High Impact Insights: Fast-Tracking Population Health

Effective population assessment can require steep investment from health plans, including staff training and time as well as data management initiatives and solutions. It’s a complicated, ongoing process for many plans.

Key challenges include:

1. Combining and refreshing 8-10 data sources¹

• Including administrative and EHR data, disease conditions, quality and documentation gaps, and supplemental data like social drivers of health (SDOH)
• This can be time-consuming to create and complex to manage

2. An investment of up to 18 months and $1.5 million for a 200k-member plan to²:

• Create a data warehouse bringing disparate data sources together
• Support build maintenance of comprehensive patient health profiles across member population

1. According to NCQA’s Population Health Management Roadmap for Integrated Delivery Networks, “Data integrated from a variety of sources is the best way to get a full picture of a population and a true understanding of its characteristics and needs…Having a single location for aggregated data is important to population health management.” https://www.ncqa.org/ wp-content/uploads/2019/11/20191216_PHM_ Roadmap.pdf
2. Time and cost calculations assume five to six engineers, two solution engineers, and two product analysts for a total of nine resources costing about $1.5M to work on building a data cloud platform capable of integrating various kinds of data sources (i.e., payer administrative raw data, analytics output data, cost and utilization output data, etc.). Two to three months is typical for analysts to understand the data models and perform analysis on the data.

With Inovalon Healthcare Data Lake™, the health plan was able to achieve rapid integration and analysis of disparate data sources to deliver more comprehensive member profiles, more efficiently. Armed with the right technology, they empowered their care management teams to:

• Bring together multiple data sources and provide on-demand access to the data consumers within the health plan
• Rapidly identify the most vulnerable member populations
• Empower programs across the enterprise with up-to-date information upon each administrative data refresh

Inovalon integrated medical and pharmacy claims with cost and other administrative data shared by the health plan. Modules were set up to analyze the data upon each customer data refresh, including:

• Quality and risk analytics to identify clinical quality and risk score accuracy gaps
• Johns Hopkins ACG model to identify disease conditions, utilization, ER visits, and hospitalizations
• Supplemental SDOH datasets to inform a comprehensive member profile

Analytics ran by Inovalon Healthcare Data Lake identified the health plan’s top 10% of members by utilization cost.

For these 10% of members, data on quality gaps, disease conditions, race, ethnicity, and a variety of SDOH factors (such as income and education) were quickly provided to the health plan.

The health plan identified two chronic disease conditions – Diabetes and Cardiovascular Disease – to target and were able to create comprehensive member profiles and individualized care plans for those members with open gaps.

Within 60 days of data integration, the health plan received a rapid population assessment identifying the top 10% of members accounting for over 85% of total claim costs.

This group was:

• 3X more likely to visit the ER
• 40X more likely to be admitted to the hospital

Within this group:

• 70% had 2+ chronic conditions
• 50% had cardiovascular disease
• 50% had 5+ chronic conditions
• 20% were diagnoses with diabetes

To inform member engagement and intervention efforts, the analysis isolated where members in the top 10% resided, down to 9-digit ZIP codes, based on disease conditions, eligibility and gaps for quality measures, SDOH, cost profiles, ER visits, and hospitalizations.