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Reducing Out-of-Pocket Cost Barriers to Specialty Drug Use Under Medicare Part D: Addressing the Problem of "Too Much Too Soon"
Jalpa A. Doshi, PhD; Pengxiang Li, PhD; Amy R. Pettit, PhD; J. Samantha Dougherty, PhD; Ashley Flint, MPP; and Vrushabh P. Ladage, BS

Reducing Out-of-Pocket Cost Barriers to Specialty Drug Use Under Medicare Part D: Addressing the Problem of "Too Much Too Soon"

Jalpa A. Doshi, PhD; Pengxiang Li, PhD; Amy R. Pettit, PhD; J. Samantha Dougherty, PhD; Ashley Flint, MPP; and Vrushabh P. Ladage, BS
Medicare claims analyses offer insight into how proposed policy changes would affect out-of-pocket prescription costs for Part D beneficiaries requiring specialty drugs.
Our analysis had several limitations. First, as with all administrative databases, Medicare claims may be subject to errors or omissions. Second, we examined 2012 data and applied policy changes that took effect under the ACA in that year. As noted above, if the ACA remains in effect, the coverage gap will be phased out by 2020 and the catastrophic coverage limit will be higher; thus, the catastrophic coverage limit (and our proposed annual OOP spending maximum) will increase and the figures presented here will represent an underestimate of patient OOP spending. Our analysis is not able to account for future changes to the ACA that may impact Medicare policy. Third, given the availability of claims data, we limited our sample to FFS Medicare Part D beneficiaries; to illustrate the real-world OOP cost burden in patients prescribed continual treatment throughout the year, we further limited our sample to full-year users of specialty drugs. However, our proposed strategies are recommended for, and our incremental cost and financing calculations apply to, all Medicare Part D beneficiaries (FFS and Medicare Advantage) regardless of whether they were full- or part-year users of specialty drugs. Our calculations do not account for any increases in specialty drug utilization and spending that would occur among part-year users in response to lower and more stable monthly cost sharing under our proposed strategies. Similarly, as the number of beneficiaries eligible for and requiring specialty drug treatments increases over the years, the incremental cost of our proposed strategies would further increase. It is notable that our estimated costs begin at a relatively modest amount (less than $2 per month per beneficiary), however.

As with most aspects of healthcare, the fine-grained logistical details of implementing our proposed strategies will be straightforward in some cases and more complex in others. Redistribution of annual OOP costs in the form of a stable monthly payment is least complicated for individuals who are prescribed medications for continuous use throughout the coverage year (as in our sample), whereas protocols would have to be developed for those who initiate treatment later in the year. For example, if a patient fills a prescription in September that would have carried a $1500 coinsurance payment, he or she may need to continue to pay the remaining balance on that prescription into the following year. Although this does increase the complexity somewhat, much of the rest of the healthcare system bills patients for remaining OOP costs after a service is rendered (eg, imaging tests, surgeries, hospitalizations). Developing adjustments in pharmacy and insurance procedures that are more in step with the advances in pharmaceutical treatments is a worthwhile goal.

Indeed, the expanding role of self-administered pharmaceutical treatments in the management of serious life-threatening, chronic, and/or rare diseases also argues for a less siloed approach and greater attention to overall OOP costs for patients. Our analysis addresses prescription drug OOP costs only, yet patients are also responsible for OOP costs related to premiums, medical deductibles, and medical co-pays and coinsurance. Unlike most employer and health insurance exchange plans, which integrate medical and prescription drug expenses into a combined annual OOP maximum spending limit,23,24 all Medicare beneficiaries currently lack an annual OOP maximum limit for their Part D prescription drug spending and the majority have no annual maximum for other OOP medical spending. Our proposal represents an important first step toward addressing these issues.

CONCLUSIONS

Specialty drugs represent vital treatments for patients who often have few or no effective alternatives available, and consistent use can often help to prevent disease progression and other costly complications. Yet, these treatments can only be effective if patients can afford to utilize them. Thus, Medicare Part D policies that support access and adherence are critically important. Our analyses indicate that efforts to alleviate financial barriers to specialty drug adherence should include attention to both the amount and timing of OOP costs.

Author Affiliations: Division of General Internal Medicine, Department of Medicine, Perelman School of Medicine (JAD, PL, VPL), Leonard Davis Institute of Health Economics (JAD, PL), Center for Public Health Initiatives (ARP), University of Pennsylvania, Philadelphia, PA; PhRMA (JSD, AF), Washington, DC.

Source of Funding: PhRMA, Washington, DC.

Author Disclosures: At the time of the study, Dr Doshi reported serving as a consultant for Alkermes, Inc, Forest Laboratories (now Allergan), Ironwood Pharmaceuticals, Shire, and Vertex Pharmaceuticals; and had received research funding from AbbVie Inc, Biogen, Humana, Inc, Janssen, PhRMA, Pfizer Inc, Regeneron, Sanofi, and the National Pharmaceutical
Council. Dr Doshi’s spouse holds stock in Merck & Co, Inc, and Pfizer Inc. Dr Dougherty and Ms Flint are employees of PhRMA. Drs Li and Pettit and Mr Ladage have no conflicts to report.
 
Authorship Information: Concept and design (JAD, PL, ARP, JSD, AF); acquisition of data (JAD, PL, VPL); analysis and interpretation of data (JAD, PL, ARP, VPL); drafting of the manuscript (JAD, PL, ARP, JSD, AF); critical revision of the manuscript for important intellectual content (JAD, PL, ARP, JSD, AF, VPL); statistical analysis (PL); obtaining funding (JAD); administrative, technical, or logistic support (VPL); and supervision (JAD, PL).

Address Correspondence to: Jalpa A. Doshi, PhD, University of Pennsylvania, 1223 Blockley Hall, Philadelphia, PA 19104. E-mail: jdoshi@mail.med.upenn.edu.

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