One way healthcare providers can use big data to generate revenue fast

The search is on for the perfect balance between the new and the old, the needs of now and the promises of the future—and between line items on provider costs and investment budgets.

Before I get to the particulars on one way U.S. healthcare providers (and providers elsewhere who are paid largely by private insurers) can generate revenue fast using big data, let me first explain how the focus in current thinking went a bit askew—creating an either-or fallacy and blinding many to solving the money crunch more creatively.

Put bluntly, there is no Sophie’s Choice here. Providers need not sacrifice patient treatment now in order to improve patient care in the future or vice versa. But at first glance, this is hard to see.

Lofty finger-pointing and real world hand-wringing...

The White House recently appointed Dr. DJ Patil as the first ever Chief Data Scientist at the White House’s Office of Science and Technology Policy. He is also Deputy Chief Technology Officer for Data Policy. And, yes, his duties include working on the Administration’s Precision Medicine Initiative.

While the thinking behind these moves is largely considered admirable, many in the healthcare industry wonder what path such lofty goals will take in reality. Will it lead healthcare to all that’s great and good, or will it dangerously detract from patient needs that the industry is struggling to meet right now?

That’s a question bedeviling healthcare providers worldwide who are also struggling to harness big data and precision medicine.

The search is on for the perfect balance between the new and the old, the needs of now and the promises of the future—and between line items on provider costs and investment budgets.

Where the rub is…

Jennifer Bresnick sums up the situation nicely in a post in HealthITAnalytics:

Where will Patil and other data science experts take the industry if it commits to hopping on board the big data bus?  The centerpiece of the new precision medicine project, the creation of a large-scale DNA databank, may be a desirable development for medical researchers, genomics buffs, and pharmaceutical companies. 

But the majority of healthcare organizations aren’t primarily focused on hoarding genomes to uncover treatments for rare cancers. They want to use big data to get paid. They need help treating diabetics that come to the emergency department again and again, and coordinating care for the stroke patients that need round-the-clock monitoring. They want healthcare big data to help them prevent heart attacks, cope with the financial stresses of obesity, and ease the inevitable transition into risk-sharing and accountable care.

My, that is quite the wish list, isn’t it?

The truth is that big data can’t fix all of those things—not by itself, anyway. It can successfully address many of these issues but it isn’t a panacea. One thing it can do right now, however, is help resolve money issues.

Why it’s so hard for providers to get paid

So, let’s address the part Bresnick mentioned that interests healthcare providers the most: getting paid. The single biggest reason healthcare providers are having trouble getting paid is because the payers are often singularly focused on not paying.

Private health insurers in particular often go to great lengths to find reasons to decline claims from providers. The reason is simple. Private insurers’ true customers are their stockholders and not the patients who pay premiums every month, nor providers who the insurance industry needs in order to have a product to sell in the first place. Ergo, claims are often routinely declined, whether or not they are valid, to ensure optimum stockholder returns.

Of course, undeniably legitimate claims are paid but even those are often paid only if the provider has been exhaustively persistent. The common practice is a frustrating process that both buys time for the insurer and ensures that some claims will not be pursued by providers to the bitter end.

Meanwhile, provider resources are drained.

In addition, insurers such as Blue Cross Blue Shield of North Carolina and the U.S. Centers for Medicare & Medicaid Services (CMS) have released provider pricing lists to the public which fuels comparative price shopping and forces provider prices and margins down.

Problems with cash flow and drained resources coupled with new, evolving pricing pressures creates the industry perception that healthcare cannot afford to divert attention from current issues in order to embrace precision medicine, big data, and other future-looking initiatives.

The better course is not to summarily pursue this false choice, but to solve the initial problem at its source.

One way healthcare providers can use big data to get paid faster

There are many ways to use big data to generate more revenue and create new revenue streams. But here we’ll discuss one that is uniquely suited to speeding payment from private insurers.

First, use big data to find the claim payment and denial patterns per insurer. There is most definitely a pattern there because whether they use automation or human workers to pay or decline claims, they have a set process in place to handle that consistently. Find that pattern.

Next, develop a strategy to address each insurer’s pattern. That may be finding what documents, procedure codes, or other supporting information a particular insurer repeatedly uses as a reason to decline claims and adding that info to your claim submissions from the outset to shorten or negate those delays.

Or, it may be discovering that an insurer uses stall tactics such as routinely declining certain claims, say, three times before paying. If that’s the case, automate three claim submissions in quick succession thereby shortening the time frame of achieving approval and receiving a check.

Whatever pattern you find in claim denials, address it or counter it. Automate your strategy as much as possible to make the costs of implementation as low as possible.

Another tactic is to develop a strategy from the information you learned on each insurer that will enable you to make the costs of claim denials more expensive to the insurer than paying the claim. Insurance companies, like any business, will go the cheaper route. Make paying you the cheaper route.

Yet another tactic is to mirror the public information route insurers took when they revealed provider pricing. Perhaps your group or a nonprofit professional organization can publish which insurers are slow pays and the tactics they use to avoid paying claims? Public information will help your patients make good choices in insurance companies and plans and thereby avoid financial difficulties in their lives too.

I’m sure you’ll come up with your own ideas. One word of caution, weigh all ideas carefully before implementing them and be sure to run them past your legal advisors first.

The basic idea here is to change the game and get your pay. How exactly you choose to do that is up to you.

But that’s the beauty of big data. It can make clear the things that were hidden from you before—so that you can change the game now.

Once this drain on provider resources is plugged and cash flow is flowing again, it will be easier for providers to tend to the present, while simultaneously embracing the future in patient care. You’ll still have some challenges before you, but at least you’ll be on better financial footing.

Good luck to you in your endeavors.

The nuviun industry network is intended to contribute to discussion and stimulate debate on important issues in global digital health. The views are solely those of the author.