The Unsustainable Burden
The use and cost of specialty drugs is causing an unsustainable burden for healthcare systems in the US and around the world. On the one hand, specialty medications help some of the country’s most severely ill patients to battle their diseases. Often, specialty drugs offer life changing benefits for these patients. So simply denying access is generally not an option, at least not in the US. Also, as many specialty drugs are biologics, they lack cheaper, generic alternatives. Even biosimilars, which are projected to grow to be a market worth $60-70 billion in the next five years in the US alone, will only impact competing drug prices by 10%-30% at the most – while also lacking direct substitution as is available within an already 80-90% generic non-specialty market. The current cost burden to payers, providers and patients will quadruple to $400 billion by 2020 in the US alone. And in that same timeframe, specialty drugs will account for just 2% of all prescriptions, yet drive 50% of all prescription drug cost.
Traditional Utilization Management (UM) Doesn’t Work in Specialty
Health plans and PBMs are continuing to rely on relatively ineffective approaches to “managing” specialty drug use and cost in their networks. Traditional Utilization Management and Formulary Management techniques that worked so well with non-specialty drugs, have been unable to optimize patient care while managing associated costs of specialty drugs. We continue to see year over year growth in specialty trend (the growth of drug use and cost) soaring upwards of 10-20% per year, with some plans even reporting trend growth of 30% or more. The bottom line is that even when payers dip into their UM arsenal, everything from prior authorization, to preferred formulary tiers, to quantity limits, to site of care optimization, and the list goes on and on…nothing works well enough to truly change the unsustainable specialty drug trend line. What would lead us to believe that the same old, standard UM approaches would work for infinitely more complex diseases, requiring precise, targeted decisions to ensure an optimal patient health outcome at a value-based cost with minimal drug spend waste?
Four Game Changers in Specialty Drug Management
So what is the solution to the untenable problem with specialty drugs? How can we continue to ensure access to these critically necessary, innovative medicines that support our most severely ill patients? Many have opined that there are no silver bullet solutions on the horizon. Solving the specialty drug conundrum will require innovative solutions for four longstanding pain points, that have held us back in the past. The good news is this – there is nothing stopping us from solving this problem right now. Here are the four keys to changing the game in specialty drug management:
1. Diverse Big Data Sets: To enable predictive targeting in niche specialty diseases, we must integrate diverse, big data sets at the patient level
2. Deep Sub-Level Analytics: Analytics must go deeper, to more specific sub-population levels – as this is where both precision and waste reside in specialty drug utilization
3. Integrated Systems Lead the Way: Integrated provider-payer systems are uniquely positioned to lead the way on new, collaborative business models
4. Biopharma Embraces Pay-for-Value: Drug pricing is best disrupted at the edges – biopharma must commit to pay-for-value with the rest of the healthcare ecosystem.
Let’s take a closer look at each of our key points for change, and what’s required to better manage specialty drug use, cost and outcomes.
1. Diverse Big Data Sets
Specialty care disease effect smaller patient population sizes when compared to “big” chronic disease areas such as diabetes, asthma, and hypertension. What this means is that when we attempt to deploy technology to help with complex decision support in specialty disease areas, any one payer or provider system rarely can simply analyze their own data, as sample sizes at a sub-population level will often be too small to create valid and reliable results on their own. Also, to achieve a real world data set with true predictive power, it is not enough to just analyze payer claims data, provider EMR data, or lab results data alone. There’s simply not enough predictive power in one single type of data. We need to “boost the power” of the data in two ways if we hope to take on the specialty drug use and cost challenges. First, the predictive, decision support power of data is increased, not by adding more data of the same type, but by adding more data of different types for the same exact patient. Second, we must seek do more sharing integrated, de-identified data for small specialty disease areas across institutional boundaries in order to boost predictive power.
2. Deep, Sub-Level Analytics
If we truly want to solve the specialty drug crisis that exists in healthcare today, we need to recognize that drug waste is not driven merely by biopharmaceutical company pricing practices. While it is popular in payer and provider circles to blame everything on drug prices being too high, the truth of the matter is that there’s lower hanging fruit we can get at right away, that still drives real economic savings, when it comes to specialty drug waste. This problem is further exacerbated by today’s often outdated approaches to drug UM, that simply do not work in specialty diseases the way they have proven to do so in non-specialty areas. The solution is to look beyond comparative drug effectiveness at the disease level. We’ve got to go to a sub-population level if we want to get at critical waste categories such as inappropriate use, high clinician variability, real world safety issues and poor adherence. Clinical trial information is generally not helpful in this regard, as there is very little comparative information at a sub-population level. At the sub-population level of granularity, we can much more clearly find aggregated “deposits” of waste that can be eradicated via proactive, evidence-backed, value-based decision support technologies – these new disruptive platforms will align all risk takers in making the best decision – namely payers, at-risk provider systems, value-reimbursed clinicians, and co-insured patients – and someday very soon, we will be able to replace or retire traditional drug UM methods at a fraction of the operational cost. If done correctly, for example, we won’t need to describe the changes to today’s “UM workhorse” for specialty drugs, the Prior Authorization (PA) decision – we can simply perform the entire process within the advanced analytics engine in real time. Where, in many cases, today’s PA processes are relatively manual and labor intensive (e.g., phone calls, faxes, spreadsheets, UM coordinators, UM nurses, UM physicians, UM pharmacists, etc.), in the future we will make decisions not off a broad formulary based almost entirely on cost comparisons, we will make instantaneously optimal decisions regarding the exact right drug, for the exact right patient, where the best value-based decision is delivered for the patient and payer both in terms of cost AND health outcome. This capability is not only possible today, it becomes an essential “must have” if we expect to realize both the economic and clinical targets envisioned in a new population health world at scale.
3. Integrated Systems Lead the Way
The growing use and cost of specialty drugs is not solvable by any one constituency within today’s healthcare ecosystem alone. This is nothing new. Yet, year after year we talk about the need for collaboration between the four “big Ps” in the drug space (e.g., payers, providers, producers, and patients), and nothing much ever materializes beyond the occasional scattershot pilot. The inherent lack of trust and misalignment of financial incentives, continues to bring us back to square one, as if an endless loop of healthcare’s version of the movie “Groundhog Day”. Often in healthcare, collaboration is made more difficult by starting with incompatible dance partners. Win-win proclamations often decay into a “big win” for one party and a “little or no win” for the other side. In specialty drugs, it’s all about getting enough of the right data, integrated at a patient level, in order to increase the predictive power required to drive sub-population level decision support. Who is best equipped to unlock the solution to managing specialty drugs right now? The answer may surprise you – namely provider-sponsored health plans, working in tandem with their parent provider health system (who today is more motivated than ever before to successfully operate with capitated or at-risk reimbursement) and the clinicians and patients who work with both. Who are these players? Think prominent health systems such as Kaiser, Intermountain, UPMC, Geisinger, Presbyterian and Providence, who have all the data needed – minimally claims, EMR and lab data for the same exact patient – within the confines of their own health plan and health system business units. Yes, ultimately we will need to prove these decision support solutions work between the mega-large for-profit health plans and their affiliated Accountable Care Organization (ACO) provider partners, but these relationships today generally lack the trust, scale and two-way data sharing that will be required at the start.
4. Biopharma Embraces Pay-for-Value
As we witness the dramatic shift toward fee-for-value (or pay-for performance) across all provider sectors, the last bastion of fee-for-service sits in one of the most innovative and advanced sectors in all of healthcare – biopharmaceuticals. Drug manufacturers have fended off every challenge by well-funded lobbyists in the payer, provider and patient advocacy segments to get the US government to take control and set drug prices, as has occurred in other countries around the world. Price disruption is possible, yet it is not going to happen right now in the way most would suggest. The immediate pricing solution opportunity lies “at the edges,” and not at the price per prescription per se. In the case of specialty drugs, the first level of success to reduce price will come by moving drug companies away from fee-for-service. Every biopharmaceutical manufacturer knows they must deliver a “give” in the debate on pricing, and this is where they know they must go next, if they want to stave off government intervention on pricing decisions. There seems to be support on all sides for risk based contracting (RBC) “done right”. Payers, providers and biopharmaceutical companies all agree with the intent of RBC, but, to date, have lacked a true, real world, precision data source that can fairly and accurately underpin the give and take of rebates and price discounts based upon quantifying the pockets of waste in drug use and spend. To date, we have lacked sub-population level, real world information regarding categories of waste such as comparative efficacy, inappropriate (over/under) use, patient safety, non-adherence, and comparative value.. As we solve for the pain points described in #1, #2 and #3 above, innovative industry contracting solutions that monitor the exchange of value between payers and drug manufacturers can be delivered. Think of this as the precision analytics required to truly enable the promise of precision medicine – the exact right drug, for the exact right patient, to generate an acceptable health outcome, all at an optimized, value-based cost. We don’t need to go for the drug company jugular in order to have an impact on price. The actual total drug cost per disease area will drop by 10-30%, even if the price of each successful, fully paid, prescription stays the same.
Precision, Predictability and Cost Management Now Possible
Everything we need to solve this pressing challenge is in place – the diverse big data sources, the advanced analytic techniques, the sophisticated technology platforms, the right initial business model partners and motivated paying customers. It won’t be perfect at the start, but there’s no doubt that we will begin to eliminate wasteful and unnecessary use and cost of specialty drugs within a very short period of time, while delivering a better, more targeted health outcomes for patients in need of innovative medicines. We’ve already started the journey. There are early success stories in areas such as Oncology and Hepatitis C. There’s more work to be done, and many will opine that the journey is too difficult and littered with past failed attempts, but the effort will result in immediate upside. And as we go to scale, one therapeutic area at a time, we will see 15-20% specialty drug trend lines dropping to single digit growth without stifling new drug innovation. We will pay only for the value we receive. But to know the value we receive, we must deploy advanced analytic platforms that leverage the availability of integrated, diverse, big data to dramatically shift our course forever from volume to value. So let’s get on with solving the specialty drug crisis in healthcare – the time is now!