CASE STUDY
Improving Healthcare Outcomes With Machine Learning
Hospital
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.
The Challenge
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.
The Result
How Pariveda helped improve health outcomes:
- 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.
The Impact
With Pariveda’s model, Children's Hospital helps parents and doctors understand and manage healthcare costs.
With Pariveda’s model, Children's Hospital helps parents and doctors understand and manage healthcare costs.
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Healthcare & Life Sciences
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