How Leveraging Integrated Data Creates Superior Risk Management
Good data fuels good decision-making. Businesses and leaders who rely on data to inform their strategy are proven to outperform those who do not leverage data and analytics by a factor of 23. To harness this advantage, leaders must foster a culture of data-driven decision-making, emphasizing training staff on data interpretation and identifying essential data streams. This approach empowers teams to make informed decisions with complete insights.
Once a data-driven culture is established, organizations can leverage advanced data integration tools. Solutions such as automation, business intelligence, and risk management information systems (RMIS) enable organizations to drive strategic initiatives and enhance their competitive edge. However, this requires high-quality, integrated data at the core of operations.
What do we mean by that and why does it matter?
Integrated data consolidates various datasets from different sources into a coherent format, much like assembling a puzzle. This unified view allows risk managers to gain insights, identify patterns, and make informed decisions. For instance, healthcare providers rely on a comprehensive view of patient data to deliver effective care. Similarly, risk managers use data from claims, managed care, and safety to evaluate program outcomes.
Organizations should prioritize metrics aligned with their objectives. Understanding these metrics is crucial; for example, a decrease in physical therapy costs might seem positive, but if it coincides with increased visits per claim, it could indicate deeper issues. Key risk management metrics include:
- Return to Work (RTW) Rate: Measures the reintegration of injured employees.
- Litigation Rate (Lit Rate): Aims to reduce legal disputes.
- Network Utilization: Evaluates the quality of care.
- Triage Rate: Ensures appropriate care for employees.
- Pharmacy Utilization: Monitors opioid prescriptions to prevent over-prescription.
Despite the increasing accessibility of data tools, organizations face several barriers to integration.
Barriers (and Solutions) to Integration
Successfully combining disparate sources of data into a coherent and unified format is not without its challenges. The most significant challenges include:
- Lack of Centralized Data: Many organizations lack a centralized repository for data, leading to inefficient manual entry. Solutions include using an RMIS platform, engaging in data exchanges among vendors, and integrating claims solutions.
- Multiple System Platforms: Different platforms can complicate data integration. To address this, organizations should implement data standardization practices, utilize a single source of record, and adopt integrated claims solutions.
- Data Security Concerns: With rising data security issues, risk management leaders must ensure strict protocols are in place. This involves establishing Data Protection Agreements with vendors and fostering collaboration between IT and security teams.
- Scalability Challenges: Scaling operations can introduce complexities, such as managing multiple data exchanges and storage concerns. To mitigate this, organizations should limit data sources to relevant vendors and employ a single integrated platform to streamline data intake.
By comprehensively analyzing integrated data, organizations can uncover patterns, anticipate challenges, and optimize program performance. This strategic approach enables risk managers to derive actionable insights, driving meaningful change within their programs. &