Updated June 2019
Jennifer Atkins, Vice President, Network Solutions, Blue Cross Blue Shield Association

When you make an important business decision, you are most likely basing that decision on data: sales, ROI, depreciation, value—these are all data-driven aspects of a sound decision-making process. Decision-making in healthcare is no different, and the power of data is transforming the way we look at care delivery and network performance.  

Fueling higher-performing networks

In recent years, there have been unprecedented advancements in capturing and using data, and today, data is the foundation for fueling higher-performing healthcare. Robust data and analytics unlock collaborative opportunities between payers and providers and drive more informed consumer decisions, optimizing value-based healthcare. They also guide the design and use of supporting networks within benefit programs, which are increasingly tailored to best balance objectives around healthcare quality, cost and access. 

More ways data is impacting healthcare

Data is foundational to the improvement of care delivery performance and utilization. Blue Cross and Blue Shield (BCBS) companies, for instance, share data with providers to support more objective member referrals, improve care coordination across settings, understand gaps in care, identify at-risk patients, focus care management and target health interventions. 

Identifying risk factors

Predictive modeling further enhances effective collaboration between providers and payers. For example, data-driven models can help identify risk factors and predict hospital readmissions for patients with chronic diseases like diabetes to support preventive care and improve case management processes. The richer the data, the more powerful the model can be at uncovering accurate predictors that have the potential to keep your employees healthier and out of the hospital.

Balancing healthcare quality, cost and access

The reality is that there isn’t a one-size-fits-all solution when it comes to balancing quality, cost and access. Data can be analyzed to understand and target employee care needs across geographies. Sophisticated analytics can be used to model network and benefit designs and to project utilization scenarios, predicting total cost savings that can be achieved by various design levers. But achieving an accurate prediction requires validity and reliability that stem from an appropriate depth and breadth of data from case examples. 

Modeling of this nature can support advanced and tailored solutions, such as tiered networks and benefits. These solutions are designed to shift utilization to higher-performing providers and require a rigorous application of deep claims data and national industry benchmarks to sufficiently evaluate provider performance.

Using data to find the right healthcare solution

Data-driven network designs can enable you to guide your employees to higher-performing providers while providing optimal accessibility to care that meets their needs. These networks can also reduce your employees’ healthcare expenses and positively impact your organization’s bottom line. As such, ensuring that comprehensive data is put to work when designing or determining the right solution for your business is essential.