Do you or your employees have metabolic syndrome? Do you know what metabolic syndrome is? The term is relatively new, so don’t feel bad if you haven’t heard of it.
Metabolic syndrome is not a disease. It’s a cluster of conditions—high blood pressure, high blood sugar, excess body fat around the waist, and abnormal cholesterol or triglyceride level—that occur together, increasing your risk of heart disease, stroke, and diabetes.
Metabolic syndrome is not a disease. It’s a cluster of conditions that occur together, increasing your risk of heart disease, stroke, and diabetes.
Having just one of these conditions doesn’t mean you have metabolic syndrome. However, having any of the conditions increases your risk of serious disease. Having multiple factors can cause serious health problems.
Metabolic syndrome can increase your risk of developing:
Around 20-25% of the adult population has metabolic syndrome. But lifestyle changes can delay or even prevent the development of serious health problems if you have one or more of the factors.
150 mg/dL or higher
Using a cholesterol medicine
Cholesterol: Low Good Cholesterol (HDL)
For men: Less than 40 mg/dL
For women: Less than 50 mg/dL
Using a cholesterol medicine
High Blood PressureEither
Having blood pressure of 130/85 mm Hg or greater
Using a high blood pressure medicine
The exact cause of metabolic syndrome is not known. Many features are associated with insulin resistance, meaning that the body doesn’t use insulin efficiently to lower glucose and triglyceride levels. Insulin resistance is rooted in a combination of genetic and lifestyle factors. Lifestyle factors include diet, activity, and perhaps interrupted sleep patterns.
Usually, there are no immediate physical symptoms. Medical problems associated with metabolic syndrome develop over time. This ticking time bomb effect makes it important that employees “know their numbers.”
Offering and participating in a wellness program with health risk assessments are extremely beneficial to the long-term health of employees.
That being said, a customized, data-driven disease management program is where a high return on investment (ROI) occurs. These programs focus on the prevention of chronic illness through highly targeted care management, identified by in-depth data analysis.
Data analysis is performed on an employer’s claims data, providing the ability to drill down to the individual level to see who is at risk and how to best mitigate that risk.
Using predictive modeling, employees at risk are identified, establishing the disease burden of your members by assessing their risk of incurring medical claims based on their diagnoses and use patterns.
Metabolic syndrome is a ticking time bomb that makes it important for employees to “know their numbers.”
Each individual is assigned a risk score. The prospective risk is the chance a patient’s costs will be in the highest stratum of all employees in the next year.
According to an employer-based data set with almost 14 million members, 60% of the healthcare cost incurred were generated by 4% of the members.
Data analytics can help determine these members because it’s critical that you concentrate on the at-risk members to help keep your benefits costs from rising. It’s also imperative to analyze the data and determine who is not in that 4%, but is at risk of moving into that category in the upcoming years. Targeting those members who are at risk of moving is key to cost containment.
Employers and consultants can look at the larger employer demographic to identify tools and programs that fit specific population needs, then make data-driven decisions to establish the details and action plans of the programs. For example, you can identify certain pre-disease states in your population, then set up proper incentives to enhance engagement. If a large pocket of employees are millennials, then communicating via an app or text pushes is more effective than paper.
A robust data analytic platform enables you to identify your members with metabolic syndrome to intervene before they hit the chronic state. Then you can encourage lifestyle changes and implement or promote existing programs to disrupt the disease state progression.
You can use data analytics to measure the effectiveness of programs and interventions, easily isolating members who have a certain condition or disease, and evaluating their costs before and after implementation. You can also monitor members who engage in programs or adhere to programs or treatment plans compared to those who don’t participate in your programs.