The Power of Predictive Modeling

 

 

Imagine a risk assessment tool that enables you to predict who is likely to use to have major health problems.  Imagine a data management tool that helps companies to develop programs to improve the health of their employees.  Imagine a needs assessment tool that helps those employees to improve their health.  Predictive modeling is that tool.

 

Predictive modeling is the use of computer software applications to analyze likelihoods.  For years it has been used in the fields of archaeology, anthropology, biology and other sciences.  It’s commonly used to predict the likelihood of air pollution, earthquakes, hurricanes and now, terrorist attacks.  Predictive modeling is used to analyze trends in shoplifting, consumer behavior, credit risk, cell phone usage, credit card balances and college enrollment. 

 

Now health plans sponsored by insurance carriers and employers utilize predictive modeling to create and implement programs to improve the health of their health plan members.   More than a quarter of the cost of employee benefits goes to health care.  As health care costs continue to rise, employers are faced with a dilemma.  They can shift more of the cost to their employees and risk alienating or losing their workforce, or they can find creative ways to help stabilize or reduce health care costs of employees.  Many employers choose the creative path by working with their health plans that use predictive modeling.

 

Health insurers have moved beyond traditional underwriting and actuarial techniques like trend analysis.  Advanced mathematical models and sophisticated computer technology make predictive modeling a highly desirable tool for health plans.  Predictive modeling has the ability to weigh complex variables using multiple statistical measures.  It provides a more accurate picture of data than analysis made through traditional processes. It allows companies to gain a clear picture of the cost drivers in their health plans.  Why is this so important?

 

By understanding who is likely to need health care the most, health plan insurers can price their premiums more effectively.  They can also staff offices and call centers more efficiently to save money and better serve customers.  Some insurance companies determine marketing and growth strategies by using the data to examine the nature of the employment pool.  Predictive modeling has become an effective, multi-purpose tool for the health insurance industry.

 

Employers reap the benefits of predictive modeling as well.  Companies that combine needs assessments with predictive modeling are in a better position to help improve the health of their employees and their families.  This, in turn, promotes low absenteeism, high productivity, positive morale and reduced short-term disability and insurance costs.  Companies can use predictive modeling data to determine their needs for wellness and disease management programs for their employees.  Employers who have a clear picture of employee health can develop effective programs to address diseases such as diabetes, asthma and depression.  These types of programs have the added benefit of building a positive image of the company in the minds of the employees.

 

Predictive modeling makes good sense for employees, too.  We know that medical problems can be attributed to lifestyle choices.  These same disease management programs encourage proper diet and exercise to ward off potential costly diseases.  Wellness programs help us lower our blood pressure, lose weight, quit smoking and reduce our stress levels.

 

Companies that assist their employees in establishing health-care goals increase the likelihood of a program’s success.  Individuals who have easy access to such programs are more likely to use them.  Employer-sponsored programs can positively impact lifestyle decisions and ultimately, the physical, emotional and mental well-being of employees.  It’s a winning situation for health plan insurers, employers and employees.

 

Predictive modeling helps companies more accurately determine how they can best provide health care benefits to their plan members.  Insurers and employers will discover it to be a valuable tool if they use it reasonably and logically.  As advances in technology continue, predictive modeling will play a larger role in managing the risk and the future cost of health care.