Resource Corner Blog

Analyze to Understand | Why You Need Behavioral Health Analytics


At its core, analyzing is the act of thinking deeply. Of taking in various pieces of information from multiple sources and producing results. Or analytics.

I’ll take a…

We do this every day, both at our agencies and at coffee shops – behavioral health analytics and caffeine analytics. Think about the last time you walked into Starbucks and had to decide what to order. You analyzed multiple pieces of information in less than a minute. How hungry were you? How desperately did you need caffeine? How much time did you have before you had to be at work-enough for the barista to toast a bagel or should you ask for a muffin? Your analysis told you that you were hungry, very desperate for caffeine, and had time for a bagel if you sped a little bit driving to work. You used analytics to make that final decision. 

Health Analytics-It’s a Real Major!

Analytics is important. It can streamline decision making and make business processes more efficient. More individuals are realizing this and majors and careers are being built around analytics. Every field has a need for analytics, but D’Youville College, a private college in Buffalo, NY with a prominent healthcare program, focused on health analytics when building their new program. Students in this field of study will graduate with a bachelor’s in a field that is quickly growing. They learn about a wide range of topics-from anatomy to statistical analysis-and how to share their insights with an audience.

I’m currently in my final semester of this program. This program is new at D’Youville and not very common elsewhere so I get a lot of questions about what I’m actually studying and why it’s important.

My major can very easily be divided into a health segment and an analytics segment. In the healthcare portion, we learn about the many components of the healthcare system: insurance companies, hospitals, primary care doctors, behavioral health clinics, and more. We have a basic understanding of how the human body functions. And we learn many of the terms and acronyms used to depict the health field: MU, COPE, CDS system, EHR, etc.

In the other portion of my major, we tackle analytics. We learn about the tools and resources available to us to compile data, understand it, and relate our understanding to others. Our data analysis classes focus on taking large data sets and painting a picture of what’s happening, of what the numbers are saying. When analyzing data, we’re looking for areas that need to be improved. When working in healthcare, this takes on an extra layer of importance because when you improve a process, you make it easier to help patients.

Putting It Into Practice

I’m required to complete two internships related to my major. I did my first at TenEleven Group. This behavioral health software company gave me insights into a different realm of healthcare. Jason Hurley, TenEleven’s Reporting Services and Information Strategist and author of the recent blog post Keeping It Simple | Data Presentation & Bar Graph Readability, was my supervisor. With over 100 customers, TenEleven has a lot of data. TenEleven collects data to see how well their customers are performing, and to see if they can help. I would work with Jason and other members of the TenEleven team to analyze the data and create visuals to help explain my analysis.

I worked on a project about the amount of time it takes for our customers to create a billable claim after an appointment has taken place. We divided this process into three stages:

  1. Progress Note Float, or the amount of time from when an appointment occurs to when a progress note is completed and signed by a supervisor.
  2. Create the Claim, or the amount of time from when a progress note is completed and signed by a supervisor to when a claim is created.
  3. Billing File Generation, or the amount of time from when a claim is created to when the billing file is generated and sent out.

I went through our collected data and analyzed our findings. After completing my analysis, I created visuals to represent my analytics. For example, in the agency below, their overall billing cycle lasted 26.4 days with the Billing File Generation stage taking the longest amount of time. This agency set a goal to lower their Billing File Generation period and their billing cycle as a whole. A year later, they collected new data and found that their overall Billing File Generation decreased to 8 days. However, their overall billing life-cycle went from 26.4 days to 28.4 days because their other two stages increased.

Because we used data analytics, we can measure our progress and see what is and isn’t working. With the help of this analysis, the agency can see exactly where the issue lies. This information shows them that they didn’t pay enough attention to the first two stages of the billing cycle because they were focused on decreasing the third stage. When they reassess their process again, they can use what they learned from this analysis to make sure that they focus on the billing cycle as a whole, not just parts of it.

Under Jason’s guidance, I was able to take what I learned in the classroom about painting a picture from data sets and apply it to a real-life project.

Why You Should Care

When I started this internship, I wasn’t exactly sure what behavioral health was or how broad of a topic it is. Behavioral health covers mental health and substance abuse, which in themselves contain a number of subsets. It’s the study of our emotions and how they influence our behaviors. That’s a lot. And for those of you managing or working in behavioral health clinics, trying to make sense of the data you’re pulling in on all of these different facets, it’s overwhelming.

Data analytics can help. A dedicated data analyst can turn your pile of numbers and figures into something that means something. It can turn the insane number of “missing progress note” alerts clogging your inbox into realizing that it takes 15 days for a progress note to be completed because you don’t have a structured submission process. You can’t do anything about the number of alerts clogging your inbox except get frustrated. You can do something if you know your problem is that you don’t have a structured process-create one! Data analytics makes that possible.

Taking a Look Back

Looking back on my internship at TenEleven, I learned a lot. I learned all the quintessential internship tidbits like the importance of paying attention to details. But more importantly, I saw firsthand the difference data can make. Being able to analyze data in a behavioral health setting can streamline a process so a clinician is less overworked and can offer better care. Or it can show a manager the need for a streamlined billing process. Ultimately, it enables clinics to provide better care to their clients, which should always be the end goal.

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