One scenario that I have seen play itself out on multiple occasions over the past year is that of a plan sponsor trying to understand whether or not they really need to be considering a move away from a reimbursement plan to a pay-direct drug (PDD) plan design. The issues and questions that arise are generally the same:

  • Will a move to a PDD plan allow for better management of the benefit?
  • Will moving to a drug card increase utilization and plan costs because of the added convenience, the disappearing of the “shoebox effect,” and potentially less coordination of benefits (in the event PDD spousal plans have been more attractive options for the family in the past)?
  • Which side will have a bigger financial impact: gains from better management or losses from an increase in claims?

That is a tough question to answer if one is left to guess. If you are a paid advisor, guessing incorrectly could cost you your client and harm your reputation. If you are a human resources professional, guessing incorrectly could result in daily taunting from your colleagues in the finance department or some very stern questions from company executives. Fortunately, the guess work can be completely eliminated by using the same tool by which all other important business decisions are made in sophisticated businesses—math.

The nice part is that the math here is very simple (especially for those of us who weren’t overly fond of calculus)—adding up the benefits and subtracting the liabilities to provide the opportunity in the given year of consideration. To consider the overall financial impact, the math can be a bit more challenging (looking at future values of each annual opportunity calculated above), but fortunately the numbers produced from the benefits—liabilities equation above over a two- to three-year period are often strong enough to assist in decision making.

Here are the components of the equation in a vast majority of cases. It is important to keep in mind, these are not the only potential benefits, there are the ones that can be quantified and measured. At the same time, any direct costs associated with making a change are not included in the equation because the components of any direct plan design change costs will be different for each group.

Potential Benefits (all measurable)

Enhanced pricing controls: in this era of dynamic drug pricing driven by legislative and competitive pressures, two-tiered pricing, etc. the benefits of enhanced pricing controls are priceless (pun intended)

  • Improved definition and adjudication of covered products (including hospital-use only drugs, life-sustaining over-the-counter drugs, products with no DIN listed, etc.)
  • Ability to quantify savings from mandatory generic substitution
  • Opportunity to institute appropriate therapeutic limits to minimize potential inappropriate use of the benefit
  • Optimization of chronic therapies
  • Gains that can be achieved through the introduction of a more managed plan design (a vital consideration in this era of public-sector downloading, and the emergence of specialty drugs for very common chronic conditions)

Potential Liabilities (all measurable)

  • Provision for the carry-over of reimbursement claims from previous period (i.e., claims from previous year submitted in current period along with existing PDD claims—an issue in the first year only and simply a cash flow issue, not a utilization issue)
  • Determining the size of the “shoebox effect” based on the existing claims patterns
  • Determining sensitivity analyses related to possible changes in coordination of benefits

The other benefit to this equation is that at the same time that the math is being worked on as per the formula above, other key metrics can be isolated that be used to determine if a change-over to a drug card (a perceived benefit to plan members) can be instituted at the same time as constructive, responsible, but not necessarily major a change to the existing plan design. These metrics include:

  • Generic and multi-source brand drug penetration rates
  • Specialty drug penetration rates
  • Plan-level utilization and claim cost figures (that can be benchmarked to provide a frame of reference)

Injecting math into this process can be achieved by looking at plan-specific drug claims data over a 24 to 36 month period. That same data set can be used to determine the impact of alternate plan designs in the event the current trend is not acceptable or sustainable for a given plan sponsor.

There is no right answer—the decision to move from reimbursement to PDD depends entirely on the given group’s current experience, its disease state and demographic profile, its geographical distribution, and the financial performance goals established for its benefit plans. One can’t make the argument that if it worked for Company A, it will work for us to the same extent. Similarly, one can’t argue that if a change for Company B didn’t turn out as expected that it will turn out adversely for us as well.

In the end, there is no perfect solution outside of employing the skills of a Nostradamus, but simple math in this case will do the trick. The best part for HR professionals and their advisors: finance can never come back at you when you employ the same decision making tools as they do—numbers. Math is still the best plan review and design tool available. Thankfully there are ways to make the math easy enough for all of us non-actuaries to understand, but robust enough to allow for appropriate decision making.