September/October 2010, Vol 3, No 5

THE PEER-REVIEWED FORUM FOR EVIDENCE IN BENEFIT DESIGN ™ SEPTEMBER/OCTOBER 2010

VOLUME 3, NUMBER 5

FOR PAYERS, PURCHASERS, POLICYMAKERS, AND OTHER HEALTHCARE STAKEHOLDERS

EDITORIAL

U.S. Rebukes Health Insurers Janet Adamy

Resisting the Urge to Flatten Healthcare Robert E. Henry

REGULATORY

Assessment of Medicare Part D Communications to Beneficiaries ™

Meghana Aruru, PhD, MBA, BSPharm; J. Warren Salmon, PhD

Stakeholder Perspective by Jack E. Fincham, PhD, RPh BUSINESS

A Comparison of Drug Formularies and the Potential for Cost-Savings Andrea L. Kjos, PharmD, PhD; Jon C. Schommer, PhD; Yingli Yuan, PhD

Stakeholder Perspective by Jeff Januska, PharmD CLINICAL

Managing Dyslipidemia in Primary Care with Restricted Access to Lipid-Modifying Therapy John T. Lynch, MPH; Catherine E. Cooke, PharmD, BCPS, PAHM; Jonathan Rosen, MD; Sanjay Gandhi, PhD; Michael F. Bullano, PharmD

Stakeholder Perspective by Matthew Mitchell, PharmD, MBA

◆

Generic Drug Trends

◆

Industry Trends

©2010 Engage Healthcare Communications, LLC www.AHDBonline.com

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To learn more, visit us at millennium.com. ©2010 Millennium Pharmaceuticals, Inc. All rights reserved.

EDITORIAL BOARD

CLINICAL EDITOR

PHARMACY BENEFIT DESIGN

Nirav R. Shah, MD, MPH Assistant Professor of Medicine NYU School of Medicine, NYC Senior Investigator, Geisinger Health System, Danville, PA

Thomas G. McCarter, MD, FACP Chief Clinical Officer Executive Health Resources, PA

Joel V. Brill, MD Chief Medical Officer, Predictive Health, Phoenix, AZ William J. Cardarelli, PharmD Director of Pharmacy Atrius Health Harvard Vanguard Medical Associates

GOVERNMENT EDITOR

Kevin B. “Kip” Piper, MA, FACHE President, Health Results Group Sr. Counselor, Fleishman-Hillard Washington, DC

HEALTH INFORMATION TECHNOLOGY

J. B. Jones, PhD, MBA Research Associate, Geisinger Health System, Danville, PA

Leslie S. Fish, PharmD Sr. Director of Pharmacy Services Fallon Community Health Plan, MA

Victor J. Strecher, PhD, MPH Professor and Director, Center for Health Communications Research University of Michigan Schools of Public Health and Medicine, Ann Arbor Founder and Chief Visionary Officer HealthMedia, Johnson & Johnson Co.

ACTUARY

David Williams Milliman Health Consultant Windsor, CT CANCER RESEARCH

Al B. Benson, III, MD, FACP Professor of Medicine Associate Director for Clinical Investigations Robert H. Lurie Comprehensive Cancer Center, Northwestern University President, ACCC Past Chair, Board of Directors, NCCN

Michael S. Jacobs, RPh National Clinical Practice Leader Buck Consultants, Atlanta Matthew Mitchell, PharmD, MBA Manager, Pharmacy Services SelectHealth, Salt Lake City, UT

HEALTH OUTCOMES RESEARCH

Gordon M. Cummins, MS Director, IntegriChain

Paul Anthony Polansky, BSPharm, MBA Former Executive VP and Chief Pharmacy Officer, Sanovia Corp., Philadelphia, PA

Kavita V. Nair, PhD Associate Professor, School of Pharmacy University of Colorado at Denver

Samuel M. Silver, MD, PhD, FACP Professor, Internal Medicine Director, Cancer Center Network Division of Hematology/Oncology Assistant Dean for Research University of Michigan Health Systems

Scott R. Taylor, RPh, MBA Associate Director, Industry Relations Geisinger Health System, Danville, PA

Gary M. Owens, MD President, Gary Owens Associates Glen Mills, PA

POLICY & PUBLIC HEALTH

Joseph R. Antos, PhD Wilson H. Taylor Scholar in Health Care Retirement Policy American Enterprise Institute

Timothy S. Regan, BPharm, RPh Executive Director, Xcenda Palm Harbor, FL

Jack E. Fincham, PhD, RPh Professor of Pharmacy, School of Pharmacy University of Missouri, Kansas City

CARDIOLOGY RESEARCH MANAGED CARE & GOVERNMENT AFFAIRS

Michael A. Weber, MD Professor of Medicine Department of Medicine (Cardiology) State University of New York

Sharad Mansukani, MD Chief Strategic Officer, Nations Health Senior Advisor, Texas Pacific Group, FL

ENDOCRINOLOGY RESEARCH

MANAGED MARKETS

James V. Felicetta, MD Chairman, Dept. of Medicine Carl T. Hayden Veterans Affairs Medical Center, Phoenix, AZ

Jeffrey A. Bourret, MS, RPh, FASHP Senior Director, Customer Marketing & Innovation, US Specialty Customers Pfizer Specialty Business Unit, PA

EMPLOYERS

Charles E. Collins, Jr, MS, MBA Associate Director, Managed Markets Marketing, Boehringer-Ingelheim, CT

Alberto M. Colombi, MD, MPH Corporate Medical Director PPG Industries, Pittsburgh, PA

PERSONALIZED MEDICINE

F. Randy Vogenberg, RPh, PhD Principal, Institute of Integrated Healthcare Sharon, MA Senior Fellow, Jefferson School of Population Health

Wayne A. Rosenkrans, Jr, PhD Chairman and President, Personalized Medicine Coalition, Distinguished Fellow, MIT Center for Biomedical Innovation PHARMACOECONOMICS

Jeff Jianfei Guo, BPharm, MS, PhD Associate Professor of Pharmacoeconomics & Pharmacoepidemiology, College of Pharmacy, University of Cincinnati Medical Center, OH

EPIDEMIOLOGY RESEARCH

Joshua N. Liberman, PhD Vice President, Strategic Research CVS Caremark, Hunt Valley, MD

American Health & Drug Benefits

REIMBURSEMENT POLICY

William E. Fassett, BSPharm, MBA, PhD Professor of Pharmacy Law & Ethics Vice Chair, Dept. of Pharmacotherapy College of Pharmacy, Washington State University, Spokane, WA

Arthur F. Shinn, PharmD, FASCP President, Managed Pharmacy Consultants, Lake Worth, FL

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J. Warren Salmon, PhD Professor of Health Policy & Administration School of Public Health University of Illinois at Chicago

PATIENT ADVOCACY

Wayne M. Lednar, MD, PhD Global Chief Medical Officer Director, Integrated Health Services DuPont, Wilmington, DE

300

Alex Hathaway, MD, MPH, FACPM President & Founder, J.D. BioEdge Health quality and biomedical research consultancy

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www.AHDBonline.com

Grant D. Lawless, BSPharm, MD, FACP Executive Director for Payor Relations Corporate Account, Amgen, CA RESEARCH & DEVELOPMENT

Michael F. Murphy, MD, PhD Chief Medical Officer and Scientific Officer Worldwide Clinical Trials Faculty, Center for Experimental Pharmacology and Therapeutics, HarvardMIT Division of Health Sciences and Technology, Cambridge, MA SPECIALTY PHARMACY

Atheer A. Kaddis, PharmD Vice President, Managed Markets Diplomat Specialty Pharmacy Swartz Creek, MI James T. Kenney, RPh, MBA Pharmacy Operations Manager Harvard Pilgrim Health Care, Wellesley, MA

September/October 2010

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exploring

DIABETES inspired to make a

DIFFERENCE

Copyright Š2010, Boehringer Ingelheim Pharmaceuticals, Inc. All rights reserved.

(06/10)

DI77201MHC-A

SEPTEMBER/OCTOBER 2010

VOLUME 3, NUMBER 5

THE PEER-REVIEWED FORUM FOR EVIDENCE IN BENEFIT DESIGN ™

™

™

FOR PAYERS, PURCHASERS, POLICYMAKERS, AND OTHER HEALTHCARE STAKEHOLDERS

TABLE OF CONTENTS Publisher Nicholas Englezos nick@engagehc.com 732-992-1884

EDITORIAL

308 U.S. Rebukes Health Insurers (available in the print version only) Janet Adamy

Associate Publisher Maurice Nogueira maurice@engagehc.com 732-992-1895

308 Resisting the Urge to Flatten Healthcare Robert E. Henry

Editorial Director Dalia Buffery dalia@AHDBonline.com 732-992-1889

REGULATORY

Associate Editor Lara J. Reiman lara@engagehc.com 732-992-1892

310 Assessment of Medicare Part D Communications to Beneficiaries Meghana Aruru, PhD, MBA, BSPharm; J. Warren Salmon, PhD

Editorial Assistant Jessica A. Smith

317 Stakeholder Perspective by Jack E. Fincham, PhD, RPh

Senior Production Manager Lynn Hamilton

BUSINESS

Business Manager Blanche Marchitto

321 A Comparison of Drug Formularies and the Potential for Cost-Savings Andrea L. Kjos, PharmD, PhD; Jon C. Schommer, PhD; Yingli Yuan, PhD

Editor-in-Chief Robert E. Henry rhenry@AHDBonline.com 732-992-1885

330 Stakeholder Perspective by Jeff Januska, PharmD

Mission Statement Continued on page 304

American Health & Drug Benefits is included in the following indexing and database services: EMBASE/Elsevier Cumulative Index to Nursing and Allied Health Literature (CINAHL) EBSCO research databases Standard Periodical Directory BPA Worldwide membership applied for August 2010.

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American Health & Drug Benefits is founded on the concept that health and drug benefits have undergone a transformation: the econometric value of a drug is of equal importance to clinical outcomes as it is to serving as the basis for securing coverage in formularies and benefit designs. Because benefit designs are greatly affected by clinical, business, and policy conditions, this journal offers a forum for stakeholder integration and collaboration toward the improvement of healthcare.

This publication further provides benefit design decision makers the integrated industry information they require to devise formularies and benefit designs that stand up to today’s special healthcare delivery and business needs.

Contact Information: For reprints, subscription information, and editorial queries, please contact: editorial@AHDBonline.com T: 732-992-1892 F: 732-992-1881

September/October 2010

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Vol 3, No 5

We focus on the human in human health care

At Eisai (a•zi), caring for people is our work Satisfying unmet medical needs and increasing benefits to patients, their families, and caregivers is Eisai’s human health care (hhc) mission.

This includes the development of innovative medicines– notably the discovery of the world’s most widely used treatment for Alzheimer’s disease.

Eisai is recognized for our business and patient advocacy partnerships, as well as our commitment to working with healthcare professionals to achieve improved patient care worldwide.

That is our quest. That is our promise. That is what makes us Eisai.

Ingenuity that Drives Innovation in Neurology, GI Disorders, and Oncology/Critical Care

Visit us at www.eisai.com, or 1-888-274-2378 © 2009 Eisai Inc. CO-0100-0905

SEPTEMBER/OCTOBER 2010

VOLUME 3, NUMBER 5

THE PEER-REVIEWED FORUM FOR EVIDENCE IN BENEFIT DESIGN ™

™

™

FOR PAYERS, PURCHASERS, POLICYMAKERS, AND OTHER HEALTHCARE STAKEHOLDERS

TABLE OF CONTENTS

(Continued)

CLINICAL

340 Managing Dyslipidemia in Primary Care with Restricted Access to Lipid-Modifying Therapy John T. Lynch, MPH; Catherine E. Cooke, PharmD, BCPS, PAHM; Jonathan Rosen, MD; Sanjay Gandhi, PhD; Michael F. Bullano, PharmD 347 Stakeholder Perspective by Matthew Mitchell, PharmD, MBA

DEPARTMENTS

333 GENERIC DRUG TRENDS FDA’s Approval Process Borne Out by a Large Study: But Communicating Generics’ Safety and Efficacy to the Public Leaves Much to Be Desired Dalia Buffery, MA, ABD 350 INDUSTRY TRENDS Healthcare Reform: Quality Outcomes Measurement and Reporting Cary Sennett, MD, PhD

American Health & Drug Benefits, ISSN 19422962 (print); ISSN 1942-2970 (online), is published 6 times a year by Engage Healthcare Communications, LLC, 241 Forsgate Drive, Suite 205A, Monroe Township, NJ 08831.

Copyright © 2010 by Engage Healthcare Communications, LLC. All rights reserved.

American Health & Drug Benefits and The Peer-Reviewed Forum for Evidence in Benefit Design are trademarks of Engage Healthcare Communications, LLC. No part of this publication may be reproduced or transmitted in any form or by any means now or hereafter known, electronic or mechanical, including photocopy, recording, or any informational storage and retrieval system, without written permission from the Publisher. Printed in the United States of America.

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The ideas and opinions expressed in American Health & Drug Benefits do not necessarily reflect those of the Editorial Board, the Editors, or the Publisher. Publication of an advertisement or other product mentioned in American Health & Drug Benefits should not be construed as an endorsement of the product or the manufacturer’s claims. Readers are encouraged to contact the manufacturers about any features or limitations of products mentioned.

Neither the Editors nor the Publisher assume any responsibility for any injury and/or damage to persons or property arising out of or related to any use of the material mentioned in this publication.

CAPTION CONTEST

348

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DEXILANT WORKS A

SECOND SHIFT TO HELP SHUT DOWN ACID PUMPS

DEXILANT is the first and only PPI with a Dual Delayed Release™ (DDR) formulation, which provides a second release of drug Mean plasma concentration (in healthy subjects; day 5; ng/mL)1 1200 1000 800 600 400

DEXILANT 60 mg 200

DEXILANT 30 mg

0 0

6

12

18

24

Time (h)

s DEXILANT 30 mg provided full 24-hour heartburn relief in a majority of symptomatic non-erosive gastroesophageal reflux disease patients at week 41 Conclusions of comparative efficacy cannot be drawn from this information.

Indications DEXILANT is indicated for healing all grades of erosive esophagitis (EE) for up to 8 weeks, maintaining healing of EE for up to 6 months, and treating heartburn associated with symptomatic non-erosive gastroesophageal reflux disease (GERD) for 4 weeks.

Important Safety Information DEXILANT is contraindicated in patients with known hypersensitivity to any component of the formulation. Hypersensitivity and anaphylaxis have been reported with DEXILANT use. Symptomatic response with DEXILANT does not preclude the presence of gastric malignancy.

Most commonly reported treatment-emergent adverse reactions: diarrhea (4.8%), abdominal pain (4.0%), nausea (2.9%), upper respiratory tract infection (1.9%), vomiting (1.6%), and flatulence (1.6%).

Do not co-administer atazanavir with DEXILANT because atazanavir systemic concentrations may be substantially decreased. DEXILANT may interfere with absorption of drugs for which gastric pH is important for bioavailability (e.g., ampicillin esters, digoxin, iron salts, ketoconazole). Patients taking concomitant warfarin may require monitoring for increases in international normalized ratio (INR) and prothrombin time. Increases in INR and prothrombin time may lead to abnormal bleeding and even death. Concomitant tacrolimus use may increase tacrolimus whole blood concentrations.

Please see adjacent brief summary of prescribing information for DEXILANT.

FORMERLY

KAPIDEX™ (dexlansoprazole)

BRIEF SUMMARY OF FULL PRESCRIBING INFORMATION DEXILANT (dexlansoprazole) delayed release capsules INDICATIONS AND USAGE DEXILANT is indicated for: K D85 851<9>7 ?6 1<< 7B145C ?6 5B?C9F5 5C?@8179D9C 6?B E@ D? G55;C K =19>D19>9>7 851<9>7 ?6 6?B E@ D? =?>D8C 1>4 K D85 DB51D=5>D ?6 851BD2EB> 1CC?391D54 G9D8 >?> 5B?C9F5 71CDB?5C?@81751< B56<EH 49C51C5 ( 6?B G55;C CONTRAINDICATIONS - " $* 9C 3?>DB19>4931D54 9> @1D95>DC G9D8 ;>?G> 8I@5BC5>C9D9F9DI D? 1>I 3?=@?>5>D ?6 D85 6?B=E<1D9?> I@5BC5>C9D9F9DI 1>4 1>1@8I<1H9C 81F5 255> B5@?BD54 G9D8 - " $* EC5 [see Adverse Reactions].

WARNINGS AND PRECAUTIONS Gastric Malignancy )I=@D?=1D93 B5C@?>C5 G9D8 - " $* 4?5C >?D @B53<E45 D85 @B5C5>35 ?6 71CDB93 =1<97>1>3I ADVERSE REACTIONS Clinical Trials Experience *85 C165DI ?6 - " $* G1C 5F1<E1D54 9> @1D95>DC 9> 3?>DB?<<54 1>4 E>3?>DB?<<54 3<9>931< CDE495C 9>3<E49>7 @1D95>DC DB51D54 6?B 1D <51CD =?>D8C 1>4

@1D95>DC DB51D54 6?B ?>5 I51B &1D95>DC B1>754 9> 175 6B?= D? I51BC =5491> 175 I51BC G9D8 65=1<5 1E31C91> <13; C91> 1>4 ?D85B B135C )9H B1>4?=9J54 3?>DB?<<54 3<9>931< DB91<C G5B5 3?>4E3D54 6?B D85 DB51D=5>D ?6 =19>D5>1>35 ?6 851<54 1>4 CI=@D?=1D93 ( G8938 9>3<E454 @1D95>DC ?> @<1352? @1D95>DC ?> - " $* =7

@1D95>DC ?> - " $* =7 1>4 @1D95>DC ?> <1>C?@B1J?<5 =7 ?>35 419<I C 3<9>931< DB91<C 1B5 3?>4E3D54 E>45B G945<I F1BI9>7 3?>49D9?>C 14F5BC5 B513D9?> B1D5C ?2C5BF54 9> D85 3<9>931< DB91<C ?6 1 4BE7 31>>?D 25 49B53D<I 3?=@1B54 D? B1D5C 9> D85 3<9>931< DB91<C ?6 1>?D85B 4BE7 1>4 =1I >?D B56<53D D85 B1D5C ?2C5BF54 9> @B13D935 #?CD ?==?><I (5@?BD54 4F5BC5 (513D9?>C *85 =?CD 3?==?> 14F5BC5 B513D9?>C D81D ?33EBB54 1D 1 89785B 9>3945>35 6?B - " $* D81> @<1352? 9> D85 3?>DB?<<54 CDE495C 1B5 @B5C5>D54 9> *12<5

Table 2: Incidence of Treatment-Emergent Adverse Reactions in Controlled Studies Placebo

DEXILANT 60 mg (N=2218) %

DEXILANT Total (N=2621) %

Lansoprazole 30 mg (N=1363) %

Adverse Reaction 91BB851 24?=9>1< &19> $1EC51

(N=896) %

DEXILANT 30 mg (N=455) %

+@@5B (5C@9B1D?BI Tract Infection

,?=9D9>7 <1DE<5>35

4F5BC5 (513D9?>C (5CE<D9>7 9> 9C3?>D9>E1D9?> > 3?>DB?<<54 3<9>931< CDE495C D85 =?CD 3?==?> 14F5BC5 B513D9?> <5149>7 D? 49C3?>D9>E1D9?> 6B?= - " $* D85B1@I G1C 491BB851

%D85B 4F5BC5 (513D9?>C %D85B 14F5BC5 B513D9?>C D81D G5B5 B5@?BD54 9> 3?>DB?<<54 CDE495C 1D 1> 9>3945>35 ?6 <5CC D81> 1B5 <9CD54 25<?G 2I 2?4I CICD5= Blood and Lymphatic System Disorders: 1>5=91 <I=@8145>?@1D8I Cardiac Disorders: 1>79>1 1BB8ID8=91 2B14I31B491 385CD @19> 545=1 =I?31B491< 9>61B3D9?> @1<@9D1D9?> D138I31B491 Ear and Labyrinth Disorders: 51B @19> D9>>9DEC F5BD97? Endocrine Disorders: 7?9D5B Eye Disorders: 5I5 9BB9D1D9?> 5I5 CG5<<9>7 Gastrointestinal Disorders: 124?=9>1< 49C3?=6?BD 124?=9>1< D5>45B>5CC 12>?B=1< 6535C 1>1< 49C3?=6?BD 1BB5DD C 5C?@817EC 25J?1B 2?G5< C?E>4C 12>?B=1< 2B51D8 ?4?B 3?<9D9C =93B?C3?@93 3?<?>93 @?<I@ 3?>CD9@1D9?> 4BI =?ED8 4E?45>9D9C 4IC@5@C91 4IC@81791 5>D5B9D9C 5BE3D1D9?> 5C?@8179D9C 71CDB93 @?<I@ 71CDB9D9C 71CDB?5>D5B9D9C 71CDB?9>D5CD9>1< 49C?B45BC 71CDB?9>D5CD9>1< 8I@5B=?D9<9DI 49C?B45BC ( E<35BC 1>4 @5B6?B1D9?> 85=1D5=5C9C 85=1D?385J91 85=?BB8?94C 9=@19B54 71CDB93 5=@DI9>7 9BB9D12<5 2?G5< CI>4B?=5 =E3EC CD??<C >1EC51 1>4 F?=9D9>7 ?B1< =E3?C1< 2<9CD5B9>7 @19>6E< 456531D9?> @B?3D9D9C @1B5CD85C91 ?B1< B53D1< 85=?BB8175 General Disorders and Administration Site Conditions: 14F5BC5 4BE7 B513D9?> 1CD85>91 385CD @19> 389<<C 655<9>7 12>?B=1< 9>6<1==1D9?> =E3?C1< 9>6<1==1D9?> >?4E<5 @19> @IB5H91 Hepatobiliary Disorders: 29<91BI 3?<93 38?<5<9D891C9C 85@1D?=571<I Immune System Disorders: 8I@5BC5>C9D9F9DI Infections and Infestations: 31>4941 9>653D9?>C 9>6<E5>J1 >1C?@81BI>79D9C ?B1< 85B@5C @81BI>79D9C C9>EC9D9C F9B1< 9>653D9?> FE<F? F179>1< 9>653D9?> Injury, Poisoning and Procedural Complications: 61<<C 6B13DEB5C :?9>D C@B19>C ?F5B4?C5

@B?354EB1< @19> CE>2EB> Laboratory Investigations: "& 9>3B51C54 "* 9>3B51C54 )* 9>3B51C54 29<9BE29> 453B51C54 9>3B51C54 2<??4 3B51D9>9>5 9>3B51C54 2<??4 71CDB9> 9>3B51C54 2<??4 7<E3?C5 9>3B51C54 2<??4 @?D1CC9E= 9>3B51C54 <9F5B 6E>3D9?> D5CD 12>?B=1< @<1D5<5D 3?E>D 453B51C54 D?D1< @B?D59> 9>3B51C54 G5978D 9>3B51C5 Metabolism and Nutrition Disorders: 1@@5D9D5 381>75C 8I@5B31<35=91 8I@?;1<5=91 Musculoskeletal and Connective Tissue Disorders: 1BD8B1<791 1BD8B9D9C =EC3<5 3B1=@C =EC3E<?C;5<5D1< @19> =I1<791 Nervous System Disorders: 1<D5B54 D1CD5 3?>FE<C9?> 49JJ9>5CC 85141385C =97B19>5 =5=?BI 9=@19B=5>D @1B5CD85C91 @CI38?=?D?B 8I@5B13D9F9DI DB5=?B DB975=9>1< >5EB1<791 Psychiatric Disorders: 12>?B=1< 4B51=C 1>H95DI 45@B5CC9?> 9>C?=>91 <9294? 381>75C Renal and Urinary Disorders: 4ICEB91 =93DEB9D9?> EB75>3I Reproductive System and Breast Disorders: 4IC=5>?BB851 4IC@1B5E>91 =5>?BB81791 =5>CDBE1< 49C?B45B; Respiratory, Thoracic and Mediastinal Disorders: 1C@9B1D9?> 1CD8=1 2B?>389D9C 3?E78 4IC@>?51 8933E@C 8I@5BF5>D9<1D9?> B5C@9B1D?BI DB13D 3?>75CD9?> C?B5 D8B?1D Skin and Subcutaneous Tissue Disorders: 13>5 45B=1D9D9C 5BID85=1 @BEB9D9C B1C8 C;9> <5C9?> EBD931B91 Vascular Disorders: 455@ F59> D8B?=2?C9C 8?D 6<EC8 8I@5BD5>C9?> 449D9?>1< 14F5BC5 B513D9?>C D81D G5B5 B5@?BD54 9> 1 <?>7 D5B= E>3?>DB?<<54 CDE4I 1>4 G5B5 3?>C945B54 B5<1D54 D? - " $* 2I D85 DB51D9>7 @8IC9391> 9>3<E454 1>1@8I<1H9C 1E49D?BI 81<<E39>1D9?> 35<< <I=@8?=1 2EBC9D9C 35>DB1< ?25C9DI 38?<53ICD9D9C 13ED5 453B51C54 85=?7<?29> 458I4B1D9?> 49125D5C =5<<9DEC 4IC@8?>91 5@9CD1H9C 6?<<93E<9D9C 71CDB?9>D5CD9>1< @19> 7?ED 85B@5C J?CD5B 8I@5B7<I35=91 8I@5B<9@945=91 8I@?D8IB?949C= 9>3B51C54 >5EDB?@89<C # 453B51C5 >5EDB?@5>91 ?B1< C?6D D9CCE5 49C?B45B @?<I49@C91 @?<IEB91 B53D1< D5>5C=EC B5CD<5CC <57C CI>4B?=5 C?=>?<5>35 D8B?=2?3ID85=91 D?>C9<<9D9C %D85B 14F5BC5 B513D9?>C >?D ?2C5BF54 G9D8 - " $* 2ED ?33EBB9>7 G9D8 D85 B135=1D5 <1>C?@B1J?<5 31> 25 6?E>4 9> D85 <1>C?@B1J?<5 @13;175 9>C5BD , () ( * %$) C53D9?> Postmarketing Experience 4F5BC5 B513D9?>C 81F5 255> 945>D96954 4EB9>7 @?CD 1@@B?F1< ?6 - " $* C D85C5 B513D9?>C 1B5 B5@?BD54 F?<E>D1B9<I 6B?= 1 @?@E<1D9?> ?6 E>35BD19> C9J5 9D 9C >?D 1<G1IC @?CC92<5 D? B5<912<I 5CD9=1D5 D859B 6B5AE5>3I ?B 5CD12<9C8 1 31EC1< B5<1D9?>C89@ D? 4BE7 5H@?CEB5 Eye Disorders: 2<EBB54 F9C9?> Gastrointestinal Disorders: ?B1< 545=1 General Disorders and Administration Site Conditions: 61391< 545=1 Immune System Disorders: 1>1@8I<13D93 C8?3; B5AE9B9>7 5=5B75>3I 9>D5BF5>D9?> )D5F5>C ?8>C?>C CI>4B?=5 D?H93 5@945B=1< >53B?<IC9C C?=5 61D1< Respiratory, Thoracic and Mediastinal Disorders: @81BI>751< 545=1 D8B?1D D978D>5CC Skin and Subcutaneous Tissue Disorders: 75>5B1<9J54 B1C8 <5E3?3ID?3<1CD93 F1C3E<9D9C DRUG INTERACTIONS Drugs with pH-Dependent Absorption Pharmacokinetics - " $* 31EC5C 9>8929D9?> ?6 71CDB93 1394 C53B5D9?> - " $* 9C <9;5<I D? CE2CD1>D91<<I 453B51C5 D85 CICD5=93 3?>35>DB1D9?>C ?6 D85 , @B?D51C5 9>8929D?B 1D1J1>1F9B G8938 9C 45@5>45>D E@?> D85 @B5C5>35 ?6 71CDB93 1394 6?B 12C?B@D9?> 1>4 =1I B5CE<D 9> 1 <?CC ?6 D85B1@5ED93 56653D ?6 1D1J1>1F9B 1>4 D85 45F5<?@=5>D ?6 , B5C9CD1>35 *85B56?B5 - " $* C8?E<4 >?D 25 3? 14=9>9CD5B54 G9D8 1D1J1>1F9B D 9C D85?B5D931<<I @?CC92<5 D81D - " $* =1I 9>D5B65B5 G9D8 D85 12C?B@D9?> ?6 ?D85B 4BE7C G85B5 71CDB93 @ 9C 1> 9=@?BD1>D 45D5B=9>1>D ?6 ?B1< 29?1F19<129<9DI 5 7 1=@939<<9> 5CD5BC 497?H9> 9B?> C1<DC ;5D?3?>1J?<5 Warfarin ? 14=9>9CDB1D9?> ?6 - " $* =7 1>4 G1B61B9> =7 494 >?D 16653D D85 @81B=13?;9>5D93C ?6 G1B61B9> ?B $( ?G5F5B D85B5 81F5 255> B5@?BDC ?6 9>3B51C54 $( 1>4 @B?D8B?=29> D9=5 9> @1D95>DC B5359F9>7 && C 1>4 G1B61B9> 3?>3?=9D1>D<I >3B51C5C 9> $( 1>4 @B?D8B?=29> D9=5 =1I <514 D? 12>?B=1< 2<5549>7 1>4 5F5> 451D8 &1D95>DC DB51D54 G9D8 - " $* 1>4 G1B61B9> 3?>3?=9D1>D<I =1I >554 D? 25 =?>9D?B54 6?B 9>3B51C5C 9> $( 1>4 @B?D8B?=29> D9=5 Tacrolimus ?>3?=9D1>D 14=9>9CDB1D9?> ?6 45H<1>C?@B1J?<5 1>4 D13B?<9=EC =1I 9>3B51C5 G8?<5 2<??4 <5F5<C ?6 D13B?<9=EC 5C@5391<<I 9> DB1>C@<1>D @1D95>DC G8? 1B5 9>D5B=5491D5 ?B @??B =5D12?<9J5BC ?6 .&

USE IN SPECIFIC POPULATIONS Pregnancy Teratogenic Effects &B57>1>3I 1D57?BI *85B5 1B5 >? 145AE1D5 1>4 G5<< 3?>DB?<<54 CDE495C G9D8 45H<1>C?@B1J?<5 9> @B57>1>D G?=5> *85B5 G5B5 >? 14F5BC5 65D1< 56653DC 9> 1>9=1< B5@B?4E3D9?> CDE495C ?6 45H<1>C?@B1J?<5 9> B1229DC 531EC5 1>9=1< B5@B?4E3D9?> CDE495C 1B5 >?D 1<G1IC @B5493D9F5 ?6 8E=1> B5C@?>C5 - " $* C8?E<4 25 EC54 4EB9>7 @B57>1>3I ?><I 96 3<51B<I >55454

A reproduction study conducted in rabbits at oral dexlansoprazole doses up to 30 mg per kg per day (approximately 9-fold the maximum recommended human dexlansoprazole dose (60 mg) revealed no evidence of harm to the fetus due to dexlansoprazole. In addition, reproduction studies performed in pregnant rats with oral lansoprazole at doses up to 40 times the recommended human dose and in pregnant rabbits at oral lansoprazole doses up to 16 times the recommended human dose revealed no evidence of impaired fertility or harm to the fetus due to lansoprazole.

Nursing Mothers It is not known whether dexlansoprazole is excreted in human milk. However, lansoprazole and its metabolites are present in rat milk following the administration of lansoprazole. As many drugs are excreted in human milk, and because of the potential for tumorigenicity shown for lansoprazole in rat carcinogenicity studies [see Carcinogenesis, Mutagenesis, Impairment of Fertility], a decision should be made whether to discontinue nursing or to discontinue the drug, taking into account the importance of the drug to the mother.

Pediatric Use Safety and effectiveness of DEXILANT in pediatric patients (less than 18 years of age) have not been established.

Geriatric Use In clinical studies of DEXILANT, 11% of patients were aged 65 years and over.

No overall differences in safety or effectiveness were observed between these patients and younger patients, and other reported clinical experience has not identified significant differences in responses between geriatric and younger patients, but greater sensitivity of some older individuals cannot be ruled out.

Renal Impairment No dosage adjustment of DEXILANT is necessary in patients with renal impairment. The pharmacokinetics of dexlansoprazole in patients with renal impairment are not expected to be altered since dexlansoprazole is extensively metabolized in the liver to inactive metabolites, and no parent drug is recovered in the urine following an oral dose of dexlansoprazole.

Hepatic Impairment No dosage adjustment for DEXILANT is necessary for patients with mild hepatic impairment (Child-Pugh Class A). DEXILANT 30 mg should be considered for patients with moderate hepatic impairment (Child-Pugh Class B). No studies have been conducted in patients with severe hepatic impairment (Child-Pugh Class C).

OVERDOSAGE There have been no reports of significant overdose of DEXILANT. Multiple doses of DEXILANT 120 mg and a single dose of DEXILANT 300 mg did not result in death or other severe adverse events. Dexlansoprazole is not expected to be removed from the circulation by hemodialysis. If an overdose occurs, treatment should be symptomatic and supportive.

CLINICAL PHARMACOLOGY Pharmacodynamics Antisecretory Activity The effects of DEXILANT 60 mg (n=20) or lansoprazole 30 mg (n=23) once daily for five days on 24-hour intragastric pH were assessed in healthy subjects in a multiple-dose crossover study.

Serum Gastrin Effects The effect of DEXILANT on serum gastrin concentrations was evaluated in approximately 3460 patients in clinical trials up to 8 weeks and in 1023 patients for up to 6 to 12 months. The mean fasting gastrin concentrations increased from baseline during treatment with DEXILANT 30 mg and 60 mg doses. In patients treated for more than 6 months, mean serum gastrin levels increased during approximately the first 3 months of treatment and were stable for the remainder of treatment. Mean serum gastrin levels returned to pre-treatment levels within one month of discontinuation of treatment.

Enterochromaffin-Like Cell (ECL) Effects There were no reports of ECL cell hyperplasia in gastric biopsy specimens obtained from 653 patients treated with DEXILANT 30 mg, 60 mg or 90 mg for up to 12 months.

During lifetime exposure of rats dosed daily with up to 150 mg per kg per day of lansoprazole, marked hypergastrinemia was observed followed by ECL cell proliferation and formation of carcinoid tumors, especially in female rats [see Nonclinical Toxicology].

Effect on Cardiac Repolarization A study was conducted to assess the potential of DEXILANT to prolong the QT/QTc interval in healthy adult subjects. DEXILANT doses of 90 mg or 300 mg did not delay cardiac repolarization compared to placebo. The positive control (moxifloxacin) produced statistically significantly greater mean maximum and time-averaged QT/QTc intervals compared to placebo.

NONCLINICAL TOXICOLOGY Carcinogenesis, Mutagenesis, Impairment of Fertility The carcinogenic potential of dexlansoprazole was assessed using lansoprazole studies. In two 24-month carcinogenicity studies, Sprague-Dawley rats were treated orally with lansoprazole at doses of 5 to 150 mg per kg per day, about 1 to 40 times the exposure on a body surface (mg/m2) basis of a 50 kg person of average height [1.46 m2 body surface area (BSA)] given the recommended human dose of lansoprazole 30 mg per day.

Lansoprazole produced dose-related gastric ECL cell hyperplasia and ECL cell carcinoids in both male and female rats [see Clinical Pharmacology].

In rats, lansoprazole also increased the incidence of intestinal metaplasia of the gastric epithelium in both sexes. In male rats, lansoprazole produced a dose-related increase of testicular interstitial cell adenomas. The incidence of these adenomas in rats receiving doses of 15 to 150 mg per kg per day (4 to 40 times the recommended lansoprazole human dose based on BSA) exceeded the low background incidence (range = 1.4 to 10%) for this strain of rat.

In a 24-month carcinogenicity study, CD-1 mice were treated orally with lansoprazole doses of 15 mg to 600 mg per kg per day, 2 to 80 times the recommended human dose based on BSA. Lansoprazole produced a dose-related increased incidence of gastric ECL cell hyperplasia. It also produced an increased incidence of liver tumors (hepatocellular adenoma plus carcinoma). The tumor incidences in male mice treated with 300 mg and 600 mg lansoprazole per kg per day (40 to 80 times the recommended lansoprazole human dose based on BSA) and female mice treated with 150 mg to 600 mg lansoprazole per kg per day (20 to 80 times the recommended human dose based on BSA) exceeded the ranges of background incidences in historical controls for this strain of mice. Lansoprazole treatment produced adenoma of rete testis in male mice receiving 75 to 600 mg per kg per day (10 to 80 times the recommended lansoprazole human dose based on BSA).

The potential effects of dexlansoprazole on fertility and reproductive performance were assessed using lansoprazole studies. Lansoprazole at oral doses up to 150 mg per kg per day (40 times the recommended lansoprazole human dose based on BSA) was found to have no effect on fertility and reproductive performance of male and female rats.

PATIENT COUNSELING INFORMATION [see FDA-Approved Patient Labeling in the full prescribing information] Information for Patients Tell your patients to watch for signs of an allergic reaction as these could be serious and may require that DEXILANT be discontinued.

To ensure the safe and effective use of DEXILANT, this information and instructions provided in the FDA-approved patient labeling should be discussed with the patient. Inform patients of the following: DEXILANT is available as a delayed release capsule.

DEXILANT may be taken without regard to food.

DEXILANT should be swallowed whole.

K <D5B>1D9F5<I - " $* 31@CE<5C 31> 25 ?@5>54 1>4 14=9>9CD5B54 1C follows: - Open capsule; - Sprinkle intact granules on one tablespoon of applesauce; - Swallow immediately.

Distributed by Takeda Pharmaceuticals America, Inc. Deerfield, IL 60015 U.S. Patent Nos. - 5,045,321; 5,093,132; 5,433,959; 6,462,058; 6,664,276; 6,939,971; and 7,285,668.

DEXILANT is a trademark of Takeda Pharmaceuticals North America, Inc. and used under license by Takeda Pharmaceuticals America, Inc. All other trademark names are the property of their respective owners. Š2009, 2010 Takeda Pharmaceuticals America, Inc. For more detailed information, see the full prescribing information for DEXILANT or contact Takeda Pharmaceuticals America, Inc. at 1-877-825-3327.

KAP0110 R6-Brf; March 2010 L-LPD-0310-2

Reference: 1. DEXILANT (dexlansoprazole) package insert, Takeda Pharmaceuticals America, Inc. DEXILANTâ&#x201E;˘, KAPIDEXâ&#x201E;˘ (dexlansoprazole), and Dual Delayed Releaseâ&#x201E;˘ are trademarks of Takeda Pharmaceuticals North America, Inc., and are used under license by Takeda Pharmaceuticals America, Inc. Š2010 Takeda Pharmaceuticals North America, Inc. LPD-01139 6/10 Printed in U.S.A.

EDITORIAL

Resisting the Urge to Flatten Healthcare Robert E. Henry, Editor-in-Chief

T

he infuriating reality of healthcare is that it must be run in a systematic way, and that one aspect of that system must be policy (the other 2 are clinical and business). And of course, policy means that politicians ultimately weigh in and “decide” things fundamentally outside their areas of expertise. Not known for consistent fiscal brilliance, their stamp on healthcare often means that much of the downstream effects of legislation consist of crisis management aimed at containing the clinical or economic ruin the legislation overlooked during the planning phase.

Before we go into the latest example of how the new healthcare legislation is spilling over its banks (or causing a run on them?), there is a gem of a quote from the seminal movie A Man for All Seasons about a statesman with an unswerving conscience and a brilliant grasp of natural law, who insisted that his government’s legislation conform to this reality. He was Sir Thomas More, and you guessed it, he was executed for his stance. The issue then was the proposition that a king should run the only church allowed in the country of England.

When “asked” to sign the oath of allegiance, Sir Thomas refused. His logic bears repeating at every session of Congress: “Some men think the Earth is round, others think it flat; it is a matter capable of question.

But if it is flat, will the King’s command make it round?

And if it is round, will the King’s command flatten it?

No, I will not sign.”

For policymakers in Congress and the White House responsible for the Health Care and Education Reconciliation Act of 2010 (HCERA), their incentives and areas of knowledge are showing signs of detachment from those of the stakeholders in the rest of the country, whose job it is to carry out the legislation. One wonders if they have really asked themselves whether this legislation is founded on their view of desirability without evidence of its compliance with natural laws of economics and medicine, which owe no allegiance to any officials, elected or appointed—laws that will ultimately supersede any man-made fiat.

The latest round—it is increasingly fitting to evoke

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boxing imagery when describing interstakeholder dialogue—involves Kathleen Sebelius, Secretary of the US Department of Health and Human Services, warning Karen Ignagni, the health insurance industry’s top lobbyist, that health plans must not raise their premiums to cover increased costs occasioned by the HCERA. Her proclamation gives rise to concern that Ms Sebelius may be dabbling in world-flattening legislative attempts: “We will not stand idly by as insurers blame their premium hikes and increased profits on the requirement that they provide consumers with basic protections.”

I do not know if it is the use of the royal “we” that suggests arrogance, or the more troubling wording throughout the rest of that pithy, dangerous sentence.

Instead of a neutral question as to whether insurers are “basing” their premium hikes on the HCERA’s new requirements, she leaps to the pejorative “blame” conclusion. This is not dialogue, but the launching of salvos. And the assumptions build as this revealing sentence continues. These business professionals in a free society are now operating under a “requirement” to provide consumers with “basic protections.” The assumption is that Ms Sebelius knows exactly what constitutes such protections, and that they do not fluctuate but are immutable.

Operating on the notion that they practice their trade in a free society, the insurers are daring to ask why they are so required. They obey economic laws that will stand long after this administration is gone, laws that state that increased benefits may be regarded by some as “basic protections” but are by no means inevitable; they must be paid for. And unlike the federal government, which, if it controlled healthcare, could provide (temporarily) these basic protections by devaluing the dollar and printing spurious money to pay for them, private industry can only pay out benefits based on the monies paid into the system from plan members.

The autocracy of Ms Sebelius’s stance goes deep.

There is a “let them [in this case, the insurers] eat cake” attitude inherent in her remarks. Somehow or other, insurers must come up with increased benefits without

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increasing premiums. And the micromanagement of our healthcare, which is what has alarmed Americans ever since this unpopular, ideologically driven legislation was proposed, is something we are expected to go along with, as if sacrificing fiscal sanity for whatever passes as “basic protections” is not subject to debate.

Healthcare is ruled not by any Congress or administration, Democrat or Republican, but by the “iron triangle” of cost, quality, and access. Warp this triangle out of shape, elongate one of its points, and you do so at the

expense of the other two.

This world of healthcare, Ms Sebelius, is not flat; it is not even round; it is triangular. And if you want to avoid ruining a marvelous instrument providing care for so many Americans, listen to the other stakeholders and get in-step with the dance that medicine in the free market created. The rhythm is unforced, and it makes a lot of people happy. It is not that business does not want to dance with the policy sector; it just does not want to dance off the cliff. ■

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REGULATORY

Assessment of Medicare Part D Communications to Beneficiaries Meghana Aruru, PhD, MBA, BSPharm; J. Warren Salmon, PhD

Stakeholder Perspective, page 317

Am Health Drug Benefits.

2010;3(5):310-317. www.AHDBonline.com Disclosures are at end of text

Background: Older Americans receive healthcare benefits through the federal Medicare program. The Centers for Medicare & Medicaid Services provides comprehensive information to Medicare beneficiaries regarding benefits, plan options, and enrollment policies primarily through the annual Medicare & You handbook and the Medicare website. Few studies have assessed the overall readability and, therefore, the usefulness of this handbook for adequately educating beneficiaries. Healthcare communications written at higher levels than the readers’ comprehension levels cannot be well understood.

Objective: To measure the readability of the 2008 Medicare & You handbook provided to all Medicare beneficiaries.

Method: For our analysis, the 2008 version of the Medicare & You handbook was downloaded from the Centers for Medicare & Medicaid Services website. Passages of ≥250 words were saved individually in Windows Notepad as text files. Shorter passages (ie, <250 words) were combined with the next continuing passage. Each file was then uploaded into the Internet-based Lexile analyzer (the Lexile Framework for Reading). Figures, pictures, and tables were not included in the analysis.

Results: Approximately 70% of analyzed passages were written at approximately the 5th- to 12th-grade levels (Lexile scores: 790L-1290L), whereas 30% of the passages were written at levels above grade 12 (Lexile scores: 1310L-1910L).

Conclusion: Medicare beneficiaries who have less than a high-school level education may find the passages analyzed in this study difficult to read and comprehend as discussed, indicating the need for simplified communication. Our study provides recommendations to improve the handbook for better comprehension by beneficiaries.

R

esearch on health communications has gained prominence over the past few years.1 In the United States, healthcare consumers are expected to read and act on communications from various sources, including federal and state governments, the Social Security Administration, private insurance plans, managed care organizations, and voluntary health agencies. Written materials are not the only means of acquiring health information, but they are the most widely used tool for disseminating crucial information. Therefore, it is necessary to evaluate the quality of such communications for accuracy and to reduce redundancy and errors.

According to a 1992 national survey, most American elderly beneficiaries read at the 5th-grade level.2 There is an appropriate concern that healthcare materials are

Dr Aruru is Assistant Professor, Chicago College of Pharmacy, Midwestern University, Downers Grove, IL, and Dr Salmon is Professor of Health Policy & Administration, School of Public Health, University of Illinois at Chicago.

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written at higher grade levels and may not adequately educate or benefit the intended population.3-6 Most studies in health communications measure patient knowledge of a specific disease state.3-6 It is, however, important to measure patient comprehension of healthcare materials in addition to their knowledge. Such comprehension may be affected by a variety of factors, including, but not limited to, inadequate health literacy, readability of materials, and complexity of addressed topic(s), as well as readers’ interest levels and cognitive abilities.

The Medicare program is divided into 4 parts: A, B, C, and D. Part D is the recent outpatient prescription drug benefit introduced through the Medicare Modernization Act (MMA) of 2003, implemented on January 1, 2006. Most people pay a monthly premium for this prescription coverage. Enrollment in Part D is voluntary, with penalties for late sign-ups.

Medicare Part D Under Medicare Part D, distinct types of plans are offered to beneficiaries—stand-alone prescription drug

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plans (PDPs) or Medicare Advantage Prescription Drug (MA-PD) plans incorporating prescription drug coverage with other managed care benefits.7 In principle, based on the MMA standard benefit design, a Medicare beneficiary is involved in cost-sharing. Part D’s standard benefit design has a unique feature known as the coverage gap or doughnut hole.

Each year this coverage gap is expected to widen, and in 2010 the standard benefit package involves an annual deductible ($310), 25% of drug costs up to the initial limit for the doughnut hole ($2830 in total costs for covered drugs), and little cost-sharing beyond the upper limit for the doughnut hole ($6440). This means that beneficiaries who have a standard benefit plan and do not receive low-income subsidies would be responsible for $4550 in out-of-pocket costs before reaching the catastrophic coverage limit of $6440.8 Although the standard benefit must be offered by PDPs and MA-PDs, most plans also offer actuarially equivalent plans. Some of these plans may involve partial or complete coverage during the doughnut hole.8 Several new concepts were introduced within Part D, including the doughnut hole, formulary management, step therapy, and quantity limits.

It is important to realize that many elderly beneficiaries may not have been familiar with some or all of these concepts in the previous Medicare program. Beneficiaries receive information from the Centers for Medicare & Medicaid Services (CMS) through its Medicare & You handbook, the Medicare website (www.medicare.gov), and a toll-free telephone number.

In Part D, formularies vary considerably within different plans and among different PDPs or MA-PDs.9 Quantity limits are put in place by a plan sponsor to restrict the amount of drug prescribed (eg, 3 months).

Step therapy requires that a certain drug be tried out before the prescribing of a newer and/or more expensive therapy to prevent improper utilization. Prior authorization requires healthcare providers to seek approval before providing certain drugs to beneficiaries.

These concepts are managed care tools used to control prescription drug utilization. Although many people with previous insurance may be familiar with these terms, many elderly beneficiaries may not be familiar with these terms, either because of a lack of previous insurance, dependence on caregivers/spouses/children for insurance matters, and/or their own cognitive or educational limitations.

Medicare Communications with Beneficiaries The Balanced Budget Act of 1997 mandated that general and managed care plan comparison information be mailed to all current beneficiaries by October 15 of

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KEY POINTS ➤

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The readability of Medicare information provided to beneficiaries has not been well studied.

A 1992 national survey indicates that most Medicare beneficiaries read at the 5th-grade level.

The current study evaluated the readability level of the 2008 Medicare & You handbook used to communicate with Medicare beneficiaries.

Of the 64 passages analyzed, 30% scored above the 12th-grade level, and 70% scored between the 5th- and 12th-grade levels.

This gap in readability presents a particular concern with the introduction of Medicare Part D, which included new concepts that might not have been familiar to many beneficiaries A subanalysis of the 38 passages in Part D sections revealed that about 10 passages had reading difficulty level beyond grade 12, and 10 passages were at 10th-grade reading level.

The authors offer recommendations on how to improve the readability level of Medicare communication with beneficiaries.

each year, beginning in 1999. CMS (formerly known as the Healthcare Financing Administration) initiated a National Medicare Education Program (NMEP) to inform and educate beneficiaries about Medicare+ Choice plans and provide them with general and comparative information about their health insurance options.10 “The specific objectives of the campaign are to ensure that beneficiaries have access to accurate and reliable information, are aware of the different health plan choices available to them, understand the consequences of choosing different plans, and are able to use the information provided to them when making decisions.”10

The Medicare & You Handbook CMS would like Medicare beneficiaries to view the Medicare program and its private sector partners as trusted and reliable sources of information.10,11 The agency developed the consumer handbook Medicare & You to explain health plan options to beneficiaries. This handbook (formerly known as the Medicare Handbook) was pilot tested in 5 states and the Kansas City metropolitan statistical area in the fall of 1998, when CMS mailed the handbook to 5.1 million beneficiaries.12-14 The Medicare & You 2000 handbook was mailed to all 39 million elderly and disabled beneficiaries in the fall of 1999. Later versions were mailed each fall to beneficiaries. The education campaign also provided a toll-free

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Table 1 Components of CMS Educational Campaign Beneficiary mailings that included the Medicare & You handbook (CMS mailed the Medicare & You 2006 handbook in October 2005) Toll-free telephone line: 1-800-Medicare Website portal: www.Medicare.gov Alliances with national and local organizations National Train-the-Trainer program State- and community-based special information campaigns Enhanced beneficiary counseling from State Health Insurance Assistance programs Targeted and comprehensive assessment of outreach efforts CMS indicates Centers for Medicare & Medicaid Services.

telephone helpline; an Internet information database; support and training; counseling services; and state- and community-based outreach efforts (Table 1).

The Medicare & You handbook is one of the key sources of information for Medicare beneficiaries— information that is extremely detailed and legitimate, because it comes from CMS and from several other sources, such as plan materials, state and local organizational information, and the Medicare website. In 2008, there were 59 geographic-specific versions of the handbook with drug and health plan comparison charts for particular states. The 2008 handbook had approximately 120 pages (depending on the version used) and was issued in English, Spanish, Braille (English only), audio, and large print. Each fall, CMS mails a geographicspecific version of this handbook to all households of persons with Medicare coverage.

Assessment of Medicare Communications Relatively few studies have examined the appropriateness of the Medicare & You handbook for informing and educating beneficiaries. The handbooks and worksheets used to compare plan information would be useful to new beneficiaries if they were mailed up to 1 year in advance, and would increase the likelihood of new beneficiaries actually using the worksheets to compare plans and make better-informed choices.12 Our study focused exclusively on this handbook, because it is the most comprehensive document regarding Medicare. Beneficiaries have access to other sources of Medicare-related information, but analyzing these pieces of information is beyond the scope of this study.

In 2006, the US Government Accountability Office (GAO) analyzed 6 of 70 CMS documents on Medicare Part D and indicated that reading levels for analyzed pas-

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sages ranged from 7th grade to post-college. The majority of American seniors read at or below the 5th-grade level, suggesting a significant scope for improvement.15 Findings from a more recent GAO study indicate that CMS’s model annual notice of change did not communicate drug plan changes effectively to beneficiaries.15 This study showed that “the language contained in the mailings was at a reading level too high for beneficiaries, and it contained irrelevant information.”15 Other studies conclude that based on reading materials, individuals aged ≥65 years are less proficient than younger adults in locating information in documents to make health-related decisions.16 A 2003 national survey on adult literacy demonstrated that 27% of Medicare beneficiaries were unable to understand information in short, simple texts.17 In light of evidence that some older individuals face challenges in reading and retaining written information,15 the design and evaluation of appropriate writing materials for the elderly population are particularly important.

Readability testing of written communications may be a first step toward compiling healthcare materials that are comprehensible and beneficial for the intended readers.

Evaluating Readability Readability of healthcare materials is an emerging yet underrated area of academic research. Readability is the ease or comfort of reading text and includes legibility (ie, words can be read) and comprehension (ie, understanding the text). In the 1930s, psychologists studying the processing of written information concluded that longer sentences (>20 words) are difficult to grasp, and readers find it easier to understand simple words.16 Indices used to measure readability depend on sentence length and the number of “hard words” that appear in each sentence.18 Readability analyses—primarily used in schools to ascertain that students can read and comprehend materials at particular grade levels—are a necessary and useful tool when preparing important and timely information, such as Part D prescription drug coverage. Previous studies have shown that readability of written healthcare communication is consistently beyond average patients’ reading grade levels.3-6 As mentioned earlier, approximately 20% of the US adult population cannot read beyond a 5th-grade level.2 It is therefore important that all adult healthcare materials be written at a 5th-grade level or lower to adequately educate the target population.

Methods Our study measured the readability of the CMSproduced 2008 Medicare & You handbook, a compre-

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Table 2 Lexile Results for the Medicare & You 2008 Handbook Grade level

Passages, N (%)

Lexile scores, range

Average Lexile score

Grade level

Average grade level

<12th grade

45 (70.31)

790L-1290L

1163.78

4.5-11.5

10.23

>12th grade

19 (29.69)

1310L-1910L

1442.5

>12

N/A

hensive, lengthy document detailing plan options and benefits for Medicare beneficiaries.

Data We downloaded the 2008 English version of the Medicare & You handbook from the CMS website. Based on the online Lexile Framework for Reading (www.lexile. com) measurement instructions, all passages with >250 words were saved individually in Windows XP Notepad as text files. Passages with <250 words were combined with the next continuing passage.

A total of 64 passages were analyzed using the Lexile Framework for Reading (permission to use and include results in the study was obtained before beginning the study). Tables, illustrations, and figures were not included in the analysis.

Instrument Lexile measures have been used in the assessment of adult communications.19-21 Assessing the readability of healthcare materials is a fairly new endeavor. The Lexile Framework for Reading was developed with federal funding in the 1980s. Older methods were more routine for school level assessments (Flesch-Kincaid, Dale-Chall, Simple Measure of Gobbledygook) and have limited use in measuring the readability of adult communications.

The Lexile formula is based on sentence length and word frequency counts. Based on the Lexile theory of comprehension, passages with higher scores (between 1800L and 1900L) are more difficult to read than passages with lower scores (between 1300L and 1400L).

Grade levels were calculated by averaging the corresponding grade regions of the Lexile scores. For example, a Lexile score of 670 would fall into 2 regions—3rd and 4th grade. This score was assigned the average of these 2 grade levels—3.5.

Results Nearly 30% of the Medicare & You handbook (19 of 64 passages) scored above 12th-grade readability levels, and 70% of the handbook (45 of 64 passages) scored from 5th- to 12th-grade readability levels (Table 2). An average grade level of 10.23 for the

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Frequencies of the Medicare & You Handbook Passages Table 3 at Approximate Grade Levels 5-12 Passages, N (Total = 45)

Grade level

Percentage of total handbook

1

4.5

2.2

1

6.0

2.2

2

6.5

4.4

2

8.5

4.4

4

7.5

8.88

5

10.5

11.11

15

11.0

33.33

15

11.5

33.33

handbook suggests that there were more passages at higher reading levels.

Beyond the 12th grade, the number of years of education to achieve advanced degrees may vary; therefore, averaging the number of years of schooling beyond the 12th grade may lead to errors in estimation. Average grade levels were therefore not computed for the 19 passages (ie,˜30% of the material) that were beyond the 12th-grade readability range (Table 2).

Table 3 presents the grade-level readability of the 45 passages that were within the 5th- to 12th-grade readability range. Few passages scored (Lexile scores) at lower grade levels. Only 2 passages were found to correspond to an approximately 7th-grade level (actual level, 6.5), and only 1 passage scored a Lexile value that corresponded to an approximately 5th-grade reading level.

Subanalysis: Lexile Scores for the Part D Sections Because Medicare Part D introduced new concepts that may have been unfamiliar to beneficiaries accustomed to the Medicare program for Part A and Part B, a subanalysis of Part D sections was necessary.

Part D sections were found on pages 37 to 74 in Section 2 of the handbook, and on pages 76 to 88 in Section 3. Some information in Section 3—such as information about grievances—is common to all the different Medicare programs (Parts A, B, C, D). However,

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because information to file for appeals and exceptions may be more important in the context of Part D, this information was included in the subanalysis.

Lexile measures were computed for Part D passages.

There were a total of 38 passages with ≥250 words. The mean Lexile score for these passages was 1243.68L, with a minimum score of 970L and a maximum score of 1690L. Of the 38 passages on Medicare Part D, 10 passages (26%) showed a difficulty level beyond 12th grade.

Approximately 10 passages (26% of the Part D sections) had a 12th-grade reading level and 10 passages (26%) had a 10th-grade reading level. Only 1 of 38 (2.6%) passages had an approximate 6th-grade reading difficulty level, and the remaining 7 passages (18%) had gradelevel difficulties ranging from 7th to 9th grade.

Discussion The Medicare & You handbook could be a much more useful tool for informing and educating beneficiaries. It contains pertinent information about plan choices, appeals, grievances, and exceptions, but omits a basic understanding of the societal context of the program, fails to list current challenges facing the program, and does not do an adequate job of explaining the meaning of Medicare reform for beneficiaries and their families.22 Changes in the recent congressional legislation will warrant explanation of governmental influence on the Medicare program.

The problem with written educational materials is that there is often a gap between the reader’s Lexile measure (ability to read and understand text) and text Lexile measures. The Medicare handbook’s Lexile scores indicate an average grade level of approximately 10th grade. This may be higher than the average beneficiary’s reading level and their grade level of education.

Nineteen passages of 64 (30% of the handbook) were beyond the 12th-grade education level, indicating that these passages may not be readable or comprehensible by the average beneficiary.

The Medicare handbook is a standardized document that provides information on how to enroll, types of plans, procedures for grievances, and a definition of terms, but it does not conform to an individual’s specific situation. For example, if a beneficiary who may be eligible for a low-income subsidy is enrolled in a plan and would like to change it, there is very little information in the handbook on how to do so.

Healthcare communicators face numerous problems when dealing with a large subset of the population. With the increased complexity of Part D and the need to secure proper and safe use of pharmacotherapy, beneficiaries and their families have a greater need to understand instructions, follow procedures, interpret coverage infor-

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mation and forms, and then act on all these steps to make the best decision for their health.

This is vital to properly selecting a drug plan for their prescription benefit. This process—daunting enough for people with adequate literacy skills—can compromise the health and safety of persons with low literacy skills, as well as of US residents with limited English proficiency.23 At the beginning of the implementation of Part D in 2006, there were many plans (approximately 30-60, depending on the state) available to Medicare beneficiaries.24 During the first 2 years of implementation, 22.5 million (53%) beneficiaries signed up for Part D.25 A significant majority of Part D beneficiaries reported that the benefit was too complicated, and observers suggested that such complexity might have thwarted some beneficiaries in finding a suitable plan.26 Assessing the impact of Part D on healthcare utilization by the elderly is extremely important to evaluating the program’s viability.

The introduction of private plans into Medicare has created a market scenario in which beneficiaries are free to choose from a number of different plan offerings.

Whether offering multiple plans affects healthcare utilization, adherence to medication, or improved quality of life for the elderly is not yet known. This may be partly because Part D is a newer program, and obtaining a longitudinal database of Part D beneficiaries to demonstrate such outcomes will take time. CMS is just now assembling such data for researchers.

To evaluate Part D’s sustainability, it is important to understand whether elderly beneficiaries are able to make the type of informed choices that are expected of them. Medicare is a social policy program introduced as a benefit by right of citizenship. In this social policy, the introduction of private parties has also brought about managed care techniques, such as formulary restrictions, copayments, coinsurances, step therapy, quantity limits, the doughnut hole, penalties for late sign-ups, and annual enrollment periods. It is important to recognize that these concepts may be unknown to many elderly beneficiaries, who may not be cognitively intact to process them along with the additional burden of weighing and sifting multiple plan options, some of which may not be significantly different from one another.

For beneficiaries who are disabled or have cognitive impairments, the burden of selecting, enrolling in, and utilizing plan benefits may rest on their caregivers, families, or even the long-term care facilities where they reside. Because of penalties for late sign-ups that may last for the beneficiary’s entire plan period, it is important to ensure that beneficiaries sign up in a timely manner.

Decision-making for elderly beneficiaries to enroll in a Part D plan is certainly not easy, and caregivers who

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have assisted seniors will agree that this decision-making requires a certain level of knowledge, literacy, and cognition to navigate the plethora of choices available.

Existing beneficiaries also need to reevaluate their plan choices to ensure their optimal outcomes.

Because CMS is the administering agency for Medicare and Medicaid, it can be assumed that any communication coming from the agency would be complete and be accurately designed to benefit seniors. As previously noted, CMS ideologically claims that it would like beneficiaries to make informed choices and perceive the Medicare program and its private partners as trusted and reliable sources of information.10 However, Medicare communications have not always been written at beneficiaries’ educational and/or health literacy levels.

The readability problem with Medicare documents is neither new nor unique to Medicare publications. In the case of David v Heckler, the husband of a female patient in New York received a letter from the Department of Health and Human Services (DHHS) in 1984 when his wife died of cancer.27 Like many Medicare beneficiaries, the patient’s husband received far less remuneration than what he had expected. The letter explained why he received such little remuneration. His inability to understand the letter brought Legal Services Corporation to file a class action suit on behalf of all Medicare beneficiaries in the state of New York. Legal Services pointed out that 48% of the Medicare population had less than a 9th-grade education. Dr Edward Fry (originator of the Fry Readability Graph) testified that the letter was written at grade-16 level, or at a level suitable for persons with a college-level education. As a result, the judge ordered DHHS Secretary Margaret Heckler to take “prompt action” to improve the readability of Medicare communications.27 There is still significant scope for improvement.

According to Dr Fry’s testimony, inclusion of tables and pictorial depictions may improve the readability of a document.27 The 2008 Medicare & You handbook is comprised mostly of text, with few tables and charts. Almost all the tables and figures are placed toward the end of the book, and for the Part D sections, 26% of the 38 passages had a readability level beyond 12th grade.

The Part D private market is not inherently stable.

Since 2006, several plans opted out of the program, thereby necessitating that beneficiaries reevaluate their choices for the next year.

Policymakers may benefit by continuing to monitor beneficiary satisfaction with plans and learn important information through research on how well beneficiaries comprehend plan benefits and key factors behind such decision-making. Few studies have assessed elderly beneficiaries’ knowledge about Medicare, and even fewer have

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evaluated comprehension of the newer Part D concepts.

As the federal government anticipates the rollout of various programs to reform the healthcare system, comprehension of all new directions is vital for the public’s understanding, support, and benefit. In 2010, President Obama signed the Health Care Reform Bill, which includes future recommendations and implications for Medicare, particularly Part D.

Effects of the 2010 Healthcare Reform on Part D Under the new Patient Protection and Affordable Care Act (PPACA) of 2010, there is a provision for a “voluntary agreement with the Pharmaceutical Research and Manufacturers of America (PhRMA) to provide discounts of 50% for brand-name drugs used by Part D enrollees in the Part D coverage gap. Manufacturers of prescription drugs will be required to enter into agreements with Medicare Part D drug plan sponsors to provide discounts on drugs provided to plan enrollees in the coverage gap period beginning January 1, 2011.”9 The discount amount, along with the actual amount paid by the enrollee, will be counted toward costs incurred by the enrollee. Beneficiaries receiving any low-income subsidies or manufacturer discounts are not eligible for this discount. The PPACA mandates participation in this program by manufacturers, further stating that, “Drugs sold and marketed in the US by a manufacturer will not be covered under Part D unless the manufacturer agrees to participate in the discount program.”9 Section 1101 of the Health Care and Education Reconciliation Act of 2010 added provisions to close the coverage gap (ie, doughnut hole) over the course of 10 years, by 2020.28 Medicare Part D beneficiaries entering the doughnut hole in 2010 would also receive a $250 rebate. Cost-sharing in the doughnut hole for brandname drugs (minus the $250 rebate) has dropped from 100% to 25%.9 Subsequent reductions in cost-sharing on the enrollee’s part will occur over the span of 10 years, thereby closing the coverage gap completely by 2020.

Generic drugs are not a part of the 50% discount program, and beneficiary cost-sharing in the doughnut hole will be reduced to 25% by 2020 (Part D will pay for 75% of the generic drug’s costs).9 Limitations Readability formulas do not measure persistence, an important aspect of comprehension. Engaging reading material written at the appropriate comprehension level will likely induce persistence to read, which is important in today’s healthcare system. Elderly beneficiaries need to not only read and comprehend but also to continue reading information provided to derive maximum utility. Constant involvement to protect one’s health is a

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salient necessity in the US healthcare system of late, given the high prevalence of underinsurance amidst health equity issues. Several older studies in the field of readability research have shown significant relationships between persistence and readability.29,30 Our study did not measure persistence, nor did it involve readers to assess their readability levels. Further analysis is needed to ascertain whether certain portions of the Medicare handbook text should be rewritten to improve comprehensibility for beneficiaries and their families.

Conclusions Medicare communications to beneficiaries are vast and extensive. Few studies have examined the extent and usefulness of such materials in educating beneficiaries properly to make appropriate choices. In a consumeroriented society, it is crucial that beneficiaries understand their choices before they make them. The breadth and depth of information may serve to further confuse and overwhelm elderly beneficiaries.

Although the NMEP—of which the Medicare & You handbook is a component—gets evaluated on a periodic basis, the question remains whether this communication is comprehensible to, or even readable by, beneficiaries.

It must be noted that the 2010 English version of the handbook has incorporated only few changes. For example, the glossary of terms is at the beginning of the book, unlike in previous versions. A summary of the 4 parts of Medicare is provided at the beginning for quick reference, including contact information for various services.

Nevertheless, the new Part D prescription drug benefit is philosophically and programmatically different from the previous original parts. As such, the following recommendations are offered for improving the communications, based on our analysis of the 2008 handbook.

A. Consider writing Part D as a separate supplement. Medicare Part D is a new benefit, which is very different from Part A and Part B. To better understand Part D concepts, it would be useful to have a separate supplement or addendum on Part D to differentiate pharmacy benefits from hospital and medical benefits.

B. Include new information about dual eligibility and lowincome subsidies. For beneficiaries who fall into either category, a separate section on hardship and affording Medicare Part D may be appropriate, as opposed to inclusion in the overall text. The legislative objective of Part D, after all, was to alleviate financial barriers to drug access.

C. Include charts, figures, tables, or graphs to help some beneficiaries better understand their choices. Most beneficiaries may find reading continuous text difficult because of visual problems, declining cognition, or

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other problems. Therefore, inclusion of visual aids, such as charts or figures, may become more appealing to these beneficiaries and thereby aid in the learning process.

D. Add several case vignettes. In the entire section on Part D, only 1 case example was used (for step therapy). Using more case studies or examples to demonstrate or simulate real-life situations may help beneficiaries understand how these concepts work.

E. Arrange Part D sections in a single supplement to improve the continuity of content. Part D sections are spread out on pages 52-66, 84, 87-88, 99-101, and 107-111 of the handbook.

F. Provide for separate sections on enrollment and appeals/grievances. Writing the Part D supplement as 2 separate sections—plan enrollment and plan appeals/grievances—may help to improve the clarity of these concepts.

Periodically rechecking the document by CMS after incorporating changes would be a useful means of ascertaining whether readability of the material has improved. All these are practical targets for improving the reading material. Our analysis is especially relevant to the CMS staff and their private partners who need to consider our findings in reworking the Medicare & You handbook and all other communications to Part D beneficiaries. We recommend further periodic retesting of the handbook with readers for a better assessment of its comprehensibility. ■ Disclosure Statement Dr Aruru and Dr Salmon have nothing to disclose.

References 1. Hornik RC, ed. Public Health Communication: Evidence for Behavior Change.

Mahwah, NJ: Lawrence Erlbaum Associates; 2002.

2. National Center for Education Statistics. National Assessment of Adult Literacy (NAAL). National Adult Literacy Survey (NALS). 1992. http://nces.ed.gov/pubs 2001/2001457tech.pdf. Accessed March 9, 2010.

3. Davis TC, Crouch MA, Wills G, et al. The gap between patient reading comprehension and the readability of patient education materials. J Fam Pract. 1990; 31:533-538.

4. Berland GK, Elliott MN, Morales LS, et al. Health information on the Internet: accessibility, quality, and readability in English and Spanish. JAMA. 2001;285: 2612-2621.

5. Estrada CA, Hryniewicz MM, Higgs VB, et al. Anticoagulant patient information material is written at high readability levels. Stroke. 2000;31:2966-2970.

6. Smith H, Gooding S, Brown R, Frew A. Evaluation of readability and accuracy of information leaflets in general practice for patients with asthma. BMJ. 1998;317:264.

7. Gold M. The Landscape of Private Firms Offering Medicare Prescription Drug Coverage in 2006. Kaiser Family Foundation. www.kff.org/medicare/upload/7474.pdf.

Accessed February 5, 2010.

8. US Department of Health & Human Services, Centers for Medicare & Medicaid Services. Medicare basics. www.medicare.gov/Publications/Pubs/pdf/10050.pdf.

Accessed January 10, 2010.

9. Davis PA, Hahn J, Morgan PC, et al; for Congressional Research Service. Medicare provisions in PPACA (P.L. 111-148). CRS Report for Congress. April 21, 2010. www.aamc.org/reform/summary/PPACMedicareProvision042810.pdf. Accessed January 10, 2010.

10. Berkman ND, Bann C, Kuo M, et al. Analysis of Medicare beneficiary knowledge data using the Medicare Current Beneficiary Survey (MCBS). Phase 3.1. Final Report. RTI International. 2002. www.cms.gov/Reports/downloads/berkman_ 2002_7.pdf. Accessed January 10, 2010.

11. Goldstein E. Assessment of the National Medicare Education Program: supply

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and demand for information. Health Care Financ Rev. 1999;21:129-131.

12. Harris-Kojetin LD, McCormack LA, Jael EMF, Lissy KL. Beneficiaries’ perceptions of new Medicare health plan choice print materials. Health Care Financ Rev. 2001;23:21-35.

13. Goldstein E, Teichman L, Crawley B, et al. Lessons learned from the National Medicare & You Education Program. Health Care Financ Rev. 2001;23:5-20.

14. Carman KL, Short PF, Farley DO, et al. Epilogue: early lessons from CAHPS demonstrations and evaluations. Consumer Assessment of Health Plans Study. Med Care. 1999;37(suppl 3):MS97-MS105.

15. US Government Accountability Office. Medicare Part D. Opportunities exist for improving information sent to enrollees and scheduling the annual election period.

2008. www.gao.gov/new.items/d094.pdf. Accessed January 2010.

16. Hibbard J, Greene J, Tusler M. An assessment of beneficiary knowledge of Medicare coverage options and the prescription drug benefit. May 2006. http://assets.aarp.org/ rgcenter/health/2006_12_medicare.pdf. Accessed September 9, 2009.

17. Kutner M, Greenberg E, Jin Y, Paulsen C; for the National Center for Education Statistics, Institute of Education Sciences. The health literacy of America’s adults: results from the 2003 National Assessment of Adult Literacy. 2006. US Department of Education (NCES 2006–483). http://nces.ed.gov/pubs2006/2006483_1.pdf.

Accessed January 10, 2010.

18. Hall JC. The readability of original articles in surgical journals. ANZ J Surg. 2006; 76:68-70.

19. Wolf MS, Davis TC, Shrank WH, et al. A critical review of FDA approved medication guides. Patient Educ and Counsel. 2006;62:316-322.

20. Wolf MS, Davis TC, Tilson HH, et al. Misunderstanding of prescription drug warning labels among patients with low literacy. Am J Health Syst Pharm. 2006;63:1048-1055.

21. Wolf MS, Chang CH, Davis T, Makoul G. Development and validation of the Communication and Attitudinal Self-Efficacy scale for cancer (CASE-cancer).

Patient Educ Couns. 2005;57:333-341.

22. Bernstein J, Stevens RA. Public opinion, knowledge, and Medicare reform.

Health Aff (Millwood). 1999;18:180-193.

23. Villarruel AM, Portillo CJ, Kane P. Communicating with limited English proficiency persons: implications for nursing practice. Nurs Outlook. 1999;47:262-270.

24. Kaiser Family Foundation. Medicare Part D Plan Enrollment and Plan Characteristics. 2006. www.kff.org/medicare/upload/7426-02.pdf. Accessed February 6, 2010.

25. Polinski JM, Bhandari A, Saya UY, et al. Medicare beneficiaries knowledge of and choices regarding Part D, 2005 to the present. Ethics, Public Policy Med Econ.

2010;58:950-966.

26. Hoadley J. Medicare Part D: simplifying the program and improving the value of information for beneficiaries. Issue brief (Commonw Fund). 2008;39:1-15.

27. David v Heckler, 591 F.Supp. 1033 (E.D.N.Y., 1984). www.fastcase.com/Google/ Start.aspx?C=cc0de5afbc82ca7abc8929ad8494150ba890ba54220920cc&D=a281b2 e1feb0792396a4e9215f1b84ba2c9da8d14688d101. Accessed February 1, 2010.

28. Health Care and Education Reconciliation Act of 2010, H.R. 4872, §1101.

29. Schramm W. Measuring another dimension of newspaper readership. Journalism Quarterly. 1947;24:293-306.

30. Swanson CE. Readability and readership: a controlled experiment. Journalism Quarterly. 1948;25:339-343.

STAKEHOLDER PERSPECTIVE Medicare Part D Education Materials Must Address Recipients’ Literacy Level POLICYMAKERS: The Medicare Part D drug benefit began on January 1, 2006, after a 2-year restricted period of a drug discount card benefit for seniors and Medicare enrollees. Part D has engendered much discussion and remains a controversial program, with a mixed track record. Part D is administered by the Centers for Medicare & Medicaid Services (CMS) through stand-alone prescription drug plans or Medicare Advantage plans. CMS began overseeing this program without any experience in managing an outpatient drug benefit and should be commended for their early and continuing efforts.

Remaining hurdles, however, need to be addressed before the program can reach its goals. One hurdle is the enrolling of eligible Medicare recipients in Part D: an estimated 12% of eligible recipients remain with no Part D drug coverage, as well as 13% of those aged <65 years who are disabled.1 Program enrollment costs have increased and are a hindrance to many Medicare recipients.2 As a component of the Patient Protection and Affordable Care Act, Part D enrollees will begin to receive a $250 payment starting in October 2010 to help defer expenses within the coverage gap (doughnut hole).2 Lack of drug coverage may result from many other factors, including the readability of Medicare Part D materials. Considering that 64% of those who are disabled, aged <65 years, and with Medicare coverage are estimated to have a cognitive and/or mental impairment,1 readability becomes a crucial consideration.

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Among those aged ≥65 years, an estimated 23% have a cognitive/mental impairment.1 In light of these facts, the study by Aruru and Salmon provides a significant addition to the literature. The authors’ findings that 70% of the Medicare & You handbook is written at a 5th- to 12th-grade reading comprehension level, and 30% of the handbook is written at a level above grade 12, highlight a dramatic problem within Medicare materials meant to enable understanding of this important social insurance program.

The authors provide specific suggestions for Part D informative materials. Their suggestion to separate out a segment on Medicare Part D is a cogent one, and as they note, Part D may be foreign to Medicare enrollees and their families. The suggested use of case study vignettes as a teaching tool is also good. The authors’ evaluation points to Medicare Part D materials as especially complex from a readability perspective: CMS needs to address this shortcoming in its future promotional and education materials.

References 1. Kaiser Family Foundation. Medicare Fact Sheet. Medicare and nonelderly people with disabilities. September 2010. www.kff.org/medicare/upload/8100.pdf.

Accessed September 22, 2010.

2. Hoadley J, Summers L, Hargrave E, et al. Medicare Part D Spotlight. Medicare prescription drug plans in 2010 and key changes over five years: summary of findings. September 2010. Kaiser Family Foundation. November 2009. http://kff.org/medicare/upload/8096.pdf. Accessed September 22, 2010.

Jack E. Fincham, PhD, RPh Professor of Pharmacy Practice and Administration University of Missouri–Kansas City

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JOIN AHDB PEER REVIEW American Health & Drug Benefits (AHDB) is looking for medical and pharmacy directors, P & T Committee members, and other experts in benefit design who are interested in joining our peer reviewers and assist in maintaining the high quality of articles published in the journal.

You will be asked to review at least 1 or 2 articles per year in your area of expertise. Reviewers’ names will be published in AHDB at the end of the year.

Reviewers should have at least 1 area of expertise in a health-related field for which they feel qualified to assess the content and quality of manuscripts submitted for publication in AHDB.

Articles fall into 3 main areas related to healthcare: Regulatory, Business, and Clinical. These main categories are represented from the different vantage points of all stakeholders in healthcare and are divided into many subcategories, including (but not limited to):

® Administration/Management ® Benefit design ® Disease management/state (eg, asthma, ® ® ® ® ® ® ® ® ® ® ®

infectious diseases, pain management, schizophrenia) Drug therapy (including biologics, generics) Drug utilization Employer benefits Finance/economics Health information technology Health policy/reform Patient education/initiatives/quality-of-life issues Pharmacoeconomics: cost-benefit analysis, cost-effectiveness Pharmacy management: pharmacology, specialty pharmacy, pharmacy benefits Reimbursement: Medicare/Medicaid, health insurance, prior authorization Research: methods, study design, data collection/analysis

To become a peer reviewer, please complete the form below and fax to: 732-992-1881 or e-mail to editorial@ahdbonline.com Reviewer Information _______________________________________________________________________________________ First Name Last Name Credentials _______________________________________________________________________________________ Title Company _______________________________________________________________________________________ Address _______________________________________________________________________________________ E-mail Phone

BUSINESS

A Comparison of Drug Formularies and the Potential for Cost-Savings Andrea L. Kjos, PharmD, PhD; Jon C. Schommer, PhD; Yingli Yuan, PhD

Background: Brand-name drug costs have been escalating in the United States, and the reasons for this are not immediately clear. A lack of adequate and accurate information about drug effectiveness, safety, and cost has implications for drug utilization and cost.

Objective: To explore the extent to which health plan formularies were consistent with recommended drug listings and identify what would be the potential cost-savings on total drug expenditures if the utilization rate of the recommended therapies was increased.

Method: This study compared publicly available recommended drug listings with the formularies of 8 major health plans in Minnesota. Data from 1 of the health plans underwent an indepth case analysis to evaluate the potential impact on pharmaceutical expenditures, using increased utilization rate scenarios of the recommended drugs.

Results: Health plans were similar with respect to degree of coverage for the recommended drugs. However, the case analysis showed that by increasing the utilization rate of recommended drugs, a potential cost-savings of more than 50% could be realized for the evaluated health plan for some therapeutic categories.

Conclusion: This study demonstrates an approach to assessing drug formularies using publicly available, recommended drug lists that incorporated evidence for effectiveness, safety, and cost. By using the application of this type of reliable information, formulary changes can be guided to incentivize value-based utilization for patient populations.

I

n the United States, brand-name price inflation for prescription drugs has outpaced overall prescription drug price inflation.1,2 Although certain forces in the market may account for this situation, this study focused on the lack of adequate and accurate information that is needed in the market to optimize utilization of prescription drugs and mediate costs.

Lack of Cost Information Often, there is a lack of cost-related information on prescription drugs, which is evident from discussions surrounding the contracts between manufacturers and insurers who declare price and rebate information as Dr Kjos is Assistant Professor, Social and Administrative Pharmacy, College of Pharmacy and Health Sciences, Drake University, Des Moines, IA; Dr Schommer is Professor, College of Pharmacy, University of Minnesota, Minneapolis; Dr Yuan is a Statistician for IMS Health, Inc., Plymouth Meeting, PA. Some of the information described in this article was presented at the 155th and 156th annual meetings of the American Pharmacists Association, San Diego, CA, March 2008, and San Antonio, TX, April 2009, respectively.

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2010;3(5):321-330. www.AHDBonline.com Disclosures are at end of text

“proprietary and confidential”3 when there is a lack of data quantifying added value for new treatment options,4 or information related to actual acquisition costs for economic research. Evidence has shown that patients, providers, and other decision makers do not know the net cost of prescription drugs.5-7 Given this lack of costrelated information, there is growing pressure from a whole system perspective, both public and private, for the healthcare system to take a closer look at costs when considering drug formularies as a strategy to help remedy some of the issues of escalating costs in the market.

Prescription Drug Utilization and Cost Complexities Prescription drug expenditure growth represents a part of the healthcare system that is closely watched.

Prescription drug expenditures trends from 2007 to 2008 showed that spending increased by 1.8%—with total spending increasing from $279.6 billion to $284.7 billion.8 Spending on this segment of healthcare is not immune to external economic forces. The recent decades’ expansion of spending for prescription drugs was projected to continue in 2010 to 4.5%, and continue to rise in the future as a result of the overall improv-

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KEY POINTS ➤

➤

➤

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Evidence has shown that patients, providers, and other decision makers do not know the net cost of prescription drugs.

This study compared formulary lists from 8 health plans and drug utilization and cost data from 1 health plan in Minnesota with publicly available drug list recommendations to identify degree of coverage and what would be the potential costsavings on total drug expenditures if the utilization rate of the recommended drugs increased.

Results showed a high variation among the 8 plans between therapeutic categories for recommended drug coverage.

The plans were similar in coverage of recommended drugs across a single therapeutic category.

Increased coverage of recommended drugs was shown to produce greater potential cost-savings to the health plan.

These findings demonstrate a way to prioritize formulary changes and subsequent prescription utilization for patient populations. Improvement of drug formularies lowers overall prescription drug costs and has the potential to promote a more balanced pharmaceutical market to combat the ongoing rise of prescription drug prices.

ing economy, price increases for generic medications, and other factors.9 The utilization process that impacts spending on prescriptions is complex. Healthcare providers and consumers are faced with difficult decisions and often competing perspectives that shape the choice of prescription medications.10 Ideally, these decisions are made based on the best information and evidence that is available to achieve optimal patient outcomes with respect to effectiveness and safety, in addition to cost and value. Given the recent economic downturn, discussions of cost, whether pertaining to cost-effectiveness11 or out-of-pocket expenditures,12 are an important component of understanding prescription drug choice and utilization trends.

Cost is not the sole driver for choice of therapeutic products by patients; it is just one factor interwoven into a network of utilization dynamics involving multiple stakeholders. The choice of a prescription drug may be influenced by a variety of coexisting factors inside and outside the healthcare system, including the physician or pharmacist13; insurance or health plan14; promotional marketing15; and public policy.16 In addition, these decisions are often constrained by a perceived lack of evi-

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dence for comparative effectiveness,17 perceived lack of information about total net cost to the system or to the patient,5,6 or perceived lack of transparency with respect to incentives (positive or negative) that influence the formulary status.7 One example that demonstrated this lack of information for comparative effectiveness was the creation of a commissioned task force to provide guidance on the use of secondary databases as a way to supplement available clinical trial information on comparative effectiveness of prescription drugs.17 An example demonstrating a lack of cost information was given by Shrank and colleagues, who reported that prescribers are often not aware of patients’ costs for prescriptions and do not feel responsible for managing these costs.6 A different example suggesting the presence of uneven information was discussed in a report from the Pharmacy Benefit Management Institute, which indicated that only about half (52.3%) of surveyed employers perceived the nature of the financial relationship with their pharmacy benefit manager as transparent.7 All these are examples of how a lack of information is tied to various stakeholders of prescription drug utilization.

Key Research Questions This lack of information with respect to prescription drug effectiveness, safety, and cost, in combination with the prominent role of managed care in prescription utilization, presents the following study questions: 1. What is the extent of similarity between health plans’ formularies and a recommended drug listing from an outside source?

2. What would be the potential for cost-savings if a drug formulary was modified to be more aligned with these recommended products?

Given these questions, there is a need to critically examine public and private drug benefit programs and related utilization with respect to the potential for costsavings through the guidance of a recommended drug list. Past research has examined the potential economic benefit of prescription benefit plans increasing utilization of generically available prescriptions.18,19 To date, however, no comparable research has examined the current state of health plans or the potential financial impact when drug effectiveness, safety, and cost are used as considerations for a projected formulary change.

To contribute to formulary research that demonstrates the importance of information related to effectiveness, safety, and cost, as well as the potential costsavings from using approaches that apply these types of information, this study had 3 objectives: 1. To explore the extent to which health plan formularies were consistent with a recommended listing of drugs

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2. To document the extent to which 1 plan’s actual drug utilization patterns were consistent with the listing of recommended drugs 3. To identify the potential cost-savings on total drug expenditures from increasing the proportion of recommended drug therapies.

Methods This study was conducted in 2 parts. Part 1 compared a publicly available listing of recommended drugs20 against the formularies of 8 major health plans in Minnesota. (The names of the plans are not disclosed for several reasons. First, our goal was not to categorize plans or make judgments as to the individual level of plan prescription coverage but to demonstrate a standardized comparison approach to evaluate prescription drug formularies. Second, formulary information changes frequently and, therefore, may not be an accurate representation of the coverage for the plan at the current time. Third, it was consistent with our Institutional Review Board approval, because confidentiality was to be maintained for the unit of analysis, or in this case, the health plan. Finally, in Minnesota nearly all health plan formularies were publicly available on each of their respective websites.)

Using the findings from Part 1, we included in Part 2 a case study of a self-insured employer’s drug benefit plan to evaluate the potential impact on utilization and expenditures if the use of recommended therapies was increased.

Our study was based on data from publicly available information on safety, effectiveness, and medications cost.20 This information is referred to in this article as “recommended” drugs or medication reports. The bases for comparison were the specified recommended medication reports.

The recommended medication reports were publicly available online in reports called Best Buy Drugs.21 Consumer Reports Health Best Buy Drugs is an educational program of Consumers Union. Consumers Union compiled these reports based on other independent sources.21 The first source consisted of scientific reviews from the Drug Effectiveness Review Project (DERP).21 DERP is a 13-state initiative, based at Oregon Health & Science University, that compares drugs based on effectiveness and safety for state Medicaid programs and places their reports in the public domain.22 The second source incorporated was information provided by the Agency for Healthcare Research and Quality.21 The cost information provided in the reports came from national average prescription prices as would be reflected for cash-paying customers.21 These medication reports are divided into therapeutic categories and are updated regularly to reflect changes in

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Table 1 Profiled Categories for Recommended Drugs Therapeutic/drug category ACE inhibitors ADHD Alzheimer’s disease Antidepressants Antihistamines Antipsychotics Beta-blockers Calcium channel blockers Diabetes (oral) Hormones (estrogenic, for menopause) Insomnia NSAIDs Overactive bladder Proton pump inhibitors Statins Triptans (migraine) ACE indicates angiotensin-converting enzyme; ADHD, attentiondeficit/hyperactivity disorder; NSAIDs, nonsteroidal antiinflammatory drugs.

brand and generic drug status, emerging evidence, and price. These report profiles designate a choice of which drug(s) within each therapeutic category is to be interpreted as an overall recommended choice when factors of effectiveness, safety, and cost are considered together.

Within each report profile is a list of often-prescribed medications for each therapeutic class, along with dosages, prices, and other pertinent prescribing information (eg, indications or other dosage forms). Each report contains information on all the drugs evaluated and the resulting recommended medication(s). Every therapeutic category contains specific recommended drugs based on effectiveness, safety, and cost. Table 1 provides an overview of the therapeutic drug categories that are included in this study.

Part 1: Data Collection Part 1 of the study involved compiling a comprehensive medication list for the available drug categories, using the publicly available information for the recommended medication reports. In essence, a new formulary was created based on the recommended medication reports. Each therapeutic category’s list was then supplemented with Medi-Span Price-Chek PC data (Medi-Span). The MediSpan data were used to give complete information for each drug entity in each identified drug category.

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Once the recommended information was reconciled with the Medi-Span data, the drug lists were categorized according to all drugs in a therapeutic category, drugs reviewed by the publicly available information reports, and drugs chosen as a recommended drug. In Part 1, we used reports from a publicly available information source and their recommendations20-22 and then expanded this information back into a fully populated database of complete medication information for each therapeutic category.

We compared data from the 8 health plan formularies with the recommended drugs within each therapeutic category. Data were summarized by computing the total number of drug entities in the therapeutic category, the number of drug entities covered by each health plan, and the number of recommended drugs covered by each health plan. For each health plan, we calculated the percentage of covered drugs that are recommended drugs based on the total number of drug entities covered.

The health plans evaluated for Part 1 covered lives through private employee-based sponsorship, as well as public programs; therefore, a mix of public and private sponsorship was represented. Exceptions, or special requirements for plan coverage, were noted whenever the information was available for each of the 8 health plans. All data used in Part 1 were obtained during calendar year 2007.

Part 2: Case Analysis In Part 2 we used an in-depth case analysis of cost and utilization information for 1 of the 8 health plans. This was a private, employer-sponsored plan. In addition, in this part of the study we evaluated potential cost-savings that could theoretically be obtained if drug utilization aligned with the recommended medications reports. For this potential cost-savings we used 2 different summative and percentage calculation strategies to illustrate possible scenarios.

For Part 2, detailed data were obtained from a major employer (with 36,924 covered lives) for calendar year 2007, which was 1 of the 8 evaluated health plans evaluated in Part 1. The National Drug Code level drug data were matched to the list of recommended drug(s) within each of the therapeutic categories. As in Part 1, drug description data were used from Medi-Spanâ&#x20AC;&#x2122;s Price-Chek PC to facilitate the matching of recommended drugs with the actual drug utilization data for this health plan.

Next, the share of prescription volume (measured as days of therapy) filled with recommended drugs was determined. The actual amount of total drug expenditures (ie, plan and member cost) for these prescriptions was determined. The actual cost of recommended drugs

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was then identified, using the same 2007 employer data.

Total drug expenditures were projected, assuming that 100% or 85% of prescriptions were filled with recommended drugs at the actual reported cost rather than with the actual drugs used at their actual cost. The differences in total drug expenditures using the employerâ&#x20AC;&#x2122;s actual data were compared with projected drug expenditures using publicly available recommended drugs to find the potential cost-savings.

Theoretically, one could use the recommended drug for 100% of the prescriptions filled by a given drug benefit plan. However, as most clinicians realize, there are times when the first-line recommended drug may not be the best drug for a given patient. Assuming that the firstline preferred drug is appropriate 85% of the time, and that other drugs are appropriate 15% of the time, we used an 85% recommended drug rate to provide a more realistic estimate of the cost impact from using recommended drugs.

Results Data used in Part 1 of this study described the extent to which the 8 health plan formularies were consistent with recommended drugs. Data for this comparison were summarized by computing total medication coverage in each therapeutic category and recommended drug coverage. These data were translated into percentages for interpretation, giving a percentage of recommended coverage. These percentages were calculated using the number of recommended drugs divided by the total number of medications in each health plan for each therapeutic category.

Part 1 of the analysis is summarized in Figure 1.

Results show the cumulative percentages of recommended drugs covered by each health plan (identified as AH). Across all health plans, cumulative totals were similar. In contrast, a high variation is seen between therapeutic categories for recommended drug coverage.

For example, recommended drugs in the triptan and statin categories had greater recommended drug coverage (ranges, 54%-100% and 29%-61%, respectively) compared with oral diabetic or antipsychotic medications (ranges, 22%-38% and 19%-38%, respectively).

However, health plans were similar in recommended drug coverage across a single therapeutic category. For example, oral diabetic medications had a 22% to 38% recommended drug coverage range across all health plans. Antidepressant medications ranged from 8% to 12% across all plans.

In sum, the study objective of measuring consistency between health plan formularies and recommended drug listings showed that some drug categories had greater consistency with the recommended drugs. Health plans

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Figure 1 Cumulative Percentage of Recommended Therapeutic/Drug Coverage, by Health Plan (A-H) 700%

TRIP 67%

600% STAT 42%

TRIP 83%

500% STAT 57%

TRIP 82%

PPI 25%

TRIP 54%

TRIP 55%

TRIP 55%

NSAIDs 30% TRIP 100%

INSOM 10%

STAT 52%

HORM 50%

Cumulative percentage

PPI 14% NSAIDs 15%

NSAIDs 14% HORM 46%

DIAB 34%

TRIP 55%

STAT 57%

INSOM 22%

400%

STAT 61%

STAT 53%

NSAIDs 19% INSOM 7%

INSOM 22%

HORM 47%

STAT 29% PPI 17% NSAIDs 11% INSOM 13%

DIAB 38% STAT 56% CCB 61% NSAIDs 23%

HORM 45% DIAB 28%

PPI 33% PPI 13%

HORM 51%

NSAIDs 28%

HORM 61%

INSOM 17% DIAB 22%

300%

DIAB 34% CCB 54%

CCB 55% CCB 54%

BB 53%

AHIST 27%

100%

CCB 51%

OVBL 38%

HORM 59%

DIAB 28%

BB 48%

OVBL 50%

APSY 21% ADEP 8%

ADEP 11%

ALZH 40%

ALZH 40%

OVBL 27%

BB 57%

AHIST 60%

ADEP 8%

APSY 38% ADEP 12%

ALZH 64%

ALZH 33%

ALZH 50% ADHD 28%

ADHD 28%

ADHD 18%

ACE 27%

ACE 27%

ACE 34%

A

B

C

0%

ADHD 23% ADHD 16% ACE 19%

ADHD 29%

ACE 33%

D

DIAB 37%

CCB 41%

BB 59%

E

OVBL 33% APSY 29%

APSY 29%

APSY 27% AHIST 27%

ALZH 83%

BB 47%

OVBL 60%

ADEP 9%

APSY 19%

ADEP 11%

CCB 40%

HORM 43%

CCB 38%

APSY 38%

OVBL 27%

OVBL 50% APSY 19%

BB 64%

BB 64% BB 50%

200%

DIAB 31%

NSAIDs 17% INSOM 15%

AHIST 8% ADEP 11%

AHIST 23% ADEP 10%

ALZH 64%

ALZH 54% ADHD 15%

ADHD 33%

ACE 22%

ACE 22%

ACE 24%

F

G

H

Health plans NOTE: Percentage calculated as number of recommended drugs covered divided by total number of drugs in each health plan (A-H) for each therapeutic/drug category. Maximum cumulative percent would be 100% x 16 = 1600%. Several plans did not cover any recommended drugs in some categories.

ACE indicates angiotensin-converting enzyme inhibitors; ADEP, antidepressants; ADHD, attention-deficit/hyperactivity disorder; AHIST, antihistamines; ALZH, Alzheimerâ&#x20AC;&#x2122;s disease; APSY, antipsychotics; BB, beta-blockers; CCB, calcium channel blockers; DIAB, diabetes; HORM, hormones; INSOM, insomnia; NSAIDs, nonsteroidal anti-inflammatory drugs; OVBL, overactive bladder; PPI, proton pump inhibitors; STAT, statins; TRIP, triptans.

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Figure 2 Total Cost and Potential Cost-Savings with 85% and 100% Recommended Drug Utilization, $ $500,000

$1,000,000

$1,500,000

$2,000,000

$2,500,000

$3,000,000

$3,500,000

3,036,771 2,647,926

Antidepressants

2,141,476 2,270,344

Statins

523,061 374,715 1,699,654

Proton pump inhibitors

Beta-blockers

ACE inhibitors

1,310,724 1,087,613 275,179 71,777 14,905

Total costa Savings w/ 100% utilization Savings w/ 85% utilization

201,406 77,989 55,177 712,542 657,646 552,431

Antihistamines

Diabetes, oral

430,032 287,873 170,371

Insomnia (after generic Ambien)

421,314 333,921 271,680 216,269 182,839 125,808

NSAIDs

320,905 182,465 143,271

Hormones (estrogenic)

313,571

Calcium channel blockers

35,682 16,548 644,265 403,882 327,413

ADHD

a

Total cost associated with filled prescriptions. Cost calculations based on sum of actual ingredient cost to the health plan, dispensing fee charged by pharmacy, and any taxes incurred by the sale.

ACE indicates angiotensin-converting enzyme; ADHD, attention-deficit/hyperactivity disorder; NSAIDs, nonsteroidal anti-inflammatory drugs.

were largely consistent with one another in terms of percentages of recommended drug coverage.

Part 2 of the analysis determined the extent of consistency between the recommended drugs and the utilization data from 1 of the 8 health plans. Recommended drugs accounted for an average of 39% of the days of therapy used by the drug plan in 2007. The recommended drug share by days of therapy ranged from a low of 6% (antihistamines) to a high of 89% (Alzheimerâ&#x20AC;&#x2122;s disease drugs) across the categories studied.

Cost-savings could have been realized in 13 of the 16 categories through increased use of the recommend-

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ed drugs. The overall savings from the use of recommended drugs for 100% of prescriptions would have resulted in a 52% savings in total drug expenditures.

The use of recommended drugs for 85% of prescriptions would have produced a 41% savings across the therapeutic categories.

Figure 2, Table 2, and Table 3 show cost summary and potential cost-savings information. In Figure 2, only categories with cost-savings are shown. Of the 16 categories evaluated, 12 displayed a potential for cost-savings in the 85% recommended drug utilization scenarios (Figure 2 and Table 3). Table 3 displays cost-savings as a

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Table 2 2007 Total and Projected Cost-Savings for 1 Health Plan (36,924 members)

Therapeutic/ drug category

Total Rx actual, Na

Total costsavings if 85% Total recommended cost/day Total cost Total cost/day actual, $b actual, $c recommended, $d utilization, $e

Total costsavings if 100% recommended utilization, $f

Comments

Antidepressants

35,557

3,036,771

2.14

0.26

2,141,476

2,647,926

High utilization, cost, and potential savings

Statins

20,558

2,270,344

2.22

1.66

374,715

523,061

High utilization, cost, and potential savings

Proton pump inhibitors

12,266

1,699,654

3.37

0.78

1,087,613

1,310,724

High utilization, cost, and potential savings

Migraine

3051

878,125

16.98

17.42

(8491 cost increase)

(34,335 cost increase)

Older drugs not as safe Recommended drugs have higher cost

Antipsychotics

3153

787,230

8.38

11.12

(213,901 cost increase)

(264,456 cost increase)

Older drugs not as safe Recommended drugs have higher cost

Antihistamines

9228

712,542

1.98

0.15

552,431

657,646

High utilization, cost, and potential savings

ADHD

4770

644,265

3.87

1.39

327,413

403,882

Diabetes, oral

7758

430,032

1.28

0.42

170,371

287,873

Insomnia (after generic Ambien)

7662

421,314

2.11

0.42

271,680

333,921

Hormones (estrogenic)

5045

320,905

1.16

0.52

143,271

182,465

Calcium channel blockers

4912

313,571

1.39

1.25

16,548

35,682

11,996

275,179

0.47

0.35

14,905

71,777

5731

216,269

1.33

0.25

125,808

182,839

11,872

201,406

0.35

0.21

55,177

77,989

Overactive bladder

997

96,124

2.66

3.49

(28,295 cost increase)

(36,683 cost increase)

Older drugs not as safe Recommended drugs have higher cost

Alzheimer’s disease

81

20,084

6.05

5.71

(1823 cost increase)

1778

Mixed results, savings only demonstrated at 100%

145,856

12,510,561

3.49

2.79

5,101,464

6,472,948

Beta-blockers NSAIDs ACE inhibitors

Totals a

Total prescriptions filled during calendar year 2007. actual cost associated with filled prescriptions; cost calculations based on sum of actual ingredient cost to the health plan, dispensing fee charged by the pharmacy, and any taxes incurred by the sale. c Total cost per day of therapy calculated based on a typical 30-day supply at the most common dosage and used the same cost calculation as “total cost actual.” d Total cost per day of therapy of the recommended medication; if >1 drug was specified as recommended, the less expensive option is represented. e Total cost-savings if utilization was shifted to 85% of all prescriptions in the therapeutic category were written for recommended drugs. Calculations made based on determining the total number of prescriptions for 85% of all prescriptions and multiplying the actual cost, then subtracting the actual cost of 85% utilization from the total actual cost. f Total cost-savings if utilization was shifted to 100% and all prescriptions were for recommended drugs.

ACE indicates angiotensin-converting enzyme; ADHD, attention-deficit/hyperactivity disorder; NSAIDs, nonsteroidal anti-inflammatory drugs. bTotal

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Table 3 Potential Cost-Savings, Percent Dollars, with 85% or 100% Recommended Drug Utilization Therapeutic/ drug category

85% Recommended filled, %

100% Recommended filled, %

Categories with potential for cost-savings Antidepressants

70.5

87.2

Statins Proton pump inhibitors

16.5 64.0

23.0 77.1

Beta-blockers ACE inhibitors Antihistamines Diabetes, oral Insomnia NSAIDs Hormones (estrogenic) Calcium channel blockers

5.4 27.4 77.5 39.6 64.5 58.2

12.3 31.2 92.3 66.9 79.3 84.5

44.6

56.9

5.3

11.4

ADHD

50.8

62.7

Categories without potential for cost-savings Migraine

–1.0

–3.9

Antipsychotics Overactive bladder

–27.2 –29.4

–33.6 –38.2

Alzheimer’s disease

–9.1

8.9

Total potential cost-savingsa

40.8

51.7

a Total potential cost-savings was calculated from the sum total cost of all evaluated categories (including those that did not have a potential cost-savings) divided by the sum total of the cost if 85% or 100% of prescriptions were filled with recommended drugs.

ACE indicates angiotensin-converting enzyme; ADHD, attentiondeficit/hyperactivity disorder; NSAIDs, nonsteroidal antiinflammatory drugs.

percentage of dollars potentially saved if utilization were shifted to either 85% or 100% of the recommended drug use. In addition, Table 2 shows the therapeutic categories (highlighted) with highest overall utilization and the highest potential cost-savings from increased use of recommended drugs. Antidepressants had the highest overall potential cost-savings—71% (Table 3).

Discussion The relatively high cost differential ($2.14 vs $0.26) seen between nonrecommended and recommended antidepressant drugs makes potential cost-savings sub-

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stantial ($2,647,926/yr) if all (100%) plan members were to switch to a recommended antidepressant medication. For statins, potential cost-savings were not as high ($523,061/yr). Potential cost-savings for proton pump inhibitors were similar to those of antidepressants, showing a large differential in average cost of therapy for nonrecommended and recommended drugs ($3.37 vs $0.78). This, compounded by the high utilization (12,266 total prescriptions in 2007), yielded a large potential cost-savings of $1,310,724 annually.

Antihistamines had a lower utilization than the previous 3 categories mentioned (9228 total prescriptions in 2007); however, because of the very low daily cost for over-the-counter loratadine ($0.15/day), the potential cost-savings still topped a half million ($657,646).

Some data in Table 2 show the opposite outcome— increased cost from increasing use of recommended drugs.

A switch to the recommended drug could actually increase health plan spending in these categories if 100% (or even 85%) of the patients were switched. For example, if 100% of the prescriptions were preferred medications, it would cost the health plan $34,335, $264,456, and $36,683 more for migraine, antipsychotic, and overactive bladder medications, respectively. These results are also represented as percentages in Table 3.

The reason for these findings was that all these categories contained older generic therapeutic agents that may be less effective (regardless of their lower cost), or have an increased number of potential side effects compared with the newer, often branded, products.

The cost if 85% of drugs were prescribed as recommended was considered in Figure 2 and Tables 2 and 3, because this was seen as a more realistic portrayal of the actual potential cost-savings in place of the cost if 100% of drugs were prescribed as recommended.

Some therapeutic categories have the potential for high patient variability; therefore, the preferred drug may not be the most optimal therapeutic choice. For example, with the antidepressant medications, patients are often switched several times before finding an efficacious option and then maintaining it for the long-term.

Overall, however, the trend for the cost if 85% of drugs were prescribed as recommended closely follows that of cost if 100% of drugs were prescribed as recommended, in that there is still potential for cost-savings when using the 85% scenario for most therapeutic categories.

To summarize Part 2, using 1 major health plan as a case study, overall results showed that using recommended drug information as an approach for a prescription drug benefit could reduce costs by more than 50% for some therapeutic categories (eg, antihistamines, 78%; antidepressants, 71%; insomnia, 65%; proton pump inhibitors, 64%; nonsteroidal anti-

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inflammatory drugs, 58%; Table 3). However, although not all categories displayed a potential for cost-savings, an overall total potential cost-savings was calculated as a percentage from the sum total cost of all evaluated categories, including those without a potential costsavings, divided by the total of the cost if 85% or 100% of prescriptions were filled with recommended drugs.

This overall potential cost-savings was 40.8% if all 16 drug categories were switched to 85% of recommended drugs and 51.7% if all 16 drug categories were switched to 100% recommended drugs.

Limitations This study had several limitations. Only 8 health plans in Minnesota were evaluated, and only 1 of the 8 plans was evaluated in Part 2 of the study. The study only used Best Buy Drugs20 as the basis for the recommended drug used for comparison. This list could be challenged as having its own set of limitations, or perhaps as not being the optimal basis for comparison.

In addition, for this study, we assumed that formulary stakeholders are not influenced by competing incentives (eg, manufacturer rebates). We also assumed that out-of-pocket incentives for patients are not relevant for the comparison.

Finally, the prescription drug market is a rapidly changing environment with changes in patent status, the number of generic manufacturers, and the everincreasing number of available treatments, strengths, and dosage forms. Considering the fluid nature of this market, this study represents a cross-sectional view that may not reflect the current drug market.

Conclusions As prices for prescription drugs continue to rise, there remains a lack of information to stakeholders—particularly cost information. This lack of information was described as one issue creating the potential for inefficiencies in the market. Using a comparison of 8 major health plans and 1 case study of utilization information showed that certain therapeutic drug categories have a large potential for projected cost-savings. By using a recommended drug list for modifying drug formularies, health plans could reduce their costs by nearly 41% if 85% of prescriptions were shifted to recommended drugs, or nearly 52% if 100% of all prescriptions were shifted to recommended drugs.

This study demonstrates an approach to assessing drug formularies using a publicly available, online resource for recommended prescription drug information, based on effectiveness, safety, and cost. Stakeholders involved in drug formularies may benefit from using this type of information with respect to effective-

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ness, safety, and cost to determine ways to improve outcomes and decrease costs. Aligning formularies with the best available information may slow the rise of costs associated with the use of medications.

The findings presented here are important to the drug formulary literature, because they demonstrate an application of reliable, recommended drug information based on effectiveness, safety, and cost as a way to prioritize formulary changes and subsequent prescription utilization for patient populations. Not only could the improvement of drug formularies lower overall prescription drug costs, it also has the potential to promote a more balanced pharmaceutical market to combat the ongoing rise of prescription drug prices. ■ Acknowledgment Financial support for this study was provided by the Attorney General Consumer and Prescriber Education Grant Program. The authors gratefully acknowledge the participation of Dr Stephen Schondelmeyer and Dr Marcia Worley in the larger study, some of which findings are the basis for the current article.

Disclosure Statement Dr Schommer is currently Principal Investigator for a graduate student traineeship (a position held by 1 of his graduate students for 1 academic year), Novartis Pharmaceuticals, but had no affiliation with this company at the time this research was conducted; Dr Yuan is an employee of IMS Health; Dr Kjos has nothing to disclose.

References 1. Gross D, DeLeno Neuworth D, eds. Average manufacturer price increases for widely used brand name and specialty prescription drugs reach record levels. AARP Rx Watchdog Rep. April 2009;1-3. http://assets.aarp.org/www.aarp.org_/cs/health/ rx_watchdog_apr09.pdf. Accessed January 4, 2010.

2. Schondelmeyer SW. Statement on prescription drug price inflation: are prices rising too fast? Statement before Subcommittee on Health, Congress of the United States House of Representatives, December 8, 2009. http://energycommerce.house. gov/Press_111/20091208/schondelmeyer_testimony.pdf. Accessed January 4, 2010.

3. Kemp K; for the Office of the Assistant Secretary for Planning and Evaluation, US Department of Health & Human Services. Conference summary: pharmaceutical pricing practices, utilization, and costs. http://aspe.hhs.gov/health/reports/Drugpapers/kemp1.htm. Accessed January 4, 2010.

4. Kleinke JD. The price of progress: prescription drugs in the health care market.

Health Aff (Millwood). 2001;2:43-60.

5. Kohl H, Shrank WH. Increasing generic drug use in Medicare Part D: the role of government. J Am Geriatr Soc. 2007;55:1106-1109.

6. Shrank WH, Young HN, Ettner SL, et al. Do the incentives in 3-tier pharmaceutical benefit plans operate as intended? Results from a physician leadership survey.

Am J Manag Care. 2005;11:16-22.

7. Pharmacy Benefit Management Institute, LP. Prescription drug benefit cost and plan design report 2008-2009 edition. www.pbmi.com/2008_report/pdfs/Revised_ Report_20112009.pdf. Accessed December 22, 2009.

8. Hoffman J, Doloresco F, Vermeulen L, et al. Projecting future drug expenditures— 2010. Am J Health Syst Pharm. 2010;67:919-928.

9. Sisko A, Truffer C, Smith S, et al. Health spending projections through 2018: recession effects add uncertainty to the outlook. Health Aff (Millwood). 2009;28: w346-w357. Epub 2009 Feb 24.

10. Schommer JC, Worley MM, Kjos AL, et al. A thematic analysis for how patients, prescribers, experts, and patient advocates view the prescription choice process. Res Social Adm Pharm. 2009;5:154-169. Epub 2009 Jan 21.

11. Baio G, Russo P. A decision-theoretic framework for the application of cost-

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effectiveness analysis in regulatory processes. Pharmacoeconomics. 2009;27:645-655.

12. Schommer JC, Chen Y, Kjos AL, et al. Decision making regarding prescription drugs: out-of-pocket pressures. Drug Benefit Trends. 2009;21:278-289.

13. Shrank WH, Stedman M, Ettner SL, et al. Patient, physician, pharmacy, and pharmacy benefit design factors related to generic medication use. J Gen Intern Med. 2007;22:1298-1304. Epub 2007 Jul 24.

14. Roebuck MC, Liberman JN. Impact of pharmacy benefit design on prescription drug utilization: a fixed effects analysis of plan sponsor data. Health Serv Res. 2009;44:988-1009. Epub 2009 Jan 28.

15. Kyle GJ, Nissen LM, Tett SE. Pharmaceutical company influences on medication prescribing and their potential impact on quality use of medicines. J Clin Pharm Ther.

2008;33:553-559.

16. Kesselheim AS. Think globally, prescribe locally: how rational pharmaceutical policy in the U.S. can improve global access to essential medicines. Am J Law Med. 2008;34:125-139.

17. Berger ML, Mamdani M, Atkins D, Johnson ML. Good research practices for comparative effectiveness research: defining, reporting and interpreting nonrandom-

ized studies of treatment effects using secondary data sources: the ISPOR Good Research Practices for Retrospective Database Analysis Task Force report—part I. Value Health. 2009;12:1044-1052. Epub 2009 Sep 29.

18. Fischer MA, Avorn J. Economic consequences of underuse of generic drugs: evidence from Medicaid and implications for prescription drug benefit plans. Health Serv Res. 2003;38:1051-1063.

19. Haas JS, Phillips KA, Gerstenberger EP, Seger AC. Potential savings from substituting generic drugs for brand-name drugs: medical expenditure panel survey, 1997-2000. Ann Intern Med. 2005;142:891-897.

20. Consumers Union of U.S. Inc. Consumer Reports: Best Buy Drugs. 2009. www.consumerreports.org/health/best-buy-drugs/index.htm. Accessed January 4, 2010.

21. Consumers Union of the U.S. Inc. About Consumer Reports Health: Best Buy Drugs. www.consumerreports.org/health/about/best-buy-drugs.htm#abtproject.

Accessed July 26, 2010.

22. Oregon Health & Science University. Drug Effectiveness Review Project (DERP). www.ohsu.edu/ohsuedu/research/policycenter/DERP/. Updated 2008.

Accessed January 4, 2010.

STAKEHOLDER PERSPECTIVE Aligning Stakeholders Can Maximize the Opportunity for Cost-Savings on Drugs PAYERS: Depending on their line of business, healthcare payers are constantly tasked with administering a comprehensive and quality-based pharmacy benefit under the constraints of a budgeted portion of either a premium (commercial and Medicare plans) or capitation (Medicaid or state-sponsored plans).

Although the goal should be to maximize utilization from a preferred formulary or a recommended drug list, incentives that are not aligned with adherence to these preferred agents lead to missed opportunities for cost-savings, increased cost-shifting to employers and beneficiaries/members, and inefficiencies within the healthcare system.

The authors of this new study/article demonstrate that (1) utilization of medications from preferred formularies or recommended drug lists are not currently maximized by health plans, and (2) opportunities for cost-savings are available; the challenge, however, is to align all stakeholders to maximize the opportunity for savings.

The monies realized through greater adherence to a preferred formulary could potentially reduce premiums to employer groups, improve provider reimbursement, and broaden network access and mitigate costsharing through member copays, coinsurance, and member premium contribution.

The challenges to payers lie in the identification of true prescription cost and benefit design preference, and then relaying that information in a meaningful way to network prescribers and members/bene-

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ficiaries, along with a message explaining how they can personally benefit from greater adoption of these tools, through things such as greater reimbursement or lower copays/premiums.

PATIENTS/MEMBERS: Medical benefit cost trends continue to escalate, and the prescription component of a comprehensive medical coverage is not exempt from this phenomenon. In the attempt to offer a viable and affordable benefit plan to employer groups, health plans continue to cost-shift the rising expense trends to end-user members/beneficiaries, by means of increased deductibles, increasing patient copays/coinsurance, and premium-sharing.

The level of a beneficiary’s contribution has risen to the point where patient adherence drops off when members can no longer afford to bear “their” share under their current benefit design for drug coverage. If members/patients could better appreciate how their alignment with preferred benefits—especially regarding pharmaceuticals and a preferred drug list—could reduce their coverage expense and mitigate, perhaps even reduce, some of their cost-sharing obligation, we would most likely see increased adoption of preferred products and lesser influence by outside factors, be it direct-to-consumer pharmaceutical companies’ campaigns or direct-to-prescriber programs.

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Jeff Januska, PharmD Director of Pharmacy CenCal Health, Santa Barbara, CA

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GENERIC DRUG TRENDS

FDA’s Approval Process Borne Out by a Large Study: But Communicating Generics’ Safety and Efficacy to the Public Leaves Much to Be Desired

By Dalia Buffery, MA, ABD

I

n September 2010, the US Food and Drug Administration (FDA) conducted a webinar for the media to review the basic information concerning FDA’s approval of generic drugs1 in an attempt to promote the public’s understanding of generics and dispel common misconceptions about this growing branch of pharmaceutical products that are surrounded by a veil of confusion and controversy. Although much of the information provided by the FDA in that webinar could be considered common knowledge, such reiteration of the basic facts should not be seen as redundant, considering that the “drug wars” among generic and brand-name pharmaceutical makers (that stem largely from cost concerns) often are positioned as issues related to patient safety and product efficacy rather than finances.

Robert L. West, Deputy Director of the FDA’s Office of Generic Drugs (OGD) conducted the webinar. Mr West’s foremost concern was the message of safety and efficacy of generics, while simultaneously acknowledging that generic utilization continues to grow and by now constitutes the bulk of all prescriptions written in the United States.2 This in itself did not seem to pose a problem for him. If generics “represent 70% of the total prescriptions dispensed in the United States,”2 which is a considerable increase from “about 50% just a year ago,” according to Mr West,1 it would seem unnecessary to tout generic drugs yet again as being as safe and effective as brand-name drugs. Such a growth in the utilization rate should be sufficient evidence for these qualities (patient safety and product efficacy).

Indeed, as has been discussed often on the pages of American Health & Drug Benefits, the numbers are impressive. According to Mr West, “each year, more than 2.6 billion prescriptions are filled in the U.S. [sic] using generic drugs”2 compared with “approximately 1.2 billion brand-name prescriptions dispensed each year.”2 Nevertheless, writing prescriptions is no guarantee of patient adherence, and therein may lie the rub, which is where better education is needed.

To receive FDA approval for a generic drug, Mr

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West indicated, the manufacturer must demonstrate that its product2: • Contains the same active ingredient as the brandname drug • Has the same strength of the active ingredient as in the brand drug • Is of the same dosing formulation (eg, tablet, capsule) • Has the same route of administration as the brand drug (eg, oral, injection).

Furthermore, although generic drugs rely on evidence collected in the original clinical studies conducted by the brand drug manufacturer, generic manufacturers must also demonstrate that the specific generic formulation carries bioequivalence and pharmaceutical equivalence to the brand-name drug.2 This is often the cause for concern and contention about the actual benefit of and justification for generic product utilization.

This very concern was recently evaluated by FDA/OGD investigators (including many pharmacists) in a study published late last year.3 The investigators compared the evidence used by the FDA between 1996 and 2007 to establish the bioequivalence of generics and brand-name drugs.3 The goal of the study was to evaluate how well the bioequivalence measures used to approve generics compared with those used for the brand-name drugs. A total of 2070 studies were included in this analysis.

The results showed a mean standard deviation of geometric mean ratios of 1.00 ± 0.60 for drug peak plasma concentration (Cmax) and 1.00 ± 0.40 for area under the curve (AUC) plasma drug concentration.2,3 The average differences between generic and brandname drugs in these measures (Cmax and AUC) were 4.35% and 3.56%, respectively.3 And in 98% of these studies, the generic AUC differed from that of the brand product by <10%.2,3 The investigators concluded that these studies support the FDA’s use of its criteria for the approval process of generic formulations for brand-name products.3 This analysis, although scientifically sound, is anything but simple.

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Mr West admitted that the issue of bioequivalence is a frequent cause for misinformation, leading to considerable inconsistent and inaccurate assertions about the difference in the levels of the active ingredient that is present in the brand and the generic drug, resulting in claims that vary by more than a 40% difference, from –20% to +25%.2 The reason for this, the OGD Deputy Director suggests, is the complexity of the statistical analyses involved in the evidence for bioequivalence2; an intriguing observation that merits consideration, yet his own explanation of generic bioequivalence to the public relied on this very same study as the basis for the FDA’s articulation of this phenomenon.2

Bioequivalence is a frequent cause for misinformation, resulting in claims that vary by more than a 40% difference, from –20% to +25%.

Indeed, in an ideal world, simpler calculations and explanations may help a greater number of stakeholders to accept or reject the bioequivalence of these 2 similar yet competing groups of products that theoretically have a unified goal of helping patients. Complexity is not too helpful when seeking the understanding of consumers, especially with regard to drug therapy, of which payers and providers are well aware. Convincing patients to use medications is often a long and arduous task, with which

pharmaceutical companies, too, have been struggling for years. Yet the makers of brand-name products have found innovative ways to illustrate to consumers why using pharmaceuticals can often help improve their health and well-being. Using simple and clear language that does not require high-level education is crucial.

The FDA, and perhaps the makers of generic products, must also find innovative and more patient-focused ways of simplifying the complex issues of bioequivalence to consumers, who are after all, the ultimate target of the drug companies but are often the ones who do not buy into the very idea of generics (“cheap” is not always a positive and is often peculiarly suspect, especially when it comes to the American consumer). Lack of understanding of the true benefits of drug therapy is among the well-known causes of patient lack of adherence.

Although the FDA’s effort to explain bioequivalence is commendable, its very way of explanation and choice of communication with the public leave much to be desired. Improved channels of communication and clearer messages are needed to clarify a complex issue in simple but convincing words. ■

References 1. US Food and Drug Administration. FDA basics webinar on generic drugs. September 2010. www.fda.gov/AboutFDA/Transparency/Basics/ucm225778.htm. Accessed September 27, 2010.

2. West RL. Generic drugs. September 2010. www.fda.gov/downloads/AboutFDA/ Transparency/Basics/UCM226568.pdf. Accessed September 27, 2010.

3. Davit BM, Nwakama PE, Buehler GJ, et al. Comparing generic and innovator drugs: a review of 12 years of bioequivalence data from the United States Food and Drug Administration. Ann Pharmacother. 2009;43:1583-1597.

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We Take Quality To Heart.

Over the past five decades, Mylan Pharmaceuticals has established the systems necessary to ensure the quality of the generic products that we manufacture. Every step in the process includes quality controls and quality assurance measurements that are integrated into the production procedures.

In addition to routine quality checks and re-checks, Mylan has dedicated resources and professionals that are focused on operational excellence. The objective is clear … to continually improve the systems and procedures in place to be sure they will result in quality generics.

At Mylan, every person in our domestic and global network takes quality very seriously, and it’s why we are proud that America’s pharmacists rank our products highest in quality year after year.*

800.RX.MYLAN • www.mylanpharms.com *U.S. Pharmacist Generic Company Surveys. 2006-2009 ©2010 Mylan Pharmaceuticals Inc.

MYNMKT392A

CALL FOR PAPERS American Health & Drug Benefits offers an open forum for all healthcare stakeholders to exchange ideas and present their data, innovations, and initiatives to facilitate patient-centered healthcare and benefit design models that meet the needs of all stakeholders—Distributors, Employers, Evaluators, Manufacturers, Patients, Payers, Providers, Purchasers, Regulators, and Researchers.

Readers are invited to submit articles that aim at improving the quality of patient care and the US healthcare delivery system in general and of benefit design strategies in particular. All articles will undergo a blind peer review, and acceptance is based on that review.

Areas of high interest include: • Adherence Issues • Benefit Design • Comparative Effectiveness Analyses • Cost-Effectiveness Analyses • Decision-Making Tools

• Healthcare Trends • Health Economics • Health Plan Initiatives/Innovation • Health Information Technology • Innovation in Patient Care

• Off-Label Use/Misuse • Original Research • Pharmacoeconomics • Reimbursement Strategies • Wellness Programs

Clinical topics of interest include: AGING/DEMENTIA—With the aging of the US population, there is a growing need for early implementation of outcome-based preventive and therapeutic strategies for older people.

ALLERGIES—Allergies, such as allergic or seasonal rhinitis, affect millions of Americans daily, resulting in a significant economic burden and human cost.

Undertreatment and lack of adherence are common obstacles to patient management.

ARTHRITIS—Musculoskeletal conditions, such as rheumatoid arthritis or osteoporosis, are on the increase, yet many patients are undiagnosed and untreated.

Comparing new and available therapies is a key target for improving patient outcomes and reducing costs.

DIABETES, OBESITY—The increasing comorbid epidemics of these twin conditions mandates a thorough examination of best therapies, adherence issues, access, and prevention strategies. We invite articles that will address how to improve patient outcomes and best individualized patient care.

GASTROINTESTINAL CONDITIONS— Recognizing GI conditions, such as hepatitis C, Crohn’s disease, or inflammatory bowel disorder, remains a challenge.

INFECTIOUS DISEASES—The spread of common and emerging pathogens within the hospital and in the community remains a major concern requiring increased vigilance.

CANCER CARE—The growing focus on biologic agents dictates an enhanced study of these therapeutic options, including reimbursement policies, costmanagement, industry trends, and the biologic pipeline updates.

MENTAL DISORDERS—Depression, bipolar disorder, and schizophrenia exert a huge financial and human burden on individuals, employers, and payers.

Topics of interest include comparative effectiveness analyses, best practices, and reimbursement.

CARDIOVASCULAR DISEASE—Still a leading cause of morbidity and mortality among men and women. Original, outcome-based research on appropriate therapies, cost-comparisons, emerging prevention strategies, and comparative effectiveness of best practices will enhance readers’ decision-making.

PAIN MANAGEMENT—Chronic pain is associated with a slew of complicated medical disorders and an enormous economic burden, yet pain medications are still underused. Appropriate topics include best therapies, diagnosis, and clinicians’ anxiety about addiction issues and potential misuse.

Manuscripts should follow the Guidelines for Authors, available at www.AHDBonline.com For more information, call 732-992-1892

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For your members with moderate to severe plaque psoriasis

Indication STELARA™ is indicated for the treatment of adult patients (18 years or older) with moderate to severe plaque psoriasis who are candidates for phototherapy or systemic therapy.

Dosing STELARA™ is administered by subcutaneous injection.

• For patients weighing ≤100 kg (220 lbs), the recommended dose is 45 mg initially and 4 weeks later, followed by 45 mg every 12 weeks • For patients weighing >100 kg (220 lbs), the recommended dose is 90 mg initially and 4 weeks later, followed by 90 mg every 12 weeks In patients weighing >100 kg, 45 mg was also shown to be efficacious. However, 90 mg resulted in greater efficacy in these patients.

The safety and efficacy of STELARA™ have not been evaluated beyond two years.

Dosage forms and strengths STELARA™ contains 90 mg of ustekinumab per mL. • 45 mg/0.5 mL in a single-use, prefilled syringe, with an NDC number of 57894-060-03 • 90 mg/1 mL in a single-use, prefilled syringe, with an NDC number of 57894-061-03

Please see Important Safety Information and Brief Summary of Prescribing Information for STELARA™ on the following pages. www.STELARAinfo.com

IMPORTANT SAFETY INFORMATION Infections STELARA™ may increase the risk of infections and reactivation of latent infections. Serious bacterial, fungal, and viral infections were reported. Infections requiring hospitalization included cellulitis, diverticulitis, osteomyelitis, gastroenteritis, pneumonia, and urinary tract infections. STELARA™ should not be given to patients with a clinically important active infection and should not be administered until the infection resolves or is adequately treated.

Instruct patients to seek medical advice if signs or symptoms suggestive of an infection occur. Exercise caution when considering use of STELARA™ in patients with a chronic infection or a history of recurrent infection.

Theoretical Risk for Vulnerability to Particular Infections Individuals genetically deficient in IL-12/IL-23 are particularly vulnerable to disseminated infections from mycobacterium, Salmonella, and Bacillus Calmette-Guerin (BCG) vaccinations. Serious infections and fatal outcomes have been reported in such patients. It is not known whether patients with pharmacologic blockade of IL-12/IL-23 from treatment with STELARA™ will be susceptible to these types of infections. Consider appropriate diagnostic testing as dictated by clinical circumstances.

Pre-Treatment Evaluation of Tuberculosis (TB) Evaluate patients for TB prior to initiating treatment with STELARA™. STELARA™ should not be given to patients with active TB. Initiate treatment of latent TB before administering STELARA™. Patients should be monitored closely for signs and symptoms of active TB during and after treatment with STELARA™.

Malignancies STELARA™ is an immunosuppressant and may increase the risk of malignancy. Malignancies were reported among patients who received STELARA™ in clinical studies. The safety of STELARA™ has not been evaluated in patients who have a history of malignancy or who have a known malignancy.

Reversible Posterior Leukoencephalopathy Syndrome (RPLS) One case of RPLS has been reported in a STELARA™-treated patient. If RPLS is suspected, discontinue STELARA™ and administer appropriate treatment.

RPLS is a neurological disorder, which is not caused by an infection or demyelination. RPLS can present with headache, seizures, confusion, and visual disturbances. RPLS has been associated with fatal outcomes.

Immunizations Prior to initiating therapy with STELARA™, patients should receive all immunizations recommended by current guidelines. Patients being treated with STELARA™ should not receive live vaccines. BCG vaccines should not be given during treatment or within one year of initiating or discontinuing STELARA™. Exercise caution when administering live vaccines to household contacts of STELARA™ patients, as shedding and subsequent transmission to STELARA™ patients may occur. Non-live vaccinations received during a course of STELARA™ may not elicit an immune response sufficient to prevent disease.

Concomitant Therapies The safety of STELARA™ in combination with other immunosuppressive agents or phototherapy has not been evaluated. Ultraviolet-induced skin cancers developed earlier and more frequently in mice genetically manipulated to be deficient in both IL-12 and IL-23 or IL-12 alone. The relevance of these findings in mouse models for malignancy risk in humans is unknown.

Please see Brief Summary of Prescribing Information for STELARA™ on the following page.

Reference: STELARA™ Prescribing Information 12/2009. Horsham, PA: Centocor Ortho Biotech Inc.

representing the products of www.STELARAinfo.com

©2010 Centocor Ortho Biotech Services, LLC

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Most Common Adverse Reactions The most common adverse reactions (≥3% and higher than that with placebo) in clinical trials for STELARA™ 45 mg, STELARA™ 90 mg, or placebo were: nasopharyngitis (8%, 7%, 8%), upper respiratory tract infection (5%, 4%, 5%), headache (5%, 5%, 3%), and fatigue (3%, 3%, 2%), respectively.

Brief Summary of Prescribing Information for STELARA™ (ustekinumab) STELARA™ Injection, for subcutaneous use See package insert for Full Prescribing Information INDICATIONS AND USAGE: STELARA™ is indicated for the treatment of adult patients (18 years or older) with moderate to severe plaque psoriasis who are candidates for phototherapy or systemic therapy. CONTRAINDICATIONS: None. WARNINGS AND PRECAUTIONS: Infections STELARA™ may increase the risk of infections and reactivation of latent infections. Serious bacterial, fungal, and viral infections were observed in subjects receiving STELARA™ (see Adverse Reactions). STELARA™ should not be given to patients with any clinically important active infection. STELARA™ should not be administered until the infection resolves or is adequately treated. Instruct patients to seek medical advice if signs or symptoms suggestive of an infection occur. Exercise caution when considering the use of STELARA™ in patients with a chronic infection or a history of recurrent infection. Serious infections requiring hospitalization occurred in the psoriasis development program. These serious infections included cellulitis, diverticulitis, osteomyelitis, viral infections, gastroenteritis, pneumonia, and urinary tract infections. Theoretical Risk for Vulnerability to Particular Infections Individuals genetically deficient in IL-12/IL-23 are particularly vulnerable to disseminated infections from mycobacteria (including nontuberculous, environmental mycobacteria), salmonella (including nontyphi strains), and Bacillus Calmette-Guerin (BCG) vaccinations. Serious infections and fatal outcomes have been reported in such patients. It is not known whether patients with pharmacologic blockade of IL-12/IL-23 from treatment with STELARA™ will be susceptible to these types of infections. Appropriate diagnostic testing should be considered, e.g., tissue culture, stool culture, as dictated by clinical circumstances.

Pre-treatment Evaluation for Tuberculosis Evaluate patients for tuberculosis infection prior to initiating treatment with STELARA™. Do not administer STELARA™ to patients with active tuberculosis. Initiate treatment of latent tuberculosis prior to administering STELARA™. Consider anti-tuberculosis therapy prior to initiation of STELARA™ in patients with a past history of latent or active tuberculosis in whom an adequate course of treatment cannot be confirmed. Patients receiving STELARA™ should be monitored closely for signs and symptoms of active tuberculosis during and after treatment. Malignancies STELARA™ is an immunosuppressant and may increase the risk of malignancy. Malignancies were reported among subjects who received STELARA™ in clinical studies (see Adverse Reactions). In rodent models, inhibition of IL-12/IL-23p40 increased the risk of malignancy (see Nonclinical Toxicology). The safety of STELARA™ has not been evaluated in patients who have a history of malignancy or who have a known malignancy. Reversible Posterior Leukoencephalopathy Syndrome One case of reversible posterior leukoencephalopathy syndrome (RPLS) was observed during the clinical development program which included 3523 STELARA™-treated subjects. The subject, who had received 12 doses of STELARA™ over approximately two years, presented with headache, seizures and confusion. No additional STELARA™ injections were administered and the subject fully recovered with appropriate treatment. RPLS is a neurological disorder, which is not caused by demyelination or a known infectious agent. RPLS can present with headache, seizures, confusion and visual disturbances. Conditions with which it has been associated include preeclampsia, eclampsia, acute hypertension, cytotoxic agents and immunosuppressive therapy.

Fatal outcomes have been reported. If RPLS is suspected, STELARA™ should be discontinued and appropriate treatment administered. Immunizations Prior to initiating therapy with STELARA™, patients should receive all immunizations appropriate for age as recommended by current immunization guidelines. Patients being treated with STELARA™ should not receive live vaccines. BCG vaccines should not be given during treatment with STELARA™ or for one year prior to initiating treatment or one year following discontinuation of treatment. Caution is advised when administering live vaccines to household contacts of patients receiving STELARA™ because of the potential risk for shedding from the household contact and transmission to patient. Non-live vaccinations received during a course of STELARA™ may not elicit an immune response sufficient to prevent disease. Concomitant Therapies The safety of STELARA™ in combination with other immunosuppressive agents or phototherapy has not been evaluated. Ultraviolet-induced skin cancers developed earlier and more frequently in mice genetically manipulated to be deficient in both IL-12 and IL-23 or IL-12 alone (see Nonclinical Toxicology). ADVERSE REACTIONS: The following serious adverse reactions are discussed elsewhere in the label: Infections (see Warnings and Precautions); Malignancies (see Warnings and Precautions); and RPLS (see Warnings and Precautions). Clinical Studies Experience The safety data reflect exposure to STELARA™ in 2266 psoriasis subjects, including 1970 exposed for at least 6 months, 1285 exposed for at least one year, and 373 exposed for at least 18 months. Because clinical trials are conducted under widely varying conditions, adverse reaction rates observed in the clinical trials of a drug cannot be directly compared to rates in the clinical trials of another drug and may not reflect the rates observed in practice. Adverse reactions listed below are those that occurred at a rate of at least 1% and at a higher rate in the STELARA™ groups than the placebo group during the placebo-controlled period of STUDY 1 and STUDY 2. The numbers (percentages) of adverse reactions reported for placebo-treated patients (n=665), patients treated with 45 mg STELARA™ (n=664), and patients treated with 90 mg STELARA™ (n=666), respectively, were: Nasopharyngitis: 51 (8%), 56 (8%), 49 (7%); Upper respiratory tract infection: 30 (5%), 36 (5%), 28 (4%); Headache: 23 (3%), 33 (5%), 32 (5%); Fatigue: 14 (2%), 18 (3%), 17 (3%); Diarrhea: 12 (2%), 13 (2%), 13 (2%); Back pain: 8 (1%), 9 (1%), 14 (2%); Dizziness: 8 (1%), 8 (1%), 14 (2%); Pharyngolaryngeal pain: 7 (1%), 9 (1%), 12 (2%); Pruritus: 9 (1%), 10 (2%), 9 (1%); Injection site erythema: 3 (<1%), 6 (1%), 13 (2%); Myalgia: 4 (1%), 7 (1%), 8 (1%); Depression: 3 (<1%), 8 (1%), 4 (1%). Adverse drug reactions that occurred at rates less than 1% included: cellulitis and certain injection site reactions (pain, swelling, pruritus, induration, hemorrhage, bruising, and irritation). One case of RPLS occurred during clinical trials (see Warnings and Precautions).

Infections In the placebo-controlled period of clinical studies of psoriasis subjects (average follow-up of 12.6 weeks for placebo-treated subjects and 13.4 weeks for STELARA™-treated subjects), 27% of STELARA™-treated subjects reported infections (1.39 per subject-year of follow-up) compared with 24% of placebo-treated subjects (1.21 per subject-year of follow-up).

Serious infections occurred in 0.3% of STELARA™-treated subjects (0.01 per subject-year of follow-up) and in 0.4% of placebo-treated subjects (0.02 per subject-year of follow-up) (see Warnings and Precautions). In the controlled and non-controlled portions of psoriasis clinical trials, 61% of STELARA™-treated subjects reported infections (1.24 per subject-year of follow-up).

Serious infections were reported in 0.9% of subjects (0.01 per subject-year of follow-up).

Malignancies In the controlled and non-controlled portions of psoriasis clinical trials, 0.4% of STELARA™-treated subjects reported malignancies excluding non-melanoma skin cancers (0.36 per 100 subject-years of follow-up). Non-melanoma skin cancer was reported in 0.8% of STELARA™-treated subjects (0.80 per 100 subject-years of follow-up) (see Warnings and Precautions). Serious malignancies included breast, colon, head and neck, kidney, prostate, and thyroid cancers. Immunogenicity The presence of ustekinumab in the serum can interfere with the detection of anti-ustekinumab antibodies resulting in inconclusive results due to assay interference. In STUDIES 1 and 2, antibody testing was done at time points when ustekinumab may have been present in the serum. In STUDY 1 the last ustekinumab injection was between Weeks 28 and 48 and the last test for anti-ustekinumab antibodies was at Week 52. In STUDY 2 the last ustekinumab injection was at Week 16 and the last test for anti-ustekinumab antibodies was at Week 24. In STUDY 1 (N=743), antibody results were found to be positive, negative, and inconclusive in 38 (5%), 351 (47%), and 354 (48%) patients, respectively. In STUDY 2 (N=1198), antibody results were found to be positive, negative, and inconclusive in 33 (3%), 90 (8%), and 1075 (90%) patients, respectively. The data reflect the percentage of subjects whose test results were positive for antibodies to ustekinumab in a bridging immunoassay, and are highly dependent on the sensitivity and specificity of the assay. Additionally, the observed incidence of antibody positivity in an assay may be influenced by several factors, including sample handling, timing of sample collection, concomitant medications and underlying disease. For these reasons, comparison of the incidence of antibodies to ustekinumab with the incidence of antibodies to other products may be misleading. DRUG INTERACTIONS: Drug interaction studies have not been conducted with STELARA™. Live Vaccines Live vaccines should not be given concurrently with STELARA™ (see Warnings and Precautions). Concomitant Therapies The safety of STELARA™ in combination with immunosuppressive agents or phototherapy has not been evaluated (see Warnings and Precautions). CYP450 Substrates The formation of CYP450 enzymes can be altered by increased levels of certain cytokines (e.g., IL-1, IL-6, IL-10, TNF , IFN) during chronic inflammation. Thus, ustekinumab could normalize the formation of CYP450 enzymes. A role for IL-12 or IL-23 in the regulation of CYP450 enzymes has not been reported.

However, upon initiation of ustekinumab in patients who are receiving concomitant CYP450 substrates, particularly those with a narrow therapeutic index, monitoring for therapeutic effect (e.g., for warfarin) or drug concentration (e.g., for cyclosporine) should be considered and the individual dose of the drug adjusted as needed (see Clinical Pharmacology). USE IN SPECIFIC POPULATIONS: Pregnancy Pregnancy Category B There are no studies of STELARA™ in pregnant women. STELARA™ should be used during pregnancy only if the potential benefit justifies the potential risk to the fetus. No teratogenic effects were observed in the developmental and reproductive toxicology studies performed in cynomolgus monkeys at doses up to 45 mg/kg ustekinumab, which is 45 times (based on mg/kg) the highest intended clinical dose in psoriasis patients (approximately 1 mg/kg based on administration of a 90 mg dose to a 90 kg psoriasis patient). Ustekinumab was tested in two embryo-fetal development toxicity studies. Pregnant cynomolgus monkeys were administered ustekinumab at doses up to 45 mg/kg during the period of organogenesis either twice weekly via subcutaneous injections or weekly by intravenous injections. No significant adverse developmental effects were noted in either study. In an embryo-fetal development and pre- and post-natal development toxicity study, three groups of 20 pregnant cynomolgus monkeys were administered subcutaneous doses of 0, 22.5, or 45 mg/kg ustekinumab twice weekly from the beginning of organogenesis in cynomolgus monkeys to Day 33 after delivery. There were no treatment-related effects on mortality, clinical signs, body weight, food consumption, hematology, or serum biochemistry in dams. Fetal losses occurred in six control monkeys, six 22.5 mg/kg-treated monkeys, and five 45 mg/kg-treated monkeys.

Neonatal deaths occurred in one 22.5 mg/kg-treated monkey and in one 45 mg/kg-treated monkey. No ustekinumab-related abnormalities were observed in the neonates from birth through six months of age in clinical signs, body weight, hematology, or serum biochemistry. There were no treatment-related effects on functional development until weaning, functional development after weaning, morphological development, immunological development, and gross and histopathological examinations of offsprings by the age of 6 months. Nursing Mothers Caution should be exercised when STELARA™ is administered to a nursing woman. The unknown risks to the infant from gastrointestinal or systemic exposure to ustekinumab should be weighed against the known benefits of breast-feeding. Ustekinumab is excreted in the milk of lactating monkeys administered ustekinumab. IgG is excreted in human milk, so it is expected that STELARA™ will be present in human milk. It is not known if ustekinumab is absorbed systemically after ingestion; however, published data suggest that antibodies in breast milk do not enter the neonatal and infant circulation in substantial amounts. Pediatric Use Safety and effectiveness of STELARA™ in pediatric patients have not been evaluated. Geriatric Use Of the 2266 psoriasis subjects exposed to STELARA™, a total of 131 were 65 years or older, and 14 subjects were 75 years or older. Although no differences in safety or efficacy were observed between older and younger subjects, the number of subjects aged 65 and over is not sufficient to determine whether they respond differently from younger subjects. OVERDOSAGE: Single doses up to 4.5 mg/kg intravenously have been administered in clinical studies without dose-limiting toxicity. In case of overdosage, it is recommended that the patient be monitored for any signs or symptoms of adverse reactions or effects and appropriate symptomatic treatment be instituted immediately. PATIENT COUNSELING INFORMATION: Instruct patients to read the Medication Guide before starting STELARA™ therapy and to reread the Medication Guide each time the prescription is renewed.

Infections Inform patients that STELARA™ may lower the ability of their immune system to fight infections. Instruct patients of the importance of communicating any history of infections to the doctor, and contacting their doctor if they develop any symptoms of infection. Malignancies Patients should be counseled about the risk of malignancies while receiving STELARA™.

Prefilled Syringe Manufactured by: Vial Manufactured by: Centocor Ortho Biotech Inc., Centocor Ortho Biotech Inc., Horsham, PA 19044, Horsham, PA 19044, License No. 1821 at License No. 1821 at Baxter Pharmaceutical Solutions, Cilag AG, Bloomington, IN 47403 Schaffhausen, Switzerland 1-800-457-6399 25US10041 © Centocor Ortho Biotech Inc. 2009 December 2009

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Managing Dyslipidemia in Primary Care with Restricted Access to Lipid-Modifying Therapy John T. Lynch, MPH; Catherine E. Cooke, PharmD, BCPS, PAHM; Jonathan Rosen, MD; Sanjay Gandhi, PhD; Michael F. Bullano, PharmD

John T. Lynch

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2010;3(5):340-348. www.AHDBonline.com Disclosures are at end of text

Background: Many patients with dyslipidemia do not achieve goal low-density lipoprotein cholesterol levels. The barriers to achieving goal include inadequate assessment of cardiovascular risk status, medication cost, formulary restrictions, patient lack of adherence, and inadequate counseling time. Removing barriers may improve goal attainment and reduce the risk for cardiovascular events.

Objective: To identify opportunities to improve dyslipidemia management in primary care by examining low-density lipoprotein cholesterol goal attainment in patients with unrestricted or restricted access to lipid-modifying therapy.

Method: A total of 5936 adult patients from a primary care practice with a low-density lipoprotein measurement were categorized by coronary heart disease risk into 1 of 4 lipidmodifying therapy groups: unrestricted (fluvastatin, lovastatin, pravastatin, or simvastatin monotherapy); restricted (atorvastatin, rosuvastatin, or simvastatin/ezetimibe fixed-dose combination); other (lipid-modifying combination statin therapy or a nonstatin lipid-modifying therapy); and no lipid-modifying therapy. The primary outcome was low-density lipoprotein cholesterol goal attainment by lipid-modifying therapy group. Logistic regression identified associated demographic and clinical factors.

Results: In this cohort, 78.1% of the patients achieved low-density lipoprotein cholesterol goal levels. Overall goal attainment rates were lower in the high and very high coronary heart disease risk categories, at 52.6% and 31.6%, respectively. For patients at elevated coronary heart disease risk (high or very high), the rates of low-density lipoprotein cholesterol goal attainment were 14 to 16 percentage points higher for patients receiving restricted lipidmodifying therapy compared with patients receiving unrestricted lipid-modifying therapy (high coronary heart disease risk: 68% vs 52%, respectively; very high coronary heart disease risk: 42% vs 28%, respectively). Increasing age, male sex, and use of restricted lipid-modifying therapy were significantly associated with improved low-density lipoprotein cholesterol goal attainment. Of the 1298 patients who were not at low-density lipoprotein cholesterol goal, 54.1% were not receiving any lipid-modifying therapy. For each coronary heart disease risk category, there was a significantly higher percent utilization of unrestricted lipid-modifying therapy compared with restricted lipid-modifying therapy (P <.001).

Conclusion: A significant number of patients at elevated risk for coronary heart disease remain untreated or have low-density lipoprotein cholesterol levels above target. Removing barriers to the use of restricted lipid-modifying agents in patients at risk for heart disease provides an opportunity to improve low-density lipoprotein cholesterol levels.

Mr Lynch is Executive Director, Connecticut Center for Primary Care, and Medical Director for ProHealth Physicians, Inc, Farmington, CT; Dr Cooke is President, PosiHealth, Inc, and Clinical Associate Professor, University of Maryland School of Pharmacy, Baltimore, MD; Dr Rosen is Medical Director for ProHealth Physicians, Inc, Farmington, CT; Dr Gandhi is Director, Health Economics and Outcomes Research for AstraZeneca LP, Wilmington, DE; and Dr Bullano is Director, Health Economics and Outcomes Research for AstraZeneca LP, Wilmington, DE.

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he National Cholesterol Education Program (NCEP) Adult Treatment Panel (ATP) III guidelines and 2004 update stress the importance of achieving low-density lipoprotein cholesterol (LDL-C) goals in patients with dyslipidemia.1,2 Patients at higher coronary heart disease (CHD) risk have lower LDL-C goals and require more aggressive lipid-modifying therapy to achieve these goals than patients at lower CHD risk. Reducing LDL-C with lipid-modifying therapy in patients at higher CHD risk yields greater relative benefits in reducing the risk of CHD events compared with such treatment in patients at lower CHD risk.1,2 Despite awareness of the importance of appropriately managing patients with dyslipidemia, evaluations of current practice reveal that only about 40% to 75% of all patients with dyslipidemia achieve goal LDL-C levels.3-6 The likelihood of goal attainment is inversely associated with cardiovascular (CV) risk.5,7 Reported rates of LDLC goal attainment range from 50% to 98% in patients at lower CHD risk,3,5,8,9 and from 10% to 70% in patients at higher CHD risk.5,6,8,10 Only about 20% to 30% of patients at very high risk achieve goal LDL-C levels.5,6 Several barriers to achieving goal LDL-C levels have been reported in the literature, including patient, physician, and system barriers.11-14 A study of primary care providers in the United States identified barriers to initiating statin therapy, such as concerns about cost, patient adherence, and lack of adequate counseling time.11 In a managed care organization (MCO), cost and adherence were also of concern and were found to be inversely related.12 Non-Medicaid MCO patients with higher copayments were more likely to discontinue statin therapy sooner than those with lower copayments.12 MCOs use preferred drug lists (PDLs) to have an impact on prescribing. In one study of Medicaid recipients, significant decreases (range, 65%-97%) were found in the proportion of statin prescriptions filled for off-PDL (ie, restricted) medicines after the adoption of a Medicaid PDL.13 Physicians have difficulty assigning CHD risk status and following guideline-recommended interventions.11 Other studies have confirmed that physicians are unaware of national guidelines for statin use.14 When physicians underestimate CHD risk status, drug therapy restrictions may result in undertreatment of patients with dyslipidemia, especially those at higher CHD risk.

Removing barriers to achieving nationally recommended LDL-C goals in patients at increased CHD risk may reduce the risk of CV events. The objective of our study was to identify opportunities to improve dyslipidemia management in primary care by examining LDLC goal attainment in patients with unrestricted and restricted access to lipid-modifying therapy.

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Despite widespread awareness of the importance of lipid management in patients with dyslipidemia, many patients do not achieve target cholesterol levels.

Previous studies have reported barriers to achieving goal LDL-C levels, which involve patients, physicians, and the healthcare system as a whole.

This study included 5936 patients with medical and pharmacy coverage who had an LDL-C measurement and were either receiving different types of lipid-modifying therapies or no therapy.

Pharmacy coverage restricted the initial lipidmodifying therapy with a step-edit on atorvastatin, rosuvastatin, and simvastatin/ezetimibe fixed-dose combination.

Cholesterol goal attainment was unaffected by the type of lipid-modifying therapy used by patients at low risk, but in patients at higher risk, more patients reached LDL-C goal with one of the drugs included in the restricted coverage category.

This finding has implications to payers’ drug coverage decisions and clinicians’ prescribing decisions.

Methods Study Population Patients were retrospectively identified from the largest primary care group practice in Connecticut, which serves approximately 320,000 patients. In addition to the internal patient care database, this primary care practice routinely receives data on hospitalizations, emergency department visits, and pharmacy claims for their patients insured by a regional MCO. To be eligible for inclusion in this study, patients had to be insured by the regional MCO, have at least 1 office visit to the primary care group practice, and have at least 1 LDL-C measurement during 2007. LDL-C values reported from the laboratory were calculated by using a formula that includes total cholesterol, high-density lipoprotein cholesterol (HDL-C), and triglycerides; patients had to have these additional lipid parameters available for CHD risk stratification. Patients were excluded if they were younger than age 18 years on January 1, 2007, or if they had no associated pharmacy claims data.

Data Collection Data from the primary care practice and managed care claims databases during 2007 were combined to create individual patient profiles. These patient profiles

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contained information from office visits, hospitalizations, and emergency department care. Patient profiles contained unique deidentified patient numbers, demographic data (ie, age and sex), clinical data (ie, diagnoses/procedures and laboratory data), and prescription claims data. Data on diagnoses and procedures were obtained from office visits, hospitalizations, and emergency department care. Laboratory results included LDL-C. Patient identities were masked throughout the study in a limited data set format in accordance with the Health Insurance Portability and Accountability Act.

Coronary Heart Disease Risk Status Patients were stratified into CHD risk categories of low, moderate, high, and very high using a modified NCEP ATP III approach1,2 (see Appendix at www.AHDB online.com). International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes, Current Procedural Terminology, version 4 (CPT-4) codes, and pharmacy claims data were used to stratify patients by hierarchy into the highest risk category.

Patients were considered to be at high CHD risk (goal LDL-C <100 mg/dL) if they had any ICD-9-CM codes for myocardial infarction, other ischemic heart disease, angina pectoris, symptomatic carotid artery disease, peripheral arterial disease, abdominal aortic aneurysm, or diabetes mellitus; any CPT-4 claims for coronary artery bypass graft or percutaneous transluminal coronary angioplasty; or any pharmacy claims for antidiabetic agents. Patients identified as having high CHD risk (clinical CHD) were considered to be at very high CHD risk (goal LDL-C <70 mg/dL) if they also had claims indicating diabetes, intermediate coronary syndrome, or dysmetabolic syndrome X (metabolic syndrome).

Patients with diabetes must also have had other comorbid codes within the high CHD risk category to be classified as having very high CHD risk.

The remaining patients with at least 2 risk factors were considered to be at moderate risk (goal LDL-C <130 mg/dL).1,2 Risk factors included age ≥45 years for men or age ≥55 years for women, HDL-C <40 mg/dL, and hypertension as defined by ICD-9-CM codes or by pharmacy claims for an antihypertensive medication.

Patients who did not meet the criteria for very high, high, or moderate CHD risk categories were placed into the low CHD risk (goal LDL-C <160 mg/dL) category.

Outcome Measures The primary outcome measure was the percentage of patients achieving LDL-C goals. In accordance with the NCEP ATP III guidelines and the 2004 update,1,2 LDL-C goals were defined as <160 mg/dL for the low CHD risk category, <130 mg/dL for the moderate CHD risk cate-

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gory, <100 mg/dL for the high CHD risk category, and <70 mg/dL for the very high CHD risk category. For patients with more than 1 LDL-C value, the most recent value was utilized. An analysis was conducted in patients who had not achieved goal LDL-C values to identify opportunities to improve dyslipidemia management in this practice.

Dyslipidemia Treatment Patterns The use of lipid-modifying therapy was determined from the pharmacy claims and grouped based on the mechanistic types of lipid-modifying therapy and expected patterns of therapy (eg, monotherapy or combination therapy). Types of lipid-modifying therapy included statins (atorvastatin, fluvastatin, lovastatin, pravastatin, rosuvastatin, or simvastatin); simvastatin/ ezetimibe fixed-dose combination; fibrates (fenofibrate or gemfibrozil); niacin; cholesterol absorption inhibitors (ezetimibe); and bile acid sequestrants (cholestyramine or colestipol).

Patients receiving a statin as monotherapy or the simvastatin/ezetimibe fixed-dose combination were further classified into “unrestricted” and “restricted” categories.

The unrestricted and restricted lipid-modifying therapy categories were based on a step-therapy program instituted by the regional MCO during the study examination period (ie, 2007). As part of the program, patients were required to “step through” (ie, cumulative pharmacy fills for at least a 90-day supply) therapy with either lovastatin or simvastatin. After this trial, patients would become “eligible” to receive atorvastatin, rosuvastatin, or simvastatin/ezetimibe fixed-dose combination therapy under their prescription benefit.

For circumstances in which patients were prescribed a restricted medication and elected not to follow the steptherapy program, they would pay the full cost of their restricted lipid-modifying therapy medication out of pocket. Accordingly, the restricted statin lipid-modifying therapy group included patients receiving atorvastatin or rosuvastatin monotherapy or the simvastatin/ ezetimibe fixed-dose combination.

The unrestricted statin group contained patients who were receiving fluvastatin, lovastatin, pravastatin, or simvastatin monotherapy.

Patients observed taking more than 1 lipid-modifying therapy type (ie, multipill combination therapy) or a non−statin-containing lipid-modifying therapy were categorized into the “other” group.

The last group—no lipid-modifying therapy—included patients who had no prescription claims observed for any lipid-modifying therapy type. For patients who switched therapy, the most recent prescription was used to categorize into a lipid-modifying therapy group.

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Excluded patients aged <18 years N = 9957

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Excluded patients without any office visits or prescription data in 2007 N = 15,309

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Excluded patients without any LDL-C values N = 4467

Adults with commercial insurance from regional managed care organization N = 25,712

Adults with ≥1 visit to primary care provider in 2007 N = 10,403

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LDL-C Goal Attainment A total of 4638 patients (78.1%) met their LDL-C goal levels. As CHD risk increased, the percentage of patients achieving goal LDL-C decreased (low, 90.8%; moderate, 67.1%; high, 52.6%; very high, 31.6%). A similar pattern of decreasing goal attainment with increasing CHD risk was found in patients in the other lipid-modifying therapy group (low, 84.7%; moderate, 64.0%; high, 58.1%; very high, 31.3%).

For all CHD risk categories except the lowest, goal achievement increased as drug therapy progressed from

Patients with commercial insurance from regional managed care organization N = 35,669

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Results Member Demographics A total of 5936 patients met the study inclusion criteria, which represented 17% of the patients seen in this large group practice who were also insured by the regional MCO (Figure 1). The baseline characteristics of these patients are presented in Table 1. In this primary care setting, the majority of patients were categorized as having low CHD risk (58.6%). A total of 2458 patients (41.4%) were at an elevated CHD risk: 24.6% at moderate, 14.9% at high, and 1.9% at very high CHD risk.

Hypertension was the most common risk factor, found in 45.3% of patients. Diabetes was present in 12.2% of the cohort, which automatically placed these patients into high or very high CHD risk categories.

Of the 1626 patients who received statin monotherapy or a simvastatin/ezetimibe fixed-dose combination, 986 and 658 patients were categorized as unrestricted and restricted lipid-modifying therapy, respectively (Table 2). This equates to an approximate 60/40 split in the 1626 patients receiving statin-based therapy.

Unrestricted lipid-modifying therapy utilization was higher than restricted lipid-modifying therapy for each CHD risk category. Of note, 3849 patients (64.8%) were not treated with any lipid-modifying therapy; most of them were in the low CHD risk category (n = 2739).

Figure 1 Large Patient Population in Primary Care Group Practice

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Statistical Analysis Descriptive statistics were used to report sample characteristics, treatment patterns, and NCEP ATP III LDLC goal attainment rates. Categorical variables are reported as frequencies and percentages, and continuous variables are reported as mean ± standard deviation. Chisquare tests were used to compare LDL-C goal attainment among the lipid-modifying therapy groups, and demographic and clinical factors associated with LDL-C goal attainment were evaluated using logistic regression.

Statistical significance was set at an accepted alpha (P <.05). All statistical analyses were performed using SAS version 9.1 (SAS Institute, Cary, NC) and Stata version 8.1 (Stata Corporation, College Station, TX).

Patients with ≥1 LDL-C value in 2007 N = 5936 NOTE: The total population in this practice is approximately 320,000.

LDL-C indicates low-density lipoprotein cholesterol.

Table 1 Baseline Patient Characteristics Characteristica

Patients N (%)

Age (yrs), mean ± SD [range]

44.9 ± 13.5 [18-92]

Men, any age Men ≥45 yrs

2984 (50.3) 2169 (36.5)

Women, any age Women ≥55 yrs

2952 (49.7) 996 (16.8)

Diagnosis Diabetes or on antidiabetic medication Hypertension or on antihypertensive therapy

724 (12.2) 2688 (45.3)

CHD risk status Low Moderate High Very high

3478 (58.6) 1461 (24.6) 883 (14.9) 114 (1.9)

a Data on ethnicity not collected. Total patients = 5936.

CHD indicates coronary heart disease; SD, standard deviation.

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Table 2 Lipid-Modifying Therapy Utilization, by CHD Risk Group Therapy group, by CHD risk category, N (%) LMT group

Low risk (N = 3478)

Moderate risk (N = 1461)

High risk (N = 883)

Very high risk (N = 114)

All patients (N = 5936)

No therapy

2739 (78.8)

799 (54.7)

298 (33.7)

13 (11.4)

3849 (64.8)

Unrestricted therapiesa

392 (11.3)

312 (21.4)

228 (25.8)

36 (31.6)

968 (16.3)

Restricted therapiesb

229 (6.6)

211 (14.4)

185 (21.0)

33 (28.9)

658 (11.1)

Other lipid therapyc

118 (3.4)

139 (9.5)

172 (19.5)

32 (28.1)

461 (7.8)

a Fluvastatin, pravastatin, lovastatin, or simvastatin monotherapy. b Atorvastatin monotherapy, rosuvastatin monotherapy, or simvastatin/ezetimibe c

fixed-dose combination.

Fibrates, niacin, ezetimibe, and bile acid sequestrants as monotherapy alone or in multipill combination therapy.

CHD indicates coronary heart disease; LMT, lipid-modifying therapy.

Figure 2 LDL-C Goal Attainment, by Lipid-Modifying Therapy Group 100

Patients achieving goal LDL-C, %

90

LMT groups: None Unrestricted Restricted (N = 5475)

92 (2524/2739)

86

86

(337/392) (197/229)

79

80

72

(166/211)

68

(224/312)

70

(126/185)

63 (501/799)

60

52 (118/228)

50

42

40

(14/33)

(120/298)

40

28 (10/36)

30 15

20

(2/13)

10 0 Low

Moderate

High

Very high

CHD risk categories CHD indicates coronary heart disease; LDL-C, low-density lipoprotein cholesterol; LMT, lipid-modifying therapy.

no therapy to unrestricted therapy to restricted therapy (P <.001) (Figure 2). For patients at elevated CHD risk (high or very high), the rates of LDL-C goal attainment were 14 to 16 percentage points higher for patients receiving restricted lipid-modifying therapy compared with patients receiving unrestricted lipid-modifying therapy (high CHD risk: 68%-52%; very high CHD risk: 42%-28%).

Factors in the multivariable logistic regression model that were significantly associated with improved LDL-C goal attainment were increasing age (odds ratio, 1.04; 95% confidence interval [CI], 1.02-1.06), male sex (odds ratio, 1.37; 95% CI, 1.07-1.76), and use of restricted

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lipid-modifying therapy (odds ratio, 1.46; 95% CI, 1.141.86). Patients at moderate (odds ratio, 0.34; 95% CI, 0.25-0.48), high (odds ratio, 0.17; 95% CI, 0.12-0.23), and very high (odds ratio, 0.05; 95% CI, 0.03-0.09) CHD risk were less likely to achieve LDL-C goal when compared with patients at low risk (data not shown).

Patients Not at LDL-C Goal As CHD risk increased, the percentage of patients not achieving goal LDL-C increased (low, 9.2%; moderate, 32.9%; high, 47.4%; very high, 68.4%). Further examination of the 1298 patients who were not at LDLC goal revealed that 702 (54.1%) patients were not

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Discussion The intent of our study was to identify targets for quality improvement initiatives. Clearly, the data support attention in the higher CHD risk categories.

About half of the patients in the high CHD risk category and two thirds of the patients in the very high CHD risk category did not achieve goal LDL-C levels.

These patients represent the largest healthcare burden.1,2 They are more likely to suffer adverse CV outcomes and associated costs than patients at lower CHD risk. National guidelines have stressed the importance of aggressively managing this population, yet current practice yields suboptimal results.1,2 Patients at higher CHD risk have lower LDL-C goals, and more difficulty attaining goal LDL-C.4-8,15,16 In addition to CHD risk status, greater percentage LDL-C reduction and lack of titration have been associated with decreased likelihood of achieving goal.15-18 In a study of patients newly initiated on statin therapy, the percentage of LDL-C reduction required to achieve goal was found to independently predict goal attainment.16 Patients who required at least a 15% reduction in LDLC level or who were at elevated CHD risk were less likely to achieve goal compared with patients who required less than a 15% reduction or who were low risk.16 Despite having pharmacy coverage, patients and physicians in our study faced restrictions in choice of lipid-modifying therapy. The restricted lipid-modifying therapy options were atorvastatin, rosuvastatin, and simvastatin/ezetimibe fixed-dose combination. These agents demonstrate superior percentage reductions in LDL-C values versus agents included in the unrestricted lipid-modifying therapy group across various practice settings.19-24 In our study, goal attainment was unaffected by lipid-

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Figure 3 Use of Unrestricted and Restricted LMT in Patients Not at LDL-C Goal Levels LMT groups: Restricted Unrestricted 100 80

Utilization, %

receiving any lipid-modifying therapy, 279 (21.5%) were receiving unrestricted lipid-modifying therapy, 155 (11.9%) were receiving restricted lipid-modifying therapy, and 162 (12.5%) were receiving other lipid-modifying therapy.

Among patients not achieving goal with either unrestricted or restricted lipid-modifying therapy (n = 434), many more patients were receiving unrestricted lipidmodifying therapy than restricted lipid-modifying therapy (57.8%-63.2% vs 33.8%-42.2%), and this trend was significant across low, moderate, and high CHD risk categories (P <.001; Figure 3). Patients receiving unrestricted lipid-modifying therapy required, on average, an additional 17.9% reduction in LDL-C levels to achieve goal LDL-C, with the high and very high CHD risk categories requiring the largest reductions, at 22.7% and 21.7%, respectively.

36.8

33.8

34.9

63.2

66.2

65.1

Low a (N = 87)

Moderate a (N = 133)

Higha (N = 169)

42.2

60 40 57.8

20 0

Very high (N = 45)

CHD risk groups a P <.001 for comparison of restricted versus unrestricted LMT use.

CHD indicates coronary heart disease; LDL-C, low-density lipoprotein cholesterol; LMT, lipid-modifying therapy.

modifying therapy use in the low CHD risk category, but more patients in the moderate, high, and very high CHD risk categories achieved goal LDL-C if they were receiving restricted lipid-modifying therapy. The disparity in LDL-C goal attainment between restricted and unrestricted lipid-modifying therapy groups was greater in higher CHD risk categories.

Patients in the high and very high CHD risk categories were more likely to achieve LDL-C goal if they were receiving restricted lipid-modifying therapy compared with unrestricted lipid-modifying therapy. In addition, for patients not at LDL-C goal, the use of unrestricted agents was greater in all of the CHD risk categories compared with the use of restricted lipid-modifying therapy. Agents in the unrestricted lipid-modifying therapy group could have been titrated to higher doses or switched to restricted agents with increased LDL-C lowering potential. However, evidence demonstrates that such modifications occur infrequently.15,17,18 In a recent study of 1654 patients newly initiated with simvastatin therapy, only 45.6% were found to be at LDL-C goal.17 In those patients who did not achieve LDL-C goal, a majority (85.4%) were not titrated from the initial simvastatin dose or switched to another statin.17 In a study of high CHD risk patients treated in a primary care setting within a Veterans Administration Medical Center, only 16% of patient visits resulted in an increased statin dose in patients with uncontrolled LDLC levels.18 Similar results were found in a study by

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Lindgren and colleagues, who examined 1166 patients with uncontrolled LDL-C values at 3 months.15 In 87.3% of these patients, there were no changes to the lipidmodifying therapy regimen. Of the 12.7% of patients with changes, approximately 74% had a change in the dose of the original lipid-modifying therapy, and 26% were prescribed a different lipid-modifying therapy. At 12 months, only 7.9% of the original cohort had attained LDL-C goal levels.15 Few patients who are not controlled on their initial regimen achieve goal LDL-C levels.15,25 In a prospective study of patients at high CHD risk with uncontrolled LDL-C levels, only 14% attained goal within 6 months.25 This low level of goal attainment occurred despite a protocol that instructed the study sites to titrate the prescribed statin as necessary to achieve LDL-C goal <100 mg/dL. Clinical inertia (eg, lack of titration) or patient nonadherence to lipid-modifying therapy can partly explain why even after longer follow-up, LDL-C goal attainment remains elusive. For patients who do have changes to their lipid-modifying therapy regimen, there is an increased risk for nonpersistence. In a study of patients with comorbid hypertension and dyslipidemia, patients who had changes to their lipid-modifying therapy were less likely to persist with their lipid-modifying therapy compared with those who remained on their initial lipid-modifying therapy regimen.26 To effectively manage formulary restrictions, systematic interventions are needed to improve LDL-C goal attainment. One study showed that using an educational intervention improved LDL-C goal attainment rates from 49% to 62%.18 After receiving this education, clinicians were more likely to increase the statin dose.18 Another study demonstrated that clinical pharmacist involvement improved LDL-C goal attainment rates by 17%, after a therapeutic conversion from one statin to other statins or statin combination products.27 Although these programs are effective, they are often only pilot studies and are not sustained for long periods.

Limitations An overestimation of LDL-C goal attainment might have occurred in this study, because patients were conservatively segmented into CHD risk categories. Data, such as family history of CHD, smoking status, and blood pressure measurements, were unavailable.

Without these data, there was no way to determine the complete number of CHD risk factors or to calculate 10year risk of having a CHD event. These additional data may have categorized patients into higher CHD risk categories, with more aggressive LDL-C goals. The result would likely have been a greater percentage of patients having LDL-C levels not at goal.

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In addition, some patients might have received drug samples, and there was no way of accounting for this supply of medication. The impact of samples without any prescription claims could affect lipid-modifying therapy group categorization and rate of LDL-C goal attainment by lipid-modifying therapy group. Similarly, patients who paid cash for their lipid-modifying therapies could have been miscategorized by lipid-modifying therapy group, which could affect the rate of LDL-C goal attainment per lipid-modifying therapy group.

Finally, we did not obtain information on medication adherence. Patients with poor medication adherence are less likely to achieve goal LDL-C values. If the percentage of patients who were nonadherent was different in the various lipid-modifying therapy groups, this could affect the discrepancy in LDL-C goal attainment.

Conclusion A significant number of patients at elevated risk for CHD remain untreated or have LDL-C levels above target; these patients are either not receiving lipidmodifying therapy or their current regimens are suboptimal. In this study, although patients receiving restricted lipid-modifying therapy agents were more likely to achieve LDL-C goal, the use of these agents was relatively low. These patterns of lipid-modifying therapy use may be helpful to discern approaches to achieve higher LDL-C goal attainment rates.

Removing barriers to the use of restricted agents in patients at elevated CHD risk provides an opportunity to achieve goal LDL-C levels aimed at decreasing the risk of subsequent CV disease events.

It is imperative that clinicians have the opportunity to individualize lipid-modifying therapy according to the patientâ&#x20AC;&#x2122;s CHD risk status and LDL-C goal, with the intent of achieving goal LDL-C with the initial therapy prescribed. To enable clinicians and patients to achieve goals, unrestricted access to initial lipid-modifying therapy regimens that are expected to achieve goal should be a standard formulary strategy for patients at high CHD risk. â&#x2013; Acknowledgment This study was supported by funding from AstraZeneca.

Disclosure Statement Mr Lynch and Dr Rosen receive research grant support from AstraZeneca and Novartis; Dr Cooke receives research grant support from AstraZeneca, Novartis, and Pfizer; Drs Gandhi and Bullano are employees of AstraZeneca LP.

References 1. Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. Executive summary of the Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment

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of High Blood Cholesterol in Adults (Adult Treatment Panel III). JAMA. 2001;285: 2486-2497.

2. Grundy SM, Cleeman JI, Merz CN, et al. Implications of recent clinical trials for the National Cholesterol Education Program Adult Treatment Panel III guidelines.

Circulation. 2004;110:227-239. Erratum in: Circulation. 2004;110:763.

3. Van Ganse E, Souchet T, Laforest L, et al. Ineffectiveness of lipid-lowering therapy in primary care. Br J Clin Pharmacol. 2005;59:456-463.

4. Stacy TA, Egger A. Results of retrospective chart review to determine improvement in lipid goal attainment in patients treated by high-volume prescribers of lipid-modifying drugs. J Manag Care Pharm. 2006;12:745-751.

5. Waters DD, Brotons C, Chiang CW, et al. Lipid Treatment Assessment Project 2: a multinational survey to evaluate the proportion of patients achieving low-density lipoprotein cholesterol goals. Circulation. 2009;120:28-34.

6. Van Ganse E, Laforest L, Alemao E, et al. Lipid-modifying therapy and attainment of cholesterol goals in Europe: the Return on Expenditure Achieved for Lipid Therapy (REALITY) study. Curr Med Res Opin. 2005;21:1389-1399.

7. Laforest L, Moulin P, Souchet T, et al. Correlates of LDL-cholesterol goal attainment in patients under lipid lowering therapy. Atherosclerosis. 2008;199:368-377. Epub 2008 Jan 11.

8. Latts LM. Assessing the results: phase 1 hyperlipidemia outcomes in 27 health plans. Am J Med. 2001;110(suppl 6A):17-23.

9. Davidson MH, Maki KC, Pearson TA, et al. Results of the National Cholesterol Education (NCEP) Program Evaluation Project Utilizing Novel E-Technology (NEPTUNE) II survey and implications for treatment under the recent NCEP writing group recommendations. Am J Cardiol. 2005;96:556-563.

10. Hilleman DE, Monaghan MS, Ashby CL, et al. Physician-prompting statin therapy intervention improves outcomes in patients with coronary heart disease.

Pharmacotherapy. 2001;21:1415-1421.

11. Doroodchi H, Abdolrasulnia M, Foster JA, et al. Knowledge and attitudes of primary care physicians in the management of patients at risk for cardiovascular events.

BMC Fam Pract. 2008;9:42.

12. Ellis JJ, Erickson SR, Stevenson JG, et al. Suboptimal statin adherence and discontinuation in primary and secondary prevention populations. J Gen Intern Med. 2004;19:638-645.

13. Headen AE Jr, Masia NA, Axelsen KJ. Effects of medicaid access restrictions on statin utilisation for patients treated by physicians practising in poor and minority neighbourhoods. Pharmacoeconomics. 2006;24(suppl 3):41-53.

14. Tsang JL, Mendelsohn A, Tan MK, et al; for the Vascular Protection Registry and Guidelines Oriented Approach to Lipid Lowering Registry Investigators. Discordance between physicians’ estimation of patient cardiovascular risk and use of evidencebased medical therapy. Am J Cardiol. 2008;102:1142-1145. Epub 2008 Aug 15.

15. Lindgren P, Borgström F, Stålhammar J, et al. Determinants of cholesterol goal attainment at 12 months in patients with hypercholesterolaemia not at consensus

goal after 3 months of treatment with lipid-lowering drugs. Int J Clin Pract. 2007; 61:1410-1414.

16. Kamat SA, Gandhi SK, Davidson M. Comparative effectiveness of rosuvastatin versus other statin therapies in patients at increased risk of failure to achieve low-density lipoprotein goals. Curr Med Res Opin. 2007;23:1121-1130.

17. Willey VJ, Bullano MF, Shoetan NN, Gandhi SK. Therapy modifications and low-density lipoprotein cholesterol goal attainment rates associated with the initiation of generic simvastatin. Curr Med Res Opin. 2010;26:121-128.

18. Goldberg KC, Melnyk SD, Simel DL. Overcoming inertia: improvement in achieving target low-density lipoprotein cholesterol. Am J Manag Care. 2007;13: 530-534.

19. Jones P, Kafonek S, Laurora I, Hunninghake D. Comparative dose efficacy study of atorvastatin versus simvastatin, pravastatin, lovastatin, and fluvastatin in patients with hypercholesterolemia (the CURVES study). Am J Cardiol. 1998;81:582-587.

Erratum in: Am J Cardiol. 1998;82:128.

20. McKenney JM, Jones PH, Adamczyk MA, et al; for the STELLAR study group.

Comparison of the efficacy of rosuvastatin versus atorvastatin, simvastatin, and pravastatin in achieving lipid goals: results from the STELLAR trial. Curr Med Res Opin. 2003;19:689-698.

21. Bays HE, Ose L, Fraser N, et al. A multicenter, randomized, double-blind, placebo-controlled, factorial design study to evaluate the lipid-altering efficacy and safety profile of the ezetimibe/simvastatin tablet compared with ezetimibe and simvastatin monotherapy in patients with primary hypercholesterolemia. Clin Ther. 2004;26: 1758-1773.

22. Ohsfeldt RL, Gandhi SK, Fox KM, et al. Effectiveness and cost-effectiveness of rosuvastatin, atorvastatin, and simvastatin among high-risk patients in usual clinical practice. Am J Manag Care. 2006;12(15 suppl):412-423.

23. Bullano MF, Wertz DA, Yang GW, et al. Effect of rosuvastatin compared with other statins on lipid levels and National Cholesterol Education Program goal attainment for low-density lipoprotein cholesterol in a usual care setting. Pharmacotherapy.

2006;26:469-478.

24. Bullano MF, Kamat S, Wertz DA, et al. Effectiveness of rosuvastatin versus atorvastatin in reducing lipid levels and achieving low-density lipoprotein cholesterol goals in a usual care setting. Am J Health Syst Pharm. 2007;64:276-284.

25. Foley KA, Simpson RJ Jr, Crouse JR 3rd, et al. Effectiveness of statin titration on low-density lipoprotein cholesterol goal attainment in patients at high risk of atherogenic events. Am J Cardiol. 2003;92:79-81.

26. Robertson TA, Cooke CE, Wang J, et al. Effect of medication burden on persistent use of lipid-lowering drugs among patients with hypertension. Am J Manag Care.

2008;14:710-716.

27. Miller AE, Hansen LB, Saseen JJ. Switching statin therapy using a pharmacistmanaged therapeutic conversion program versus usual care conversion among indigent patients. Pharmacotherapy. 2008;28:553-561.

STAKEHOLDER PERSPECTIVE Appropriate Medication Selection Key to Cost-Effective Therapy, Patient Adherence MEDICAL/PHARMACY DIRECTORS: Because of the high cost of treatment and the clinical sequelae of cardiovascular disease, primary and secondary preventive measures are continually on payers’ minds. Cholesterol-lowering drugs are among the top-budgeted therapeutic classes for most payers, making this class a priority category for appropriate utilization management.

In their study, Lynch and colleagues addressed important issues in cholesterol management. Based on their data relevant to low-density lipoprotein cholesterol (LDL-C) goal attainment, particularly in

those who are at high and very high risk for coronary heart disease (CHD), better cholesterol management is paramount for the prevention of cardiovascular events. An interesting follow-up to this study would include the doses used and adherence and persistence patterns within the risk groups of patients with CHD. In the introduction, the authors cite a study showing that high copay cost is inversely related to patient medication adherence. One of the keys to the delivery of and payment for cost-effective therapy is appropriate therapy selection.

In the current study, the largest group of treated Continued

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STAKEHOLDER PERSPECTIVE (Continued) and untreated patients is within the low CHD risk group. In this group, treating patients with more potent and more expensive brand-name statin therapy did not produce better results based on the percentage of patients achieving their goal LDL-C level.

In reviewing these data, it appears that the most costeffective therapy was not selected for the largest group of patients. One can, therefore, understand the rationale for some type of utilization management— in this case step-therapy requirement—for this group of patients.

One alternative to the 90-day supply requirement of a generic, less-potent statin may be the exploration of a step-therapy requirement (or noncoverage) applicable only to the lower doses of the brand-name statins. This may provide more options for patients who initially require greater levels of LDL-C reductions, without wasting money to achieve LDL-C levels that could be achieved, for example, with simvastatin 40 mg/day. This approach may emphasize the importance of appropriate statin and dose selection.

The data presented by Lynch and colleagues highlight the importance of provider education regarding not only initial medication selection but also the need for adequate dose titration that is necessary for LDL-C goal attainment.

PATIENTS: Adherence to cholesterol-lowering therapy has historically been poor. In fact, a recent analysis determined that statin adherence and persistence is worse than adherence to oral antidiabetes medications or angiotensin receptor blockers.1 In addition to providers, patients also need continual education concerning the importance of cholesterol management. All barriers to medication adherence should be addressed to identify solutions, including cost-effective alternatives, when appropriate.

1. Yeaw J, Benner JS, Walt JG, et al. Comparing adherence and persistence across 6 chronic medication classes. J Manag Care Pharm. 2009;15:728-740.

Matthew Mitchell, PharmD, MBA Manager, Pharmacy Services SelectHealth, Salt Lake City, UT

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Healthcare Reform: Quality Outcomes Measurement and Reporting Cary Sennett, MD, PhD Chief Medical Officer, MedAssurant, Inc This article is based in part on a presentation at the annual meeting of the America’s Health Insurance Plans in May 2010 in Las Vegas, NV.

T

he Patient Protection and Affordable Care Act (PPACA)1 and the Health Care and Education Reconciliation Act2 of 2010 may be the first steps in the process of federal healthcare reform, but many of the provisions of the PPACA represent further movement on a path that has been laid out over the past decade by policymakers in the public and the private sectors—the historical aim of increasing value in healthcare. As healthcare reform changes the shape of the US healthcare system, the PPACA sends a strong signal that quality will be a central driver of this change.

In an environment that rewards value and quality, attention to outcomes measurement and improvement will be essential to the success of organizations across the healthcare system. This includes health plans and the physicians and institutions with which they interact. The volume and complexity of healthcare quality data will increase quickly. Investment in the infrastructure and programs needed to support quality measurement, reporting, and improvement will likely be driven by the simultaneous increase in demands for transparency and accountability at all levels of the healthcare system.

The PPACA, as well as the regulations and legislation that will follow, are driven by forces that rely profoundly on the measurement of health system performance in 2 core areas—the expansion of insurance to more Americans, and an effort to ensure consumer protection and affordability. But PPACA signals that these forces will drive the next stages of change—payment reform and delivery system reform.

Payment reform is, and increasingly will be, driven by the trend toward value-based rather than servicebased purchasing. As quality becomes part of the foundation for economic success at all levels of the healthcare system, increased coordination of care and more sophisticated population management will be necessary. The link between demonstrated performance and economic success, which began more than a decade ago, will move from the periphery to the center of healthcare. Healthcare organizations, and individual

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physicians, will have to respond. Now is the time for them to prepare.

Opportunities for Quality Outcomes Measurement and Reporting With the expansion of insurance and consumer protection forming the backbone of healthcare reform, the language of the acts themselves speaks not only to affordability but also to value. Value-based purchasing strategies, beginning with health plans and ending with the consumer, will create pressure on institutions to perform. Performance must become quantifiable, so the development of metrics to measure all facets of healthcare performance will be a key element of the reform process and is explicitly funded by the reform legislation, as discussed below.

Much of the language in the PPACA speaks to a greater awareness of coordination of care and how improved coordination at each level of the system increases value for the patient and decreases cost through enabling better clinical outcomes and the elimination of wasteful and redundant medical spending. One bonus that creates a powerful incentive for care management programs is the Care Coordination and Management Performance Bonus for Medicare Advantage (MA) plans.

The following excerpt from the PPACA explains this particular bonus and points to health reform priorities in terms of clinical and quality outcomes: “For years beginning with 2014…in the case of an MA plan that conducts 1 or more programs described [as]… (i) Care management programs that— (I) target individuals with 1 or more chronic conditions; (II) identify gaps in care; and (III) facilitate improved care by using additional resources like nurses, nurse practitioners, and physician assistants. (ii) Programs that focus on patient education and selfmanagement of health conditions, including interventions that—

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(I) help manage chronic conditions; (II) reduce declines in health status; and (III) foster patient and provider collaboration.

[The bonus would be] equal to the product of— (i) 0.5% of the national monthly per capita cost for expenditures for individuals enrolled under the original Medicare fee-for-service program for the year; and (ii) The total number of programs.”1 Older systems of quality measurement will be expanded. For example, the Physician Quality Reporting Initiative (PQRI) introduced by the Centers for Medicare & Medicaid Services (CMS), which once offered Medicare reimbursement for providers who reported a limited set of metrics, will likely become a requirement, and quality reporting will no longer be an option.

Investment in systems to support the measurement and reporting of metrics related to PQRI should increase as physicians face stronger incentives to participate.

Starting in 2010, CMS’s Five-Star Quality Rating system—a performance rating system for MA plans—will be used to create bonuses for plans that achieve 4 or 5 quality stars. Increased reimbursement will be determined by a plan’s ability to effectively demonstrate performance.

The PPACA defines these quality performance bonuses on an incremental scale, with plans eligible for a 1.5% bonus in 2012 and up to a 5% bonus in 2014.

These new financial incentives are bound to significantly shape health plan priorities in the future.

Implications for Quality Outcomes Measurement and Reporting The most notable implication of healthcare reform on quality outcomes measurement and reporting is that quality, explicitly measured, will be more tightly linked to overall economic success through the emergence of achievement-based bonuses, value-based purchasing, and exchange-enabled competition among health insurers. The demand for transparency and enhanced public reporting create a significant challenge to institutions, which will have to be able to use data for the quantitative measurement of performance and to understand how to use that information to guide efforts to improve performance.

Pilot programs, such as accountable care organizations (ACOs) and the Medicare bundled payment program, are evidence that clinical outcomes will be implicated in the determination of the monetary value of healthcare. Subsequent quality-based competition between managed care plans and delivery system–based entities (eg, ACOs) could also emerge as consumers are offered new options and have more information to guide choice.

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Health insurers will not be the only level of the system affected by these changes; providers contracted with health plans will be under additional pressure to measure and improve care. Measured and reported quality in the clinic setting may enhance opportunities for health plans to value-purchase and may create opportunities for health plans to support their networks with programs to further enable improvement.

Starting in 2010, CMS’s Five-Star Quality Rating system—a performance rating system for MA plans—will be used to create bonuses for plans that achieve 4 or 5 quality stars. Increased reimbursement will be determined by a plan’s ability to effectively demonstrate performance.

Driven by the $75 million annually appropriated by the PPACA for quality measure development between 2010 and 2014, quality metrics will advance across a broader surface. More robust measures of clinical quality and outcomes will emerge, including measures to assess: • Health outcomes and functional status of patients • Management and coordination of care across episodes of care • Care transitions for patients across the continuum of providers, healthcare settings, and health plans.

With CMS’s triennial assessment of gaps in quality measures, the expectation is that there will be more specific metrics for the assessment of coordination of care and metrics to accurately address safety, efficiency, and patient experience. This broader set of metrics—many much more complex than those available today—will require more complex calculations to measure quality.

At the same time, healthcare organizations—from health plans to individual physicians—will find further challenges, managing and improving the more complex care processes on which these broader and more robust metrics will shine a light.

How Health Plans Can Prepare for Increasing Demands for Quality Data Management Strategic investment will not only lead to positive and significant return on investments (ROIs); it will also enable health plans to create more value for their covered members.

Invest in Measurement The HEDIS (Healthcare Effectiveness Data and Information Set) measures developed by the National

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Committee for Quality Assurance are an important starting point, but a starting point nonetheless. First, health plans must assess themselves comparatively against the competition. They will need to define the internal processes that influence the accepted measures of quality to understand why they rank the way they do.

Beyond comparative assessment, health plans will need an infrastructure for compiling information about the providers with whom they contract; quality measures will include data related to clinical outcomes for which the providers are responsible. As healthcare reform drives accountability, it will be the responsibility of the health plan to determine and constantly improve the value of the providers who comprise their network.

With the rise of value-based purchasing, health plans will have to be more transparent regarding their performance and will have to demonstrate that they are delivering and improving value across their entire network.

Invest in Improvement Health plans should be aware that the 2012 MA reimbursements will be based on the 2011 CMS Five-Star Quality Rating system. Improvement in those areas will increase reimbursement almost immediately. The key is knowing where you are starting, understanding what measures represent the best opportunity for improvement in the Five-Star Quality Rating system, and then focusing resources on making the changes that will lead to the largest improvement in the plan’s overall star rating.

Buy on Value and Partner with Providers to Improve Value Just as purchasers are beginning to buy based on value, so should health plans. Provider evaluation and

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assessment form the basis for contract decision-making and allow plans to work with providers to improve performance and quality metrics. Pay-for-performance and other value-based purchasing strategies reinforce accountability at all levels of the system. Risk-sharing between health plans and providers will be combined with information-sharing and investment in other programs to support provider performance improvement for the benefit of the purchaser, provider, and payer—and, of course, the patient.

Conclusion With pressure to create a more value-driven, transparent, and accountable marketplace, and with appropriated funding for quality measure development, the PPACA is going to drive significant increases in the extent and complexity of reporting requirements at all levels of the healthcare system. The PPACA’s commitment to patient protection, expansion of insurance coverage, and affordability demands investment on the part of CMS, health plans, and providers. With the rise of value-based purchasing, health plans will have to be more transparent regarding their performance and will have to demonstrate that they are delivering and improving value across their entire network. The potential ROI is significant for quality measurement and reporting, and for systems that enable documentable improvements. The PPACA has established bonus incentives in the language of reform to begin rewarding health plans and providers almost immediately for achievement, and appears to guarantee that investment today will lead to economic success and better quality healthcare for patients in the very near future. ■ References 1. Patient Protection and Affordable Care Act, H.R. 3590. http://democrats.senate. gov/reform/patient-protection-affordable-care-act-as-passed.pdf. Accessed July 19, 2010.

2. Health Care and Education Reconciliation Act of 2010, H.R. 4872. http:// frwebgate.access.gpo.gov/cgi-bin/getdoc.cgi?dbname=111_cong_bills&docid=f:h4872 enr.txt.pdf. Accessed July 19, 2010.

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Victoza® (liraglutide [rDNA origin] injection) Rx only BRIEF SUMMARY. Please consult package insert for full prescribing information.

WARNING: RISK OF THYROID C-CELL TUMORS: Liraglutide causes dose-dependent and treatment-duration-dependent thyroid C-cell tumors at clinically relevant exposures in both genders of rats and mice. It is unknown whether Victoza® causes thyroid C-cell tumors, including medullary thyroid carcinoma (MTC), in humans, as human relevance could not be ruled out by clinical or nonclinical studies. Victoza® is contraindicated in patients with a personal or family history of MTC and in patients with Multiple Endocrine Neoplasia syndrome type 2 (MEN 2). Based on the findings in rodents, monitoring with serum calcitonin or thyroid ultrasound was performed during clinical trials, but this may have increased the number of unnecessary thyroid surgeries. It is unknown whether monitoring with serum calcitonin or thyroid ultrasound will mitigate human risk of thyroid C-cell tumors. Patients should be counseled regarding the risk and symptoms of thyroid tumors [see Contraindications and Warnings and Precautions].

INDICATIONS AND USAGE: Victoza® is indicated as an adjunct to diet and exercise to improve glycemic control in adults with type 2 diabetes mellitus. Important Limitations of Use: Because of the uncertain relevance of the rodent thyroid C-cell tumor findings to humans, prescribe Victoza® only to patients for whom the potential benefits are considered to outweigh the potential risk. Victoza® is not recommended as first-line therapy for patients who have inadequate glycemic control on diet and exercise. In clinical trials of Victoza®, there were more cases of pancreatitis with Victoza® than with comparators. Victoza® has not been studied sufficiently in patients with a history of pancreatitis to determine whether these patients are at increased risk for pancreatitis while using Victoza®. Use with caution in patients with a history of pancreatitis.

Victoza® is not a substitute for insulin. Victoza® should not be used in patients with type 1 diabetes mellitus or for the treatment of diabetic ketoacidosis, as it would not be effective in these settings. The concurrent use of Victoza® and insulin has not been studied.

CONTRAINDICATIONS: Victoza® is contraindicated in patients with a personal or family history of medullary thyroid carcinoma (MTC) or in patients with Multiple Endocrine Neoplasia syndrome type 2 (MEN 2).

WARNINGS AND PRECAUTIONS: Risk of Thyroid C-cell Tumors: Liraglutide causes dose-dependent and treatment-duration-dependent thyroid C-cell tumors (adenomas and/or carcinomas) at clinically relevant exposures in both genders of rats and mice. Malignant thyroid C-cell carcinomas were detected in rats and mice. A statistically significant increase in cancer was observed in rats receiving liraglutide at 8-times clinical exposure compared to controls. It is unknown whether Victoza® will cause thyroid C-cell tumors, including medullary thyroid carcinoma (MTC), in humans, as the human relevance of liraglutide-induced rodent thyroid C-cell tumors could not be determined by clinical or nonclinical studies [see Boxed Warning, Contraindications]. In the clinical trials, there have been 4 reported cases of thyroid C-cell hyperplasia among Victoza®-treated patients and 1 case in a comparator-treated patient (1.3 vs. 0.6 cases per 1000 patient-years). One additional case of thyroid C-cell hyperplasia in a Victoza®-treated patient and 1 case of MTC in a comparator-treated patient have subsequently been reported. This comparator-treated patient with MTC had pre-treatment serum calcitonin concentrations >1000 ng/L suggesting pre-existing disease. All of these cases were diagnosed after thyroidectomy, which was prompted by abnormal results on routine, protocol-specified measurements of serum calcitonin. Four of the five liraglutide-treated patients had elevated calcitonin concentrations at baseline and throughout the trial. One liraglutide and one non-liraglutide-treated patient developed elevated calcitonin concentrations while on treatment. Calcitonin, a biological marker of MTC, was measured throughout the clinical development program. The serum calcitonin assay used in the Victoza® clinical trials had a lower limit of quantification (LLOQ) of 0.7 ng/L and the upper limit of the reference range was 5.0 ng/L for women and 8.4 ng/L for men. At Weeks 26 and 52 in the clinical trials, adjusted mean serum calcitonin concentrations were higher in Victoza®treated patients compared to placebo-treated patients but not compared to patients receiving active comparator. At these timepoints, the adjusted mean serum calcitonin values (~ 1.0 ng/L) were just above the LLOQ with between-group differences in adjusted mean serum calcitonin values of approximately 0.1 ng/L or less. Among patients with pre-treatment serum calcitonin below the upper limit of the reference range, shifts to above the upper limit of the reference range which persisted in subsequent measurements occurred most frequently among patients treated with Victoza® 1.8 mg/day. In trials with on-treatment serum calcitonin measurements out to 5-6 months, 1.9% of patients treated with Victoza® 1.8 mg/day developed new and persistent calcitonin elevations above the upper limit of the reference range compared to 0.8-1.1% of patients treated with control medication or the 0.6 and 1.2 mg doses of Victoza®. In trials with on-treatment serum calcitonin measurements out to 12 months, 1.3% of patients treated with Victoza® 1.8 mg/day had new and persistent elevations of calcitonin from below or within the reference range to above the upper limit of the reference range, compared to 0.6%, 0% and 1.0% of patients treated with Victoza® 1.2 mg, placebo and active control, respectively. Otherwise, Victoza® did not produce consistent dose-dependent or time-dependent increases in serum calcitonin. Patients with MTC usually have calcitonin values >50 ng/L. In Victoza® clinical trials, among patients with pre-treatment serum calcitonin <50 ng/L, one Victoza®-treated patient and no comparator-treated patients developed serum calcitonin >50 ng/L. The Victoza®-treated patient who developed serum calcitonin >50 ng/L had an elevated pre-treatment serum calcitonin of 10.7 ng/L that increased to 30.7 ng/L at Week 12 and 53.5 ng/L at the end of the 6-month trial. Follow-up serum calcitonin was 22.3 ng/L more than 2.5 years after the last dose of Victoza®. The largest increase in serum calcitonin in a comparator-treated patient was seen with glimepiride in a patient whose serum calcitonin increased from 19.3 ng/L at baseline to 44.8 ng/L at Week 65 and 38.1 ng/L at Week 104. Among patients who began with serum calcitonin <20 ng/L, calcitonin elevations to >20 ng/L occurred in 0.7% of Victoza®-treated patients, 0.3% of placebo-treated patients, and 0.5% of active-comparator-treated patients, with an incidence of 1.1% among patients treated with 1.8 mg/day of Victoza®. The clinical significance of these findings is unknown. Counsel patients regarding the risk for MTC and the symptoms of thyroid tumors (e.g. a mass in the neck, dysphagia, dyspnea or persistent hoarseness). It is unknown whether monitoring with serum calcitonin or thyroid ultrasound will mitigate the potential risk of MTC, and such monitoring may increase the risk of unnecessary procedures, due to low test specificity for serum calcitonin and a high background incidence of thyroid disease. Patients with thyroid nodules noted on physical examination or neck imaging obtained for other reasons should be referred to an endocrinologist for further evaluation. Although routine monitoring of serum calcitonin is of uncertain value in patients treated with Victoza®, if serum calcitonin is measured and found to be elevated, the patient should be referred to an endocrinologist for further evaluation. Pancreatitis: In clinical

trials of Victoza®, there were 7 cases of pancreatitis among Victoza®-treated patients and 1 case among comparator-treated patients (2.2 vs. 0.6 cases per 1000 patient-years). Five cases with Victoza® were reported as acute pancreatitis and two cases with Victoza® were reported as chronic pancreatitis. In one case in a Victoza®-treated patient, pancreatitis, with necrosis, was observed and led to death; however clinical causality could not be established. One additional case of pancreatitis has subsequently been reported in a Victoza®-treated patient. Some patients had other risk factors for pancreatitis, such as a history of cholelithiasis or alcohol abuse. There are no conclusive data establishing a risk of pancreatitis with Victoza® treatment. After initiation of Victoza®, and after dose increases, observe patients carefully for signs and symptoms of pancreatitis (including persistent severe abdominal pain, sometimes radiating to the back and which may or may not be accompanied by vomiting). If pancreatitis is suspected, Victoza® and other potentially suspect medications should be discontinued promptly, confirmatory tests should be performed and appropriate management should be initiated. If pancreatitis is confirmed, Victoza® should not be restarted. Use with caution in patients with a history of pancreatitis. Use with Medications Known to Cause Hypoglycemia: Patients receiving Victoza® in combination with an insulin secretagogue (e.g., sulfonylurea) may have an increased risk of hypoglycemia. In the clinical trials of at least 26 weeks duration, hypoglycemia requiring the assistance of another person for treatment occurred in 7 Victoza®-treated patients and in no comparator-treated patients. Six of these 7 patients treated with Victoza® were also taking a sulfonylurea. The risk of hypoglycemia may be lowered by a reduction in the dose of sulfonylurea or other insulin secretagogues [see Adverse Reactions]. Macrovascular Outcomes: There have been no clinical studies establishing conclusive evidence of macrovascular risk reduction with Victoza® or any other antidiabetic drug.

ADVERSE REACTIONS: Clinical Trials Experience: Because clinical trials are conducted under widely varying conditions, adverse reaction rates observed in the clinical trials of a drug cannot be directly compared to rates in the clinical trials of another drug and may not reflect the rates observed in practice. The safety of Victoza® was evaluated in a 52-week monotherapy trial and in four 26-week, add-on combination therapy trials. In the monotherapy trial, patients were treated with Victoza® 1.2 mg daily, Victoza® 1.8 mg daily, or glimepiride 8 mg daily. In the add-on to metformin trial, patients were treated with Victoza® 0.6 mg, Victoza® 1.2 mg, Victoza® 1.8 mg, placebo, or glimepiride 4 mg. In the add-on to glimepiride trial, patients were treated with Victoza® 0.6 mg, Victoza® 1.2 mg, Victoza® 1.8 mg, placebo, or rosiglitazone 4 mg. In the add-on to metformin + glimepiride trial, patients were treated with Victoza® 1.8 mg, placebo, or insulin glargine. In the add-on to metformin + rosiglitazone trial, patients were treated with Victoza® 1.2 mg, Victoza® 1.8 mg or placebo. Withdrawals: The incidence of withdrawal due to adverse events was 7.8% for Victoza®-treated patients and 3.4% for comparator-treated patients in the five controlled trials of 26 weeks duration or longer. This difference was driven by withdrawals due to gastrointestinal adverse reactions, which occurred in 5.0% of Victoza®-treated patients and 0.5% of comparator-treated patients. The most common adverse reactions leading to withdrawal for Victoza®-treated patients were nausea (2.8% versus 0% for comparator) and vomiting (1.5% versus 0.1% for comparator). Withdrawal due to gastrointestinal adverse events mainly occurred during the first 2-3 months of the trials. Tables 1 and 2 summarize the adverse events reported in ≥5% of Victoza®-treated patients in the five controlled trials of 26 weeks duration or longer.

Table 1: Adverse events reported in ≥ 5% of Victoza®-treated patients or ≥5% of glimepiride-treated patients: 52-week monotherapy trial All Victoza® N = 497 Glimepiride N = 248 (%) (%) Adverse Event Term Nausea 28.4 8.5 Diarrhea 17.1 8.9 Vomiting 10.9 3.6 Constipation 9.9 4.8 Upper Respiratory Tract Infection 9.5 5.6 Headache 9.1 9.3 Influenza 7.4 3.6 Urinary Tract Infection 6.0 4.0 Dizziness 5.8 5.2 Sinusitis 5.6 6.0 Nasopharyngitis 5.2 5.2 Back Pain 5.0 4.4 Hypertension 3.0 6.0 Table 2: Adverse events reported in ≥ 5% of Victoza®-treated patients and occurring more frequently with Victoza® compared to placebo: 26-week combination therapy trials

Adverse Event Term Nausea Diarrhea Headache Vomiting

Adverse Event Term Nausea Diarrhea Constipation Dyspepsia

Add-on to Metformin Trial Glimepiride + Placebo + All Victoza® + Metformin Metformin Metformin N = 242 N = 121 N = 724 (%) (%) (%) 15.2 4.1 3.3 10.9 4.1 3.7 9.0 6.6 9.5 6.5 0.8 0.4 Add-on to Glimepiride Trial All Victoza® + Placebo + Glimepiride Rosiglitazone + Glimepiride N = 695 N = 114 Glimepiride N = 231 (%) (%) (%) 7.5 1.8 2.6 7.2 1.8 2.2 5.3 0.9 1.7 5.2 0.9 2.6

Add-on to Metformin + Glimepiride Placebo + Metformin Glargine + Metformin Victoza® 1.8 + Metformin + + Glimepiride + Glimepiride Glimepiride N =114 N =232 N =230 (%) (%) (%) Adverse Event Term Nausea 13.9 3.5 1.3 Diarrhea 10.0 5.3 1.3 Headache 9.6 7.9 5.6 Dyspepsia 6.5 0.9 1.7 Vomiting 6.5 3.5 0.4 Add-on to Metformin + Rosiglitazone Placebo + Metformin All Victoza® + Metformin + Rosiglitazone N = 355 + Rosiglitazone N = 175 (%) (%) Adverse Event Term Nausea 34.6 8.6 Diarrhea 14.1 6.3 Vomiting 12.4 2.9 Decreased Appetite 9.3 1.1 Anorexia 9.0 0.0 Headache 8.2 4.6 Constipation 5.1 1.1 Fatigue 5.1 1.7 Gastrointestinal adverse events: In the five clinical trials of 26 weeks duration or longer, gastrointestinal adverse events were reported in 41% of Victoza®-treated patients and were dose-related.

Gastrointestinal adverse events occurred in 17% of comparator-treated patients. Events that occurred more commonly among Victoza®-treated patients included nausea, vomiting, diarrhea, dyspepsia and constipation. In clinical trials of 26 weeks duration or longer, the percentage of patients who reported nausea declined over time. Approximately 13% of Victoza®-treated patients and 2% of comparator-treated patients reported nausea during the first 2 weeks of treatment. Immunogenicity: Consistent with the potentially immunogenic properties of protein and peptide pharmaceuticals, patients treated with Victoza® may develop anti-liraglutide antibodies.

Approximately 50-70% of Victoza®-treated patients in the five clinical trials of 26 weeks duration or longer were tested for the presence of anti-liraglutide antibodies at the end of treatment.

Low titers (concentrations not requiring dilution of serum) of anti-liraglutide antibodies were detected in 8.6% of these Victoza®-treated patients. Sampling was not performed uniformly across all patients in the clinical trials, and this may have resulted in an underestimate of the actual percentage of patients who developed antibodies. Cross-reacting anti-liraglutide antibodies to native glucagon-like peptide-1 (GLP-1) occurred in 6.9% of the Victoza®-treated patients in the 52-week monotherapy trial and in 4.8% of the Victoza®-treated patients in the 26-week add-on combination therapy trials. These cross-reacting antibodies were not tested for neutralizing effect against native GLP-1, and thus the potential for clinically significant neutralization of native GLP-1 was not assessed. Antibodies that had a neutralizing effect on liraglutide in an in vitro assay occurred in 2.3% of the Victoza®-treated patients in the 52-week monotherapy trial and in 1.0% of the Victoza®-treated patients in the 26-week add-on combination therapy trials.

Among Victoza®-treated patients who developed anti-liraglutide antibodies, the most common category of adverse events was that of infections, which occurred among 40% of these patients compared to 36%, 34% and 35% of antibody-negative Victoza®-treated, placebo-treated and active-control-treated patients, respectively. The specific infections which occurred with greater frequency among Victoza®-treated antibody-positive patients were primarily nonserious upper respiratory tract infections, which occurred among 11% of Victoza®-treated antibody-positive patients; and among 7%, 7% and 5% of antibody-negative Victoza®-treated, placebo-treated and active-control-treated patients, respectively. Among Victoza®-treated antibody-negative patients, the most common category of adverse events was that of gastrointestinal events, which occurred in 43%, 18% and 19% of antibody-negative Victoza®-treated, placebo-treated and active-control-treated patients, respectively. Antibody formation was not associated with reduced efficacy of Victoza® when comparing mean HbA1c of all antibody-positive and all antibody-negative patients.

However, the 3 patients with the highest titers of anti-liraglutide antibodies had no reduction in HbA1c with Victoza® treatment. In clinical trials of Victoza®, events from a composite of adverse events potentially related to immunogenicity (e.g. urticaria, angioedema) occurred among 0.8% of Victoza®-treated patients and among 0.4% of comparator-treated patients. Urticaria accounted for approximately one-half of the events in this composite for Victoza®-treated patients. Patients who developed anti-liraglutide antibodies were not more likely to develop events from the immunogenicity events composite than were patients who did not develop anti-liraglutide antibodies.

Injection site reactions: Injection site reactions (e.g., injection site rash, erythema) were reported in approximately 2% of Victoza®-treated patients in the five clinical trials of at least 26 weeks duration. Less than 0.2% of Victoza®-treated patients discontinued due to injection site reactions.

Papillary thyroid carcinoma: In clinical trials of Victoza®, there were 6 reported cases of papillary thyroid carcinoma in patients treated with Victoza® and 1 case in a comparator-treated patient (1.9 vs. 0.6 cases per 1000 patient-years). Most of these papillary thyroid carcinomas were <1 cm in greatest diameter and were diagnosed in surgical pathology specimens after thyroidectomy prompted by findings on protocol-specified screening with serum calcitonin or thyroid ultrasound. Hypoglycemia: In the clinical trials of at least 26 weeks duration, hypoglycemia requiring the assistance of another person for treatment occurred in 7 Victoza®-treated patients (2.6 cases per 1000 patient-years) and in no comparator-treated patients. Six of these 7 patients treated

with Victoza® were also taking a sulfonylurea. One other patient was taking Victoza® in combination with metformin but had another likely explanation for the hypoglycemia (this event occurred during hospitalization and after insulin infusion) (Table 3). Two additional cases of hypoglycemia requiring the assistance of another person for treatment have subsequently been reported in patients who were not taking a concomitant sulfonylurea. Both patients were receiving Victoza®, one as monotherapy and the other in combination with metformin. Both patients had another likely explanation for the hypoglycemia (one received insulin during a frequently-sampled intravenous glucose tolerance test, and the other had intracranial hemorrhage and uncertain food intake).

Table 3: Incidence (%) and Rate (episodes/patient year) of Hypoglycemia in the 52-Week Monotherapy Trial and in the 26-Week Combination Therapy Trials Victoza® Active Placebo Treatment Comparator Comparator Glimepiride None Monotherapy Victoza® (N = 497) (N = 248) Patient not able to self−treat 0 0 — Patient able to self−treat 9.7 (0.24) 25.0 (1.66) — Not classified 1.2 (0.03) 2.4 (0.04) — Glimepiride + Placebo + Add-on to Victoza® + Metformin Metformin Metformin Metformin (N = 724) (N = 242) (N = 121) Patient not able to self−treat 0.1 (0.001) 0 0 Patient able to self−treat 3.6 (0.05) 22.3 (0.87) 2.5 (0.06) Rosiglitazone + Placebo + Add-on to Glimepiride Victoza® + Glimepiride Glimepiride Glimepiride (N = 695) (N = 231) (N = 114) Patient not able to self−treat 0.1 (0.003) 0 0 Patient able to self−treat 7.5 (0.38) 4.3 (0.12) 2.6 (0.17) Not classified 0.9 (0.05) 0.9 (0.02) 0 Placebo + Add-on to Victoza® + Metformin + None Metformin + Metformin + Rosiglitazone Rosiglitazone Rosiglitazone (N = 355) (N = 175) Patient not able to self−treat 0 — 0 Patient able to self−treat 7.9 (0.49) — 4.6 (0.15) Not classified 0.6 (0.01) — 1.1 (0.03) Insulin glargine Placebo + Add-on to Victoza® + Metformin + + Metformin + Metformin + Metformin + Glimepiride Glimepiride Glimepiride Glimepiride (N = 230) (N = 232) (N = 114) Patient not able to self−treat 2.2 (0.06) 0 0 Patient able to self−treat 27.4 (1.16) 28.9 (1.29) 16.7 (0.95) Not classified 0 1.7 (0.04) 0 In a pooled analysis of clinical trials, the incidence rate (per 1,000 patient-years) for malignant neoplasms (based on investigator-reported events, medical history, pathology reports, and surgical reports from both blinded and open-label study periods) was 10.9 for Victoza®, 6.3 for placebo, and 7.2 for active comparator. After excluding papillary thyroid carcinoma events [see Adverse Reactions], no particular cancer cell type predominated. Seven malignant neoplasm events were reported beyond 1 year of exposure to study medication, six events among Victoza®treated patients (4 colon, 1 prostate and 1 nasopharyngeal), no events with placebo and one event with active comparator (colon). Causality has not been established. Laboratory Tests: In the five clinical trials of at least 26 weeks duration, mildly elevated serum bilirubin concentrations (elevations to no more than twice the upper limit of the reference range) occurred in 4.0% of Victoza®-treated patients, 2.1% of placebo-treated patients and 3.5% of active-comparatortreated patients. This finding was not accompanied by abnormalities in other liver tests. The significance of this isolated finding is unknown.

OVERDOSAGE: In a clinical trial, one patient with type 2 diabetes experienced a single overdose of Victoza® 17.4 mg subcutaneous (10 times the maximum recommended dose). Effects of the overdose included severe nausea and vomiting requiring hospitalization. No hypoglycemia was reported. The patient recovered without complications. In the event of overdosage, appropriate supportive treatment should be initiated according to the patient’s clinical signs and symptoms.

More detailed information is available on request.

For information about Victoza® contact: Novo Nordisk Inc., 100 College Road West, Princeton, New Jersey 08540, 1−877-484-2869 Date of Issue: January 2010 Version: 1 Manufactured by: Novo Nordisk A/S, DK-2880 Bagsvaerd, Denmark Victoza® is a registered trademark of Novo Nordisk A/S. Victoza® is covered by US Patent Nos. 6,268,343; 6,458,924; and 7,235,627 and other patents pending. Victoza® Pen is covered by US Patent Nos. 6,004,297; 6,235,004; 6,582,404 and other patents pending. © 2010 Novo Nordisk A/S 140586-R1 4/2010

Once-daily Victoza® : Can provide the additional benefit of weight loss Safety and tolerability were studied in clinical trials that included nearly 4000 patients

Targets beta cells Provides powerful and sustained reductions in A1C*

Victoza® is not indicated for the management of obesity, and weight change was a secondary end point in clinical trials.

Visit VictozaPro.com to learn more.

Indications and usage Victoza® is indicated as an adjunct to diet and exercise to improve glycemic control in adults with type 2 diabetes mellitus.

Because of the uncertain relevance of the rodent thyroid C-cell tumor findings to humans, prescribe Victoza® only to patients for whom the potential benefits are considered to outweigh the potential risk.

Victoza® is not recommended as first-line therapy for patients who have inadequate glycemic control on diet and exercise.

In clinical trials of Victoza®, there were more cases of pancreatitis with Victoza® than with comparators. Victoza® has not been studied sufficiently in patients with a history of pancreatitis to determine whether these patients are at increased risk for pancreatitis while using Victoza®. Use with caution in patients with a history of pancreatitis.

Victoza® is not a substitute for insulin. Victoza® should not be used in patients with type 1 diabetes mellitus or for the treatment of diabetic ketoacidosis, as it would not be effective in these settings.

The concurrent use of Victoza® and insulin has not been studied.

Important safety information Liraglutide causes dose-dependent and treatment-durationdependent thyroid C-cell tumors at clinically relevant exposures in both genders of rats and mice. It is unknown whether Victoza® causes thyroid C-cell tumors, including medullary thyroid carcinoma (MTC), in humans, as human relevance could not be ruled out by clinical or nonclinical studies. Victoza® is contraindicated in patients with a personal or family history of MTC and in patients with Multiple Endocrine Neoplasia syndrome type 2 (MEN 2). Based on the findings in rodents, monitoring with serum calcitonin or thyroid ultrasound was performed during clinical trials, but this may have increased the number of unnecessary thyroid surgeries. It is unknown whether monitoring with serum calcitonin or thyroid ultrasound will mitigate human risk of thyroid C-cell tumors. Patients should be counseled regarding the risk and symptoms of thyroid tumors.

If pancreatitis is suspected, Victoza® should be discontinued. Victoza® should not be re-initiated if pancreatitis is confirmed.

When Victoza® is used with an insulin secretagogue (e.g. a sulfonylurea) serious hypoglycemia can occur. Consider lowering the dose of the insulin secretagogue to reduce the risk of hypoglycemia.

There have been no studies establishing conclusive evidence of macrovascular risk reduction with Victoza ® or any other antidiabetic drug.

The most common adverse reactions, reported in ≥5% of patients treated with Victoza® and more commonly than in patients treated with placebo, are headache, nausea, diarrhea, and anti-liraglutide antibody formation. Immunogenicity-related events, including urticaria, were more common among Victoza®-treated patients (0.8%) than among comparator-treated patients (0.4%) in clinical trials.

Victoza® has not been studied in type 2 diabetes patients below 18 years of age and is not recommended for use in pediatric patients.

Victoza® should be used with caution in patients with renal impairment and in patients with hepatic impairment.

Please see brief summary of Prescribing Information on adjacent page. *Victoza® was evaluated in a 52-week monotherapy trial and in four 26-week, add-on combination trials.

Victoza® is a registered trademark of Novo Nordisk A/S. © 2010 Novo Nordisk A/S

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