professionals are assisted in diagnosis, treatment planning, and risk factor identification but retain ultimate responsibility for the patient’s care, represent the strongest potential for AI in healthcare over the next several years. By reducing perceived risk, healthcare providers will be more likely to employ the technology, and measurable benefits in patient outcomes and operational efficiency will begin to be delivered at scale.  Enterprises may face a number of challenges when using AI for business operations, including identifying the exact use cases, a lack of awareness about what really needs to be done, verifying the exact requirements based on the data input, and testing the business needs for functionality, performance, scalability, security, and more. Despite the significant media attention, AI-powered solutions have only made tiny efforts toward tackling important concerns and have yet to make a meaningful overall impact on the global healthcare industry. If many critical hurdles can be overcome in the coming years, it has the potential to play a key role in how future healthcare systems run, supplementing clinical resources and assuring the best possible patient results.

4. The Impact of AI in Transforming Healthcare Organizations Cigniti’s extensive experience in AI, machine learning, and analytics helps businesses improve their operations and quality assurance methods. Need help? Talk to our healthcare testing experts and AI experts to learn more about the impact of AI in transforming healthcare organizations. Read the full blog to know more: https://www.cigniti.com/blog/ai-healthcare