Healthcare Payers: Navigating the Road to Digital Transformation

Digital healthcare concept, man hand using smartphone and virtual screen.

Today, the CIOs of healthcare payer organizations have a new mission: put member health front and center. And to do this, payer organizations need to transform their data and analytics efforts.

Payers that have successful data strategies can achieve better healthcare outcomes for their members while lowering their claims costs. They can ensure standards of care and making a direct link between performance and reimbursements.

The rise of healthcare-related IoT intelligent devices adds to the diversity and complexity of datasets that have the potential to improve care quality and patient outcomes. This data is valuable to members and payers, but it must be managed and governed appropriately.

As Julie Hill, an Anthem Blue Cross Board Member, stated, “It no longer works to have seven platforms for collecting metrics around performance. The opportunity for us today is to ‘mine the metadata for healthcare outcomes.’ This is a huge cultural shift, but it is also a moral imperative and increasingly, an economic imperative.”

Healthcare Payers Struggle with Data Integration

While the potential for a successful value-based care model rests on data and analytics, payers have struggled to overcome the data integration complexities inherent in creating a unified view of members — the foundation of value-based care.

Payers must pull together an enormous volume and variety of information from multiple sources including claims, patient and pharmacy records, IoT data, social media activity, and clinical data. The challenges are technical — aggregating data from a variety of systems — but also cultural. Clinical data sits on the healthcare provider side of the fence. To use data effectively, payers and providers must work together much more closely than in a fee-for-service arrangement. They must work as partners, not adversaries.

Data Governance Takes on Heightened Importance

At the mention of data governance, most people think “compliance.” But compliance is not the only vital component of robust data governance. Certainly, payers shoulder a heavy regulatory burden. But data also plays a crucial role in the competitive survival of a payer organization. That’s why several healthcare payers have hired chief data officers (CDOs).

Typically CDOs have much broader responsibilities than ensuring compliance. In fact, their primary mission is ensuring the quality and integrity of an organization’s data assets — especially member data, the crown jewels. Moreover, payers need to aggregate data to drive population health and pay-for-performance arrangements, which requires a unified view across HL7 classifications for health and medical transactions.

But to be clear, payer CDOs are focused on changing the quality of healthcare. One payer said they want to prevent the following: a patient goes in for surgery, they return home, and then they return for care. Could a drug or home healthcare have prevented this consequence? The answer to this can be found in data and in particular driving provider process improvement.

The opportunity to drive the above change will occur as payers create trustworthy data. Payers need data that supports the predictive and prescriptive analytical models that help provide quality healthcare.

According to one payer organization, “This is the only way to drive lower costs and recoup more money.”

But without good data hygiene, it’s impossible to build world-class analytics. Instead, data scientists function more like data janitors — manually finding and reconciling data that is fragmented, duplicated, inconsistent, inaccurate and incomplete.

As one payer CDO put it, “We make nothing. There are no widgets like GE. Data is what we create. If we are intelligent about the data that we create, then we can make data-driven decisions. If we create better algorithms, then we can be more efficient.”

Other executives at payer organizations say they want to create a seamless experience by creating an integrated delivery system. We want to be person-centric — to be a personal healthcare advocate. At the same time, we want to manage the financial risk of healthcare.” All of this is built upon better data.

The Strategic Balance: Data Offense and Data Defense

In an article for the Harvard Business Review, Leandro DalleMule and Tom Davenport describe a strategic framework that divides data activities into data offense and defense. As they explain it, data defense and offense have distinct objectives that require different skill sets. Data defense minimizes downside risk. Defense activities include ensuring compliance, detecting fraud, preventing theft, and making sure data is correct, consistent, and trustworthy as it flows through the data supply chain.

Data offense optimizes revenue, profitability, and customer satisfaction. Offense activities include data modeling and analysis that combines internal and external data to support planning and decision-making.

Healthcare payers need an approach to data management that combines data offense and defense. It should be able to extract maximum business value from data without incurring unacceptable risk.

Such a strategy should offer core defense capabilities around data integration, quality, governance and security, delivered on-premise and in the cloud. It should allow for collaborative data preparation and enable analysts to quickly curate and share data, while automated, rule-based governance ensures standardization and enforcement of data taxonomies.

On the offense side, data scientists and data explorers should be able to discover data relationships and build advanced analytics models on their own via self-service analytics. This will accelerate the transition to patient- and population-centric care and drive better healthcare outcomes and tangible cost reduction.

For most payer organizations, adopting an approach that combines data offense and defense means reallocating resources from legacy systems. The funds invested in maintaining these environments — including hardware, storage, applications, and network infrastructure — must gradually be applied to data architecture and application modernization.

In the words of one payer CDO, “We want a seamless, integrated healthcare delivery system — connected to providers and employers. We want to manage the financial risk of healthcare while we market innovative initiatives to our members. And we want to speak with one voice.”

And the place to start is with the data.

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