Nancy L. Keating, MD, MPH

Many patients with newly diagnosed colorectal, lung, or breast cancer receive multimodality therapy (ie, surgery, chemotherapy, and/or radiation) within 6 months of diagnosis, and few of those patients received the different types of treatments at a single practice.

For bundled or episode-based payments to work in cancer care, they must be able to hold multiple distinct providers accountable for costs and quality.

Payers are increasingly using episode-based payments to reduce costs and improve quality in several areas, including joint replacements, dialysis, and hospitalizations for certain conditions. In oncology, CMS is implementing the Oncology Care Model, an episode-based alternative payment model for patients receiving chemotherapy.

 Other proposals for oncology episode-based payment models focus on patients with newly diagnosed cancer who may require surgery, radiation, and/or chemotherapy.

In models focused on newly diagnosed cancers, episodes are designed based on guideline-recommended treatments for patients with cancers of a certain type and stage. However, the multidisciplinary nature of cancer care creates a challenge in identifying which provider should receive the bundled payment for such episodes. When a patient with cancer receives multimodality care (ie, surgery, radiation, and/or chemotherapy) from different practices, it may not be readily apparent which practice should be held accountable for the costs and quality of care. We examined the prevalence of multimodality care across different practices to better characterize this challenge in colorectal, lung, and breast cancer, 3 of the most frequently diagnosed cancer types.

Using Surveillance, Epidemiology, and End Results Medicare data, we identified all fee-for-service Medicare beneficiaries with newly diagnosed colorectal, lung, or breast cancer between 2012 and 2015.

For each patient, we used Medicare claims from 2012 to 2016 to identify receipt of surgery, radiation, and chemotherapy within 6 months of diagnosis.

We assigned patients receiving each treatment to the practice (based on Taxpayer Identification Number [TIN]) that submitted the claims for that service in the National Claims History Physician/Supplier file (for surgery, radiation, or chemotherapy) or the Durable Medical Equipment file (for Part B—covered oral chemotherapy).

Among patients who received more than 1 treatment modality, we assessed how often the practice billing for one type of treatment (eg, chemotherapy) was the same as the practice billing for another (eg, surgery). We considered care to be delivered by the same practice if any practice providing one type of treatment also provided another type of treatment.

Among patients newly diagnosed with any stage of colorectal, lung, or breast cancer, the proportions who received multimodality therapy within 6 months of diagnosis were 19.6%, 6.4%, and 16.5%, respectively. Few of these patients received different types of treatment at a single practice. Specifically, of all patients receiving multimodality care for colorectal, lung, and breast cancer, only 5.8%, 17.2%, and 10.7%, respectively, received all of their care from the same practice (

Episode-based payments for patients with newly diagnosed cancer offer a promising opportunity to incentivize cost-efficient and coordinated care. Such models are straightforward for cancers requiring only 1 treatment modality (eg, stage 1 colorectal cancer, for which surgery alone is curative); however, episode-based payment models will be more complicated for patients with cancer who require multimodality care, because such care is infrequently provided by physicians billing together under the same TIN. These more complex patients are likely sicker and have higher costs than patients requiring single-modality care and may represent a real opportunity for alternative payment models to drive savings in cancer care. For episode-based payment reform to be successful in oncology, creative approaches are needed that hold multiple distinct providers accountable for costs and quality.

The authors would like to acknowledge Laurie Meneades for expert programming assistance and Lauren Riedel for research assistance.

 Department of Health Care Policy, Harvard Medical School (SG, MBL, JZ, MEC), Boston, MA; Division of Population Sciences, Dana-Farber Cancer Institute (AAW), Boston, MA; Division of General Internal Medicine, Brigham and Women’s Hospital (NLK), Boston, MA.

 This work was supported by the Laura and John Arnold Foundation. Dr Keating was additionally supported by the National Cancer Institute (K24CA181510).

 Dr Keating is on the evaluation team for the Oncology Care Model, a CMS alternative payment model. The remaining authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

 Concept and design (SG, AAW, MBL, MEC, NLK); acquisition of data (NLK); analysis and interpretation of data (SG, AAW, MBL, JZ, MEC, NLK); drafting of the manuscript (SG, AAW, NLK); critical revision of the manuscript for important intellectual content (SG, AAW, MBL, JZ, MEC, NLK); statistical analysis (MBL, JZ, MEC, NLK); obtaining funding (NLK); and supervision (NLK).

 Nancy L. Keating, MD, MPH, Department of Health Care Policy, Harvard Medical School, 180 Longwood Ave, Boston, MA 02115. Email: keating@hcp.med.harvard.edu.

1. Oncology Care Model. CMS website. innovation.cms.gov/initiatives/oncology-care. Updated August 2, 2019. Accessed September 16, 2019.

2. Hackensack Meridian Health; Cota Inc. Proposal for PTAC: oncology bundled payment program using CNA-guided care. Office of the Assistant Secretary for Planning and Evaluation website. aspe.hhs.gov/system/files/pdf/255906/OncologyBundledPaymentProgramCNACare.pdf. Published March 24, 2017. Accessed September 16, 2019.

3. Large Urology Group Practice Association. LUGPA APM for initial therapy of newly diagnosed patients with organ-confined prostate cancer. Office of the Assistant Secretary for Planning and Evaluation website. aspe.hhs.gov/system/files/pdf/255906/LUGPAAPM.pdf. Published July 5, 2017. Accessed September 16, 2019.

4. Bach PB, Mirkin JN, Luke JJ. Episode-based payment for cancer care: a proposed pilot for Medicare. 

. 2011;30(3):500-509. doi: 10.1377/hlthaff.2010.0752.

Articles

Most patients receiving multimodality cancer care receive care from different practices. Therefore, episode-based payments in oncology must hold multiple providers accountable for costs and quality.

Multimodality Cancer Care and Implications for Episode-Based Payments in Cancer

Medicare Advantage prescription drug plans (MA-PDs) and standalone prescription drug plans (PDPs) face different incentives for plan design resulting from the scope of covered benefits (only outpatient drugs for PDPs versus all drug and nondrug services for Medicare Advantage [MA]/MA-PDs). The objective is to begin to explore how MA-PDs and PDPs may be responding to their different incentives related to benefit design.

We compared 2012 PDP and MA-PD average formulary coverage, prior authorization (PA) or step therapy use, and copayment requirements for drugs in 6 classes used commonly among Medicare beneficiaries.

We primarily used 2012 Prescription Drug Plan Formulary and Pharmacy Network Files and MA enrollment data. 2011 Truven Health MarketScan claims were used to estimate drug prices and to compute drug market share. Average coverage and PA/step rates, and average copayment requirements, were weighted by plan enrollment and drug market share.

MA-PDs are generally more likely to cover and less likely to require PA/step for brand name drugs with generic alternatives than PDPs, and MA-PDs often have lower copayment requirements for these drugs. For brands without generics, we generally found no differences in average rates of coverage or PA/step, but MA-PDs were more likely to cover all brands without generics in a class.

We found modest, confirmatory evidence suggesting that PDPs and MA-PDs respond to different incentives for plan design. Future research is needed to understand the factors that influence Medicare drug plan design decisions.

We found modest, confirmatory evidence suggesting that stand-alone prescription drug plans (PDPs) and Medicare Advantage prescription drug plans (MA-PDs) respond to different incentives for plan design. MA-PDs are generally more likely to cover and less likely to require prior authorization or step therapy for brand name drugs with generic alternatives than PDPs, and MA-PDs often have lower copayment requirements for these drugs.

This paper provides suggestive evidence that a stand-alone Part D plan has drawbacks resulting from lack of integration with the medical benefit.

This information may inform efforts to regulate Medicare prescription drug plan generosity.

There are 2 types of Medicare Part D prescription drug plans. In 2010, approximately 17.7 million Medicare beneficiaries enrolled in a stand-alone prescription drug plan (PDP), continuing to receive Parts A and B benefits through the traditional Medicare program.

 Approximately 9.9 million beneficiaries enrolled in a Medicare Advantage-Prescription Drug plan (MA-PD), receiving Parts A and B benefits through the qualified Medicare Advantage (MA) plan that sponsored their MA-PD. Due to differences in the scope of benefits covered under PDPs versus MA/MA-PDs, these 2 types of plans face different incentives for drug plan design. Because of the integration of drug and nondrug coverage in MA plans and MA-PDs, MA-PDs have an incentive to provide relatively generous coverage for medications for which the incremental costs of doing so are offset by decreased medical spending over the period of expected enrollment.

 In contrast, PDPs, which are responsible only for drug expenditures, do not reap any efficiency gains with respect to Parts A and B services that may result from more generous drug coverage, and thus have lower incentives relative to MA-PDs to encourage use of drugs that may result in offsets for nondrug expenditures.

Both MA-PDs and PDPs have a choice of offering a plan with the defined standard benefit, a benefit that is actuarially equivalent to the defined standard benefit and consistent with CMS regulations governing coverage, or enhanced benefits. The defined standard benefit for 2013 has a deductible of $325. For spending between $326 and $2970, the plan pays 75% and the enrollee pays 25%. For expenditures between $2970 and $6733.75—known as the coverage gap&mdash;enrollees are responsible for a larger share, with enrollees paying 79% of generic drug expenditures and 47.5% of brand drug expenditures in the gap. For expenditures exceeding the $6733.75 catastrophic coverage limit, Medicare pays 80%, the plan pays 15%, and the enrollee pays 5%.

Previous studies have documented average aggregate (ie, aggregated across all drugs) differences in use of cost sharing and utilization management for PDPs relative to MA-PDs, with MAPDs typically offering more generous coverage.

 For example, in 2012, PDP enrollees faced some form of utilization management (ie, prior authorization [PA] requirements, step therapy requirements, or quantity limits) for 36% of drugs listed on the plan’s formulary while MA-PD enrollees faced utilization management for 31% of formulary drugs.

Also, MA-PDs had a lower average premium, were more likely to have a zero deductible, and were more likely to provide additional benefits in the coverage gap than PDPs.

Little is known about how MA-PDs and PDPs make decisions about coverage and utilization management requirements for specific medications, and data on aggregate differences in coverage levels for the 2 types of plans like the data described above do not shed much light on this complex decision-making process. To begin to explore how MA-PDs and PDPs may be responding to their different incentives around drug benefit design, we compared 2012 PDP and MA-PD average coverage, utilization management, and copayment requirements for specific drugs in several classes of medications used commonly among Medicare beneficiaries.

To identify MA-PDs and PDPs, we used the January 2012 CMS Prescription Drug Plan Formulary and Pharmacy Network Files (hereafter, “CMS formulary files”). These files contain information on plan characteristics as well as National Drug Code (NDC)-level information on formulary coverage, PA and step therapy requirements, and copayment requirements for all MA-PDs and PDPs operating in January 2012, with the exception of employersponsored MA-PDs. We excluded 125 private fee-for-service MA plans, as well as 506 special needs plans, 47 cost plans (ie, plans that Medicare contracts with a cost-reimbursement basis under Section 1876 of the Social Security Act), 61 plans serving US territories, 28 plans with no enrollment as of January 2012, and 1 plan for which formulary information was not available. After these exclusions, there were 1035 PDPs and 1512 MA-PDs in our sample.

Next, we linked the CMS formulary files for these plans with January 2012 plan enrollment information from the MA/Part D Contract and Enrollment Data available on CMS’ website.

To characterize the generosity of drug coverage in MA-PDs versus PDPs, we focused on 6 medication classes used frequently by Medicare beneficiaries for chronic medical conditions and for which at least one generic alternative was available in the class. Because drug plans generally cover all or almost all generic medications generously due to their relatively low cost, we focused analyses on brand name medications. Two of the 6 classes studied (antidepressants and antipsychotics) are Part D “protected” classes, meaning that plans must cover at least 1 formulation of every drug. The other 4 (Alzheimer’s disease medications, angiotensin receptor blockers [ARBs], bisphosphonates, and statins) are nonprotected classes, meaning that plans must cover at least two drugs in the class. Plans are permitted to use utilization management requirements like PA or step therapy to influence medication use in all classes, both protected and non-protected.

We examined 3 primary measures of coverage generosity: 1) formulary coverage; 2) use of PA and/or step therapy, conditional on formulary coverage; and 3) average copayment required for a 30-day prescription. To assess average formulary coverage, we first calculated coverage percentages for each formulation of each drug, collapsing over different NDCs for the same formulation. We expected plan coverage decisions for brand drugs to differ based on whether a generic equivalent of the brand drug was available. We also thought decisions about drugs might differ for brand combination medications (ie, medications that combine two or more molecular entities). Thus, we divided drugs into 3 categories for each class: brand drugs with a generic equivalent available, brand drugs with no generic equivalent available, and combination drugs (of the 19 combination products studied, all but 1 were brands without generic equivalents).

Within each drug class and category, we weighted the coverage percentages by plan enrollment and drug market share within the class, and then calculated the mean coverage percentage for each class and category for PDPs versus MA-PDs. We used 2011 Truven Health MarketScan data, which includes prescription drug claims for over 50 million individuals with employer-sponsored private insurance, to calculate drug market share. By weighting on the basis of drug market share, we “down-weight” observations for rarely-used drugs.

To test for a statistically-significant difference in average coverage between PDPs and MA-PDs, we calculated 

tests of the difference in the mean number of drugs covered for drug categories with more than 1 drug and 

 values from t tests of the difference in proportion covered for categories with a single drug, as well as an F-test of the null hypothesis that all effects are zero. We followed the same process for use of PA/ step therapy.

To calculate the average co-payment requirements for a 30-day prescription, we used plan-level information on the copayment required for each specific NDC from the CMS formulary files. For plans that required coinsurance rather than copayments for a given medication, we instead applied the plan’s coinsurance rate for the initial coverage period (ie, covering expenditures after the deductible is met and before the coverage gap is entered) for a specific NDC from the CMS formulary files to NDC level data on average total price (ie, average of plan plus patient payments per 30-day prescription, not accounting for any rebates negotiated between the plan and the pharmaceutical manufacturer) from the 2011 Truven Health MarketScan data. As for the coverage measures described above, we weighted observations by plan enrollment and drug market share. We calculated 

 values from t tests of the difference in weighted mean copayment requirements for each drug class and category, as well as an F-test of the null hypothesis that all effects are zero.

Finally, we calculated the percentage of MA-PD plans and the percentage of PDPs that covered all brand drugs with no generic equivalents in each class, weighting by plan enrollment but not drug market share, to ensure that we captured differences in covering all formulations, including those that are rarely used.

Brand name drugs with generic equivalents

. Generics accounted for the vast majority of prescriptions filled for drugs with generic equivalents. The average generic market share for these medications ranged from 90.8% for Alzheimer’s medications to 99.7% for statins. On average, MA-PDs were significantly more likely than PDPs to cover brand drugs with generic equivalents in all 4 non-protected classes (Alzheimer’s disease drugs, ARBs, bisphosphonates, and statins) (Table 1).

On average, PDPs covered only 2.5% to 4.6% of brands with generic equivalents for statins, bisphosphonates, and ARBs, and covered 53.5% of brand Alzheimer’s drugs with generic equivalents. MA-PDs covered significantly more of these drugs on average in all classes (12.5% more for Alzheimer’s drugs to 25.6% more for bisphosphonates, all 

 <.0001). For the 2 protected classes, coverage of antipsychotic brands with generics tended to be more generous for MA-PDs vs PDPs, although this did not reach statistical significance (

= .052). There were no statistically significant differences between PDPs and MA-PDs for antidepressants.

Conditional on formulary coverage, MA-PDs were significantly less likely than PDPs to require PA/step therapy for drugs in 3 of 6 classes (Alzheimer’s medications, bisphosphonates, and antidepressants), while MA-PDs were more likely to require PA/step therapy for ARBs than PDPs (Table 1, right columns). There were no statistically significant differences in formulary coverage for MA-PDs vs PDPs for the other 2 classes.

Average copayment requirements per 30-day prescription were lower, on average, for MA-PDs relative to PDPs for 4 classes (ARBs, bisphosphonates, statins, and antipsychotics). Average copayment requirements were higher for MA-PDs relative to PDPs for Alzheimer’s medications, and there was no statistically significant difference between the 2 plan types for antidepressants (

Brand name drugs without generic equivalents

. For brand drugs without generic equivalents, there were no statistically significant differences between MA-PDs and PDPs in either formulary coverage or PA/step therapy (weighted by drug market share, to down-weight drugs that are used rarely), with the exception of statins; MAPDs were significantly more likely than PDPs to require PA/step therapy for statins without generic equivalents (Table 1). However, compared with PDPs, a much larger proportion of MA-PDs covered all brand name medications without generic equivalents for 4 of 6 classes (ARBs, bisphosphonates, statins and antidepressants) (

.) Note that the denominator includes all drugs regardless of market share, unlike Table 1, in which the calculations are weighted by market share). For example, in the Figure, a third (33.5%) of MA-PDs covered all brand ARBs with no generic equivalents while only 5.0% of PDPs did. The Figure does not include antipsychotics (a protected class) or Alzheimer’s medications (not protected) because the proportion of both MA-PDs and PDPs covering all brands with no generics for each class was greater than 90%, allowing limited opportunity to detect coverage differences. The 3 Alzheimer’s medications in this category included the Exelon™ (rivastigmine) patch, which may provide a better delivery route than oral medications for some Alzheimer’s patients, as well as Namenda (memantine) tablets and solution, which have a specific indication for moderate to severe Alzheimer’s, have fewer side effects than the cholinesterase inhibitors, and may be disease-modifying.

Average copayment requirements per 30-day prescription were higher for MA-PDs relative to PDPs for 3 classes (ARBs, bisphosphonates, and statins) and substantially lower for MA-PDs vs PDPs for antipsychotics (Table 2). There was no statistically significant difference in average copayment requirements between MA-PDs and PDPs for Alzheimer’s medications or antidepressants.

. Results were mixed for the brand combination drugs (Table 1). MA-PDs were more likely to cover the bisphosphonate combination (alendronate plus vitamin D) and the antidepressant/antipsychotic combination (olanzapine plus fluoxetine) relative to PDPs. MAPDs were more likely to require PA/step therapy for the statin and bisphosphonate combinations and less likely to require PA/step therapy for the antidepressant/antipsychotic combination than PDPs. Average copayment requirements per 30-day prescription were significantly higher for MA-PDs than PDPs for ARB combination medications and significantly lower for MA-PDs than PDPs for the antidepressant/antipsychotic combination; there were no statistically significant differences in average co-payment requirements for the other 4 classes (Table 2).

F-tests for each of the 3 outcomes (formulary coverage, PA/step therapy, and cost sharing) rejected the null hypothesis that all effects were zero.

Across 6 medication classes used commonly by Medicare beneficiaries, we documented differences in average plan design for MA-PDs and PDPs, with MA-PDs generally offering more generous coverage, and in some cases, substantially more generous coverage. MA-PDs are more likely to cover and less likely to require PA or step therapy for brand name drugs with generic alternatives than PDPs. MA-PDs also often require a lower copayment for these drugs on average relative to PDPs. For brands without generics, we generally found no statistically significant differences in average rates of coverage and PA/ step therapy, but MA-PDs were more likely to cover all brands without generics in a given therapeutic class. Interestingly, average copayment requirements per 30-day prescription for brands without generics were sometimes higher for MA-PDs than PDPs, suggesting that PDPs may be more likely to cover only a subset of brands without generic equivalents but require lower cost sharing for those they do cover relative to MA-PDs. The fact that fewer statistically significant differences between MA-PDs and PDPs were found for the 2 protected classes than for the 4 non-protected classes we studied suggests that the 2 types of plans may be acting in a similar way with respect to the formulary protections afforded to these classes.

There are several possible explanations for why MA-PDs might cover brands with generic equivalents more generously than PDPs. One is that MA-PDs may be less concerned than PDPs about generous coverage of brand name drugs with generic equivalents due to the greater influence over clinical decision making that may result from care management processes and provider network arrangements used by MA plans/ MA-PDs relative to PDPs, which have no direct relationship with clinicians that provide services to individuals covered by traditional Medicare. For example, if a MA plan provides financial incentives or decision support that encourages generic prescribing, or the plan contracts only with clinicians with high generic prescribing rates, network clinicians may rarely prescribe brand drugs even if the drugs are covered.

A second possible explanation for the more generous coverage of brands with generic equivalents by MA-PDs could be that demand for a PDP is more sensitive to a coverage restriction for a particular drug than demand for a given MA-PD. A Medicare beneficiary who decides to join an MA plan with an MA-PD presumably selects a plan by evaluating features of both the MA plan’s nondrug coverage and its MA-PD drug coverage. As a result, if a PDP concerned about adverse selection wishes to discourage enrollment by individuals with a chronic condition associated with high medication costs, imposing coverage restrictions for medications in that class may be more likely to affect PDP enrollment of beneficiaries who use those medications than a similar restriction would affect enrollment for an MA plan and its MA-PD. Hsu and colleagues found that the risk adjustment method used for the Medicare Part D benefit, prescription drug hierarchical condition categories (RxHCCs), tended to overpredict 2006 costs for beneficiaries with low actual costs and to underpredict 2006 costs for those with high actual costs.

 If this pattern had continued since this early research was conducted, MA-PDs might have been more likely to be “overpaid” for relatively healthier enrollees, and thus perhaps better positioned to offer more generous coverage. However, CMS attempted to correct this issue in 2011 by increasing the low income subsidy (LIS) rates and decreasing the non-LIS rates. Based on the findings of Hsu and colleagues, this change may have resulted in an “overcorrection.”

A third possible explanation, although perhaps a less likely one, is that MA-PDs could have a greater incentive than PDPs to offer generous coverage of brand name drugs without generic equivalents if the plan believes that a subset of patients will only adhere to a medication regimen by taking brand name medications and that greater medication adherence in the class can lead to lower total healthcare spending (all else being equal). Enrollees who prefer a brand formulation can apply for a formulary exception allowing them to obtain the brand version at the generic price; no data are available on the extent to which formulary exceptions are granted in this situation, however. Jung, McBean, and Kim found some support for this hypothesis for statin medications.

 They documented statistically higher rates of adherence to statin therapy for MA-PD enrollees relative to PDP enrollees, although they noted that the magnitude of the difference was very small and unlikely to be clinically meaningful. However, Erten and colleagues found similar overall use of guideline- recommended diabetes medications in MA-PDs and PDPs.

 We observed more generous coverage and less cost sharing for brands with generic alternatives in MA-PDs versus PDPs for ARBs, bisphosphonates and statins, as well as lower cost sharing for antipsychotics and antidepressant/ antipsychotic combination brand drugs, all examples where one might expect a greater likelihood of offset onto nondrug expenditures resulting from medication adherence. However, we also observed better coverage for Alzheimer’s medications, a class where an offset seems less likely.

Some of the observed differences in generosity for MA-PDs and PDPs result from the fact that MA plans with premium bids below the county benchmark receive rebates from the federal government that can be used to lower their monthly Part D premium, enhance their drug benefits, or lower drug cost sharing. However, these MA plans can instead choose to use these rebates to lower their Part B premiums, enhance nondrug benefits, or lower nondrug cost sharing, so more generous drug coverage for MA-PDs is not a given.

There are several limitations to our analysis. First, we are unable to observe all factors influencing plan design decisions for PDPs and MA-PDs. We are only able to make inferences based on observed plan design differences. Second, one might expect to see different patterns of plan design for classes that have not experienced generic entry relative to classes with at least one generic option. We were unable to examine this issue because nearly all of the most common classes utilized by Medicare beneficiaries now have at least one generic alternative. Third, our analysis may underestimate differences in MA-PD and PDP coverage to the extent that a subset of MA-PDs may have the same formulary as a PDP (and vice versa) due to common ownership. Finally, drug market share may differ in privately insured populations included in the MarketScan database and Medicare Part D plans, although many of the largest PDPs are sponsored by large pharmacy benefit managers and insurers that use the same formulary and utilization management tools for both their commercial and Part D plans.

We found modest confirmatory evidence suggesting that PDPs and MA-PDs respond to the different incentives around plan design that they face as a result of the scope of their benefits: only outpatient prescription drugs in the case of PDPs and all covered drug and nondrug healthcare services in the case of MA plans offering an MA-PD. MA-PDs are generally more likely to cover and less likely to require PA or step therapy for brand name drugs with generic alternatives than PDPs, and MA-PDs often have lower copayment requirements for these drugs. For brands without generics, we generally found no differences in average rates of coverage and PA/step therapy, but MA-PDs were more likely to cover all brands without generics in a given therapeutic class. Future work is needed to understand the factors that influence Medicare drug benefit design decisions among Part D plans, the impact of those decisions on outcomes, and how Medicare beneficiaries select from among MA-PD and PDP options.

 From From Harvard Medical School, Department of Health Care Policy, Boston, MA, (HH, NK, JD, MC, JN); Brigham and Women’s Hospital, Department of Medicine, Boston, MA, (NK); Harvard University, John F. Kennedy School of Government, Cambridge, MA, and Harvard University, School of Public Health, Boston, MA (JN).

 This research was funded by the National Institute on Aging (#PO1 AG032952).

The authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

 Concept and design (HH, NL, MC, JN); acquisition of data (HH, NL, MC, JN); analysis and interpretation of data (HH, NK, JD, MC, JN); drafting of the manuscript (HH, JD); critical revision of the manuscript for important intellectual content (HH, NK, JD, MC, JN ); statistical analysis (HH, NK, JD, MC, JN); provision of study materials or patients (HH, NK, JD, MC, JN); obtaining funding (HH, NK, MC, JN); administrative, technical, or logistic support (JD); supervision (HH).

 Haiden A. Huskamp, Ph.D., Harvard Medical School, Department of Health Care Policy, 180 Longwood Avenue, Boston, MA 02115. E-mail:huskamp@hcp.med.harvard.edu.1. Medicare Payment Advisory Commission. A databook: health care spending and the Medicare program: June 2012. Washington, DC: Medicare Payment Advisory Commission; 2012:155-181.. http://www .medpac.gov/documents/Jun12DataBookEntireReport.pdf.

2. Congressional Budget Office. Offsetting effects of prescription drug use on Medicare’s spending for medical services, November 2012. http://www.cbo.gov/sites/default/files/cbofiles/attachments/43741- MedicalOffsets-11-29-12.pdf

3. Polinski JM, Mohr PE, Johnson L. Impact of Medicare Part D on access to and cost sharing for specialty biologic medications for beneficiaries with rheumatoid arthritis. Arthritis Rheum. 2009;61(6):745-54.

4. Frakt AB, Pizer SD. A first look at the new Medicare prescription drug plans. Health Aff (Millwood). 2006;25(4):W252-261.

5. Kornhuber J, Weller M, Schoppmeyer K, Riederer P. Amantadine and memantine are NMDA receptor antagonists with neuroprotective properties. J Neural Transm Suppl. 1994;43:91-104.

6. McShane R, Areosa Sastre A, Minakaran N. Memantine for dementia. Cochrane Database Syst Rev. 2006;(2):CD003154.

7. Jung K, McBean AM, Kim JA. Comparison of statin adherence among beneficiaries in MA-PD plans versus PDPs. J Manag Care Pharm. 2012; 18(2):106-115.

Medicare-Advantage Prescription drug plans (MA-PDs) and standalone PDPs appear to respond to different incentives for plan design.

Nancy L. Keating, MD, MPH

Articles

Multimodality Cancer Care and Implications for Episode-Based Payments in Cancer

Drug Plan Design Incentives Among Medicare Prescription Drug Plans