Improving Food and Drug Administration-Centers for Medicare and Medicaid Services Coordination for Drugs Granted Accelerated Approval.

Policy Points The increasing number of drugs granted accelerated approval by the Food and Drug Administration (FDA) has challenged the Medicare program, which often pays for expensive therapies despite substantial uncertainty about benefits and risks to Medicare beneficiaries. We recommend several administrative and legislative approaches for improving FDA-Centers for Medicare and Medicaid Services (CMS) coordination around accelerated-approval drugs, including promoting earlier discussions among the FDA, the CMS, and drug companies; strengthening Medicare's coverage with evidence development program; linking Medicare payment to evidence generation milestones; and ensuring that the CMS has adequate staffing and resources to evaluate new therapies. These activities can help improve the integrity; transparency; and efficiency of approval, coverage, and payment processes for drugs granted accelerated approval. CONTEXT: The Food and Drug Administration (FDA)'s accelerated-approval pathway expedites patient access to promising treatments. However, increasing use of this pathway has challenged the Medicare program, which often pays for expensive therapies despite substantial uncertainty about benefits and risks to Medicare beneficiaries. We examined approaches to improve coordination between the FDA and Centers for Medicare and Medicaid Services (CMS) for drugs granted accelerated approval. METHODS: We argue that policymakers have focused on expedited pathways at the FDA without sufficient attention to complementary policies at the CMS. Although differences between the FDA and CMS decisions are to be expected given the agencies' different missions and statutory obligations, procedural improvements can ensure that Medicare beneficiaries have timely access to novel therapies that are likely to improve health outcomes. To inform policy options and recommendations, we conducted semistructured interviews with stakeholders to capture diverse perspectives on the topic. FINDINGS: We recommend ten areas for consideration: clarifying the FDA's evidentiary standards; strengthening FDA authorities; promoting earlier discussions among the FDA, the CMS, and drug companies; improving Medicare's coverage with evidence development program; tying Medicare payment for accelerated-approval drugs to evidence generation milestones; issuing CMS guidance on real-world evidence; clarifying Medicare's "reasonable and necessary" criteria; adopting lessons from international regulatory-reimbursement harmonization efforts; ensuring that the CMS has adequate staffing and expertise; and emphasizing equity. CONCLUSIONS: Better coordination between the FDA and CMS could improve the transparency and predictability of drug approval and coverage around accelerated-approval drugs, with important implications for patient outcomes, health spending, and evidence generation processes. Improved coordination will require reforms at both the FDA and CMS, with special attention to honoring the agencies' distinct authorities. It will require administrative and legislative actions, new resources, and strong leadership at both agencies.

Variation in Medicaid and commercial payer coverage of aducanumab for Alzheimer's disease.

INTRODUCTION: Ever since the United States Food and Drug Administration (FDA) approved aducanumab and Centers for Medicare & Medicaid Service (CMS) restricted coverage for the drug, a crucial question has been how other payers will behave. This study examined how Medicaid and commercial plans cover aducanumab. METHODS: We created a database of aducanumab coverage policies issued by Medicaid fee-for-service programs (50 states and DC) and 35 of the largest commercial plans (covering ∼ 84% of the commercially insured population). RESULTS: We found that only 41% of Medicaid fee-for-service plans have issued a publicly available coverage policy for aducanumab and that there is wide variation in these coverage criteria. Although the majority of included commercial plans have issued an aducanumab coverage policy, only five plans covered aducanumab for their enrollees. Available coverage polices showed little consistency in how to measure sufficient treatment response. DISCUSSION: Differences in coverage policies mean that Alzheimer's patients' access to aducanumab may vary across jurisdictions and across commercial insurers. HIGHLIGHTS: Less than half of state Medicaid fee-for-service plans issued a publicly available coverage policy for aducanumab. Available Medicaid coverage policies varied substantially in their coverage criteria. The majority of included commercial plans issued an aducanumab coverage policy; only five plans covered aducanumab. Available coverage polices showed little consistency in how to measure sufficient treatment response.

An Evidence Review of Low-Value Care Recommendations: Inconsistency and Lack of Economic Evidence Considered.

BACKGROUND: Low-value care, typically defined as health services that provide little or no benefit, has potential to cause harm, incur unnecessary costs, and waste limited resources. Although evidence-based guidelines identifying low-value care have increased, the guidelines differ in the type of evidence they cite to support recommendations against its routine use. OBJECTIVE: We examined the evidentiary rationale underlying recommendations against low-value interventions. DESIGN: We identified 1167 "low-value care" recommendations across five US organizations: the US Preventive Services Task Force (USPSTF), the "Choosing Wisely" Initiative, American College of Physicians (ACP), American College of Cardiology/American Heart Association (ACC/AHA), and American Society of Clinical Oncology (ASCO). For each recommendation, we classified the reported evidentiary rationale into five groups: (1) low economic value; (2) no net clinical benefit; (3) little or no absolute clinical benefit; (4) insufficient evidence; (5) no reason mentioned. We further investigated whether any cited or otherwise available cost-effectiveness evidence was consistent with conventional low economic value benchmarks (e.g., exceeding $100,000 per quality-adjusted life-year). RESULTS: Of the identified low-value care recommendations, Choosing Wisely contributed the most (N=582, 50%), followed by ACC/AHA (N=250, 21%). The services deemed "low value" differed substantially across organizations. "No net clinical benefit" (N=428, 37%) and "little or no clinical benefit" (N=296, 25%) were the most commonly reported reasons for classifying an intervention as low value. Consideration of economic value was less frequently reported (N=171, 15%). When relevant cost-effectiveness studies were available, their results were mostly consistent with low-value care recommendations. CONCLUSIONS: Our study found that evidentiary rationales for low-value care vary substantially, with most recommendations relying on clinical evidence. Broadening the evidence base to incorporate cost-effectiveness evidence can help refine the definition of "low-value" care to reflect whether an intervention's costs are worth the benefits. Developing a consensus grading structure on the strength and evidentiary rationale may help improve de-implementation efforts for low-value care.

Orphan Drugs Offer Larger Health Gains but Less Favorable Cost-effectiveness than Non-orphan Drugs.

BACKGROUND: Orphan drugs offer important therapeutic options to patients suffering from rare conditions, but are typically considerably more expensive than non-orphan drugs, leading to questions about their cost-effectiveness. OBJECTIVE: To compare the value of orphan and non-orphan drugs approved by the FDA from 1999 through 2015. DESIGN: We searched the PubMed database to identify estimates of incremental health gains (measured in quality-adjusted life-years, or QALYs) and incremental costs that were associated with orphan and non-orphan drugs compared with preexisting care. We excluded pharmaceutical industry-funded studies from the dataset. When a drug was approved for multiple indications, we considered each drug-indication pair separately. We then compared incremental QALY gains, incremental costs, and incremental cost-effectiveness ratios for orphan and non-orphan drugs using the Mann-Whitney U (MWU) test (to compare median values of the different distributions) and the Kolmogorov-Smirnov (KS) test (to compare the shape of different distributions). RESULTS: We identified estimates for 49 orphan drug-indication pairs, and for 169 non-orphan drug-indication pairs. We found that orphan drug-indication pairs offered larger median incremental health gains than non-orphan drug-indication pairs (0.25 vs. 0.05 QALYs; MWU p = 0.0093, KS p = 0.02), but were associated with substantially higher costs ($47,652 vs. $2870; MWU p < 0.001, KS p < 0.001) and less favorable cost-effectiveness ($276,288 vs. $100,360 per QALY gained; MWU p = 0.0068, KS p = 0.009). CONCLUSIONS: Our study suggests that orphan drugs often offer larger health gains than non-orphan drugs, but due to their substantially higher costs they tend to be less cost-effective than non-orphan drugs. Our findings highlight the challenge faced by health care payers to provide patients appropriate access to orphan drugs while achieving value from drug spending.

What types of real-world evidence studies do U.S. commercial health plans cite in their specialty drug coverage decisions?

PURPOSE: To examine the RWE U.S. commercial health plans cite in their specialty drug coverage decisions. METHODS: We used the Tufts Medical Center Specialty Drug Evidence and Coverage Database to identify specialty drug coverage decisions (n = 7267) issued by 17 large commercial health plans. We categorized the clinical evidence plans cited in these coverage decisions (n = 5227) as randomized controlled trials (RCTs), RWE studies, and other clinical studies (studies other than RCT or RWE study). We categorized RWE studies with respect to study type, for example, case series, studies based on medical records, and so on. We compared the frequency that plans cited different categories of RWE, cited RWE for different diseases, and cited RWE for drugs on the market for different time periods. RESULTS: RWE comprised 16% of cited clinical studies. Health plans cited RWE with different frequencies (5%-31% of the cited clinical evidence). Overall, plans cited RWE categorized as medical records most often (26% of cited RWE studies). Plans varied in the frequency they cited different RWE categories. Plans most frequently cited RWE for gastroenterological diseases (35% of clinical study citations) and least frequently for respiratory diseases (11% of clinical study citations). Plans cited RWE more for drugs that have long been on the market. CONCLUSIONS: Health plans varied with respect to the number and types of RWE studies they cited in their specialty drug coverage decisions. Plans cited RWE more often for some diseases than others, and cited more RWE for older drugs.

A Review of Empirical Analyses of Disinvestment Initiatives.

BACKGROUND: Disinvesting in low-value health care services provides opportunities for investment in higher value care and thus an increase in health care efficiency. OBJECTIVES: To identify international experience with disinvestment initiatives and to review empirical analyses of disinvestment initiatives. METHODS: We performed a literature search using the PubMed database to identify international experience with disinvestment initiatives. We also reviewed empirical analyses of disinvestment initiatives. RESULTS: We identified 26 unique disinvestment initiatives implemented across 11 countries. Nineteen addressed multiple intervention types, six addressed only drugs, and one addressed only devices. We reviewed 18 empirical analyses of disinvestment initiatives: 7 reported that the initiative was successful, 8 reported that the initiative was unsuccessful, and 3 reported that findings were mixed; that is, the study considered multiple services and reported a decrease in the use of some but not others. Thirty-seven low-value services were evaluated across the 18 empirical analyses, for 14 (38%) of which the disinvestment initiative led to a decline in use. Six of the seven studies that reported the disinvestment initiative to be successful included an attempt to promote the disinvestment initiative among participating clinicians. CONCLUSIONS: The success of disinvestment initiatives has been mixed, with fewer than half the identified empirical studies reporting that use of the low-value service was reduced. Our findings suggest that promotion of the disinvestment initiative among clinicians is a key component to the success of the disinvestment initiative.

EXAMINING EVIDENCE IN U.S. PAYER COVERAGE POLICIES FOR MULTI-GENE PANELS AND SEQUENCING TESTS.

OBJECTIVES: The aim of this study was to examine the evidence payers cited in their coverage policies for multi-gene panels and sequencing tests (panels), and to compare these findings with the evidence payers cited in their coverage policies for other types of medical interventions. METHODS: We used the University of California at San Francisco TRANSPERS Payer Coverage Registry to identify coverage policies for panels issued by five of the largest US private payers. We reviewed each policy and categorized the evidence cited within as: clinical studies, systematic reviews, technology assessments, cost-effectiveness analyses (CEAs), budget impact studies, and clinical guidelines. We compared the evidence cited in these coverage policies for panels with the evidence cited in policies for other intervention types (pharmaceuticals, medical devices, diagnostic tests and imaging, and surgical interventions) as reported in a previous study. RESULTS: Fifty-five coverage policies for panels were included. On average, payers cited clinical guidelines in 84 percent of their coverage policies (range, 73-100 percent), clinical studies in 69 percent (50-87 percent), technology assessments 47 percent (33-86 percent), systematic reviews or meta-analyses 31 percent (7-71 percent), and CEAs 5 percent (0-7 percent). No payers cited budget impact studies in their policies. Payers less often cited clinical studies, systematic reviews, technology assessments, and CEAs in their coverage policies for panels than in their policies for other intervention types. Payers cited clinical guidelines in a comparable proportion of policies for panels and other technology types. CONCLUSIONS: Payers in our sample less often cited clinical studies and other evidence types in their coverage policies for panels than they did in their coverage policies for other types of medical interventions.

Thirty Years of Media Coverage on High Drug Prices in the United States--A Never-Ending Story or a Time for Change?

In recent years drug prices have increasingly become a topic of debate for patients, providers, payers and policy makers. To place the current drug price debate into historical context, we searched the New York Times and Wall Street Journal from 1985 - 2015 and found that concerns about drug prices have commonly featured in the press over the study period with recently stronger calls for change. Price levels, types of innovations, stakeholder responses, and strategies to address high prices discussed in the media suggest that concerted efforts are required to enable affordable and high-value innovations.

Medicare's enduring struggle to define "reasonable and necessary" care.

Medicare legislation mandates that the program not pay for items and services that are not "reasonable and necessary" - terms that are open to interpretation and easily politicized. In today's fiscal environment, "reasonable and necessary" warrants a closer look.

CHANGING FACE OF MEDICARE'S NATIONAL COVERAGE DETERMINATIONS FOR TECHNOLOGY.

OBJECTIVES: The Centers for Medicare and Medicaid Services (CMS) issues National Coverage Determinations (NCDs) for medical interventions expected to have a significant impact on Medicare, the health insurance program for US citizens aged 65 years and older and certain people with disabilities under the age of 65 years. The objective of this study was to evaluate NCDs issued from 1999 to 2013 to identify key trends, and to discuss implications for future CMS policy. METHODS: We used the Tufts Medical Center Medicare National Coverage Determination Database to examine characteristics of NCDs from 1999 through 2013. We examined various characteristics of NCDs, including: whether the intervention under review is used for prevention or treatment of disease, the type of intervention considered, evidence limitations cited by CMS, and coverage determination outcome. We evaluated longitudinal trends in categorical and continuous variables in the database, using Cochran-Armitage trend tests and linear regression, respectively. RESULTS: We found that NCDs increasingly focus on preventive care (p = 0.072), pertain to diagnostic imaging (p = 0.033), and evaluate health education/behavioral therapy interventions (p = 0.051). CMS increasingly cites the lack of relevant outcomes (p = 0.019) and the lack of applicability of study results to the Medicare population (p < 0.001) as evidence limitations. CMS less often restricts coverage to certain population subgroups in NCDs (p < 0.001), but increasingly applies coverage with evidence development policies (p < 0.001). CONCLUSIONS: Identified trends reflect broader changes in Medicare as CMS shifts its focus from treatment to prevention of disease, addresses potentially overutilized technologies, and attempts to issue flexible coverage policies.

US commercial health plan coverage dynamics in pulmonary arterial hypertension therapies.

BACKGROUND: Health plan coverage is central to patient access to care, especially for rare, chronic diseases. For specialty drugs, coverage varies, resulting in barriers to access. Pulmonary arterial hypertension (PAH) is a rare, progressive, and fatal disease. Guidelines suggest starting or rapidly escalating to combination therapy with drugs of differing classes (phosphodiesterase 5 inhibitors [PDE5is], soluble guanylate cyclase stimulators [sGC stimulators], endothelin receptor antagonists [ERAs], and prostacyclin pathway agents [PPAs]). OBJECTIVE: To assess the variation in commercial health plan coverage for PAH treatments and how coverage has evolved. To examine the frequency of coverage updates and evidence cited in plan policies. METHODS: We used the Tufts Medical Center Specialty Drug Evidence and Coverage database, which includes publicly available specialty drug coverage policies. Overall, and at the drug and treatment class level, we identified plan-imposed coverage restrictions beyond the drug's US Food and Drug Administration label, including step therapy protocols, clinical restrictions (eg, disease severity), and prescriber specialty requirements. We analyzed variation in coverage restrictiveness and how coverage has changed over time. We determined how often plans update their policies. Finally, we categorized the cited evidence into 6 different types. RESULTS: Results reflected plan coverage policies for 13 PAH drugs active between August 2017 and August 2022 and issued by 17 large US commercial health plans, representing 70% of covered lives. Coverage restrictions varied mainly by step therapy protocols and prescriber restrictions. Seven plans had step therapy protocols for most drugs, 9 for at least one drug, and 1 had none. Ten plans required specialist (cardiologist or pulmonologist) prescribing for at least one drug, and 7 did not. Coverage restrictions increased over time: the proportion of policies with at least 1 restriction increased from 38% to 73%, and the proportion with step therapy protocols increased from 29% to 46%, with generics as the most common step. The proportion of policies with step therapy protocols increased for every therapy class with generic availability: 18% to 59% for ERAs, 33% to 77% for PDE5is, and 33% to 43% for PPAs. The proportion of policies with prescriber requirements increased from 24% to 48%. Plans updated their policies 58% of the time annually and most often cited the 2019 CHEST clinical guidelines, followed by randomized controlled trials. CONCLUSIONS: Plan use of coverage restrictions for PAH therapies increased over time and varied across both drugs and plans. Inconsistency among health plans may complicate patient access and reduce the proportion who can persist on PAH treatments.

Illustrating potential efficiency gains from using cost-effectiveness evidence to reallocate Medicare expenditures.

OBJECTIVES: The Centers for Medicare & Medicaid Services does not explicitly use cost-effectiveness information in national coverage determinations. The objective of this study was to illustrate potential efficiency gains from reallocating Medicare expenditures by using cost-effectiveness information, and the consequences for health gains among Medicare beneficiaries. METHODS: We included national coverage determinations from 1999 through 2007. Estimates of cost-effectiveness were identified through a literature review. For coverage decisions with an associated cost-effectiveness estimate, we estimated utilization and size of the "unserved" eligible population by using a Medicare claims database (2007) and diagnostic and reimbursement codes. Technology costs originated from the cost-effectiveness literature or were estimated by using reimbursement codes. We illustrated potential aggregate health gains from increasing utilization of dominant interventions (i.e., cost saving and health increasing) and from reallocating expenditures by decreasing investment in cost-ineffective interventions and increasing investment in relatively cost-effective interventions. RESULTS: Complete information was available for 36 interventions. Increasing investment in dominant interventions alone led to an increase of 270,000 quality-adjusted life-years (QALYs) and savings of $12.9 billion. Reallocation of a broader array of interventions yielded an additional 1.8 million QALYs, approximately 0.17 QALYs per affected Medicare beneficiary. Compared with the distribution of resources prior to reallocation, following reallocation a greater proportion was directed to oncology, diagnostic imaging/tests, and the most prevalent diseases. A smaller proportion of resources went to cardiology, treatments (including drugs, surgeries, and medical devices, as opposed to nontreatments such as preventive services), and the least prevalent diseases. CONCLUSIONS: Using cost-effectiveness information has the potential to increase the aggregate health of Medicare beneficiaries while maintaining existing spending levels.

The association between US Food and Drug Administration-expedited review designations and health plan specialty drug coverage.

BACKGROUND: The US Food and Drug Administration (FDA) speeds approval of important clinical advancements through 4 expedited review programs: Priority Review, Accelerated Approval, Fast Track, and Breakthrough Therapy. Whether health plans prioritize coverage of expedited drugs relative to drugs that the FDA determined did not qualify from these programs is unclear. OBJECTIVES: To investigate how fast US commercial health plans issued coverage policies for drugs included in different numbers of FDA-expedited programs. Second, to examine the association between a drug's inclusion in an FDA-expedited program and plan coverage restrictiveness. METHODS: We used a separate dataset for each study objective. For the first objective, we created a dataset of policies issued by 17 large commercial health plans for 2018 FDA-approved drugs. Included policies were active exactly 1 year following each drug's FDA approval. We investigated the relationship between the speed of policy issuance and the number of expedited programs. We controlled for cancer and orphan indication. For the second objective, we analyzed a dataset of commercial health plan specialty drug coverage policies. We categorized drugs with respect to the number of expedited programs (0, 1, or 2+ programs). Coverage policies were categorized as whether plans imposed restrictions beyond a drug's FDA-approved labeling, for example, step therapy requirements. We used regression analysis to examine the association between FDA-expedited review and coverage restrictiveness when controlling for other relevant factors (eg, availability of alternatives). RESULTS: For our first objective, plans issued 62% (742/1,190) of policies within a year of a drug's FDA approval. In unadjusted analysis, policy issuance speed increased with each additional expedited program (hazard ratio=1.15; P<0.01). After controlling for cancer and orphan status, the number of expedited programs was not associated with faster policy issuance (hazard ratio=0.95; P=0.209). For our second objective, plans imposed coverage restrictions in 33% (672/2,027) of policies for drugs the FDA included in at least 1 FDA-expedited program vs 51% (870/1,706) of policies for drugs the FDA excluded from these programs. In multivariable regression, we did not find an association between FDA-expedited review and coverage restrictiveness after controlling for other decision-making factors (including disease prevalence, annual cost, etc). CONCLUSIONS: After controlling for other decision-making factors, we did not find that FDA-expedited approval was associated with faster coverage policy issuance, nor did we find that plans covered drugs the FDA included in expedited review programs less restrictively than drugs excluded from these programs. Our findings raise questions about why plans do not also accelerate access for these clinical advancements. DISCLOSURES: This study was funded by Janssen Scientific Affairs, LLC. Mr Ingham is an employee of Janssen Scientific Affairs, LLC, and is a stockholder of Johnson & Johnson. Dr Chambers reports grants from Janssen Scientific Affairs, LLC, during the conduct of the study.

Varied use of step therapy among Medicare Advantage plans.

OBJECTIVES: First, to examine 7 large Medicare Advantage (MA) plans' use of step therapy. Second, to compare step therapy that health plans imposed in their MA and commercial (employer) drug coverage policies. STUDY DESIGN: Database analysis. METHODS: Using data from the Tufts Medical Center Specialty Drug Evidence and Coverage Database, we evaluated 7 large MA plans' use of step therapy in their Part B drug coverage policies. First, we determined the frequency with which different MA plans applied step therapy. Second, we determined the frequency with which plans imposed step therapy protocols across International Classification of Diseases, Tenth Revision, Clinical Modification categories. Third, we compared each step therapy protocol against each drug's corresponding FDA label indication. Fourth, we examined the consistency of step therapy protocols between the same insurer's MA and commercial lines of business. RESULTS: The frequency with which the included MA plans imposed step therapy ranged from 26.1% to 63.7%. Step therapy was most common for dermatology conditions (90.2%) and least common for oncology conditions (28.6%). On average, MA plans' step therapy requirements were consistent with the drug's FDA label indication 29.0% of the time. MA plans' and commercial plans' use of step therapy differed for the same drug-indication pairs 46.1% of the time. CONCLUSIONS: MA plans vary in the frequency with which they impose step therapy protocols in their Part B drug coverage policies. Moreover, insurers often impose different step therapy protocols in their MA plan and commercial plan offerings. Differences in plans' step therapy requirements may result in variability in patients' access to care within MA.

Factors Associated with Biosimilar Exclusions and Step Therapy Restrictions Among US Commercial Health Plans.

BACKGROUND: Biosimilars have been introduced with the goal of competing with high-priced biologic therapies, yet their adoption has been slower than expected and resulted in limited efficiency gains. We aimed to explore factors associated with biosimilar coverage relative to their reference products by commercial plans in the United States (US). METHODS AND DATA: We identified 1181 coverage decisions for 19 commercially available biosimilars, corresponding to 7 reference products and 28 indications from the Tufts Medical Center Specialty Drug Evidence and Coverage database. We also drew on the Tufts Medical Center Cost-Effectiveness Analysis Registry for cost-effectiveness evidence, and the Merative™ Micromedex® RED BOOK® for list prices. We summarized the coverage restrictiveness as a binary variable based on whether the product is covered by the health plan, and if covered, the difference of payers' line of therapy between the biosimilar and its reference product. We used a multivariate logistic regression to examine the association between coverage restrictiveness and a number of potential drivers of coverage. RESULTS: Compared with reference products, health plans imposed coverage exclusions or step therapy restrictions on biosimilars in 229 (19.4%) decisions. Plans were more likely to restrict biosimilar coverage for the pediatric population (odds ratio [OR] 11.558, 95% confidence interval [CI] 3.906-34.203), in diseases with US prevalence higher than 1,000,000 (OR 2.067, 95% CI 1.060-4.029), and if the plan did not contract with one of the three major pharmacy benefit managers (OR 1.683, 95% CI 1.129-2.507). Compared with the reference product, plans were less likely to impose restrictions on the biosimilar-indication pairs if the biosimilar was indicated for cancer treatments (OR 0.019, 95% CI 0.008-0.041), if the product was the first biosimilar (OR 0.225, 95% CI 0.118-0.429), if the biosimilar had two competitors (reference product included; OR 0.060, 95% CI 0.006-0.586), if the biosimilar could generate annual list price savings of more than $15,000 per patient (OR 0.171, 95% CI 0.057-0.514), if the biosimilar's reference product was restricted by the plan (OR 0.065, 95% CI 0.038-0.109), or if a cost-effectiveness measure was not available (OR 0.066, 95% CI 0.023-0.186). CONCLUSION: Our study offered novel insights on the factors associated with biosimilar coverage by commercial health plans in the US relative to their reference products. Cancer treatment, pediatric population, and coverage restriction of the reference products are some of the most significant factors that are associated with biosimilar coverage decisions.

Commercial health plans use of patient subgroup restrictions: An analysis of orphan and US Food and Drug Administration-expedited programs.

BACKGROUND: Health plans apply utilization management criteria to guide their enrollees' access to prescription drugs. Patient subgroup restrictions (ie, clinical prerequisites for drug coverage) are a form of utilization management that have not been thoroughly investigated. OBJECTIVE: To examine the frequency with which large US commercial health plans impose patient subgroup restrictions beyond the US Food and Drug Administration (FDA) label in their coverage policies for orphan drugs and for drugs included in 1 or more FDA-expedited programs. To determine how consistently these patient subgroup restrictions align with eligibility criteria specified in each drug's pivotal clinical trial(s). METHODS: The Tufts Medical Center Specialty Drug Evidence and Coverage (SPEC) database was used, which includes coverage policies issued by 17 large US commercial health plans. SPEC contained 3,786 orphan drug policies and 4,027 FDA-expedited drug policies (current as of December 2020). SPEC data on plans' patient subgroup restrictions were assessed for the first objective. Each patient subgroup restriction was benchmarked against the corresponding eligibility criteria for a drug's pivotal clinical trial(s) for the second objective. To do so, the "Clinical Studies" section of the drug's FDA label was reviewed or, if necessary, the published manuscript describing the drug's pivotal trial(s). Patient subgroup restrictions were categorized as follows: (1) "consistent," the restriction and trial eligibility criterion are equivalent; (2) "same measure, more stringent," the restriction and trial eligibility criteria depend on the same measure, but the plan coverage is more restrictive; (3) "same measure, less stringent," the restriction and trial eligibility criteria depend on the same measure, but the plan coverage is less restrictive; and (4) "not consistent," the restriction and trial eligibility criteria depend on different measures. RESULTS: Health plans imposed patient subgroup restrictions in 20.2% of orphan drug policies (frequency varied by health plan, 11.7%-36.6%), and in 21.8% of FDA-expedited drug policies (frequency varied by health plan, 11.1%-47.9%). Of the 936 patient subgroup restrictions in orphan drug policies, 60.3% were categorized as consistent; 7.3% as same measure, more stringent; 12.0% as same measure, less stringent; and 20.5% as not consistent. Of the 1,070 patient subgroup restrictions in FDA-expedited drug policies, 57.5% were categorized as consistent; 6.7% as same measure, more stringent; 16.0% as same measure, less stringent; and 19.8% as not consistent. CONCLUSIONS: Patient subgroup restrictions for orphan drugs and FDA-expedited programs varied substantially across health plans, potentially resulting in inconsistent access to a given therapy across the approved patient population. Patient subgroup restrictions tend to be consistent with eligibility criteria specified in pivotal clinical trials. DISCLOSURES: This study was funded by Sarepta Therapeutics, Inc. Alexa C Klimchak and Lauren E Sedita are employees of Sarepta Therapeutics, Inc., and may own stock/options in the company.

Variation in Medicaid and commercial coverage of cell and gene therapies.

Growth in the availability of cell and gene therapies (CGTs) promises significant innovation in the treatment of serious diseases, but the high cost and one-time administration of CGTs has also raised concern about strain on health plan budgets and inequity in access. We used coverage information from the Tufts Medical Center Specialty Drug Evidence and Coverage (SPEC) database for 18 large commercial health plans in the US and information from state Medicaid websites to examine variation in coverage of 11 CGTs in August 2021. We found that US commercial and Medicaid health plans imposed restrictions in 53.5 % and 68.3 % of their coverage policies for the 11 included CGTs, respectively. In addition, we identified significant variation in access to CGTs across commercial plans and across Medicaid plans. Coverage restrictions for certain CGTs were more common than others; clinical requirements were often (but not always) consistent with the inclusion criteria for the clinical trial central to the drug's approval. We conclude that there is variation in access to CGTs, creating differential patient access.

Specialty drug coverage varies between health plans' medical and pharmacy benefit policies.

BACKGROUND: In an effort to control drug spending, health plans are increasingly shifting specialty drugs from their medical benefit to the pharmacy benefit. One consequence of this trend is that some health plans have both a medical and a pharmacy coverage policy for the same drug. OBJECTIVE: To examine how frequently health plans issue medical and pharmacy benefit policies for the same specialty drug and to evaluate the concordance between plans' medical and pharmacy policies when plans issue both policy types. METHODS: We identified specialty drug coverage policies from the Tufts Medical Center Specialty Drug Evidence and Coverage Database, which includes policies issued by 17 of the largest US commercial health plans. Policies were current as of August 2020. We determined plans that issued both medical and pharmacy policies. Next, we identified drugs with "medical-pharmacy policy pairs," ie, drugs for which a plan issued both a medical and a pharmacy policy. For these pairs, we compared the plan's policies while accounting for the following coverage criteria: patient subgroups (patients must meet certain clinical criteria), prescriber requirements (a specialist must prescribe the drug), and step therapy protocols (patients must first fail alternative treatments). We considered medical-pharmacy policy pairs to be discordant if coverage criteria differed, eg, the medical policy included a prescriber requirement but the pharmacy policy did not. RESULTS: Eight plans issued separate medical and pharmacy benefit coverage policies for the same specialty drug and indication. Among these 8 plans, we identified 1,619 medical-pharmacy policy pairs. Eighty-six percent of pairs were concordant (1,386/1,619), and 14% were discordant (233/1,619). Discordance was most often due to differences in plans' application of step therapy protocols (184/233), followed by prescriber requirements (52/233) and patient subgroups (25/233). Forty pairs were discordant in multiple ways. Of discordant pairs, medical policies were more restrictive 41% (96/233) of the time; pharmacy policies were more restrictive 54% (125/233) of the time; 5% of the time (12/233), the medical policy was more restrictive in some ways, but the pharmacy policy was more restrictive in others. Overall, plans imposed coverage restrictions in their medical and pharmacy policies with similar frequencies. CONCLUSIONS: Commercial health plans' medical and pharmacy coverage policies for the same specialty drugs tended to be concordant, although we found coverage criteria to be discordant 14% of the time. Medical and pharmacy policies that are inconsistent in their coverage criteria and restrictions complicate, and potentially hinder, patients' access to specialty drugs. DISCLOSURES: Drs Kauf, O'Sullivan, and Strand were employees of Alkermes, Inc., when the study was conducted and may own stock in the company. Mx Levine, Mr Panzer, and Dr Chambers have no conflicts of interest to disclose. This research study was supported by Alkermes, Inc.

Examining US commercial health plans' use of The Institute for Clinical and Economic Review's reports in specialty drug coverage decisions.

BACKGROUND: The Institute for Clinical and Economic Review (ICER) has emerged in a visible role in US health care. However, it is unclear to what extent US commercial health plans use ICER value assessments in their specialty drug coverage decisions. OBJECTIVE: To evaluate the relationship between ICER's reported cost-effectiveness ratios (CERs) and coverage restrictiveness. Also, to examine the frequency with which plans have cited ICER in their coverage policies and to investigate how frequently health plans adjusted their drug coverage criteria in the 12 months after ICER's assessments. METHODS: We analyzed the Tufts Medical Center Specialty Drug Evidence and Coverage Database, which includes specialty drug coverage decisions issued by 17 large US commercial health plans. For ICER-assessed drugs, we recorded ICER's estimated CERs in the form of cost per quality-adjusted life-year (QALY) gained. First, we used multivariate logistic regression to examine the association between ICER's reported CERs and plan coverage restrictiveness, when controlling for other factors that were likely to affect decision-making. Next, we examined how often plans cited ICER's assessments in coverage decisions issued in years 2017-2020. Lastly, we examined whether plans added or removed coverage restrictions (eg, patient subgroup restrictions or step therapy protocols) in the 12 months following ICER's assessment. RESULTS: Plans tended to cover drugs with higher (less favorable) CERs more restrictively than drugs with CERs less than $100,000 per QALY: odds ratio (OR) = 4.48 if $100,000-$175,000 per QALY; OR = 2.00 if $175,000-$500,000 per QALY; and OR = 2.10 if $500,000 or more per QALY (all P < 0.01). Plans cited ICER in 0.8% (5/622) of coverage policies in 2017, 0.6% (5/833) in 2018, 1.7% (19/1,139) in 2019, and 2.4% (33/1,406) in 2020. For drugs with CERs less than $175,000 per QALY, plans adjusted coverage in 37% of cases: added restrictions in 20%, removed restrictions in 15%, and added one restriction but removed another in 2%. For drugs with CERs of $175,000 or more, plans changed coverage criteria in 29% of cases: added restrictions in 21%, removed restrictions in 5%, and added one restriction but removed another in 4%. CONCLUSIONS: We found that when controlling for other factors, health plans' specialty drug coverage decisions were associated with ICER's estimated CERs. Plans infrequently cited ICER value assessments. We did not observe a trend for plans more often narrowing coverage criteria for drugs with CERs $175,000 or more compared with drugs with CERs less than $175,000. DISCLOSURES: This research study was supported by a consortium of funders: Amgen, Genen-tech, Janssen Pharmaceuticals, Otsuka, and GSK.