Data federation for the health insurance industry

Data federation, not big data, is the key

Although it’s hard to avoid the term “big data” these days, its pervasiveness does not make it especially helpful or even accurate. After all, so-called big data isn’t necessarily always big. It comes in all shapes and sizes. Consumer data can vary from huge to enormous, while data like income level by five-digit ZIP  code can be very small.

Big data also comes with various levels of security. Consumer data is readily available, at a price, through data vendors, while electronic medical record (EMR) data is highly sensitive and subject to the Health Insurance Portability and Accountability Act (HIPAA) privacy and data security provisions. But once the information is acquired, the key is to make it consumable by narrowing it down to the elements that provide statistically valid insight into the issue being addressed, what’s known as data federation.

Data federation is a process where data is collected from multiple independent databases and placed into a single virtual database, without ever copying or transferring the original data itself. Until recently, data federation was not a concern for health plans and health insurance brokers, because the only in depth information they needed was about a small percentage of their customers. But the new health care landscape is one where data federation can drive powerful results.

See also: How the PPACA exchange program still infuriates agents

That said, success is by no means inevitable. For one thing, health plans must embrace databases that the rest of the world has already embraced and successfully utilized. Historically, the health insurance industry has primarily used relational databases in which plans took a person’s Social Security number and modified it be used as their member ID. These databases have traditionally been impervious to information from the outside.

While health plans can maintain their relational databases, to succeed in the new marketplace requires leveraging what’s known as unstructured data — which is everything not owned by the health care plan, ranging from text mining of social media sites and DMV data to activities within payer portals. When this is done properly, the data is federated into a single virtual database and becomes actionable when making decisions related to improving the customer experience as well as the financial, clinical and operational performance of the health care plan.

A whole new ballgame with data federation

What doors swing open when the health insurance  industry takes advantage of data federation? Plenty. Go back to the Star Ratings that play such a major role in how health plans are reimbursed under Medicare Advantage. In the new value-based health care system, where outcomes and patient satisfaction are so critical, outside data is essential to reaching revenue goals because it provides the means to effectively reach and motivate members, as well as better understand, and more effectively communicate to members who have expressed dissatisfaction with the plan itself.

For example, imagine a health plan that needs to improve outcomes among its diabetic patients a few percentage points in order to achieve a Star Rating that will earn it that five percent bonus from CMS — an effort known as revenue optimization or revenue management. In that scenario, does it make sense to send out an email blast or start calling the plan’s entire patient population? No, a far more effective approach — one that the travel and retail industries already know so well — is to use data federation to tailor the right message to the right people, at the right time.

See also: 5 important wellness findings

Ultimately, health care plans need to use data federation to find and engage patients who are willing to modify and sustain a changed behavior in order to improve their own health. Again, as other industries already know well, that comes down to understanding a wealth of other factors: do they want to be contacted by text, email or a phone call? What tone of messages prompt people to respond? How frequently do they want to be contacted? In other words, it’s about understanding customer profiling and its nuances.

Agents and brokers will want to ensure that the health plans they recommend are making use of all of the data available to them, not just claims and eligibility data. Brokers need to recognize which plans see the value in leveraging data in a customer-centric approach to taking care of patients, because those are the plans that are going to result in the highest satisfaction for their customers.

Another area where the changed health care marketplace provides opportunities for plans that use data federation is in tapping into the lifetime value of their customers.

Not long ago, the concept of the lifetime value of a health care patient was unheard of. The combination of companies changing health plans almost annually and employees changing jobs often meant that the probability of an employee staying with the same health payer for several years was unlikely.

But consolidation in the industry and the establishment of health insurance exchanges means that people will likely be sticking with their health plans longer, and likely their providers as well. That not only puts a premium on good customer service, but there is now a big incentive for plans, and once again the agents and brokers who sell them, to retain and cross-sell products like life, dental, vision and disability insurance to their members. This strategy builds brand awareness and loyalty; much like Apple continues to do with computers, iPods, mobile phones, iPads and now watches.

See also: Most Gen X & Y consumers need more life insurance, but few will buy

Guess what? The analytic techniques that other industries use to pinpoint and market to high-value customers apply directly to health care.

To be clear, the health insurance industry is at the beginning of its data federation journey. But here’s the good news: those that follow and learn from the successes of the likes of banks will one day be able to speak about the olden days when customer service ratings were bad and be happy those days are long gone.