Healthcare organizations generate millions of disconnected data points and analyzing it can feel like boiling the ocean. Predictive analytics has the highest potential for value generation as it offers answers to questions that can enable healthcare organizations to thrive in the value based care environment. As the industry faces high pressure to transition to proactive ways of working.
How is data analytics used in healthcare?
Advanced data analytics assimilates unprocessed data and translates it into actionable insights that lowers care costs and lights the way for better clinical decision making. A research team from New York University's Grossman School of Medicine has developed a large language model (LLM) called NYUTron, designed to predict various healthcare outcomes, including hospital re-admissions and length of stay.
As detailed in a study published in Nature, this tool can accurately forecast 30-day all-cause readmissions, in-hospital mortality, comorbidity index, length of stay, and insurance denials, utilizing unaltered electronic health record (EHR) data. At the time of publication, NYUTron was able to predict 80% of all-cause readmissions, marking a five percent improvement over current models.
The need for AI is real in the analytics space
The integration of healthcare data analysis and artificial intelligence (AI) is poised to disrupt the healthcare industry in the coming years. AI-driven analytics will usher in a new era of innovation, focusing on patient-centric metrics and enhancing the accuracy of clinical decisions. By leveraging AI and data science, healthcare providers can categorize patients with similar profiles to predict health trends. These insights will enable hospitals and clinics to better prepare for drug studies and interactions. Additionally, real-time analytics will empower doctors to make more informed decisions, allowing them to recommend medications, tests, and treatments to patients at reduced costs.
Predictive analytics -Gazing through the crystal ball
What can happen next? This question is central to the success of care providers. Predictive analytics utilizes current and historical data to predict future events and identify trends in patient populations.
RippleCARE is an AI driven healthcare analytics and patient engagement platform that utilizes predictive analytics to reduce re-admissions, enable personalized care pathways and improve overall outcomes.
Through the predictive analytics capabilities of RippleCARE hospitals can achieve:
Better care coordination
Enhanced care coordination can significantly improve patient outcomes and satisfaction, and predictive analytics offers a powerful tool for healthcare organizations to strengthen these efforts. In hospital settings, predictive analytics assists care coordination teams in preventing negative outcomes such as patient deterioration and re-admissions while optimizing patient flow.
Achieve health equity
Researchers and clinicians are at the forefront of ensuring patients receive equitable care, but achieving this goal requires healthcare stakeholders to develop a deep and nuanced understanding of how social determinants of health (SDOH) affect patients.
Predictive analytics can extract valuable insights from the vast and complex data necessary to support these initiatives.
Personalized care plans
Predictive analytics helps in creating personalized treatment plans and care pathways. Providers gain the insights they need to make early intervention and prevent health issues before they turn fatal. The outcomes of specific drug or therapy interactions can also be gauged to provide better care. By analyzing information from large data sets derived from EHRs and patient records the role of predictive analytics is pivotal in creating personalized care journeys.
Small and incremental steps to gain immediate value
Point solutions or small-scale projects may cut back on costs for mid-sized hospitals who are taking their first steps in adopting predictive analytics. But this approach leads to data silos and fragmented processes in the long-term.
A comprehensive analytics platform with modular components that can be added as needed enables the development of a scalable strategy with long-term benefits. Instead of relying on point solutions, a unified analytics platform offers better long-term value by allowing you to acquire components as you become ready to implement them.
This approach simplifies initial complexity and cost, while enabling you to gradually enhance your analytics capabilities over time. Additionally, a standardized platform that serves the entire organization provides a consistent interface, facilitating user training and fostering a common analytics language for future cross-departmental analyses.
RippleCARE- A fresh approach
RippleCARE offers a healthcare analytics and patient experience platform that combine deep expertise and tech prowess. It offers hospitals the data they need to improve engagement, make informed clinical decisions, reduce re-admissions and transition to newer payment mechanisms.
We offer a full-featured analytics platform that can also be adopted as individual modules that can be scaled and combined.