How Your PT Program can WIN with Data and Analytics

If you ask anyone to explain the players’ role in any sport, the answer will probably be “score, of course!” But ask an award-winning coach and their answer will likely be different – the end goal is to win.  

In the claims world, things are fairly similar. For many companies, the end goal is to get an injured worker back “on the field.” But companies with the best programs don’t stop there. Their goal is not just to get an employee through treatment and back on the job. The goal is to give quality care and effectively utilize available resources to get the employee back to work as soon as safely possible while keeping costs manageable…all while making strides toward better outcomes for the entire program.  

With physical therapy playing a larger role in medical treatment and overall medical management costs, companies are already scoring in multiple ways. The number of cases requiring costly surgery and dangerous prescription drugs is going down. Recovery times are also trending in a positive direction. Across the board, physical therapy has paved the way for a better and quicker return to work journey for employees.   

So, you might ask: if the shift towards physical therapy has enabled companies to score more in the short term, what does it take to win the big game? The answer? Data and analytics. Historically, a lot of the focus has mostly been on the cost of care. And while collecting data points on cost is pretty straightforward, the industry has evolved into a world where what was previously seen as “soft” savings from treatment quality and patient-centric care are becoming more tangible and as valuable as immediate discounts. To fully get there, companies must harness the power of hundreds of data points collected throughout a patient’s journey.  

What does this look like?  Here are examples of how you can use data and analytics before, during, and after treatment to help your PT program win.  

Heading to the game with a plan  

Whether it’s basketball, football, or tennis, players must come to the field prepared. The best athletes don’t just wake up and win championships. They seek the best coaches to get them in the best shape physically, mentally, and emotionally and to help them create a winning strategy.  

To put this into a claim’s perspective, let’s take construction worker Mike as an example. While working on a project, Mike fell off a scaffolding and sustained injuries in his shoulder. Following the accident, his primary treating physician found that his injuries did not require any surgery and instead, initially prescribed six sessions of physical therapy.  

Now, the easy way to score is to do a quick search of which provider is nearest to Mike and have him complete his sessions there. But winning requires a little more than this. The nearest provider may not necessarily be the right fit for Mike. To ensure that he gets the best care, a plan must be put in place even before Mike starts treating.   

One effective strategy before sending an employee to treatment is having a consultation directly with the patient. Ideally, the consultation happens with a trained PT expert. In this call, the employee is asked baseline questions about their age, gender, location, injury severity, and chronicity. It’s also important to capture the employee’s psychosocial information at this stage, including their mental and emotional state, relationship with the employer, and their current disposition towards pain and returning to work. With this data, possible return to work barriers are identified and an employee is assigned an in-house risk score of low, moderate, or high. All these inform decisions on treatment. After all, injured workers spend more time with their physical therapist than anyone else, so it’s critical that they are assigned to a provider that best fits their needs.  

In Mike’s case, the nearest provider two miles away might be the obvious choice. But if it was found that 35-year-old Mike incurred a rotator cuff injury and was experiencing depression and anxiety as a result of the injury, the best provider may perhaps be one that’s slightly farther but specializes in shoulder injuries. Another consideration is assigning Mike to a physical therapist he might feel the most comfortable with – say, someone of the same age, gender, or race. Moreover, additional data gathered from the consultation may also contribute to him being identified as a high-risk patient, informing the adjuster that this is a case that must be closely watched.  

Keeping score and making continuous adjustments 

Throughout a game, players are usually seen strategizing with their coaches. Based on how things are going, they evaluate whether to maintain the current strategy or if a change in play is required to move the game in their favor.  

Similarly, it’s important to continuously monitor a claim and leverage data and analytics throughout treatment. By aggregating data and pulling key insights, you can employ a more effective, almost instantaneous information exchange across key players in a claim. Adjusters are given actionable insights, in the right format, at the right time so that they can make strategic decisions on what to do next. Employers or anyone looking at a claim from a broader view, on the other hand, are provided with a better picture of how a case is going and is predicted to go. This ensures things stay on track and, in cases where they don’t, additional resources are tapped.   

Another effective method is comparing the status of a claim with similar cases and evidence-based clinical guidelines. Data from these cases and guidelines around comorbidities, psychosocial status, and other factors assist in predicting how long treatment will go and additional considerations that should be made. With the right information at their fingertips, a PT partner will be able to run an analysis not just within a particular employer, but across similar injuries, demographics, regions, and providers.  

Going back to the example, since initial data has shown that Mike is a high-risk patient, the adjuster might decide to have a nurse case manager reach out to Mike periodically. This would allow close monitoring of his progress. If along the way, he has reached the recommended number of sessions based on clinical guidelines but is still not fully recovered, a clinical review could be triggered. In this peer-to-peer conversation, Mike’s treatment notes will be reviewed and possible actions to make his treatment more efficient can be planned.  

Learning for what’s ahead 

In most sports, winning one match or game isn’t the end of the story – elite performers want the championship. To continuously stay at the top of their game, players and their coaches take time to review their performance, identify winning plays, and recognize areas for improvement.  

Once an individual case is closed, all data captured should be aggregated with data from other claims. From here, one can ask several questions. Was the outcome the same as what was expected? If it wasn’t, was there something unique about this patient? If so, is this something that should be factored in for future cases? What could be done to prevent incurring the same delays and additional costs?   

Answers to these questions should feedback both to the predictive model and clinical guidelines, thereby helping teams get a better understanding of how an individual patient treats, paving the way for better predictions, and future-proofing strategy. Additionally, the data collected will give us insight into how providers in the network are doing. This allows us to ensure that providers are following clinical guidelines and providing the best quality of care.  

As you gather more data from more claims, the more robust your data set becomes. And with your data and the right PT provider with proven clinical and industry experience, you can build a program that wins. 

Getting an injured employee back to work through physical therapy gets you a point on the scoreboard, that’s for sure. But in a world that values not only immediate savings but also quality outcomes and patient-centric care, the industry must take things further. Leveraging data to inform strategy before, during, and after treatment, allows you to ensure that administered care is effective, both in cost and quality. And when you learn to plan ahead, keep score, and adjust your strategy based on learnings, you win. 

# # # 

Author bio 

Aubrie Cunningham 

Senior Vice President of Pricing and Business Intelligence 

MedRisk 

2701 Renaissance Blvd 

King of Prussia, PA 19406 

acunningham@medrisknet.com  

As Senior Vice President of Pricing and Business Intelligence, Aubrie Cunningham is MedRisk’s data analytics expert. Cunningham joined the managed care company in 2014 and oversees its Business Intelligence and Analytics team as well as its Pricing and Compliance team. She was named Employee of the Year in 2019.   

Cunningham earned her bachelor’s degree in Health Science from Philadelphia’s Drexel University and attended St. Joseph’s University where she received a Master of Health Administration (MHA) with a Concentration in Health Informatics degree.