As plan sponsors take greater ownership of their medical coverage, the appetite to harness available data has never been greater. Here are just a few reasons why employers need to become even more sophisticated as they use the mountain of data available to them:
- A projected uptick in medical insurance costs in 2016
- The looming Cadillac tax
- An aging working population with a higher prevalence of chronic conditions
- A strong trend to self-funded plans
The good news: health and medical data are being captured, harvested and interpreted using analytic tools.
“Big Data” is defined as extremely large data sets that are analyzed to reveal patterns, trends, and associations, especially relating to human behavior and interactions. It is the foundation of the revolution we are witnessing in health care data analytics. These analytical capabilities are especially vital to employers who self-fund their medical benefits plans.
Health care analytics enable us to
- identify specific utilization patterns
- follow cost trend patterns for types of services
- benchmark burden of disease
- stratify population risks
- identify excess gaps in medical care
- understand which conditions are driving high claimant costs
Health care analytics enable us to tell a story from the data, and identify solutions. Big data can also identify discrete savings opportunities around those strategies. Big data helps employers identify strategies that fine-tune how and where wellness strategies are deployed; improve the access and delivery of care, and target specific high cost and high risk populations with solutions that address those specific populations.
How Big Data Drives Health Outcomes – 3 Case Studies
Here are some of the ways that the Willis Human Capital Practice has leveraged big data analytics to help employer clients identify discreet health outcomes strategies that meet their business goals.
Fast Food Chain Reduces Emergency Room Visits
The data: A review of utilization and cost patterns for a fast food restaurant chain operating in 24 states showed an excess rate of emergency room visits and a low rate of physician office visits when compared with normative values.
Solution: Recognizing that:
- the restaurants were in largely rural areas
- the covered population was not sophisticated in accessing health care, and
- there were a disproportionately high number of visits for routine acute care,
the restaurant chain was able to make the case to hire a third-party telemedicine vendor to improve access to care for their particular population.
Textile Manufacturer Identifies Gap in Asthma Coverage
The data: A review of gaps in care in several key conditions for a textiles manufacturer who had previously resisted optioning additional case management capabilities from their carrier revealed a high level of gaps in care specifically for asthma (but not for diabetes, hypertension or coronary artery disease). Further analysis of pharmaceutical claims revealed inefficient (and potentially ineffective) prescription patterns for inhalers and other asthma medicines.
Solution: This textiles manufacturer was able to rationalize the cost of a new carrier-delivered asthma disease management intervention program that integrated pharmacy data.
Municipality Increases Adoption of Preventive Services
The data: A review of preventive screening services for a large Midwest city government revealed that many of the services they had been promoting with their internally managed health and wellness program (i.e., mammograms, colonoscopies, immunizations) were not being fully untilized. The municipality agreed that in spite of their best efforts, they needed to be more aggressive in how they promoted and incented the utilization of preventive screening services.
Solution: This municipality was able to rationalize the cost of an onsite solution that administered these services using mobile units, and communicated results with treating providers.
Big data, smartly analyzed, offers opportunities for employers to identify strategies that work specifically for the members they cover. But this is more than just having big data — this is about the smart, thoughtful, validated way that big data is leveraged.