Guest Column | June 15, 2020

Collaboration, Coordination, And Data Can Solve Many Healthcare Challenges

By Mark Buffington, BIP Capital

Doctor Data Healthcare

There is one thing about American healthcare on which most of us agree: It needs work. Stories from friends about an outrageously priced prescription drug or a hometown hospital closing its doors put a face on the facts: U.S. per capita healthcare spending is almost twice the average of other wealthy, developed countries, yet the United States performs poorly in common health metrics like life expectancy and unmanaged diabetes.1

I’m not the only American who watches with frustration as politicians discuss their views on overhauling our current system. If there is a clear bipartisan path to making American healthcare better and more affordable, no one has found it yet.

Still, as an investor in healthcare technology companies, I’m more hopeful than ever that real improvements can be made in our healthcare system. Improvements that rely more on communication, collaboration, and coordination between various segments of the healthcare industry than on one silver bullet that will automatically make everything better.

Data’s Potential To Solve Healthcare Challenges

What is the source of my hope? It’s my job to watch the industry closely, and I’ve seen a remarkable trend emerging lately: Both the public and the private sectors have discovered the potential of data to solve healthcare challenges. Data silos that already exist today can be connected with new technology to improve patient outcomes and reduce costs. From our perspective, making these connections is “low-hanging fruit” that can go a long way in saving money and improving outcomes—if we put our minds to it.

The low-hanging fruit includes such things as political action to require Electronic Medical Records (EMRs) to accommodate easy, standardized transferability of healthcare data. Currently, EMRs “hold hostage” enormously valuable data that should be allowed to move safely—and fluidly—to multiple providers of choice for true interoperability.

This low-hanging fruit also includes clear public benchmarking of all providers in the areas of cost and quality. One of the metrics we have been studying for the past few years is the Total Cost of Care (TCOC) through the care continuum for various diseases. There is no justifiable reason that the TCOC for similar cases of heart disease, diabetes, or even physical therapy should vary by as much as 250 percent—but it does. We would never buy a car of the same make and model from a dealer who is offering that car for 2.5x the cost of another dealer down the street, but that is exactly what is happening in healthcare.

A recent study in Georgia uncovered one prime example of the problem. Here’s the story:

Georgia Eyes Big Medicaid Savings With The Right Data

“Just using data better might save the state $600 million in what it spends on publicly funded medical care.” That was the first line of an article2 in the September 5, 2019, edition of The Atlanta Journal-Constitution, and it was good news. Data offers us enormous opportunities to improve patient outcomes and reduce costs if we can tap into it effectively.

How? Like other states, Georgia’s Medicaid program pays for millions of dollars of post-acute care—care provided by therapists, home health agencies, skilled nursing facilities, long-term acute care facilities, hospices, and other providers after an indigent Medicaid patient has been discharged from a hospital. Those providers are usually recommended by hospital staff with few if any restrictions and little data regarding who might provide care more economically than others of equal quality.

Currently, the state has no control over how hospitals and patients choose among the options for post-acute care. By the same token, there are no price incentives for a hospital to pick the lower-cost, equal-quality option to recommend to patients. In many cases, hospitals simply don’t know all the options.

Data can improve the scenario.

Georgia commissioned a study on this issue because it wanted to know how its post-acute Medicaid dollars were spent. Working with a data analytics company, a state government task force reviewed the company’s proprietary data showing all the post-acute care options for Medicaid patients’ diseases or conditions, listing them on a county-by-county basis and showing cost and quality data (hospital readmission rates, morbidity rates, etc.) for each.

Data analytics found that if Georgia picked lower-cost, post-acute care providers that were of equal quality to the ones the patients used, the state would have saved $600 million in Medicaid expenditures. That’s a big eye-opener not only for Georgia but for anyone interested in ways to cut expenses dramatically from our nation’s healthcare system.

Think about it. If each state in the United States saved $600 million using this approach for cutting Medicaid expenses, that’s $30 billion. And that’s just for Medicaid, which provides coverage for about 30 percent of Americans. A similar study has not been commissioned regarding Medicare post-acute expenses, but we are 100 percent convinced the savings would be even more striking there. Medicare’s fee-for-service, post-acute care expenditures are close to $60 billion, according to a comprehensive 2018 report on healthcare spending and Medicare by the Medicare Payment Advisory Commission.3

Do we support Georgia’s study and encourage the state to put the practice into action? You bet. And we are thrilled that state government is on the verge of making the cost-cutting initiative a reality. We know of keen interest from at least 15 other states in using Georgia’s work as a case study for saving money, improving access to care, and maintaining quality in their own Medicaid programs.

Have we invested in the data analytics company that made all those expenditures transparent to the state task force through a relatively simple analysis? Yes, we have.

The company fits one of our prime criteria for a healthcare technology company that shows promise and sustainability: It has a solution that builds bridges, that tears down data silos, and reveals relatively easy ways to take significant bloat from our healthcare system by building care pathways based on real data. We predict we’ll see dynamic growth in tech-enabled companies that can perform a similar service over the coming years.

Data Sharing For Better Cancer Care

Here’s another example of how data sharing can make an enormous difference in our healthcare system—not only from a cost perspective but from a very personal one, as well.

A business partner’s wife discovered she had ovarian cancer in her fifth month of pregnancy. She went to a local hospital and the prescription was to terminate the pregnancy and have a full hysterectomy. A second opinion in the same city confirmed the diagnosis and treatment plan. So, my partner and his wife traveled nearly a thousand miles to a noted cancer center in another state, where they got a much different opinion.

The hospital had developed procedures that allowed the baby to be carried to term. After a healthy delivery, the hospital performed a hysterectomy with no risk of the cancer spreading. Because the couple had taken the time and made the investment to investigate other treatment options, the story has a happy ending.

Why did the couple’s local physicians not know about the procedures and techniques that made the happy ending possible? At any cancer center, it’s difficult for physicians to keep up with best practices and emerging technologies when they’re caring for sick people every day. The physicians are not bad people. They’re just busy, and up to now, there hasn’t been a technology system available that would support them in their quest to stay up to date.

One would think the emergence of EMR technology would have laid the groundwork for sharing this vital information between hospitals. As I mentioned earlier, that’s not the case. Various EMR platforms have created a massively siloed healthcare system in which there is little incentive for open sharing of information with anyone who uses a different EMR platform. As a result, patients like my business partner and his wife must pay the price—or take the initiative to scale the walls of another silo on their own.

The good news is that a new technology platform exists for best cancer treatment practices to be shared across systems to keep tumor boards, the multidisciplinary teams that review and develop treatment plans for patients, abreast of new practices that have shown success. It’s an exciting development because we all know how expensive cancer treatments can be. Data sharing in this environment can improve the quality of care and reduce morbidity rates. It also can bring enormous cost savings by reducing the rate of recurrence when the cancer is treated right the first time.

Again, these “low-hanging fruit” problems are easily solvable if we put the focus on empowering people with information. It’s the reason our company also has invested in the firm that has developed the technology platform for sharing the best cancer treatment practices among providers. We firmly believe that this kind of information sharing is where our brightest future lies when it comes to healthcare in the United States.

Prior Authorization Burden Another Prime Target

We also see big opportunities in work being done today to simplify how healthcare providers connect with insurance carriers so that the prior authorization process is faster and more economical, without time-consuming paperwork, phone calls, and faxes that slow down the process—and add costs.

According to a survey by the American Medical Association, approximately 92 percent of physicians said that prior authorizations have a negative impact on clinical outcomes for patients, and 78 percent reported that prior authorizations can sometimes, often, or always result in patients stopping a recommended course of treatment.4

The study also revealed that 34 percent of physicians rely on staff who work exclusively on the data entry and other manual tasks associated with prior authorization. According to a Health Affairs study, the average dollar equivalent per physician is $68,274 per year to interact with health plans, a total cost of up to $31 billion annually.5 It’s another area ripe for technology to make better connections between payers and providers, take much of the manual effort out of the equation, and cut billions from our national healthcare costs.

Access For All

I’m often asked about the call by some political candidates today for “Medicare for All.” My response is that I believe in “Access for All.” Creating systems to cut unnecessary costs from healthcare is one way to achieve it.

As I travel around the country, I am constantly amazed at how many people immediately try to figure out what they disagree on. I’m also amazed to see how much common ground we have once we cut through the clutter of typical political discourse. Yet we can’t seem to be able to push reasonable, thoughtful solutions forward. That’s a sad impasse, but I believe it’s not an impenetrable one.

In America today, healthcare is a political issue. Yet there are many ways we can work collectively—beyond politics—to make healthcare less costly without requiring a total rebuild of our healthcare system. Technology is available today to support the quest. In my opinion, it holds the key to making real improvements in the quality and cost of U.S. healthcare, no matter how heated the political debate becomes.

About The Author

Mark Buffington is cofounder and CEO of BIP Capital headquartered in Atlanta.


1. Peter G. Peterson Foundation. How Does the U.S. Healthcare System Compare to Other Countries? July 22, 2019. Retrieved Feb. 19, 2020, from

2.The Atlanta Journal-Constitution. Companies Pitch Georgia Senate Health Panel on Potential for Savings. Sept. 5, 2019. Retrieved Feb. 19, 2020, from

3. Medicare Payment Advisory Commission. Health Care Spending and the Medicare Program: A Data Book. June 2018. Retrieved Feb. 19, 2020, from

4. American Medical Association press release. Survey: Patient Clinical Outcomes Shortchanged by Prior Authorization. March 19, 2018. Retrieved Feb. 19, 2020, from

5. Center for Health Innovation & Implementation Science. The Prior Authorization Burden in Healthcare. July 26, 2018. Retrieved Feb. 19, 2020, from