UnityPoint Health

UnityPoint Health had volumes of clinical and claims data but lacked consistent data definitions required to support measurement of outcomes and care quality across all care settings. The organization could not effectively segment and risk-stratify patients at risk of increased utilization due to missing predictive models. This limited its ability to drive success in risk-based contracts, including shared savings programs.

UnityPoint Accountable Care deployed the Health Catalyst Data Operating System (DOS™) platform to create a single source of truth across disparate systems. The team built predictive models that risk-stratify patients into low, rising, and high groupings to forecast inpatient admission, ED utilization, 30-day readmission, and missed outpatient visits. Care managers leverage utilization risk scores and event monitoring to perform targeted post-acute-care outreach and modify care plans.

Over the last 10 years, UnityPoint Health has averaged $31M in annual shared savings through high-quality measure performance and effective utilization management. Post-discharge improvements include 70% of discharged patients receiving care manager outreach, resulting in 3,000 more office visits and 900 more home health visits. ED visits were reduced by 40% relative through effective ambulatory care, and SNF length of stay dropped by 25% relative.

• Embedding analytics directly into strategic planning enables clinicians and business leaders to make data-informed decisions at the point of care, including during annual wellness visits.
• Risk-stratifying patients with predictive models allows care managers to focus outreach on high- and rising-risk patients, reducing unnecessary utilization.
• Consistent data definitions across all care settings are a prerequisite for reliable quality measurement and success in value-based contracts.