Maturity in Motion: Coordinated to High Performing
While you may feel ready to take that next important step with your network, Taylor warns that isn’t always an easy step to take: “Becoming a High Performing Network is its own evolution,” he said. “You are moving beyond a group that merely offers support and builds consensus to an organization that approaches its objectives as a business. You may potentially assume more risk to participate in greater financial opportunities, so the stakes can be a lot higher. It’s a big transformation, and your culture may clash with it, so it’s important to be clear about your organizational objectives.”
That being said, there isn’t just one path to achieving high-performing success. Some networks may choose to continue down the evolutionary path of a shared-savings model, while others may choose to narrow their network by teaming up with payers, brokers, and employers to create a healthcare product that features its top-notch providers. Deciding what path to pursue may depend on what reimbursement models or collaborative opportunities are available to you regionally.
Related: 4 Components of a Coordinated Health Network for Care Transformation
Regardless of the path you decide to take when pursuing high performance, there are some distinctive functions of a High Performing Network to keep in mind as you set this last effort of maturity in motion. Here are four distinctive functions of a High Performing Network, that when executed correctly, can help your network achieve operational excellence:
1. Utilizing Predictive Modeling Tools
It may come as no surprise that predictive modeling tools are essential to the evolutionary process of a network maturity. As Taylor has explained, Coordinated Networks begin employing clinical interventions by looking at what’s easiest to change first, such as care gaps. Organizations can take their interventions to the next level through predictive tools that identify high-risk patient populations and provide insight into predicted cost of care. Knowing which patients may benefit from additional resources, which providers are not as cost-effective as their peers, and what potential utilization risks there are can all help a network direct its efforts where those efforts can have the biggest impact.
Episode groupers get a great deal of attention, and rightfully so, as they can help predict costs for episodes of care, like knee replacements or cardiac bypass surgeries, and provide comparison views of the cost of care for a given service stratified by physician and practice. The Johns Hopkins’ ACG System is another important predictive modeling tool, as it analyzes risk from a more population-based perspective. The Johns Hopkins ACG system is actually the only predictive modeling tool specifically tuned for Population Health Management. The system applies its algorithms to all selected patients, not just those with an episode of care.
“When it comes to gaining a comprehensive view of your population, it’s best to have more than one system at your disposal,” said Taylor. “Both types of predictive modeling tools will help you see not only where you may be at risk, but also where you may end up being at risk without successful intervention. Predictive modeling isn’t a crystal ball; nothing is 100 percent fool proof. But you’re in a much better position to understand what you need to focus on when that kind of multidimensional evaluation is at your fingertips.”
2. Cost and Utilization Analysis
Understanding utilization trends and identifying cost-savings opportunities is an important part of being a High Performing Network. Such analysis can help determine which physicians’ patients are high-utilizers of the Emergency Department, which physicians spent the most money taking care of their diabetic patients last year, and which OB/GYN physicians are outliers for performing hysterectomies for dysfunctional uterine bleeding, etc.
Networks may already be doing this on some level by using claims information provided by payers. However, claims data doesn’t paint a picture of what needs to be amended from a clinical perspective. In fact, the reports often come out so late that it’s not something that can be rectified to recover any of those wasted costs.
“A High Performing Network doesn’t solely rely on claims data to evaluate its costs,” said Taylor. “By employing a solution that can pool all these different data sets into a consumable fashion, you can have a better understanding of where you need to streamline clinical and administrative tasks as a whole. As a result, you will often have more actionable data than the payers. Using the same data aggregated and normalized from various clinical and administrative sources and the same system to analyze your past and predicted clinical, financial, and utilization outcomes can lead to highly effective proactive interventions and improvements in those outcomes.”
Continue reading
