South Country Health Alliance (SCHA) is a county-based health plan serving twelve rural Minnesota counties. Formed in 2001, SCHA offers seven programs to its more than 41,000 members, all of whom are Medicare and Medicaid participants. SCHA’s mission is to empower and engage its members to be as healthy as they can be, build connections with local agencies and providers who deliver quality services, and be an accountable partner to the counties they serve.
SCHA’s overall objectives were to improve key performance indicators for its population health and care management programs, and better control costs while improving quality and care coordination. SCHA leadership identified four primary obstacles to achieving these objectives:
- Inability to aggregate comprehensive data from multiple community partners, all of whom used different data types, formats, schedules and rules for utilization.
- Lack of an analytical tool that would enable greater utilization transparency and help address growing cost containment pressures.
- Poor overall population management due to health care disparities in rural communities across the twelve-county service area.
- Health care delivery was focused primarily on more expensive reactive treatment versus less costly preventative care.
The Analytic Challenge
In order to address these challenges, SCHA needed to answer key questions about its member population; for example: Where are costs being generated? What are the trends in medical and prescription drug utilization? Are there anomalies in care plans, products, age groups or service categories that require management action?
Access to the comprehensive, actionable data required to answer these types of questions was difficult to obtain for two reasons. First, numerous community partners across SCHA’s geographically dispersed service area used disparate systems and datasets, so data intake was a challenge. Second, data was delivered to SCHA in multiple formats using varying monthly schedules and inconsistent rules for utilization, making the data difficult to analyze, consume and interpret.
Working closely with HDMS, SCHA’s first step was to build an enterprise data warehouse to facilitate data gathering from disparate source systems across the twelve-county service area. This enabled data intake to be standardized, allowed for more efficient data aggregation and storage, and provisioned the stored data for analysis and reporting.
The second step was to unlock the value of the warehoused data through an HDMS solution that enriched the data, enabled robust analysis through various lenses, and supported reporting of data in a consumable format to aid interpretation and decision making. The HDMS solution addressed SCHA’s functional needs, as well as ensured ease of-use to internal staff and their community partners.
- Initial cost savings: SCHA and HDMS worked together to expedite implementation of the HDMS solution by approximately 15 percent or 37 days. As a result, project costs were reduced by approximately $300,000, allowing SCHA to redirect these resources to support its mission and operations.
- Enhanced analytical insight: Using data gathered from various feeder systems and enriched through the HDMS solution, SCHA is now able to conduct in-depth analysis into key areas of its population: uncovering where gaps in care are most prevalent, tracking utilization and cost trends by program and service type, identifying service type anomalies, and more.
For example, the population can be segmented into county-by-county analytical cohorts — such as episode treatment groups (ETGs) — enabling SCHA to identify opportunities for greater efficiencies in cost or utilization. As a result, care management programs are more effective, costs are better controlled, disparities are reduced, and overall population health improved.
- Ease and consistency of reporting: Analytical reports are produced in easy-to-consume formats that vary based on the needs of the audience while preserving patient confidentiality. Community partners in each of the twelve counties are now evaluated using common metrics. Best practices of those with favorable performance characteristics are shared with partners in other counties to improve overall quality and population health.
- Improved decision making: Because of the ease with which a variety of reports can be generated, SCHA senior leadership is able to review operations more frequently and with greater consistency. Performance metrics that are outside a specified tolerance zone or trending unfavorably are quickly identified and rapidly addressed through additional management assistance and attention.
- Long-term value: SCHA is now able to transition its health care resources from reactive treatment to more effective and cost-saving preventative care, promoting greater value and member health improvement, and enabling SCHA to better fulfill their mission.