Presentation by Tamara Hayford, Chief of CBO’s Health Policy Studies Unit, at the Association for Public Policy Analysis & Management 2021 Annual Research Meeting.
Presentation by Chapin White, CBO's Deputy Director of Health Analysis, to the Leadership Fellowship Program at the National Hispanic Medical Association.
Presentation by Alice Burns and Jaeger Nelson, analysts in CBO’s Budget Analysis Division and Macroeconomic Analysis Division, to the National Tax Association.
Presentation by Kathleen Burke, John McClelland, and Jennifer Shand, analysts in CBO’s Tax Analysis Division, to the National Association of Legislative Fiscal Offices.
Presentation by Heidi Golding, an analyst in CBO’s National Security Division, at the Southern Economic Association Annual Meeting.
In this presentation, CBO provides background information on the VA health care system and past spending and describes 10-year projections by CBO on VA health spending under three different scenarios. CBO finds that, under certain assumptions, future spending required to treat veterans may be substantially higher (in inflation-adjusted dollars) than recent appropriations.
CBO uses its microsimulation tax model to simulate the effects of tax rules for a representative sample of tax filers in each year of the budget window. The model informs much of CBO’s analysis of the individual income and payroll tax system.
Presentation by Chapin White, CBO's Deputy Director of Health Analysis, to the Leadership Fellowship Program at the National Hispanic Medical Association.
Presentation by Alice Burns and Jaeger Nelson, analysts in CBO’s Budget Analysis Division and Macroeconomic Analysis Division, to the National Tax Association.
Presentation by Kathleen Burke, John McClelland, and Jennifer Shand, analysts in CBO’s Tax Analysis Division, to the National Association of Legislative Fiscal Offices.
Presentation by Heidi Golding, an analyst in CBO’s National Security Division, at the Southern Economic Association Annual Meeting.
In this presentation, CBO provides background information on the VA health care system and past spending and describes 10-year projections by CBO on VA health spending under three different scenarios. CBO finds that, under certain assumptions, future spending required to treat veterans may be substantially higher (in inflation-adjusted dollars) than recent appropriations.
CBO uses its microsimulation tax model to simulate the effects of tax rules for a representative sample of tax filers in each year of the budget window. The model informs much of CBO’s analysis of the individual income and payroll tax system.
Presentation by Chris Adams, an analyst in CBO’s Health Analysis Division, to the Health Economics Seminar Cosponsored by Boston University, Harvard University, and the Massachusetts Institute of Technology.
CBO’s health insurance simulation model (HISIM) generates estimates of health insurance coverage and premiums for the population under age 65. HISIM is used to help develop baseline projections (which incorporate the assumption that current law generally remains the same) and also to model proposed changes in policies that affect health insurance coverage.
Currently, CBO is developing and testing a new version of HISIM to respond to continued Congressional interest in understanding the effects of legislative proposals that significantly affect health insurance coverage. The new model will be used to help develop CBO’s spring 2019 baseline projections and subsequent cost estimates.
Presentation by Jessica Banthin, Deputy Assistant Director in CBO’s Health, Retirement, and Long-Term Analysis Division (HRLD), and Alexandra Minicozzi, Chief of HRLD’s Health Insurance Modeling Unit, to CBO’s panel of health advisers.
To prepare its spring 2019 baseline budget projections, CBO is using new sources of data as inputs and has completely revamped the way it models consumers’ and employers’ behavior. To that end, it has developed HISIM2, a new version of the model CBO uses to generate estimates of health insurance coverage and premiums for the population under age 65. The model is used in conjunction with other models to develop baseline budget projections (which incorporate the assumption that current law generally remains the same). It is also used to estimate the effects of proposed changes in policies that affect health insurance coverage.
HISIM2 incorporates new base data, including data from surveys and administrative data. It changes the way individuals and families are projected to choose among coverage options. And it changes the way firms are projected to take workers’ preferences into account when deciding whether to offer employment-based coverage.
HISIM2 is an updated version of the model CBO uses to generate estimates of health insurance coverage and premiums for people under age 65. The model is used along with other models to develop CBO’s baseline budget projections (which incorporate the assumption that current law generally remains the same). It is also used to estimate the effects of proposed changes in policies that affect health insurance coverage.
CBO's analyses of the distribution of household income rely on the Census Bureau's Current Population Survey (CPS) for information about receipt of government transfers, particularly means-tested transfers. CPS respondents underreport their receipt of those transfers, and that underreporting has increased over the past few decades. This presentation shows how CBO adjusts for the underreporting of means-tested transfers in its distributional analyses.
CBO’s new health insurance simulation model creates synthetic firms that mimic the real-world variations between firms to model employers’ decisions about whether to offer employment-based health insurance.
Presentation by Alexandra Minicozzi, a Unit Chief in CBO’s Health, Retirement, and Long-Term Analysis Division, at the 8th Annual Conference of the American Society of Health Economists.
Preventive medical services encompass a wide range of interventions, including vaccinations that prevent diseases from occurring and screening tests designed to detect the presence of a disease before symptoms appear. Delivering preventive medical services results in costs for each person using the service. Vaccinations may cause some of those people to avoid the targeted disease, and screenings may allow some people to receive treatment earlier. Those people generally benefit from preventive medical services, but the net result can be decreases or increases in overall health care spending.
In this presentation, CBO’s Director provides an overview of the agency’s methods for estimating the budgetary effects of proposals to expand the use of preventive medical services.
CBO and the Joint Committee on Taxation use HISIM2 to estimate the major sources of health insurance coverage and associated premiums for the U.S. population under age 65.
HISIM2 is used in conjunction with other models (for example, those for related taxes, Medicaid, and Medicare) to develop baseline insurance coverage projections and their associated budgetary costs. It is also used to estimate the effects of proposed changes in policies that affect health insurance coverage.
CBO uses HISIM2 to model firms’ decisions to offer health insurance as well as households’ decisions to enroll in health insurance. Like all of CBO’s models, HISIM2 is regularly updated. This slide deck describes the analytical methods used in HISIM2 to model firms’ decisions in CBO’s baseline budget projections as of March 6, 2020.
On June 11, CBO will present preliminary findings of a study of specialty drugs to be released by the agency later this year. The presentation provides information on the prices for specialty drugs, net of rebates and discounts, in Medicare Part D and Medicaid over the 2010–2015 period; the increase in net spending on specialty drugs in each program; and total net spending and out-of-pocket costs for specialty drugs among Medicare Part D enrollees who use such drugs.
Presentation by Anna Anderson-Cook, Jared Maeda, and Lyle Nelson (all of CBO’s Health, Retirement, and Long-Term Analysis Division) at the conference of the American Society of Health Economists.
Presentation by Michael Cohen, an analyst in CBO’s Health Analysis Division, and Tamara Hayford, Chief of CBO’s Health Policy Studies Unit, at the Congressional Research Service.
Presentation by Chris Adams, an analyst in CBO’s Health Analysis Division, to the Health Economics Seminar Cosponsored by Boston University, Harvard University, and the Massachusetts Institute of Technology.
CBO’s health insurance simulation model (HISIM) generates estimates of health insurance coverage and premiums for the population under age 65. HISIM is used to help develop baseline projections (which incorporate the assumption that current law generally remains the same) and also to model proposed changes in policies that affect health insurance coverage.
Currently, CBO is developing and testing a new version of HISIM to respond to continued Congressional interest in understanding the effects of legislative proposals that significantly affect health insurance coverage. The new model will be used to help develop CBO’s spring 2019 baseline projections and subsequent cost estimates.
Presentation by Jessica Banthin, Deputy Assistant Director in CBO’s Health, Retirement, and Long-Term Analysis Division (HRLD), and Alexandra Minicozzi, Chief of HRLD’s Health Insurance Modeling Unit, to CBO’s panel of health advisers.
To prepare its spring 2019 baseline budget projections, CBO is using new sources of data as inputs and has completely revamped the way it models consumers’ and employers’ behavior. To that end, it has developed HISIM2, a new version of the model CBO uses to generate estimates of health insurance coverage and premiums for the population under age 65. The model is used in conjunction with other models to develop baseline budget projections (which incorporate the assumption that current law generally remains the same). It is also used to estimate the effects of proposed changes in policies that affect health insurance coverage.
HISIM2 incorporates new base data, including data from surveys and administrative data. It changes the way individuals and families are projected to choose among coverage options. And it changes the way firms are projected to take workers’ preferences into account when deciding whether to offer employment-based coverage.
HISIM2 is an updated version of the model CBO uses to generate estimates of health insurance coverage and premiums for people under age 65. The model is used along with other models to develop CBO’s baseline budget projections (which incorporate the assumption that current law generally remains the same). It is also used to estimate the effects of proposed changes in policies that affect health insurance coverage.
CBO's analyses of the distribution of household income rely on the Census Bureau's Current Population Survey (CPS) for information about receipt of government transfers, particularly means-tested transfers. CPS respondents underreport their receipt of those transfers, and that underreporting has increased over the past few decades. This presentation shows how CBO adjusts for the underreporting of means-tested transfers in its distributional analyses.
CBO’s new health insurance simulation model creates synthetic firms that mimic the real-world variations between firms to model employers’ decisions about whether to offer employment-based health insurance.
Presentation by Alexandra Minicozzi, a Unit Chief in CBO’s Health, Retirement, and Long-Term Analysis Division, at the 8th Annual Conference of the American Society of Health Economists.
Preventive medical services encompass a wide range of interventions, including vaccinations that prevent diseases from occurring and screening tests designed to detect the presence of a disease before symptoms appear. Delivering preventive medical services results in costs for each person using the service. Vaccinations may cause some of those people to avoid the targeted disease, and screenings may allow some people to receive treatment earlier. Those people generally benefit from preventive medical services, but the net result can be decreases or increases in overall health care spending.
In this presentation, CBO’s Director provides an overview of the agency’s methods for estimating the budgetary effects of proposals to expand the use of preventive medical services.
CBO and the Joint Committee on Taxation use HISIM2 to estimate the major sources of health insurance coverage and associated premiums for the U.S. population under age 65.
HISIM2 is used in conjunction with other models (for example, those for related taxes, Medicaid, and Medicare) to develop baseline insurance coverage projections and their associated budgetary costs. It is also used to estimate the effects of proposed changes in policies that affect health insurance coverage.
CBO uses HISIM2 to model firms’ decisions to offer health insurance as well as households’ decisions to enroll in health insurance. Like all of CBO’s models, HISIM2 is regularly updated. This slide deck describes the analytical methods used in HISIM2 to model firms’ decisions in CBO’s baseline budget projections as of March 6, 2020.
On June 11, CBO will present preliminary findings of a study of specialty drugs to be released by the agency later this year. The presentation provides information on the prices for specialty drugs, net of rebates and discounts, in Medicare Part D and Medicaid over the 2010–2015 period; the increase in net spending on specialty drugs in each program; and total net spending and out-of-pocket costs for specialty drugs among Medicare Part D enrollees who use such drugs.
Presentation by Anna Anderson-Cook, Jared Maeda, and Lyle Nelson (all of CBO’s Health, Retirement, and Long-Term Analysis Division) at the conference of the American Society of Health Economists.
Presentation by Michael Cohen, an analyst in CBO’s Health Analysis Division, and Tamara Hayford, Chief of CBO’s Health Policy Studies Unit, at the Congressional Research Service.
Dr Dev Kambhampati | Medicare- High Expenditure Part B DrugsDr Dev Kambhampati
Dr Dev Kambhampati | Medicare- High Expenditure Part B Drugs
GAO STUDY- In 2010, the 55 highest-expenditure Part B drugs represented $16.9 billion in spending, or about 85 percent of all Medicare spending on Part B drugs, which totaled $19.5 billion. The number of Medicare beneficiaries who received each of these drugs varied from 15.2 million receiving the influenza vaccines to 660 hemophilia A patients receiving a group of biologicals known collectively as factor viii recombinant, which had the largest average annual cost per beneficiary--$217,000. Our analysis showed that most of the 55 drugs increased in expenditures, prices, and average annual cost per beneficiary from 2008 to 2010. The 5 drugs with the largest increase in Medicare expenditures over this time period also had the largest increase in the number of beneficiaries receiving each drug. Four of the 10 drugs which showed the greatest increase in expenditures were also among the 10 drugs showing the greatest price increases.
Spending on Medicare beneficiaries accounted for the majority of estimated total U.S. spending for 35 of the 55 highest-expenditure Part B drugs in 2010. For 17 of the 35, Medicare spending accounted for more than two-thirds of total U.S. spending, defined as spending by the insured population in the United States.
Topic Position paper on Proposition 8Number of Pages 1 (Dou.docxAASTHA76
Topic: Position paper on Proposition 8
Number of Pages: 1 (Double Spaced)
Number of sources: 3
Writing Style: APA
Type of document: Essay
Academic Level:Master
Category: Nursing
Language Style: English (U.S.)
Order Instructions: Attached
1.
Position Paper Written Assignment :
A position paper is a document you could present to a legislator to seek support for an issue you endorse. Present your position on a current health-care issue in a one-page paper, following the assignment guidelines below.
You can select your issue topic from newspapers, national news magazine articles, professional journals, or professional association literature; and this can be the topic you choose for your ethical issues debate.
Your position paper should:
•
Be quickly and easily understood.
•
Be succinct and clear.
•
Appear very professional with the legislator’s name and title on top and your name and your credentials at the bottom.
•
Condense essential information in one, single-spaced page, excluding the title and reference list pages.
•
Be written using correct grammar, spelling, punctuation, syntax, and APA format.
•
Clearly describe the issue that you are addressing in the opening paragraph.
•
Include 3–4 bullet points regarding why you are seeking the legislator’s vote, support, or opposition. Bullet points should be clear and concise but not repetitive and should reflect current literature that substantiates your position.
•
Summarize the implications for the nursing profession and/or patients.
•
Conclude with two recommendations that you wish to see happen related to your issue, such as a vote for or against, a change in policy, or the introduction of new legislation.
•
Use APA format (6th ed.), correct grammar, and references as appropriate.
The literature you cite must be from peer-reviewed journals and primary source information. You may use this paper as preliminary research for your ethical issues debate project that occurs in weeks 4-7.
Name the dependent and the main independent variables (identify them separately).
The dependent variable was policy indicator for expansion of Medicaid in twenty-six states; (they consider also the non- or late-expansion states, otherwise what would they use to compare these 26 Medicaid-expansion states to?) Independent variables were Medicaid spending on prescription drugs. Take a look and decide whether you need to switch your independent and dependent variables. What is the outcome here? That would be your dependent variable.
What is one of the main hypotheses? What is the treatment/stimulus? State them in your own words.
The hypothesis is to determine the growth of Medicaid drug spending in Medicaid expansion states. The stimulus is the use of Medicaid insurance. Hypothesis looks good but you need to rethink about the stimulus. Stimulus is the same as the treatment, or the independent variable.
Name the treatment and the comparison groups (identify them separately). Explain the r.
Prescription Medicines - Costs in Context January 2019PhRMA
Discussions about costs are important. We recognize that many are struggling to access the medicine they need, and have important questions about their medicine costs. And we want to help find the answers.
Prescription Medicines - Costs In Context March 2019PhRMA
Discussions about costs are important. We recognize that many are struggling to access the medicine they need, and have important questions about their medicine costs. And we want to help find the answers.
Prescription Medicines Costs in Context - June 2019PhRMA
We are in a new era of medicine where breakthrough science is transforming care with innovative treatment approaches and enabling us to more effectively treat chronic disease, the biggest cost driver.
Presentation by Jared Jageler, David Adler, Noelia Duchovny, and Evan Herrnstadt, analysts in CBO’s Microeconomic Studies and Health Analysis Divisions, at the Association of Environmental and Resource Economists Summer Conference.
Presentation by Mark Hadley, CBO's Chief Operating Officer and General Counsel, at the 2nd NABO-OECD Annual Conference of Asian Parliamentary Budget Officials.
Presentation by Daria Pelech, an analyst in CBO’s Health Analysis Division, at the Center for Health Insurance Reform McCourt School of Public Policy, Georgetown University.
This slide deck highlights CBO’s key findings about the outlook for the economy as described in its new report, The Budget and Economic Outlook: 2024 to 2034.
Presentation by CBO analysts Rebecca Heller, Shannon Mok, and James Pearce, and Census Bureau research economist Jonathan Rothbaum at the American Economic Association Annual Meeting, Committee on Economic Statistics.
Presentation by Eric J. Labs, an analyst in CBO’s National Security Division, at the Bank of America 2024 Defense Outlook and Commercial Aerospace Forum.
Presentation by Elizabeth Ash, William Carrington, Rebecca Heller, and Grace Hwang of CBO’s Labor, Income Security, and Long-Term Analysis and Health Analysis divisions to the Children’s Health Group, American Academy of Pediatrics.
Presentation by Molly Dahl, Chief of CBO’s Long-Term Analysis Unit, at a meeting of the National Conference of State Legislatures’ Budget Working Group.
In the President’s 2024 budget request, total military compensation is $551 billion, including veterans' benefits. That amount represents an increase of 134 percent since 1999 after removing the effects of inflation.
A process server is a authorized person for delivering legal documents, such as summons, complaints, subpoenas, and other court papers, to peoples involved in legal proceedings.
What is the point of small housing associations.pptxPaul Smith
Given the small scale of housing associations and their relative high cost per home what is the point of them and how do we justify their continued existance
Jennifer Schaus and Associates hosts a complimentary webinar series on The FAR in 2024. Join the webinars on Wednesdays and Fridays at noon, eastern.
Recordings are on YouTube and the company website.
https://www.youtube.com/@jenniferschaus/videos
Russian anarchist and anti-war movement in the third year of full-scale warAntti Rautiainen
Anarchist group ANA Regensburg hosted my online-presentation on 16th of May 2024, in which I discussed tactics of anti-war activism in Russia, and reasons why the anti-war movement has not been able to make an impact to change the course of events yet. Cases of anarchists repressed for anti-war activities are presented, as well as strategies of support for political prisoners, and modest successes in supporting their struggles.
Thumbnail picture is by MediaZona, you may read their report on anti-war arson attacks in Russia here: https://en.zona.media/article/2022/10/13/burn-map
Links:
Autonomous Action
http://Avtonom.org
Anarchist Black Cross Moscow
http://Avtonom.org/abc
Solidarity Zone
https://t.me/solidarity_zone
Memorial
https://memopzk.org/, https://t.me/pzk_memorial
OVD-Info
https://en.ovdinfo.org/antiwar-ovd-info-guide
RosUznik
https://rosuznik.org/
Uznik Online
http://uznikonline.tilda.ws/
Russian Reader
https://therussianreader.com/
ABC Irkutsk
https://abc38.noblogs.org/
Send mail to prisoners from abroad:
http://Prisonmail.online
YouTube: https://youtu.be/c5nSOdU48O8
Spotify: https://podcasters.spotify.com/pod/show/libertarianlifecoach/episodes/Russian-anarchist-and-anti-war-movement-in-the-third-year-of-full-scale-war-e2k8ai4
This session provides a comprehensive overview of the latest updates to the Uniform Administrative Requirements, Cost Principles, and Audit Requirements for Federal Awards (commonly known as the Uniform Guidance) outlined in the 2 CFR 200.
With a focus on the 2024 revisions issued by the Office of Management and Budget (OMB), participants will gain insight into the key changes affecting federal grant recipients. The session will delve into critical regulatory updates, providing attendees with the knowledge and tools necessary to navigate and comply with the evolving landscape of federal grant management.
Learning Objectives:
- Understand the rationale behind the 2024 updates to the Uniform Guidance outlined in 2 CFR 200, and their implications for federal grant recipients.
- Identify the key changes and revisions introduced by the Office of Management and Budget (OMB) in the 2024 edition of 2 CFR 200.
- Gain proficiency in applying the updated regulations to ensure compliance with federal grant requirements and avoid potential audit findings.
- Develop strategies for effectively implementing the new guidelines within the grant management processes of their respective organizations, fostering efficiency and accountability in federal grant administration.
The Contribution of Changes in Drug Mix and Price Growth to the Rising Costs of Brand-Name Drugs in Medicare Part D
1. Presentation at the Association for Public Policy Analysis & Management
2021 Annual Research Meeting
March 28, 2022
Tamara Hayford
Health Analysis Division
The Contribution of Changes in
Drug Mix and Price Growth to the
Rising Costs of Brand-Name Drugs in
Medicare Part D
For information about the meeting, see www.appam.org/conference-events/fall-research-conference/the-power-of-inclusion/.
2. 1
The information presented here is preliminary and is being circulated to stimulate
discussion and critical comment.
This presentation has not been subject to CBO’s regular review and editing
process. The views expressed here should not be interpreted as CBO’s.
I am grateful to Yash Patel (formerly of CBO) and Joshua Varcie for research
assistance, and to Ru Ding for programming assistance.
For related work, see Congressional Budget Office, Prices for and Spending
on Specialty Drugs in Medicare Part D and Medicaid (March 2019),
www.cbo.gov/publication/54964.
Disclaimer and Acknowledgments
3. 2
1. Because data for 2019 are incomplete, the per-enrollee and per-user analysis ends in 2017.
Examine growth in net spending and average net prescription costs for brand-
name specialty drugs in Medicare Part D from 2015 to 2019 and compare it with
growth over the 2010‒2015 period.
Examine changes in net per-enrollee and per-user spending on brand-name
specialty drugs in Medicare Part D from 2010 to 2017.1
Study Objectives
4. 3
Brand-name specialty drugs accounted for an increasing share of net Part D
spending from 2010 to 2019.
Net price growth was slower over the 2015‒2019 period than over the
2010‒2015 period.
Net price growth was the primary driver of increased average costs of a
prescription for a brand-name specialty drug from 2015 to 2019. In contrast,
increased use of more-expensive drugs was the primary driver from 2010 to
2015.
Price growth for brand-name specialty drugs over the two analytical periods was
more closely aligned when drugs that treat Hepatitis C were excluded.
Overall, per capita and per-user spending on brand-name specialty drugs
continued to increase from 2015 to 2017, but at a slower rate than occurred over
the 2010‒2015 period.
Key Findings
5. 4
In the analysis of drug prices and spending in Medicare Part D, drugs were identified by National Drug Code (NDC). Red Book data are available from IBM Micromedex and include
list prices (such as the wholesale acquisition cost), as well as drug characteristics (such as the product name, manufacturer, dosage form, and strength) by NDC.
Medicare Part D: Beneficiary-level claims data for the entire Part D population
and confidential data on manufacturers’ rebates and other discounts by drug for
the 2010‒2019 period.
IQVIA (formerly IMS Health): List of specialty drugs on the market in 2015.
Red Book: Drug characteristics, including an active ingredient identifier and a
brand/generic identifier by National Drug Code.
Data
6. 5
1. IQVIA is a private company that provides data services and health care analysis.
CBO used a definition of specialty drugs that was developed by the IQVIA
Institute for Human Data Science.1
By that definition, a specialty drug treats a chronic, complex, or rare condition
and has at least four of the following seven characteristics:
▪ Costs at least $6,000 per year,
▪ Is initiated or maintained by a specialist,
▪ Is administered by a health care professional,
▪ Requires special handling in the supply chain,
▪ Is associated with a patient payment-assistance program,
▪ Is distributed through nontraditional channels (such as a specialty
pharmacy), or
▪ Requires monitoring or counseling.
We used those criteria to identify which new drugs (entering the market between
2016 and 2019) are specialty drugs.
Defining and Identifying Specialty Drugs
7. 6
1. Drugs are defined on the basis of product name, dosage form, route of administration, and strength.
Calculate net Part D spending, the number of standardized 30-day prescriptions,
and average net prices for all brand-name drugs.
Classify drug status along two dimensions: new/older and specialty/nonspecialty.
Merge data for different years at the drug level to analyze changes in prices and
composition of use.1
Decompose increases in average net prescription costs into contributions from:
▪ Price increases,
▪ Changes in the mix of drugs on the market at the beginning of the
analytical period, and
▪ The introduction of new drugs.
Calculate year-over-year price increases for the 2015‒2019 period and compare
with the 2010‒2015 period.
Methods
8. 7
Source: Author’s analysis of Medicare Part D claims data, as well as data on discounts and rebates.
Net Per Capita Spending on Brand-Name Drugs in Medicare Part D
in 2010, 2015, and 2019
Net per capita spending on brand-name
specialty drugs continued to increase from
2015 to 2019, but at a slower rate.
Similarly, overall net spending on brand-
name specialty drugs increased from
$33.6 billion in 2015 to $46.8 billion in
2017. (Net spending was $9.4 billion in
2010.)
330
1,660
1,990
850
1,110
1,960
880
1,030
1,910
0
500
1,000
1,500
2,000
2,500
Specialty Nonspecialty Total
2010 2015 2019
2019 dollars
9. 8
Source: Author’s analysis of Medicare Part D claims data, as well as data on discounts and rebates.
Share of Net Part D Spending and Standardized Prescriptions
Attributable to Brand-Name Specialty Drugs
12
0.48
30
0.42
37
0.44
0
5
10
15
20
25
30
35
40
Share of Net Spending on Brand-Name
Specialty Drugs
Share of Standardized Prescriptions for Brand-
Name Specialty Drugs
2010 2015 2019
Percent
10. 9
Source: Author’s analysis of Medicare Part D claims data, as well as data on discounts and rebates.
n.a. = not applicable.
a. Older drugs are those on the market at the beginning of each analytical period. b. New drugs are those that were introduced during an analytical period.
Average Net Cost of a Brand-Name Prescription for Specialty and
Nonspecialty Drugs Over the 2010‒2019 Period in Medicare Part D
2019 Dollars
2010‒2015 Period 2015‒2019 Period
Average Net
Price in 2010
Average Net
Price in 2015
Compound
Annual Growth
(%), 2010 to
2015
Average Net
Price in 2015
Average Net
Price in 2019
Compound
Annual Growth
(%), 2015 to
2019
Brand-Name Specialty Drugs
All drugs 1,400 3,820 22.3 3,820 4,260 2.7
Older drugsa 1,400 2,740 14.4 3,820 4,160 2.1
New drugsb n.a. 8,930 n.a. n.a. 5,000 n.a.
Brand-Name Nonspecialty Drugs
All drugs 139 176 4.5 176 179 0.4
Older drugsa 139 171 4.0 176 173 -0.4
New drugsb n.a. 224 n.a. n.a. 634 n.a.
11. 10
Source: Author’s analysis of Medicare Part D claims data, as well as data on discounts and rebates.
Decomposing Changes in the Average Prescription Price of Brand-
Name Specialty Drugs in Part D Over the Two Analytical Periods
1,400
3,820
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
2010 2015 2015 2019
Shift Toward
New Drugs (1,090)
Shift Toward
New Drugs (100)
Shift Toward Higher-Priced
Drugs on the Market
in 2010 (800)
Shift Toward
Higher-Priced
Drugs on the
Market in 2015 (60)
Price Increases for Drugs
on the Market in 2010 (540)
Price Increases for
Drugs on the Market
in 2015 (280)
2015 Average
Prescription
Price (3,820)
2010 Average
Prescription
Price (1,400)
Average Prices In 2019 Dollars
12. 11
Source: Author’s analysis of Medicare Part D claims data, as well as data on discounts and rebates.
Average Annual Increase in Retail and Net Prices for Brand-Name
Drugs in Part D for Two Analytical Periods
10.0
8.5
10.4
7.0
5.8
7.4
5.5
4.7
6.0
1.1
2.5
-0.4
-2.0
0.0
2.0
4.0
6.0
8.0
10.0
12.0
Overall Specialty Nonspecialty Overall Specialty Nonspecialty
Percent
2010 to 2015 2015 to 2019
Retail Prices Net Prices
13. 12
Source: Author’s analysis of Medicare Part D claims data, as well as data on discounts and rebates.
Discounts and Rebates as a Share of Retail Spending on
Brand-Name Drugs in Part D
0 10 20 30 40 50 60
Overall
Specialty
Nonspecialty
Percent
2010 2015 2019
14. 13
Source: Author’s analysis of Medicare Part D claims data, as well as data on discounts and rebates.
Comparing Net Price Growth for Brand-Name Specialty Drugs Over
Two Periods, With and Without Drugs That Treat Hepatitis C
Percent
2010 to 2015 2015 to 2019
Original Analysis
Compound annual growth rate of the price of a
prescription
22.3 2.7
Average annual year-over-year price growth 5.8 2.5
Excluding Drugs That Treat Hepatitis C
Compound annual growth rate of the price of a
prescription
18.1 14.3
Average annual year-over-year price growth 7.0 4.1
15. 14
Source: Author’s analysis of Medicare Part D claims data, as well as data on discounts and rebates.
Annual Spending on Brand-Name Specialty Drugs Among Medicare
Part D Enrollees Who Used Such Drugs in 2010, 2015, and 2017
13,020
10,100
2,010
35,690
39,180
3,780
35,990
41,670
3,850
0
5,000
10,000
15,000
20,000
25,000
30,000
35,000
40,000
45,000
Per-user spending, all enrollees Per-user spending, enrollees
without cost-sharing support
Per-user out-of-pocket costs,
enrollees without cost-sharing
support
2019 Dollars
2010 2015 2017
16. 15
1. Net spending per enrollee in Part D was roughly $2,700 (in 2018 dollars) over the 2009‒2018 period. Congressional Budget Office, Prescription Drugs: Spending, Use, and Prices (January 2022),
www.cbo.gov/publication/57050.
Spending and average cost growth for brand-name specialty drugs continued to
increase after 2015, albeit at a slower rate.
▪ Slower growth was partly driven by the pricing and volume dynamics for
drugs that treat Hepatitis C.
Average cost growth fell substantially for brand-name nonspecialty drugs.
▪ Year-over-year prices fell, on average, for brand-name nonspecialty drugs
from 2015 to 2019.
Per-enrollee net spending in Part D has largely held steady in recent years.1
▪ Growing use of generic drugs offset increases in prices for brand-name
drugs.
▪ Future increases in prices for brand-name specialty drugs might have a
greater impact on Part D spending growth.
Discussion