Analytics & AI help members achieve their best health
- 3.8M Members
- $13B Revenue
The U.S. healthcare landscape can be difficult to navigate. Gaps across a care continuum, payer and provider processes, and technology create friction in patient experiences. This friction can lead to frustration, erosion of trust, and lower member engagement. A complicated, inconsistent, or broken member journey adversely affects member health, patient experience, and health outcomes. This is why Horizon BCBSNJ looks to reduce friction and improve patient outcomes across demographics and socioeconomic status.
“We want to engage our members early and often, making sure they get access to healthcare they need by making sure we’re building tools and technology that empower them in a meaningful way,” says chief data and analytics officer Vijay Venkatesan.
Analytics and data create opportunities to tailor offerings and engage all member populations and build trust in healthcare payers and providers, leading to positive outcomes.
“When looking at a risk profile of a member, there are factors outside of healthcare—components like where the member lives, whether they have access to care, and whether they need translators. These aspects, or social determinants of health, are important factors when creating packages and benefits that are appropriate and useful. It’s where analytics and data play a big role,” explains Venkatesan.
“I want to be the Google Maps, Waze, or Apple Maps for our members at every stage where they need somebody to intervene on their behalf,” shares Venkatesan.
Teradata VantageCloud on Amazon Web Services (AWS) helps Horizon BCBSNJ remove friction in the patient experience, making better use of data to empower innovation across the organization and transforming data into insights that will improve health outcomes.
Horizon BCBSNJ aims to make data and model features reusable for building cohorts of members, reducing data wrangling and spending more time on addressing member populations. This includes targeting eligible members for benefits packages, Medicare Advantage programs, disease intervention programs, or a myriad of potential initiatives from which a population of members may benefit.
“For an individual member, there may be upwards of 2,500 features. We’re building a feature and flag system that allows for building dynamic cohorts on demand. For example, we can build a cohort on demand by saying, ‘Show me all the potential people who are turning 65 next year to whom we want to advertise our Medicare Advantage program,’” explains Venkatesan.
The ability to leverage and reuse features on demand relies on VantageCloud’s Enterprise Feature Store (EFS), a curated, production-ready store of precalculated features. The EFS is model independent and significantly simplifies the journey from source data to actionable knowledge by enabling automation and reuse. By harmonizing data and creating reusable data products, stakeholders can easily search the EFS catalog for relevant features required for the intended use case. Reusability of features helps to manage data scientists’ resources more efficiently, shifting their time from data wrangling to work that really matters.
“If you’re interested in population health, you may need catalogs A, B, and C combined. If you’re doing value-based care, you may need catalogs A, C, and D combined. Each data catalog is a specific area of focus for analysis,” Venkatesan continues.
The Enterprise Feature Store is accelerating Horizon’s analytical insights and value by allowing teams to better serve members with relevant and eligible programs. Team members’ trust in data and analytics has downstream effects leading to improving member trust in their healthcare.
“Our job is to make sure that when a member wants to purchase healthcare, for whatever requirements they may have, we’re able to do that quickly and not give them 18 options that don’t make sense to them,” Venkatesan says. “This idea of building a feature and flag system, with the Enterprise Feature Store, is pretty amazing for us in terms of how we’re bringing the data and the insights together in a meaningful way.”
“Our data is organically expanding at about 18% a year. We knew that having an on-premises environment wasn’t sustainable or scalable. Between the expansion of data and the processing efficiencies, we decided to migrate to the cloud with VantageCloud on AWS,” explains Venkatesan.
As business stakeholders continue to realize value and opportunity with VantageCloud and the Enterprise Feature Store, Horizon BCBSNJ’s increase in data places increasing reliance on the scalable, accessible, and flexible cloud analytics and data platform for AI.
“VantageCloud is a means of bringing and harnessing the power of data into one platform that is reliable, scalable, and consistent, which powers our innovation and accelerates our analytics,” describes Venkatesan.
Horizon BCBSNJ’s existing cloud services rely on AWS, making the decision to move to VantageCloud on AWS easier. In migrating to VantageCloud, Horizon BCBSNJ experiences high performance and ease of access, creating platform growth—as there is no shortage of healthcare data. Users now see the value that VantageCloud can provide in driving insights and outcomes.
“Things that were taking two days to run are now finishing within minutes. We have about a 31-terabyte production environment that sees a lot of utilization and around 4,000 objects. When you look at that kind of a scale, the migration was very helpful to shrink timelines and gain efficiencies in how fast we make data available to our end consumers. It's been a very positive experience for us from that point of view,” explains Venkatesan.
The growing demand for analytics and data opens a renaissance of opportunities for Horizon BCBSNJ. With the opportunities artificial intelligence (AI) and generative AI create come challenges specific to healthcare, where trust and care decisions may be at stake.
To build ethical and trusted AI models, data must be reliable and trustworthy. Once trusted data is established, trusted AI depends on building models that are free from biases that may negatively affect the diverse socioeconomic populations Horizon BCBSNJ serves.
“You need to ensure that there’s no bias in the models you’re building. In healthcare, the hardest thing to do is to assume you can do something without knowing the implications. That’s why we’re building an AI governance framework that includes our chief privacy officer, chief legal officer, chief compliance officer, and myself to craft our constitution for AI.”
Horizon BCBSNJ aims to achieve trusted AI with data and AI models governed through oversight, regulations, and processes—all powered by VantageCloud.
“Teradata, with its history of empowering people with trusted information, will be extensible and scalable for AI use cases,” concludes Venkatesan.
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