There is a link between the transition to value-based care and an increased interest in analytics-based models that can successfully predict patient outcomes.
As providers move to payment models that reward results over total number of procedures performed, they are accepting more financial liability.
To meet that responsibility, providers must understand more about how their patients will likely use their services and the future costs of providing care.
For example, providers know it is expensive to admit a patient to a hospital. And, they face penalties when patients return to a hospital shortly after being released.
They need analytics tools that can help them forecast which patients are at the highest risk of hospitalization so they can provide care proactively.
Finding these patients requires the use of data. Optum suggests predictive modeling solutions that leverage a data set of robust size, scope and quality.
The larger the sample size, the lower the level of a model’s uncertainty. The best predictive models aggregate a large, diverse sampling, but also allow providers to incorporate their own data in a timely way.
Optum recommends combining clinical, claims, socioeconomic and care management data into one data set to paint the best picture of a patient population.
Models that accurately predict which actions to take for which patients allow providers to prioritize care coordination and carry out targeted interventions – moves that should help manage costs.
Take five minutes to learn more about the power of predictive analytics – including why today’s models are more accurate than those of years past – in the #5in5 Podcast Predictive analytics: Improving the models.
About the author
Carl Johnson, MD, EdM, MSc. is a pediatrician trained at Boston Children’s Hospital. He completed a Medical Education fellowship at Harvard Medical School and was a faculty health services researcher at The Mount Sinai School of Medicine.
Before joining Optum Analytics he worked as a physician executive at Cerner Corporation. He is a graduate of the Mount Sinai School of Medicine in New York City and has held faculty positions at Harvard Medical School, University of California at San Francisco, The Ohio State University, and The Mount Sinai School of Medicine.
Dr. Johnson believes that healthcare can be transformed with the help of the right data. When he is not helping to transform healthcare, he can be found playing tennis, cooking, perfecting his French, taking photographs, reading historical fiction, listening to music, and watching Ohio State Football.