Pop Analyzer: Stratify

The Health Catalyst Pop Analyzer™: Stratify provides a seamless process for stratifying populations using multiple pre-defined, easily customized populations and predictive risk models as building blocks. The speedy data lifecycle takes the stratified population data from ad-hoc analysis and development to an integrated analytic workflow—supported by the Data Operating System (DOS™)—within minutes, not days.

The Population Builder: Stratification Module enables you to bring in predefined populations, such as the high cancer population shown in this image.

The problem

Identifying the right patients for population health interventions is critical to any population health initiative. Not having an accurate, transparent, and flexible stratification model, organizations sometimes struggle to maximize the impact their population health team has on the overall populations they manage. In addition, teams don’t understand the algorithm that defines the population—and they can’t modify population definitions—leaving them unable to confidently demonstrate that they are identifying the right patients.

In addition, it can take months to properly create complex stratification algorithms that truly use analytics to target the right patients for the right interventions. According to a recent study, analysts spend over 50% of their time completing a non-analytics task (preparing SQL/ETL data, repeating tasks, and performing simple tasks) instead of focusing on high-impact analytics like targeted stratification.

Our approach

Stratify Data Collection enables anyone within an organization to efficiently and accurately identify patient groups based on pre-defined—yet easy-to-customize—populations and risk algorithms. Members of the care team have complete transparency into the algorithm behind population definitions—and they can easily adjust those definitions on the fly. Stratify also provides the architecture and toolkit to integrate the stratified populations into the population health workflow.

Benefits and features

• Increase efficiency, transparency, and flexibility. Gain easy access for non-SQL experts to customize and generate stratified patient lists, reducing the IT reporting burden, increasing effectiveness of care coordination, and providing clinicians with direct access to data.

• Save time. A growing list of pre-defined content, including more than 6,000 value sets, 21 predefined chronic condition registries, ED utilization (integrated claims and clinical data), transitions of care, and predictive risk models—that organizations can mix and match to identify populations ready for population health interventions. 

• Build trust. Shareable, transparent logic provides actionable data to prepare identified populations for population health interventions. 

• Avoid data silos and ineffective decision making. Data-informed decision making goes well beyond the capabilities of any single EHR—including comprehensive patient data from more than 300 sources in DOS and integrated claims and clinical data.

• Grow your ecosystem – Seamless integration with the Health Catalyst ecosystem of workflow and analytic tools drives a complete care management program.

For more information, see the Pop Analyzer data sheet.

Use cases

• A chief population health officer reviews value-based contract performance and finds that a large percentage of the cost and utilization is due to comorbid patients, primarily from seven complex chronic conditions. After implementing the Stratify Data Collection, he can quickly identify and target the specific population based on predefined chronic condition populations for the care management team to enroll patients in a chronic care management program.
• A care management director needs to improve two problem areas identified in the contract performance report: high ED utilization and high readmission rate. After an initial review, he identifies that many patients have out-of-network ED visits. Using the integrated claims and clinical data in the Stratify Data Collection, he can quickly identify the right population and publish it for care managers to begin outreach.
• An analyst and clinician work together to define populations for care management programs and share insights with leadership. The analyst spends significant time repeating tasks like integrating population definitions and developing basic results. The clinician isn’t getting the information she needs quickly enough—resulting in missed opportunities to share results and trending with leadership. With the Stratify Data Collection, the analyst can immediately normalize commonly used populations and make them available for rapid use in the Care Management Suite. The clinician can also centrally define and govern population definitions.