The Truth About Changing Healthcare Reimbursements: A Q&A with Dale Sanders

Healthcare reimbursementEditor’s Note: From time to time Health Catalyst is honored with an invitation to participate in panel discussions on healthcare. To prepare for one such event, the discussion facilitator sent us a list of fantastic questions. We approached our Senior Vice President of Strategy, Dale Sanders, with these questions, and his answers provided some unique into Health Catalyst’s approach to healthcare reimbursements, data use, and clinical improvements.

Although these questions stray a bit from our usual style, we’d like to share a few of the answers Dale provided.

And, by the way, if you have questions for us, include them as a response at the end of this blog, and we’ll try to write up an answer to your questions shortly, too.

How quickly is reimbursement changing?

Dale Sanders: Not very fast. Lots of talk, but not much happening. Eighty-nine percent of our healthcare dollars are still spent on fee-for-service encounters. There are less than five million patients affected by some form of value-based purchasing. There have been projections by several organizations, such as the Advisory Board, that we will reach 50 percent by 2020, which will be the tipping point of patient-centric quality and affordability. Even that feels too slow for my preferences. We have an informal, collegial relationship with Dr. Devi Shetty from India, sometimes called the Henry Ford of healthcare. His 29 hospitals have achieved remarkable levels of affordability and quality— $1,400 for heart valve repair, for example. He opened a hospital in the Cayman Islands and would like to attract U.S. patients and insurance companies. All of his procedures are offered at fixed-price— bundled pricing. In his negotiations with U.S. insurance companies, the insurance companies are pressuring him to unbundle his prices because their claims transaction systems are not designed to handle bundled, fixed prices. There are a few healthcare leaders in the U.S. market, such as Geisinger, who are pushing bundled and per capita pricing through their own health plans. Hopefully, those role models will stimulate faster change.

In today’s risk models, who is making the money?

DS: The risk models, notably shared savings, that are most common right now, are not very risky— we’re talking about small single digit percentages of risk for both sides (the provider and insurance companies). So, we don’t have any real risk-taking heroes right now and “making more money” is not really at stake right now. The risks are all very tentative, financially, until the experiments towards shared risk have a bit more time behind them. That said, the winners and losers are pretty evenly distributed between payers and providers, depending on two things: (1) who has the best data infrastructure for measuring quality and cost; and (2) who has the cultural and organizational structure to handle the economic model that incentivizes quality over volume. Integrated delivery networks and physician groups with robust historical data, and those whose physicians are operating on fixed salaries with bonuses that have some sort of incentive for quality, seem to be doing best because they are not motivated by patient volume and fee-for-service encounters. Plus, they have data about their own organization that allows them to project risk and strengthen their negotiating position with payers and self-funded, direct contract employers.

Who is losing the money? How are they responding?

DS: If you think of the money in terms of ROI, the roughly 330 federal ACOs have invested far more than they’ve recovered. Over $1 billion has been invested by those ACOs and, at best, only 25 percent of that has been recovered, so far. Seventy-five percent of ACOs have received zero or negative ROI. Two-thirds of the participating ACOs have declared that they will not participate in follow-on contracts unless the program is restructured to recover their investments faster. The current ACO program is incredibly complex, requiring very costly administrative overhead. The regulation is 428 pages long. That complexity and overhead makes a positive ROI even more difficult to attain. Add to that the challenges of measuring and managing quality of care for patients who are free to move in and out of an ACO at their will. The patient churn rate in some ACOs is as high as 40 percent, so long-term management of chronic diseases is almost impossible. So far, it appears that the providers are the ones who are carrying most of the risk and have lost most of the money, especially from an ROI perspective. These providers are responding by opting out of the ACO program as long as it is not simplified, and the politically motivated decision to let patients move in and out of the ACO at their discretion is not changed.

For patients who are super-high risk, how are providers taking action to prevent unnecessary admissions or readmissions? What seems to be the most successful intervention?

DS: So far, most of the attention on high-risk intervention has been focused almost exclusively on preventable readmissions, motivated by the CMS penalties. Across the country, the average readmission rate for a Medicare patient is about 17 percent. We are finding that the root causes for readmissions fall into two categories: provider-centric and patient-centric. The providers can oftentimes intervene on these high-risk patients by simply providing better discharge planning that the patients fully understand, cognitively and linguistically; prescribing and filling the patient’s first round of medication so they leave the hospital with their meds; and scheduling the first follow-up visit with the patient’s physician at the time of discharge. Those are all very simple, well-known techniques for intervention that cost literally nothing but have very big ROI for the patient. The other area of risk is patient-centric, and this is where the ACOs are really struggling because in these cases, they are now required to function like a public health system where the interventions that make a difference are all socio-economic— lifestyle changes, transportation to care, providing 24×7 home care normally provided by a family member— those sorts of things. As we expand the scope of risk intervention, enabled by predictive analytics, we are going to find that 80 percent of healthcare outcomes are attributable to socio-economic factors that most healthcare providers have never perceived as their responsibility. However, if you (the provider) are losing money in a risk-sharing contract because of poor-quality outcomes caused by socio-economic factors, those factors suddenly become your responsibility. And it’s going to take a few years to evolve this public health mentality. In the meantime, we highly encourage healthcare providers to use their own data to improve the efficiency and safety of their operations, and identify and eliminate as much waste as possible from within the four walls of their influence, while we figure out, as an industry and country, how to address these socio-economic factors without bankrupting the healthcare providers with risk-based contracts.

What kind of surprises do doctors experience when they see healthcare data for the first time? What are their responses, and do they change behaviors?

DS: The biggest surprise is usually around behaviors of their own or their peers that they thought were more evidence-based than they really are. If you ask most physicians, “How consistently do you think you practice evidence-based medicine, as currently defined by national consensus and standards bodies?,” most of them would probably respond that they practice evidence-based medicine something like 90 percent of the time. When you show them the data that indicates it’s more like 50 to 60 percent of the time, it can cause a lot of concern. We have a saying, “Data takes courage,” and it really does. Assuming that the data is accurate—and we go to great lengths to make sure that the data is accurate and high quality before releasing it to clinicians—it takes some major courage to face those numbers, admit that you are not as good as you thought you were, and then agree to improve. The other area of surprise is when we show severity-adjusted variability in care. It’s not unusual for our very unique and proprietary methods for identifying care variability to show a six to seven times difference in costs between the highest and lowest per patient and per case physicians. And the most expensive physicians on a per-case or per-patient basis sometimes have the worst quality scores and outcomes. Those care variability analytics are always very, very eye opening.

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