CASE STUDY

Improving Healthcare Outcomes With Machine Learning

$ 0 B

Hospital

0 K

Employees

At a glance

Challenge

Advancing coordination of care with a Machine Learning approach.

Result

Pariveda developed a Machine Learning model utilizing claim history and other member-related data to predict the probability of a member’s cost increase before it occurs.

Impact

The model identifies the probability of a member experiencing a 10% increase in cost as future claims are received and informs clinicians of the factors contributing to the individual’s likelihood of facing a cost increase.

Children's Hospital* is a 69-year-old world-class medical system with 10,000 employees specializing in pediatric and women’s healthcare.

Consistently ranked a top healthcare organization, Children’s Hospital administers care to over 7,500 patients daily. Supporting this effort, the hospital wanted to explore emerging technology to help guide care coordination efforts.

Managing the costs of care through predictive analytics.

Children’s Hospital generally understood cost trends for specific treatments and the factors contributing to rising costs. They hired Pariveda to build a cost prediction model to help them gain deeper insights into which members are most likely to experience cost increases to help coordinate care and develop strategic interventions.