Webinar Recap Series: The User Analytic Journey – Path 1

In a webinar, our team of data experts sat down to discuss the three paths that make up the User Analytic Journey.

To help you understand which path will lead you to your data destination, in this three-part blog series, Nicole Belles, VP of Product here at Springbuk, describes how you may use the Springbuk platform to uncover the stories your data can tell.

Perhaps you're working through your quarterly reporting and are looking to know more about the prevalence of diabetes in your population.

Your first stop on this path is Springbuk Insights™. 

Upon logging into the platform, you'll navigate to Insights:

• Insights is a dashboard of actionable opportunity; Springbuk has investigated and enriched your data to develop population-specific Insights that appear in the platform
• You can use this data to identify problems and cost drivers, understand what can be done to address it, and action steps you can take

Within Insights, the Springbuk proprietary event prediction algorithm readily identifies members who have or are at risk of developing type 2 diabetes.

Our predictive model uncovers members who are at risk for diabetes because they have a similar clinical history to those who are already diagnosed with the disease.

• As you begin your data exploration, when reviewing your dashboards, data indicates that there are 865 members within your population who have type 2 diabetes or are at risk
• Note: it's important to remember that some of the GLP-1 drugs have been approved to treat Obesity
• With this in mind, you can check the Insight card: Obesity - Preference Sensitive Condition (more than one treatment option) - and you'll find that within those with Obesity, Insights has identified that there are 126 impacted members

Continuing on your data discovery journey, you might be interested in learning more about those who have diabetes and obesity, and ask yourself, "What is their story?"

To begin to answer this, the next stop on your path is the On-Demand Story Library:

• Springbuk’s Data Science and Methodology team, led by Janet Young, M.D., have developed a series of clinical analyses that are condition-specific
• Business users, like yourself, can quickly uncover members who have diabetes and obesity to analyze their healthcare experience for all comorbidities
• You can also drill into specific diabetic and obesity episodes to understand medical and drug costs and utilization drugs for those conditions

Here, you could pick from a variety of routes to continue your data discovery on, but for now, you'd like to focus on  the Diabetes Profile.

• Within this profile, you can see the full story being woven for your diabetic population – giving you answers to Why, What (service class)  and Where (encounters)

To learn more about the three paths of the User Analytic Journey, and which one can help you find the answers you need, read the full guide here.