A Data Intelligence Cloud for Healthcare Provider Transformation Analytics

Healthcare Providers are facing a data crisis with the lack of real-time visibility into patient coverage making it difficult to provide value-based care and the current level of data interoperability with payors making it impossible to have nuanced conversations with patients about their care. So, delivering value-based care with seamless, scalable, and intelligent solutions while harnessing data and AI to drive profitable growth and better manage risk has become the rallying cry for healthcare providers in today’s rapidly changing market. Being able to understand the hundreds of data points from within the enterprise as well as publicly available data to modernize their analytics and risk platforms to improve value-based care, intelligent predictive management and safety is the prime catalyst for healthcare provider AI transformation projects.

Unfortunately, fragmented data and inefficiencies in care delivery and administrative processes increase operational expenses while aging infrastructure and legacy system bottlenecks increases operational costs, reduces efficiency, and limits compatibility with modern technologies.​ The solution is centered on cloud migration for next level scalability, security and advanced analytics, but adopting a cloud solution is complex, with risk of disruption to customer health and payment history.

Embracing these technologies successfully requires a strategic approach and alignment between IT and business objectives.

Why should healthcare provider professionals care about a data intelligence cloud?

It would be an understatement to observe that healthcare provider professionals are experts in their field and are not usually comfortable with the rapid advancements in technology. So, having the ability for an average business executive to “converse” with a machine using natural language (NLP) to get the analytics they need to make better decisions, streamlining business operations to delivering unparalleled customer experiences and decreasing operational risk by inspecting hundreds of variables instantaneously identifying the potential to healthcare providers looking to modernize their analytics and risk platforms to drive better business outcomes - enhancing patient safety and experience, operational efficiency, profitable growth, risk management, and compliance.

Modernization of legacy applications has become a “need to have” for healthcare provider organizations looking to maintain their competitive standing and operational profitability. Instead of continuing down the path of proprietary solutions that require dedicated tools and resources, many are now evaluating an data intelligence cloud solution that leverages new advancements in GenAI and reinforcement learning. Simply put, a data intelligence cloud is a cloud computing platform that leverages to power of GenAI to enhance its capabilities and transform data into usable information accessible by the average person, allowing them to harness their organization’s full potential by capturing and harnessing the right data, advanced analytics and AI capabilities. Bottomline, it democratizes AI for "Citizen Data Scientists.”

Providers face critical obstacles that hinder their transformation journey:

• Data Silos and Analytics Gaps: Fragmented data systems and outdated analytics tools prevent holistic insights and increase security risks and governance concerns, making it difficult to focus on improving patient outcomes.
• Legacy System Bottlenecks: Aging infrastructure increases operational costs, reduces efficiency, and limits compatibility with modern technologies.
• Team morale and capacity: is stretched thinner than ever making resource management key to survival.
• Cloud Migration and Scalability Hurdles: Adopting Cloud solutions is complex, with risk of disruption to customer health and payment history.

Improving outcomes and optimizing healthcare provider analytics

A successful AI transformation/data intelligence cloud project for healthcare provider operations and analytics will empower business leaders to get actionable insights in real-time while maintaining security and privacy and free data analysts to innovate instead of generating reports. Some of the specific use cases include:

• Deliver Value-Based Care: data interoperability with payers makes it possible to have nuanced conversations with patients about their care.
• Intelligent, Predictive Management: leverage AI/ML to allocate the resources you need, when and where you need them.
• Stay Modern, Stay Secure: gain future-ready infrastructure with built-in security and seamless integration of business and IT.

New developments in open-source, zero-code SaaS platforms mean that legacy system modernization projects can be tackled with a data intelligence cloud that reduces dependencies on proprietary systems and the costs of dedicated tools and resources. So, the good news is that you won’t have to wait months or even years to realize the benefits of an intelligent cloud for your life sciences operations.

Deliver value in days or even minutes instead of months or years

Vendors like UBIX deliver on the promise of a zero-code, highly scalable and flexible cloud architecture that leverages the best-in-class cloud technologies to support modern data workloads, including analytics, AI, and ML. A perfect fit for any healthcare provider AI transformation or intelligent cloud project.

With an architecture that is designed to adapt to the varying demands of healthcare providers, allowing them to integrate and analyze data from multiple sources: EHRs, claims, patient-reported outcomes, and cloud vendors, as well as build predictive models for financial and care use cases without requiring coding expertise. Ex: Personalized Payments, Operational Efficiency, Customer Segmentation. This will also automate workflows and decision-making processes to improve efficiency and outcomes. Here are three examples of the many ways it can be used:

• Predictive Staffing: leverage AI/ML to predict intake, compare with historical data, and surface staffing recommendations.
• Epic Co-Traveler Applications: aggregate data across applications and gather insights without a team of data scientists.
• Clinical Grant Assistance: surface the preliminary analysis needed to apply to clinical grants and gather insights as trials progress.

Learning how GenAI and emerging advancements like Reinforcement Learning can deliver on the promise of a data intelligence cloud for healthcare provider analytics has never been easier. Download our free eBook titled “5 Steps to AI Business Transformation Success” to help better understand the nuances of emerging AI concepts and technologies and offer a set of best practices for consideration to ensure digital transformation and business-led AI success. Or if you can spare 22 minutes for a mini–AgenticAI Readiness Workshop, you can contact one of our AI experts today.