Unifying data for better care, cost outcomes
NYUPN – OPTUM PERFORMANCE ANALYTICS VIDEO SCRIPT
With the rising cost of healthcare continuing to outpace inflation—and the swelling of the elder population pushing the number of chronic conditions ever higher—the US healthcare system needs new, innovative solutions to solve healthcare’s biggest challenges.
I’m Matt Penziner with NYUPN, a collaboration between NYU Langone Medical Center and University Physicians Network. At NYUPN, improving outcomes while controlling costs is our top priority. One of the biggest challenges is bringing disparate sources of data together to create a comprehensive patient profile, so we can identify the right patient and intervene with the right treatment at the right time, before they land in an emergency room or hospital.
Our physicians, nurses, and care managers are passionate about taking care of our patients. The sooner we can identify a high-risk patient—potentially before they even realize they’re getting sick—the sooner we can deliver the right care.
Now, Optum Performance Analytics brings together clinical and claims data, alongside socio-economic data, to support the best possible quality and cost outcomes. We can leverage advanced analytics models to address real-world solutions, incorporating the latest algorithms to quickly identify the best actions.
And we have the flexibility to expand on built-in analytics to surface additional data points, answer further questions, and create our own reports.
When a patient visits a doctor, or is admitted to a hospital that is not within our health system, that patient data – which is so important to their care – may not be communicated back into our system.
Performance Analytics helps us assimilate the data, so we can avoid unnecessary tests and care gaps, keeping the patient within our system while providing the best possible care.
NYUPN and Optum: Intelligent choices for a healthier world.
Learn how NYUPN improves performance with Optum.
NYUPN uses Optum® Performance Analytics to proactively identify high-risk patients and intervene with the right treatment at the right time. They can also assimilate disparate data to avoid care gaps and keep patients in the system.