A Clearer Crystal Ball: More Accurate Health Plan Modeling through Better Data

Health benefits change every year. Before an employer can offer new plans, those changes must be modeled out in the most precise way possible to determine what services will be included and what additional costs may be absorbed. The whole process can feel like the old whack-a-mole game. Add a certain demographic group here and another one must be eliminated there. Modify certain coverage options in one spot and unforeseen consequences for employer and employee alike will pop up elsewhere. As frustrating as this process can be, it ultimately determines what coverage options employers offer to their employees. Until recently, such modeling forecasts have been based on limited, general data sets that provide only part of the picture. The result has been that neither employees nor employers have been given the best health coverage options available to fit their needs.

The more data one has at their disposal to model changes to health plans the better. The more accurate the data, the more accurate a population's needs are, and the more customized plans can become. With health costs continuing to become a bigger and bigger piece of an employer's benefits package, it is critical that plan modeling accurately predict the needs of the employees and be offered in ways that are comprehensive, personalized and cost effective to the employer. New technology allows more customized data to be used to more accurately reflect the needs of a specific plan's participants. The result is vastly more dynamic plan models that lead to better coverage choices.

Of course, it's how superior data is used that ensures the best possible plans are being offered. By accessing and analyzing a wealth of plan-specific data, the user can modify and compare plans side-by-side in a clear and concise manner. By utilizing a company's own data and using accepted actuarial techniques to approximate the financial implications of various benefit changes, plan modeling software offers more customized, population-specific plans than simply using general data allows. By modeling up to six different plan scenarios at once, modeling software gives employers and their actuarial partners more flexibility to assess different plans and determine which ones are the most appropriate for the current and potential members.

Plan modeling tools can utilize a company's own claims database -- as well as sophisticated health data analytic software -- to develop much more accurate and customized plan options. Using an existing plan as a baseline, new forecasting solutions can analyze in seconds everything from hospital and doctor visit utilization to the breakdown of in-network to out-of-network services as well as specific demographic analyses of the age, gender and zip codes of enrollees. If a major shift occurs to a company -- an old plant closes or a new factory opens up, for example -- those changes to the plan's population group can be analyzed with other key factors to determine the financial impact of such modifications.

Better data leads to better health plan models and better health plan models lead to better plans being offered, which ultimately lead to a healthier and more productive workforce. By looking at specific health claims data for specific plans, while also maximizing broader data sets that reflect national trends, employers can assess the needs of their employees like never before. Plan modeling software offers a level of sophistication, flexibility and specificity that wasn't available until very recently.

About the Author:Denise Zeman is senior VP and chief administrative officer at HDMS, a health data and information technology company. She has over twenty years of management and consulting experience in the health care and group benefits industry, including leading the design and development of application requirements for many benefits programs.