Great expectations: Key in the move from volume to value is focusing analytics on impactability

The discovery of fire. The invention of the printing press. Manned flight. Throughout history there have been developments that significantly altered the world as we knew it, creating both concerns and opportunities.

To that list you can add the expectations surrounding the transition from traditional volume-based healthcare to the value-based model – if for no other reason than maintaining good health is core to everything else we do in life.

Make no mistake; this is no minor shift, especially at the hospital level. Whether a hospital is non-profit or for-profit, it must optimize revenue if it wants to continue delivering healthcare services to the community. That's just basic business.

Under the volume-based model, hospitals are incented to optimize around heads in beds and patients on the operating room table, with a particular emphasis on lucrative orthopedic and cardiac procedures. They are focused on drawing oncology patients and providing imaging services, all which deliver recurring revenue.

Traditionally, what rarely enters the conversation is the likelihood that the care being delivered will have enough of an impact on the patient's condition to deliver long-term benefits. Will the care make a measurable difference compared to not doing the care? If an intervention is performed on someone who will continue to deteriorate rapidly anyway, it may be of questionable value. In medical circles, this is referred to as "futile care."

That is what the value-based model seeks to change. Rather than simply paying for procedures or services rendered, reimbursement is instead focused on measures such as outcomes and patient satisfaction.

In fact, under the new value-based payment rules from the Centers for Medicare and Medicaid Services (CMS), 20 percent of the payment is based on quality based clinical processes, while 30 percent is based on outcomes, 30 percent for the patient experience and 20 percent for efficiency. Given that CMS is the single largest purchaser of healthcare in the U.S., it is definitely in a position to heavily influence the way payment is structured throughout the industry.

To succeed in this new world, providers and clinicians will need to learn to think differently. This includes the way they use analytics. Many organizations today are already using analytics to identify what needs to be done in healthcare, e.g., close gaps in care for certain patients or populations. As the focus shifts to value-based care, however, they're going to need to look deeper to determine what measurable impact taking those actions will have on those patients.

That means they will need to stratify patients on their impactability as well the severity of their condition. How likely will the patient be able to benefit from care? Hospitals will need to take into account which patients need an intervention, and if that patient can be helped by that intervention.

Another area of concern is the hospital discharge. This is a risky time for many patients because there are so many moving parts. Hospitals will need to know where to spend the expensive effort to create a smooth discharge based on known measured risk and impactability. Without these data-derived stratifications the care tends to be the same for all and these current untargeted interventions help contribute to the unsustainable increases in healthcare costs.

In a value-based environment – especially one where the emphasis is shifting from providing acute care to promoting health and wellness – hospitals must concentrate their efforts where they can actually change the outcome. Analytics can show which patients will not do well with usual care so additional systems can be put in place to optimize risk and measured outcomes.

Predictive analytics that incorporate population health management data and the patient's individual history, as well as behavioral and socioeconomic factors, can help clinicians and health systems make better decisions to ensure they are dedicating their limited resources where they can do the most good while thriving under the value-based model. These types of analytics can help providers determine how to deploy their resources more efficiently and effectively. For example, patients who typically use a lot of hospital resources, have many gaps in care and/or have a high percentage of unfilled prescriptions may have a low level of medical literacy. What they may need more than additional treatments is a targeted intervention on how to properly care for the chronic health issues they are facing.

Another way hospitals can take advantage of these deeper predictive analytics is by using them to minimize the risk of futile care, or applying resources that won't make a difference to patients who are at the end of life. Knowing who those patients are will avoid expending resources on interventions that won't change the outcomes, and may lead to an end-of-life conversation that serves patient needs more effectively than more medications or procedures. It will also allow hospitals to focus their resources where they can make a difference while meeting value-based care requirements.

On the physician side, predictive analytics can help spot outliers such as surgeons performing more spinal procedures than should be the norm, or physicians whose patients have high 30-day readmission rates. While there may be a good reason for it, you won't know until you investigate.

Analytics can also identify physicians who are not following evidence-based care standards. Hospitals will then need to take the hard step of measuring how their physicians' care meets those standards for the physicians to remain fully credentialed. Improvement systems and measurement systems will need to be enhanced to accomplish this. It will no longer be acceptable that quality of care is an afterthought because the physician does 325 spine cases a year. Through this process, hospitals can build a culture that is focused on improving care quality while simultaneously decreasing costs.

Clearly, the rules in healthcare are changing and hospitals much change with them. It's no longer about generating high volume of services. Instead, the future will be based on developing a culture that focuses on applying the right resources where they will have the greatest impact.

It's disruptive for sure. But all great innovations are.

Kevin Keck, MD, FACP, is the Chief Medical Officer at SCIO Health Analytics, where he leads the Clinical Analytics development team that assesses the leakage and the impact of quality and cost in Provider Analytics. Previously, he was the CMO of Providence Health Plan and chief of Medicine at Kaiser Permanente.

The views, opinions and positions expressed within these guest posts are those of the author alone and do not represent those of Becker's Hospital Review/Becker's Healthcare. The accuracy, completeness and validity of any statements made within this article are not guaranteed. We accept no liability for any errors, omissions or representations. The copyright of this content belongs to the author and any liability with regards to infringement of intellectual property rights remains with them.​

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