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.

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.

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.

Characterizing health plan evidence review practices.

BACKGROUND: Health plans guide enrollees' access to specialty drugs through coverage policies. Practice guidelines recommend that the evidence supporting drug coverage policies should be comprehensive and routinely updated to reflect evidence-based medicine. OBJECTIVE: To examine the frequency with which health plans update their coverage criteria and supporting evidence and to determine the pattern with which plans cited relevant literature in their coverage policies. METHODS: Coverage policies from 17 large US commercial health plans were retrieved from the Tufts Medical Center Specialty Drug Evidence and Coverage database for August 2017 and August 2019. We identified drug-indication pairs (eg, infliximab for rheumatoid arthritis) for which plans had issued coverage policies in August 2017 and August 2019. We examined the frequency with which plans reissued these policies (ie, issued a new coverage document) between these 2 time points and the frequency with which plans altered coverage criteria or updated the cited evidence. A random sample of 20 drug-indication pairs was chosen to determine the comprehensiveness of cited evidence from the Specialty Drug Evidence and Coverage database. For each pair, a systematic literature search was conducted to identify relevant clinical and economic studies. A comparison of the systematic literature search with the evidence cited in each drug-indication pair's coverage policy was conducted to determine the comprehensive nature of each coverage policy's evidence. RESULTS: We identified 4,597 instances of plans issuing a coverage policy for the same drug-indication pair in both August 2017 and August 2019. Of those 4,597 instances, plans reissued an updated coverage document in 4,468 (97%). Fifteen percent of reissued policies revised both their coverage criteria and the evidence cited, 2% only their coverage criteria, 69% only the cited evidence, and 14% made no change. A total of 2,760 literature documents were identified relevant to at least one of the 20 drug-indication pairs, of which at least one plan cited 146 of these documents at least once (5.3%). Plans cited health technology assessments, randomized controlled trials (RCTs), systematic reviews/meta-analyses, and clinical guidelines most comprehensively. CONCLUSIONS: Health plans reissued most of their specialty drug coverage policies over a 2-year period. When plans revised their drug coverage criteria, they also tended to revise the evidence cited in their coverage polices. Of all the evidence found in our systematic review, plans more comprehensively cite health technology assessments, RCTs, and systematic reviews/meta-analyses. DISCLOSURES: This study was funded by the National Pharmaceutical Council.

Patients' access to 2018 FDA-approved drugs 1 year post approval.

OBJECTIVES: To examine US commercial health plans' adoption of 2018 FDA-approved drugs. STUDY DESIGN: Database analysis. METHODS: We identified novel drugs that the FDA approved in 2018 and categorized them as follows: cancer treatment, orphan drug, included in an expedited review program, and biosimilar. Using a data set of 17 large health plans' drug coverage policies and formularies, we examined coverage 1 year following FDA approval. RESULTS: The FDA approved 66 drugs in 2018 (5 were not yet marketed 1 year following approval). For 60 of 61 drugs, some plans issued coverage policies whereas other plans included the drug in their formularies. Plans imposed restrictions (eg, step therapy) in 37% (275/742) of coverage policies. Plans covered biosimilars, orphan drugs, and cancer treatments more generously than drugs not in those categories (P < .05). Plans imposed restrictions in their policies with different frequencies (range, 7%-52%). Plans imposed utilization management (UM) in 82% (3837/4697) of formulary entries. Of those entries, plans required prior authorizations in 98%, included drugs on the highest patient co-payment tier in 70%, and imposed step therapy in 3%. Plans most often placed orphan drugs and cancer treatments on the highest cost-sharing formulary tiers (68% and 64% of the time, respectively). Plans imposed UM in their formularies with different frequencies (range, 62%-100% of entries). CONCLUSIONS: Health plans imposed fewer coverage restrictions on cancer treatments, orphan drugs, and biosimilars than on drugs not in those categories. Some plans covered 2018 FDA-approved drugs more generously than others, which has implications for patients' access to innovative therapies.

Use of prescriber requirements among US commercial health plans.

BACKGROUND: Prescriber requirements are a form of utilization management (UM) in which health plans require that a certain type of physician (eg, a rheumatologist) prescribe a drug. OBJECTIVE: To examine how a set of US commercial health plans impose prescriber requirements in their specialty drug coverage decisions. METHODS: We identified specialty drug coverage decisions from the Tufts Medical Center Specialty Drug Evidence and Coverage (SPEC) Database. SPEC includes coverage information issued by 17 large US commercial health plans. We categorized prescriber requirements as the following: (1) the drug must be prescribed in consultation, supervision, or coordination with a specialist; (2) the drug must be prescribed by a specialist (eg, a neurologist); or (3) the drug must be prescribed by a specialist with particular expertise (eg, a neurologist with expertise in spinal muscular atrophy). First, we examined how often each plan imposed prescriber requirements. Second, we determined the degree of specialization that plans required prescribing physicians to have. Third, we used Pearson's chi-square tests to examine the association between plans' use of prescriber requirements and the following drug characteristics: cancer treatment, orphan indication, pediatric indication, drug approved in the last year, black box warning, and self-administered formulation. RESULTS: Overall, health plans imposed prescriber requirements in 22.0% (1,844/8,383) of their coverage decisions, although the frequency that they did so varied (range: 0.8%-86.0%). Of prescriber requirements, 79.1% (1,459/1,844) required that the drug be prescribed in consultation, supervision, or coordination with a specialist; 18.3% (338/1,844) required that the drug be prescribed by a specialist; and 2.6% (47/1,844) required that the drug be prescribed by a specialist with particular expertise. Plans were more likely to impose prescriber requirements for drugs with the following characteristics: indicated for a pediatric population, black box warning, self-administered, and noncancer treatments (all P < 0.001). CONCLUSIONS: Health plans varied in the frequency that they imposed prescriber requirements in their specialty drug coverage decisions and with respect to the degree of specialization they required prescribing physicians to have. DISCLOSURES: This study was funded by the Center for the Evaluation of Value and Risk in Health at Tufts Medical Center. The center receives funding from a variety of sources, including government agencies, foundations, and pharmaceutical and device companies. The SPEC Database, which provided data for this study, is funded in part through a data subscription program to which a number of pharmaceutical companies subscribe. All authors are employed by the Center for the Evaluation of Value and Risk in Health. In addition, Chambers reports speaker fees from Astellas and consulting fees from Biogen and Lundbeck. The other authors have nothing to disclose. An earlier version of this study was presented as a poster at the AMCP 2021 Virtual Meeting, April 12-16, 2021.

Variation in access to hemophilia A treatments in the United States.

BACKGROUND: US commercial health plans have been found to vary in how they cover specialty drugs indicated for a range of diseases. In this study, we examined patients' access to hemophilia A (HemA) treatments across a set of large commercial health plans. OBJECTIVE: To examine variation in health plans' coverage policies for HemA treatments. METHODS: We reviewed HemA treatment coverage policies (current as of August 2019) issued by 17 commercial health plans primarily using the Tufts Medical Center Specialty Drug Evidence and Coverage Database. We categorized policies as: covered without conditions (coverage consistent with the FDA label); covered with conditions (conditions on coverage beyond the FDA label); broader coverage (coverage for a broader patient population than the FDA label); and mixed (conditions on coverage beyond the FDA label in one way, but coverage was broader than the FDA label in another). RESULTS: We identified 296 coverage policies for 26 HemA treatments, including 15 short half-life factor VIII (FVIII) products, five extended half-life FVIII products, three bypassing agents, two desmopressin products, and emicizumab. We classified 36% of policies as coverage without conditions, 50% as covered with conditions, 7% as broader coverage, and 7% as mixed. Plans applied conditions on coverage with different frequencies: two did not apply conditions in any policies; ten applied conditions in ≥50%; four applied conditions in <40%. One plan did not publish coverage policies for any HemA products. Conditions on coverage most often related to bleeding frequency (36%), although specific requirements varied. Plans applied step therapy protocols in 17% of policies. CONCLUSIONS: How health plans covered HemA treatments varied. Plans added conditions on coverage beyond the FDA label roughly half the time. Conditions most often related to bleeding frequency. Variable coverage affects patients' access to treatment, and potentially has clinical implications on disease management and disease progression.

Variation in health plan coverage of ESAs for anemia due to chronic kidney disease.

BACKGROUND: Because health plans each issue their own policies, drug coverage can vary. This variation can result in patients having unequal access to treatment. In this study, we evaluate commercial health plans' coverage policies for erythropoiesis-stimulating agents (ESAs) for patients with anemia resulting from chronic kidney disease (CKD). OBJECTIVES: To assess how a set of US commercial health plans cover ESAs for patients with anemia due to CKD. Our second objective was to examine the evidence that the plans reviewed when formulating their coverage policies. METHODS: We used the Tufts Medical Center Specialty Drug and Evidence and Coverage Database to identify coverage policies issued by 17 of the largest US commercial health plans for ESAs. The following drugs were indicated for anemia due to CKD: darbepoetin alfa, methoxy polyethylene glycol-epoetin beta, epoetin alfa (available as two brands), and epoetin alfa-epbx. Coverage policies were current as of May 2019. We determined whether the health plans applied any restrictions, such as step therapy protocols or patient subgroup restrictions, in their coverage policies. We categorized the evidence that plans cited to support their policies into seven categories: randomized controlled trials (RCTs), real-world evidence (RWE) studies (studies based on data collected in a real-world setting), other clinical studies (eg, single arm trials), systematic reviews and/or meta-analyses, clinical or treatment guidelines, health technology assessments, and economic evaluations. RESULTS: We categorized 72.5% of coverage policies (58/80 policies) as equivalent to the FDA label and 27.5% (22/80 policies) as more restrictive. In restricted policies, plans most often applied step therapy protocols (18/22 policies), followed by prescriber requirements (4/22 policies), and patient subgroup restrictions (3/22 policies). Five health plans applied restrictions in at least half of their coverage policies; seven plans did not apply restrictions in any policy. Plans that cited evidence reviewed an average of 10 citations across their ESA coverage policies, ranging from one to 29 studies. Plans varied with respect to the types of cited studies: at least 50% of evidence cited by five health plans was RCTs, while half or more of the evidence cited by four health plans was clinical or treatment guidelines. CONCLUSIONS: Health plans varied in how they covered ESAs for patients with anemia due to CKD and in the evidence cited in their coverage policies. Inconsistencies in plans' coverage policies may have implications for patients' access to ESAs. DISCLOSURES: This study was funded by Otsuka Pharmaceutical Development and Commercialization. Sanon, Redmond, and Mogahadam are employed by Otsuka Pharmaceutical. Michalopoulos was employed by Otsuka Pharmaceutical at the time of this study. Margaretos, Panzer, and Chambers are employed by Tufts Medical Center, Institute for Clinical Research and Health Policy Studies, Center for the Evaluation of Value and Risk in Health. Lai was with Tufts Medical Center, Institute for Clinical Research and Health Policy Studies, Center for the Evaluation of Value and Risk in Health at the time of this study.

Limited role of patient input in specialty drug coverage policies.

BACKGROUND: Despite increased financial contributions towards care, consumers' role in shaping their insurance benefits is unclear. OBJECTIVE: To examine the role played by patient input when US commercial health plans formulate specialty drug coverage policies, along with the benefits and challenges of considering this input. METHODS: We employed a parallel, mixed-methods approach. First, we reviewed health plans' policy development processes as reported on their websites. Second, we reviewed a data set of private health plan coverage decisions for specialty drugs and examined whether the evidence cited in policies included patient-reported outcomes (eg, health-related quality of life endpoints) and patient-based methodological designs (eg, interviews or surveys of patients). Third, we performed a survey (N = 21 respondents) and interviews (N = 5 interviewees) with plan decision-makers to determine the current role of patient input in plan decision-making, and the benefits and challenges of incorporating this data when formulating specialty drug coverage policies. RESULTS: We found that plans do not commonly solicit patient input when developing coverage policies, with only two instances of limited interaction between plans and patients or members. 1,316 (9%) of the studies plans cited in their specialty drug coverage policies included at least one patient-reported endpoint, and 0.4% (N = 62) used a patient-based methodological design. Of studies with patient-based designs, 40 used interviews, 26 included surveys/questionnaires, and one concerned shared decision-making (design categories not mutually exclusive). Almost half of the survey respondents reported having never engaged with patients or members when developing coverage policies. Among respondents who had engaged with patients or members, most reported doing so only rarely. The survey and interviews highlighted various benefits of soliciting patient input, including the value of obtaining a humanistic perspective, and several challenges, including resource requirements and the quality of obtained information. CONCLUSIONS: We found a notable lack of patient and member engagement by commercial health plans when formulating drug coverage policies. Survey respondents and interviewees identified benefits of accounting for patients' and plan members' values and preferences in specialty drug coverage policies, but also reported a number of important challenges to doing so. DISCLOSURES: National Pharmaceutical Council provided funding for this research.

Growth and capacity for cost-effectiveness analysis in Africa.

As economic evaluation becomes increasingly essential to support universal health coverage (UHC), we aim to understand the growth, characteristics, and quality of cost-effectiveness analyses (CEA) conducted for Africa and to assess institutional capacity and relationship patterns among authors. We searched the Tufts Medical Center CEA Registries and four databases to identify CEAs for Africa. After extracting relevant information, we examined study characteristics, cost-effectiveness ratios, individual and institutional contribution to the literature, and network dyads at the author, institution, and country levels. The 358 identified CEAs for Africa primarily focused on sub-Saharan Africa (96%) and interventions for communicable diseases (77%). Of 2,121 intervention-specific ratios, 8% were deemed cost-saving, and most evaluated immunizations strategies. As 64% of studies included at least one African author, we observed widespread collaboration among international researchers and institutions. However, only 23% of first authors were affiliated with African institutions. The top producers of CEAs among African institutions are more adherent to methodological and reporting guidelines. Although economic evidence in Africa has grown substantially, the capacity for generating such evidence remains limited. Increasing the ability of regional institutions to produce high-quality evidence and facilitate knowledge transfer among African institutions has the potential to inform prioritization decisions for designing UHC.

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.

Little Consistency In Evidence Cited By Commercial Plans For Specialty Drug Coverage.

We found wide variation in the evidence that US commercial health plans reported reviewing in their specialty drug coverage policies. There was little consistency in the numbers or types of studies cited by health plans. On average, only 15 percent of health plans' coverage policies cited the same study evaluating a specific drug for a specific indication.

Variation in US private health plans' coverage of orphan drugs.

OBJECTIVES: To compare coverage of orphan and nonorphan drugs, to examine variation in orphan drug coverage across the largest US private plans, and to evaluate factors influencing coverage decisions. STUDY DESIGN: Database and regression analyses. METHODS: We analyzed a data set of private health plan coverage decisions for specialty drugs (N = 5000) in 3 ways. First, we compared the frequency with which plans applied restrictions in their decisions for orphan and nonorphan drugs. Second, we examined variation in the frequency with which 17 of the largest 20 private plans applied coverage restrictions for orphan drugs. Third, we used multivariate regression to examine factors associated with restricted orphan drug coverage. RESULTS: Health plans are less likely to restrict orphan drugs compared with nonorphan drugs. Of orphan drug decisions (n = 2168), plans did not apply coverage restrictions in 70% of cases, applied restrictions in 29%, and did not cover in 1%. In contrast, of nonorphan drug decisions (n = 2832), plans did not apply coverage restrictions in 53% of cases, applied restrictions in 41%, and did not cover in 6%. The frequency of restrictions for orphan drugs varied from 11% to 65% across plans. The attributes of orphan drugs that were more likely to be associated with restrictions than others included drugs for noncancer diseases, drugs with alternatives, self-administered drugs, drugs indicated for diseases with a higher prevalence, and drugs with higher annual costs (all P <.05). CONCLUSIONS: Health plans restrict access to orphan drugs approximately one-third of the time, and restrictions vary considerably across plans. Plans more often add restrictions for orphan drugs that are indicated for diseases with a higher prevalence and that have higher annual costs.

Comparing the cost-per-QALYs gained and cost-per-DALYs averted literatures.

Background: We examined the similarities and differences between studies using two common metrics used in cost-effectiveness analyses (CEAs): cost per quality-adjusted life year (QALY) gained and cost per disability-adjusted life year (DALY) averted. Methods: We used the Tufts Medical Center CEA Registry, which contains English-language cost-per-QALY gained studies, and the Global Cost-Effectiveness Analysis (GHCEA) Registry, which contains cost-per-DALY averted studies. We examined study characteristics, including intervention type, sponsor, country, and primary disease, and also compared the number of published CEAs to disease burden for major diseases and conditions across geographic regions. Results: We identified 6,438 cost-per-QALY and 543 cost-per-DALY studies published through 2016 and observed rapid growth for both literatures. Cost-per-QALY studies most often examined pharmaceuticals and interventions in high-income countries. Cost-per-DALY studies predominantly focused on infectious disease interventions and interventions in low and lower-middle income countries. We found that while diseases imposing a larger burden tend to receive more attention in the cost-effectiveness analysis literature, the number of publications for some diseases and conditions deviates from this pattern, suggesting "under-studied" conditions (e.g., neonatal disorders) and "over-studied" conditions (e.g., HIV and TB). Conclusions: The CEA literature has grown rapidly, with applications to diverse interventions and diseases.  The publication of fewer studies than expected for some diseases given their imposed burden suggests funding opportunities for future cost-effectiveness research.