Baptist Health: Bridging the Gap Between Patient Care and Population Health
Providers
ACO
Artificial Intelligence
Data & Analytics
Ascent
2 min
About the Customer
Baptist Health is Arkansas’ largest not-for-profit health care system. They encompass hospitals, primary and specialty clinics, urgent care centers, and physician groups, across Arkansas and Eastern Oklahoma.
Problem
Limited cost and utilization insights hindered network performance assessment
Outcome
Centralized clinical and claims data improved cost and performance visibility
Baptist Health sought to complement its patient-level view with a clearer understanding of performance across entire populations. Although providers could monitor individual outcomes, limited visibility into population-level cost and utilization drivers made it difficult to identify which patients required greater attention.
Baptist Health
Baptist Health • Little Rock, AR
12
hospitals managed across Arkansas and eastern Oklahoma
300+
points of care, including 75+ primary and specialty care clinics
12,000+
employees working under the system
Building a scalable analytics foundation
Riley Lipschitz, Chief Medical Officer, and Brett Bailey, Director of Clinical Analytics, explain how Baptist Health used Arcadia’s data platform to gain a more comprehensive view of its patient populations. This gave its teams a granular understanding of performance while establishing an analytical infrastructure they could continue to build upon.
Baptist Health first applied this approach to its own health plan. The organization can now extend the same foundation to additional populations, including the Medicare Shared Savings Program and Medicare Advantage.
Looking ahead, Lipschitz and Bailey see opportunities to use AI and other technologies to operate more efficiently and better serve Baptist Health’s patient populations.
Lessons Learned
Managing patients at a personal level is essential, but viewing data at a population level allows organizations to better understand where there are gaps in care.
Building analytical infrastructure that can be reused across multiple populations is more efficient than constantly trying to build new foundations.
AI tools are useful to increase efficiency, but deeper analytical thinking must support it to provide organizational direction.
“Population health is like trying to do the right thing for the right patient at the right time.”
Customer Outcomes
Data at a finer granularity identified performance issues and their root causes
Leveraged data to engage clinicians in evaluating their care delivery performance
Built a reusable analytical infrastructure they could apply to other patient populations
The results described are specific to the customer’s data environment, technology stack, and operational context. Outcomes vary by factors such as implementation approach, data quality, organization size, and care model type. Actual savings and performance will depend on each customer’s configuration and use of Arcadia’s platform. Arcadia does not guarantee similar results for any customer.