Deductibles have grown so high in the U.S. that many patients can now no longer afford medical care despite having health insurance. Rising insurance deductibles not only present a huge obstacle to patients, but to healthcare providers too. Big data can help solve this dilemma.
The current trend is for healthcare providers to collect a patient’s insurance deductible before an office visit or procedure. That’s certainly understandable given far too few patients have, historically speaking, paid their deductibles to providers after a procedure. When large numbers of deductibles go unpaid, especially when coupled with other collection woes and new pricing pressures, providers can find themselves in significant financial trouble. On the surface, collecting deductibles beforehand is an appealing solution. Particularly when it is validated by insurers who not only applaud the tactic, but encourage it.
However, this trend has taken a nasty turn of late. Deductibles have grown so high in the U.S. that many patients can now no longer afford medical care despite having health insurance.
Deductibles are an element of any insurance product, but as deductibles have grown in recent years, a surprising percentage of people with private insurance, and especially those with lower and moderate incomes, simply do not have the resources to pay their deductibles and will either have to put off care or incur medical debt,
reports Drew Altman in an article in the Wall Street Journal.
A Kaiser Family Foundation study shows “that about a quarter of all non-elderly Americans with private insurance coverage do not have sufficient liquid assets to pay even a mid-range deductible, which at today’s rates would be $1,200 for single coverage and $2,400 for family coverage,” writes Altman.
Rising insurance deductibles not only present a huge obstacle to patients, but to healthcare providers too.
The dilemma for providers rapidly becomes whether to run the risk of not getting paid deductibles in order to treat more patients, or to stay the course on requiring deductible pre-payments and watch patients and revenues suffer as a result.
No provider can stay in business and treat patients if bankrupted by a lack of revenue. It’s doesn’t matter if that bankruptcy stemmed from collection woes or from record numbers of patients who stay away because they can’t pay, the result is the same.
So, how to solve this most perplexing and damaging problem?
How to use big data to solve the deductible dilemma
Big data is primarily thought of in healthcare circles as a means to hunt and find new cures and treatments. But it can help heal more than patients. It can help heal providers too in many ways, but in this case by spurring innovation.
There will be no single “right” answer to problems such as rising deductibles since the variables widely differ between providers. But below are a few ideas to get you started in thinking in new directions. Remember always that a good strategy is what makes big data projects successful – not the size of the data alone.
For the purpose of resolving the problem of rising deductibles, consider these ideas to spark your own ideas. Use big data to figure out feasibility and sustainability, and to predict future impact on patients and your organization. You also need to confer with your legal advisors before implementing anything.
1. Consider ways to leverage peer-to-peer lending.
Peer-to-peer lending companies could conceivably help patients get the money for their deductibles easier and faster than traditional bank loans. Perhaps you can help them pay you by establishing an arrangement through an existing peer-to-peer lender or simply by recommending patients try one. Examples of peer-to-peer (P2P) lenders are Lending Club and Prosper. These two alone have originated over $6 billion in loans to date.
You might even consider setting up a P2P lending club yourself. Considering many major banks are investing in and buying out P2Ps, you may even end up making more money later by selling it.
You can create your own P2P lending club without your organization incurring any financial risk in the process if you stick with the originate-to-distribute model, do your due diligence beforehand, and manage it well.
2. Consider ways to leverage a customer loyalty program to aid with deductible shortfalls.
One possible way would be to start a membership club where members pay a membership fee to get benefits such as guaranteed fast tracking at your organization’s urgent care centers, discounts on doctor telemedicine visits in the patient’s home, and “points” accrued through a customer loyalty program that they can exchange for “rewards.”
The money generated through this idea or something similar can be invested back into your P2P lending club, applied to cover deductibles for patients under hardship, or to invest in other ways to ensure money is available to cover deductible shortages over time.
Some people will be motivated to join just because the membership fee helps other people in need get medical treatment.
Your organization could also simply keep the money to cover any cash shortfalls down the road.
This approach may also prove valuable in combatting tactics such as this one described in an article in The Economist:
A company called Vitals approaches employees on behalf of their company’s health plan, and offers them cash rewards, and a taxi, if they agree to be treated at a cheaper provider.
3. Consider ways to leverage the sharing economy.
I wrote on what the sharing economy is and ways providers can use the sharing model to cut costs in an earlier post and in my new book, Data Divination: Big Data Strategies. But you can also use it to generate assistance on covering deductible shortfalls.
Patients, or their family members, may be able to help your organization get things done cheaper, easier, faster, and to better effect in exchange for “points” toward their deductibles. Much like Uber pairs car owners with people needing a ride for far cheaper than taxi fare, perhaps your organization can set up something similar to match patients with cars to patients who need a ride. This would be a cheap alternative to the approach of Vitals, mentioned above, saving you money in a counter move, and earning points toward the drivers' deductibles if and when they should need medical care.
There may be other ways patients can be your partners and share the load too. For example, perhaps you can award points for sharing home medical equipment once it’s no longer needed. That way the equipment can be recycled and shared with other patients, at a much reduced cost and possibly circumventing insurance altogether. Sharers get points toward their deductibles that year if they use your services; new patients get much needed medical equipment at much cheaper costs; your organization gets to keep the money from each subsequent equipment user for facilitating the sharing; and, the planet benefits from the recycling.
Note your organization doesn’t have to buy the equipment in this model. Costs associated with facilitating the sharing, some possible cleaning and/or sterilization costs, and maybe occasional storage or minor repair costs should be about all your organization would have to pay out. Be sure to compute those costs before structuring the fee for subsequent equipment users.
You can also use big data in an exploratory exercise that will help reveal possible solutions that your team may not have thought of on their own simply because the insights were not available to them before.
Remember, the beauty of big data is its ability to expose insights you didn’t have access to before. However, the real success comes from your strategy in using big data and your ability to act upon what you learn.
Good luck to you in your endeavors.
The nuviun blog is intended to contribute to discussion and stimulate debate on important issues in global digital health. The views are solely those of the author.