AHDB

THE PEER-REVIEWED FORUM FOR REAL-WORLD EVIDENCE IN BENEFIT DESIGN ™ JULY 2016

VOLUME 9, NUMBER 5

FOR PAYERS, PURCHASERS, POLICYMAKERS, AND OTHER HEALTHCARE STAKEHOLDERS

EDITORIAL

Improving Population Health by Working with Communities David B. Nash, MD, MBA

CLINICAL

Impact of Pharmacist-Provided Medication Therapy Management on Healthcare Quality and Utilization in Recently Discharged Elderly Patients Jordan D. Haag, PharmD, RPh; Amanda Z. Davis, PharmD, RPh; Robert W. Hoel, PharmD, RPh; Jeffrey J. Armon, PharmD, RPh; Laura J. Odell, PharmD, RPh; Ross A. Dierkhising, MS; Paul Y. Takahashi, MD

Stakeholder Perspective: A Systematic Approach to Medication Therapy Management in Elderly Patients with Chronic Diseases Can Improve Outcomes

By James T. Kenney, Jr, RPh, MBA ™

BUSINESS

Hospital and Health Plan Partnerships: The Affordable Care Act’s Impact on Promoting Health and Wellness Michelle Vu, PharmD candidate; Annesha White, PharmD, PhD; Virginia P. Kelley, MBA; Jennifer Kuca Hopper, MS; Cathy Liu, PharmD candidate

Stakeholder Perspective: Measurable Clarity in Healthcare Is Needed So Those Who Use the System Could Achieve a State of Well-Being

By F. Randy Vogenberg, PhD, RPh

REGULATORY

Oncologist Support for Consolidated Payments for Cancer Care Management in the United States Siva Narayanan, MSc, MHS; Emily Hautamaki, MPH

Stakeholder Perspective: Implementing Payment Reform in Oncology: Benefits and Challenges

By Byron C. Scott, MD, MBA

INDUSTRY TRENDS MACRA: The Quiet Healthcare Takeover

© 2016 Engage Healthcare Communications, LLC

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EDITORIAL BOARD

Al B. Benson III, MD, FACP, FASCO Professor of Medicine, Associate Director for Clinical Investigations Robert H. Lurie Comprehensive Cancer Center Northwestern University, IL Samuel M. Silver, MD, PhD, FASCO Professor of Internal Medicine, Hematology/Oncology Assistant Dean for Research, Associate Director Faculty Group Practice, University of Michigan Medical School

Kavita V. Nair, PhD Professor and Director, Graduate Program Track in Pharmaceutical Outcomes Research Skaggs School of Pharmacy and Pharmaceutical Sciences University of Colorado, Aurora Gary M. Owens, MD President, Gary Owens Associates Ocean View, DE Andrew M. Peterson, PharmD, PhD Dean, Mayes School of Healthcare Business and Policy, Associate Professor, University of the Sciences, Philadelphia, PA Sarah A. Priddy, PhD Director, Competitive Health Analytics Humana, Louisville, KY Timothy S. Regan, BPharm, RPh, CPh Executive Director, Strategic Accounts Xcenda, Palm Harbor, FL Vincent J. Willey, PharmD, BCACP Staff Vice President HealthCore, Inc, Wilmington, DE David W. Wright, MPH President, Institute for Interactive Patient Care Bethesda, MD

EMPLOYERS

HEALTH & VALUE PROMOTION

EDITOR-IN-CHIEF

David B. Nash, MD, MBA Founding Dean, The Dr Raymond C. and Doris N. Grandon Professor, Jefferson College of Population Health, Thomas Jefferson University Philadelphia, PA DEPUTY EDITOR

Laura T. Pizzi, PharmD, MPH, RPh Professor, Dept. of Pharmacy Practice, Jefferson School of Pharmacy, Thomas Jefferson University AGING AND WELLNESS

Eric G. Tangalos, MD, FACP, AGSF, CMD Professor of Medicine Mayo Clinic, Rochester, MN CANCER RESEARCH

Gregory Shaeffer, MBA, RPh, FASHP Vice President, Consulting Pharmacy Healthcare Solutions AmerisourceBergen, Harrisburg, PA Arthur F. Shinn, PharmD, FASCP President, Managed Pharmacy Consultants, LLC, Lake Worth, FL F. Randy Vogenberg, RPh, PhD Principal, Institute for Integrated Healthcare Greenville, SC ENDOCRINOLOGY

James V. Felicetta, MD Chairman, Dept. of Medicine Carl T. Hayden Veterans Affairs Medical Center, Phoenix, AZ Quang T. Nguyen, DO, FACP, FACE, FTOS Medical Director, Las Vegas Endocrinology Adjunct Associate Professor, Endocrinology Touro University Nevada EPIDEMIOLOGY RESEARCH

Joshua N. Liberman, PhD Executive Director, Research, Development & Dissemination, Sutter Health, Concord, CA GOVERNMENT

Kevin B. “Kip” Piper, MA, FACHE President, Health Results Group, LLC Washington, DC HEALTH INFORMATION TECHNOLOGY

Kelly Huang, PhD Vice President and General Manager Aesthetic & Corrective Business Galderma Laboratories, LP, Fort Worth, TX HEALTH OUTCOMES RESEARCH

Russell Basser, MBBS, MD, FRACP Senior Vice President Global Clinical Research and Development CSL Behring, King of Prussia, PA Diana Brixner, RPh, PhD Professor & Chair, Dept. of Pharmacotherapy Executive Director, Outcomes Research Center Director of Outcomes, Personalized Health Care Program, University of Utah, Salt Lake City Joseph E. Couto, PharmD, MBA Clinical Program Manager Cigna Corporation, Bloomfield, CT Steven Miff, PhD Senior Vice President VHA, Inc, Irving, TX

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Jeff Jianfei Guo, BPharm, MS, PhD Professor of Pharmacoeconomics & Pharmacoepidemiology, College of Pharmacy Univ. of Cincinnati Medical Center, OH PHARMACY BENEFIT DESIGN

Joel V. Brill, MD, AGAF, CHCQM Chief Medical Officer, Predictive Health Phoenix, AZ Teresa DeLuca, MD, MBA Assistant Clinical Professor, Psychiatry, Mount Sinai School of Medicine, New York, NY Leslie S. Fish, PharmD Vice President of Clinical Programs Fallon Community Health Plan, Worcester, MA John Hornberger, MD, MS Cedar Associates, LLC CHP/PCOR Adjunct Associate, Menlo Park, CA Michael S. Jacobs, RPh Sr. Director, Health & Wellness Walmart Stores, Inc Matthew Mitchell, PharmD, MBA, FAMCP Director, Pharmacy Services SelectHealth, Murray, UT Paul Anthony Polansky, BSPharm, MBA PAPRx, LLC Gulph Mills, PA Christina A. Stasiuk, DO, FACOI Senior Medical Director Cigna, Philadelphia, PA

Craig Deligdish, MD Hematologist/Oncologist Oncology Resource Networks, Orlando, FL Thomas G. McCarter, MD, FACP Chief Clinical Officer Executive Health Resources, PA Byron C. Scott, MD, MBA Associate Chief Medical Officer Truven Health Analytics, an IBM Company Chicago, IL Albert Tzeel, MD, MHSA, FACPE Regional Medical Director Medicare Operations, North Florida Humana, Jacksonville

POLICY & PUBLIC HEALTH

Jeffrey A. Bourret, PharmD, MS, BCPS, FASHP Senior Director, North America Medical Affairs Medical Lead, Specialty Payer & Channel Customer Strategy, Pfizer Inc Gary Branning, MBA Adjunct Professor, Rutgers Graduate School of Business, President, Managed Market Resources Mt Olive, NJ Richard B. Weininger, MD Chairman, CareCore National, LLC Bluffton, SC

Joseph R. Antos, PhD Wilson H. Taylor Scholar in Health Care Retirement Policy, American Enterprise Institute Washington, DC Robert W. Dubois, MD, PhD Chief Science Officer National Pharmaceutical Council, Washington, DC Jack E. Fincham, PhD, RPh Professor of Pharmacy, School of Pharmacy Presbyterian College, Clinton, SC Paul Pomerantz, MBA CEO, American Society of Anesthesiologists Park Ridge, IL J. Warren Salmon, PhD Professor of Health Policy & Administration School of Public Health University of Illinois at Chicago Raymond L. Singer, MD, MMM, CPE, FACS Chief, Division of Cardiothoracic Surgery Vice Chair, Department of Surgery for Quality & Patient Safety and Outreach Lehigh Valley Health Network, PA

PATIENT ADVOCACY

RESEARCH & DEVELOPMENT

MANAGED MARKETS

Mike Pucci Sr VP, Commercial Operations and Business Development, PhytoChem Pharmaceuticals Lake Gaston, NC

Christopher (Chris) P. Molineaux President, Pennsylvania BIO Malvern, PA Michael F. Murphy, MD, PhD Chief Medical Officer and Scientific Officer Worldwide Clinical Trials King of Prussia, PA

PAYER–PROVIDER FINANCES

Bruce Pyenson, FSA, MAAA Principal & Consulting Actuary Milliman, Inc, New York, NY

SPECIALTY PHARMACY

Atheer A. Kaddis, PharmD Executive Vice President Sales and Strategic Alignment Diplomat Specialty Pharmacy, Flint, MI James T. Kenney, Jr, RPh, MBA Pharmacy Operations Manager, Harvard Pilgrim Health Care, Wellesley, MA Michael Kleinrock Director, Research Development IMS Institute for Healthcare Informatics

PERSONALIZED MEDICINE

Amalia M. Issa, PhD, MPH Director, Program in Personalized Medicine & Targeted Therapeutics, University of the Sciences, Philadelphia, PA PHARMACOECONOMICS

Josh Feldstein President & CEO, CAVA, The Center for Applied Value Analysis, Inc, Norwalk, CT

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HEALTHCARE COMMUNICATIONS, LLC

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TABLE OF CONTENTS

Senior Vice President/Group Publisher Nicholas Englezos nenglezos@the-lynx-group.com Senior Vice President/Group Publisher John W. Hennessy jhennessy2@the-lynx-group.com Senior Editorial Director Dalia Buffery dbuffery@the-lynx-group.com Senior Associate Editor Lilly Ostrovsky Associate Editor Lara J. Lorton Editorial Assistant Cara Guglielmon Founding Editor-in-Chief Robert E. Henry Production Manager Cara Nicolini

EDITORIAL

257 Improving Population Health by Working with Communities

David B. Nash, MD, MBA CLINICAL

259 I mpact of Pharmacist-Provided Medication Therapy Management on Healthcare Quality and Utilization in Recently Discharged Elderly Patients Jordan D. Haag, PharmD, RPh; Amanda Z. Davis, PharmD, RPh; Robert W. Hoel, PharmD, RPh; Jeffrey J. Armon, PharmD, RPh; Laura J. Odell, PharmD, RPh; Ross A. Dierkhising, MS; Paul Y. Takahashi, MD 268 S takeholder Perspective: A Systematic Approach to Medication Therapy Management in Elderly Patients with Chronic Diseases Can Improve Outcomes

By James T. Kenney, Jr, RPh, MBA BUSINESS

269 H ospital and Health Plan Partnerships: The Affordable Care Act’s Impact on Promoting Health and Wellness Michelle Vu, PharmD candidate; Annesha White, PharmD, PhD; Virginia P. Kelley, MBA; Jennifer Kuca Hopper, MS; Cathy Liu, PharmD candidate 278 S takeholder Perspective: Measurable Clarity in Healthcare Is Needed So Those Who Use the System Could Achieve a State of Well-Being

By F. Randy Vogenberg, PhD, RPh

ASSOCIATION & CONGRESS DIVISION Association Director Patrice Melluso Meeting & Event Planner Linda Mezzacappa Senior Account Executive George Fuller Project Manager Rachael Baranoski Senior Project Coordinator Gretchen Dann Project Administrator Sara Mohamed

President Abigail Adair Account Group Supervisor Karie Gubbins Account Supervisors Alex Charles Deanna Martinez Senior Account Executives Jeremy Shannon Meg Spencer Business Development Advisor Saher Almaita

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President/CEO Brian Tyburski Senior Vice President/Group Publisher Russell Hennessy rhennessy@the-lynx-group.com Senior Vice President, Sales & Marketing Philip Pawelko ppawelko@the-lynx-group.com Vice President, Finance Andrea Kelly Senior Financial Assistant Audrey LaBolle Director, Human Resources Jennine Leale Medical Director Julie Strain Director, Strategy & Program Development John Welz Editorial Director Susan Berry Director, Quality Control Barbara Marino Quality Control Assistant Theresa Salerno Director, Production & Manufacturing Alaina Pede Director, Creative & Design Robyn Jacobs Design Managers Chris Alpino Lora LaRocca Director, Digital Marketing Samantha Weissman Digital Content Manager Anthony Trevean Digital Editor John Parkinson Digital Media Specialist Charles Easton IV Jr Digital Content Manager Walford Guillaume Junior Digital Developer Christina Bethencourt Executive Administrative Assistant/Office Manager Dana Rivera Administrative Assistant Colette Puhalski IT Manager Kashif Javaid Office Coordinator Robert Sorensen

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American Health & Drug Benefits, ISSN 1942-2962 (print); ISSN 1942-2970 (online), is published 9 times a year by Engage Healthcare Communications, LLC, 1249 South River Rd, Suite 202A, Cranbury, NJ 08512. Copyright © 2016

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THE PEER-REVIEWED FORUM FOR REAL-WORLD EVIDENCE IN BENEFIT DESIGN ™

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TABLE OF CONTENTS

(Continued)

REGULATORY

280 O ncologist Support for Consolidated Payments for Cancer Care Management in the United States

Siva Narayanan, MSc, MHS; Emily Hautamaki, MPH 289 S takeholder Perspective: Implementing Payment Reform in Oncology: Benefits and Challenges

By Byron C. Scott, MD, MBA DEPARTMENT

Industry Trends 256 M ACRA: The Quiet Healthcare Takeover

By James C. Capretta and Lanhee J. Chen

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MISSION STATEMENT 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.

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INDUSTRY TRENDS

Macra: The Quiet Health-Care Takeover A 962-page rule puts the federal government between doctors and patients

By James C. Capretta and Lanhee J. Chen

T

he American people have become familiar with ObamaCare’s failings: higher premiums, fewer choices and a more powerful federal health bureaucracy. Yet another important piece of health-care legislation, signed into law last year, has gone almost unnoticed.

The Medicare Access and CHIP Reauthorization Act, known simply as Macra, was enacted to replace the outdated and dysfunctional system for paying doctors under Medicare. The old system, based on the universally despised sustainable-growth rate formula, perennially threatened to impose unsustainable cuts in physicians’ fees. Macra passed Congress with bipartisan support and President Obama quickly signed it. Unfortunately, the law empowers the federal bureaucracy at the expense of the doctor-patient relationship, putting the quality of American health care at risk.

In an effort to secure broad support, Congress wrote into the law general guidance but left important details of implementation to the executive branch. What happened next was predictable: In April the administration presented a 962-page regulatory behemoth. This new set of rules uses the power of Medicare to put the federal government in charge of almost every aspect of physician care in the U.S. Macra adopts the same theory of cost control embedded in ObamaCare. It assumes that the federal government has the knowledge and wherewithal to engineer better health care through “delivery system reforms,” forgetting the utter failure of the bureaucracy’s previous effort. ObamaCare and now Macra use Medicare’s payment regulations to force hospitals and physicians to change how they care for their patients. The administration’s regulations will force doctors to comply with scores of new reporting requirements and intrusions into their practices. Physicians who refuse to bend will see their Medicare fees cut.

Macra and the new regulations force physicians to pick between a “merit-based incentive payment system” or an “alternative-payment model.” Doctors who choose the former will get paid fee-for-service, but they will receive meager annual increases of only 0.25% starting in 2019.

Reprinted with permission of the Wall Street Journal, May 31, 2016. Copyright © 2016, Dow Jones & Company, Inc. All Rights Reserved. License number 3894340740451.

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Some doctors could earn “bonus payments” but only if the federal bureaucracy approves of their performance.

These rules are purposely onerous because the administration wants physicians to opt into the alternative-payment model. In that system, the government shifts regulatory control from individual physicians to organizations with responsibility for managing patient care. Physicians serving patients through this system will be eligible for annual payment increases of 0.75%, plus bonuses distributed if their organizations hit the government’s spending targets.

The not-so-hidden agenda of the Obama administration is to use Macra and related regulations to force physicians into joining accountable-care organizations.

ObamaCare nudged hospitals and physician groups to form these organizations to manage patient care. But they are an unproven concept in Medicare, weighed down by a mountain of rules and information systems.

Early data from the administration shows that they haven’t done much to cut costs or improve quality compared with traditional Medicare.

Another major flaw is patient retention. ObamaCare stipulates that a Medicare-eligible patient be automatically put in an accountable-care organization if his doctor is affiliated with one. However, the patient remains free to see any doctor he wants, and the patient usually doesn’t even know he has been placed in such an organization. It is difficult to control costs when the patient has no knowledge of or reason to stay within the system.

In 2014, only one-quarter of the 333 accountable-care organizations received bonus payments for hitting financial and quality targets.

Many hospitals, physician groups and managed-care entities have ceased participating in the program because of its excessive rules and small rewards. Macra and the administration’s regulations are simply attempts to resuscitate accountable-care organizations through coercion.

Physicians fed up with the bureaucratic rules and low payments of fee-for-service will have no recourse except to join one of the organizations. And when physicians join, their patients come with them, whether they know it or not.

The administration’s rule ignores that Medicare already has a thriving alternative-payment model. Private Medicare Advantage plans, many of which are HMOs with decades of experience managing care, have de­ Continued on page 258

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Continued from page 256 veloped new ways of identifying and compensating the most cost-effective physicians. Some 30% of Medicare beneficiaries have voluntarily elected to get their care through these plans without being coerced, according to the 2015 Medicare Trustees Report.

Congress understandably jettisoned the failed sustainable-growth rate formula, and it is important to reward quality health care, rather than pay more for high volume. But Macra threatens to sidetrack this movement by embracing the same bureaucratic mind-set that underlies ObamaCare. A better plan would use competition and

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consumer choice to reward physicians for providing high-quality care at affordable and easily ascertained prices, without coercion by the federal government. The results would be better for physicians and their patientsâ&#x20AC;&#x201D;not to mention taxpayers. n Mr. Capretta is a senior fellow at the Ethics and Public Policy Center and a visiting fellow at the American Enterprise Institute. Mr. Chen is a research fellow at the Hoover Institution and director of domestic-policy studies in the Public Policy Program at Stanford University.

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EDITORIAL

Improving Population Health

by Working with Communities David B. Nash, MD, MBA Editor-in-Chief, American Health & Drug Benefits; Founding Dean, Jefferson College of Population Health, Philadelphia, PA

F

or more than 2 years, I have had the privilege of participating in a very important national task force that is sponsored by the National Quality Forum (NQF) in Washington, DC. The task force is charged with giving input on a critical national priority, namely, improving population health by working with communities.

This summer, the task force will provide the US Secretary of Health & Human Services (HHS) a list of potential operational measures that would guide HHS in the continuing implementation of the Affordable Care Act. As many of our readers know, in the next 2 years provider organizations will be held accountable, in part, for improving the health of the population in the communities that they serve. The goal of the NQF task force is to help frame this conversation, and then provide operational measures that could lead to appropriate methods of reimbursement.

I have attended 2 in-person meetings of the task force in Washington, DC, and participated in the Field Testing Group activity in Trenton, NJ. Although the entire scope of this task force’s work is beyond the scope of this editorial, I wish to highlight 2 key experiences—(1) my visit to the Trenton Health Team in Trenton, NJ, and (2) a quick overview of some of the other Field Testing Group sites that, together, may help to foreshadow where the nation is going as we develop reimbursable measures for community engagement.

One year ago, along with Georges C. Benjamin, MD, the President of the American Public Health Association, I visited the Trenton Health Team, a community-based health improvement collaboration serving 6 zip codes in Trenton, one of the poorest cities in the nation.1 This collaboration comprises Capital Health, St. Francis Medical Center, the City of Trenton Department of Health & Human Services, and the Henry J. Austin Health Center. The leaders of the Trenton Health Team are devoted to improving the health of the population, and they recognize that they have to overcome powerful social determinants of health, especially poverty, trauma, and low levels of educational attainment.

In my 1-day visit, I had the opportunity to tour several community centers and several bodegas, or corner grocery stores. In those bodegas were some subsidized

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fresh fruits and vegetables in special refrigerators, paid for by a grant from the Trenton Health Team. The key policy question here is: Will individuals in the lower socioeconomic strata purchase healthy fruits and vegetables if the price is subsidized? The answer is a resounding yes! I left Trenton after a busy day, feeling that we could, in fact, ameliorate some of the social determinants of health. Of course, the experience of one city does not necessarily predict success for a national policy.

Some of the other organizations participating in this project are equally impressive, including the Chronic Disease Prevention Coalition and Policy Center at the New York Academy of Medicine in New York City.

In the next 2 years provider organizations will be held accountable, in part, for improving the health of the population in the communities that they serve. The goal of the NQF task force is to help frame this conversation, and then provide operational measures that could lead to appropriate methods of reimbursement.

Their initiative, Designing a Strong and Healthy New York (DASH-NY), was launched in April 2010, with the support of the New York State Department of Health, to address obesity and chronic disease prevention through policy, systems, and environmental changes.2 They presented their early results at the recent NQF task force meeting in spring 2016, in Washington, DC. Yet another organization is the Empire Health Foundation, which is located in a 7-county region in Eastern Washington State.3 To fulfill its mission to “radically improve health in our region,” this foundation incubated the formation of its subsidiary, Better Health Together.4 Better Health Together partners with regional leaders representing multiple sectors to drive a common agenda to improve population health.

Additional amazing examples of connecting with the communities we serve include the Geneva Tower Health

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Collaborative in Cedar Rapids, IA, which houses low-income elderly and/or disabled adults.5 Working with the local healthcare delivery system, Mercy Medical Center, and the Abbe Center for Community Mental Health, the Geneva Tower Health Collaborative provides onsite services and support, thereby reducing the barriers to care, which include transportation and finances. By reducing these barriers, they truly engage with the elderly who dwell in this low-income housing organization.

Any consensus-based effort to improve the health of communities through provider organizations will take time. Bringing together the culture of public health and the culture of clinically integrated networks (which are developing across the country) is a process fraught with many challenges.

Finally, the Michigan Health Improvement Alliance (MiHIA) is a nonprofit, 501(c)(3) multistakeholder organization that operates as a regional 14-county integrator, serving a population of 800,000 in central Michigan.6 MiHIA’s efforts are to establish the region as a community of health excellence through a comprehensive focus on population health, the patient experience, and the cost of care. In other words, MiHIA’s goal is to implement the Triple Aim of the Affordable Care Act.

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Trenton Health Team, DASH-NY, Better Health Together, and MiHIA are organizations at the forefront of the revolution of how we will deliver healthcare in our country. These are the leaders in fostering true community engagement. We may one day need to collectively revisit these organizations when the funds flowing into the delivery system dwindle, and the remaining funds are connected to important new measures of improving the health of the individuals in those communities.

Any consensus-based effort to improve the health of communities through provider organizations will take time. Bringing together the culture of public health and the culture of clinically integrated networks (which are developing across the country) is a process fraught with many challenges. I feel very privileged to play even a small role in moving beyond simply articulating these challenges to participating in fixing them.

As always, I’m interested in your views as to how we may engage with the communities we serve. You can reach me via e-mail at david.nash@jefferson.edu. n

References

1. Trenton Health Team. About us. www.trentonhealthteam.org/about-us/.

Accessed May 31, 2016.

2. DASH-NY. About. www.dashny.org/about/. Accessed May 31, 2016.

3. Empire Health Foundation. Our work. http://empirehealthfoundation.org/ our-work/. Accessed June 7, 2016.

4. Better Health Together. Leading the charge to radically improve health in our region. www.betterhealthtogether.org/. Accessed May 31, 2016.

5. National Quality Forum. NQF collaborates with the Geneva Tower Health Collaborative. www.qualityforum.org/Field_Testing_the_NQF_Population_ Health_Guide_-_Geneva_Towers.aspx. Accessed May 31, 2016.

6. Michigan Health Improvement Alliance. Welcome to MiHIA. www.mihia. org. Accessed May 31, 2016.

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CLINICAL

ORIGINAL RESEARCH

Impact of Pharmacist-Provided Medication Therapy Management on Healthcare Quality and Utilization in Recently Discharged Elderly Patients Jordan D. Haag, PharmD, RPh; Amanda Z. Davis, PharmD, RPh; Robert W. Hoel, PharmD, RPh; Jeffrey J. Armon, PharmD, RPh; Laura J. Odell, PharmD, RPh; Ross A. Dierkhising, MS; Paul Y. Takahashi, MD BACKGROUND: The optimization of medication use during care transitions represents an opportunity to improve overall health-related outcomes. The utilization of clinical pharmacists during care transitions has demonstrated benefit, although the optimal method of integration during the care transition process remains unclear.

OBJECTIVE: To evaluate the impact of pharmacist-provided telephonic medication therapy management (MTM) on care quality in a care transitions program (CTP) for high-risk older adults.

METHODS: This prospective, randomized, controlled study was conducted from December 8, 2011, through October 25, 2012, in a primary care work group at a tertiary care academic medical center in the midwestern United States. High-risk elderly (aged ≥60 years) patients were randomized to a pharmacist-provided MTM program via telephone or to usual care within an existing outpatient CTP. The primary outcome was the quality of medication prescribing and utilization based on the Screening Tool to Alert Doctors to the Right Treatment (START) and the Screening Tool of Older Persons’ Prescriptions (STOPP) scores. The secondary outcomes were medication utilization using a modified version of the Medication Appropriateness Index, hospital resource utilization within 30 days of discharge, and drug therapy problems.

RESULTS: Of 222 eligible high-risk patients, 25 were included in the study and were randomized to the pharmacist MTM intervention (N = 13) or to usual care (N = 12). No significant differences were found between the 2 groups in medications meeting the STOPP or START criteria. At 30-day follow-up, no significant differences were found between the 2 cohorts in medication utilization quality indicators or in Stakeholder Perspective, hospital utilization. At 30-day follow-up, 3 (13.6%) patients had an emergency department visit or a page 268 hospital readmission since discharge. In all, 22 patients completed the study. Medication underuse was common, with 20 START criteria absent medications evident for all 25 patients at baseline, representing 15 (60%) patients with ≥1 missing medications. Overall, 55 drug therapy problems were identified at baseline, 24 (43.6%) of which remained unresolved at 30-day follow-up.

CONCLUSION: The use of a pharmacist-provided MTM program did not achieve a significant difference Am Health Drug Benefits. compared with usual care in an existing CTP; however, the findings demonstrated frequent utilization of 2016;9(5):259-268 www.AHDBonline.com inappropriate medications as well as medication underuse, and many drug therapy problems remained unresolved. The small size of the study may have limited the ability to detect a difference between the Received September 16, 2015 intervention and usual care groups.

Accepted in final form May 10, 2016

KEY WORDS: care transition program, high-risk elderly patients, medication therapy management, medication utilization, pharmacist-based, START criteria, STOPP criteria, usual care

Disclosures are at end of text

Dr Haag is Clinical Pharmacist, Department of Pharmacy; Dr Davis is Clinical Pharmacist, Department of Pharmacy; Dr Hoel is Clinical Pharmacist, Department of Pharmacy; Dr Armon is Clinical Pharmacist, Department of Pharmacy; Dr Odell is Clinical Pharmacist, Department of Pharmacy; Mr Dierkhising is Statistician, Division of Biomedical Statistics and Informatics; Dr Takahashi is Consultant, Division of Primary Care Internal Medicine; all at Mayo Clinic in Rochester, MN. This study was supported by Grant Number UL1 TR000135 from the National Center for Advancing Translational Sciences (NCATS), National Institutes of Health (NIH), and the US Department of Health and Human Services (DHHS). Its contents are solely the responsibility of the authors and do not necessarily represent the official views of NCATS, NIH, or DHHS.

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KEY POINTS Optimizing medication use and guidance by pharmacists during care transitions offer opportunities to improve patient outcomes. ➤ This study evaluated the impact of pharmacistbased MTM on the care of high-risk elderly patients during care transitions. ➤ Of 222 eligible patients, 25 were randomized to the pharmacist intervention or to usual care. ➤ At the 30-day follow-up, no significant differences were found between the 2 cohorts in medication utilization quality indicators or hospitalization. ➤ Overall, 3 patients had an emergency department visit or a hospital readmission since discharge. ➤ However, of the 55 drug therapy problems identified at baseline, 24 (43.6%) were still unresolved at 30-day follow-up. ➤ Based on the STOPP criteria, 68% of the patients were prescribed at least 1 inappropriate medication, a rate higher than in previous research. ➤ Furthermore, based on START criteria, 60% of patients had underused prescribed medications. ➤ These findings suggest a need to identify specific patient populations that may derive the most benefit from a pharmacist-based MTM program during care transitions. ➤

A

key measure of the 2010 Affordable Care Act is the improvement of care transitions within the healthcare continuum.1 Optimal medication utilization is important during these care transitions. Elderly patients have shown a higher risk for drug-related adverse events with certain medications.2-7 Thus, Medicare Part D prescription drug plans are required to offer medication therapy management (MTM) to patients who meet certain criteria.8,9 The Medicare criteria for MTM eligibility vary by plan type and by disease, and include a diagnosis of a minimum number of chronic diseases, the use of a specific minimum number of prescription medications, and the likelihood of exceeding a predetermined annual medication cost threshold.10 Patients in care transitions often meet the MTM eligibility criteria; however, the optimal model of pharmacist integration during the care transition process remains unclear.

Previous studies incorporated components of MTM into hospital discharge planning. Two studies have analyzed the impact of a pharmacist intervention via telephone shortly after hospital discharge.11,12 These studies suggest that a decrease in hospital utilization occurred within 30 days of discharge, with evidence of cost-sav-

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ings related to follow-up by a pharmacist.11,12 In one study, home-based intervention with a nurse and a pharmacist in patients with congestive heart failure was associated with reductions in unplanned readmissions and out-of-hospital deaths within 6 months of hospital discharge.13 A targeted care bundle for high-risk elderly patients that included medication counseling and reconciliation with a clinical pharmacist was associated with a decrease in unplanned acute healthcare utilization up to 30 days after discharge.14 Zillich and colleagues used a telephonic MTM intervention for patients receiving home healthcare, which demonstrated a 3-fold reduction in hospital readmissions among the lowest-risk cohort.15 A variety of screening tools have been developed to improve medication quality and reduce the prevalence of drug-related adverse events. The Screening Tool of Older Persons’ Prescriptions (STOPP) was developed to identify potentially inappropriate medications, and the Screening Tool to Alert Doctors to the Right Treatment (START) was created to identify potential prescribing omissions.

The STOPP criteria include 65 standards that are used to identify potentially inappropriate medications in an elderly patient, including drug-to-disease interactions, drug-to-drug interactions, excessive doses of a medication, and excessive duration of medication use.16 For identifying potentially inappropriate medications, we selected the STOPP criteria instead of the Beers criteria, because recent studies revealed a greater correlation between drug-related adverse events and potentially inappropriate medications defined with the STOPP criteria than with the Beers criteria, suggesting that the STOPP criteria may be more helpful clinically.17 The START criteria assess potential prescribing omissions and identify medications that are clinically indicated for specific patient populations to encourage their proper prescribing.18 The STOPP and START tools are scored by totaling the number of medications that meet certain criteria, with each potentially inappropriate medication and potential prescribing omission generating 1 point. Previous research indicates that a 0.5 decrease in STOPP score yielded a 17% risk reduction in medication-related hospital admissions.19 Although the START criteria were developed using evidence-based disease management, the clinical impact of this intervention remains to be explored.

Our objective was to assess the impact of comprehensive pharmacist-provided telephonic MTM on care quality in an outpatient care transitions program (CTP) in high-risk adults aged ≥60 years.

Methods In this prospective, randomized, controlled trial, patients were randomized in a 1 to 1 ratio to the MTM intervention or the usual care cohort. The study was conducted

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from December 8, 2011, through October 25, 2012, in a primary care work group at a tertiary care academic medical center in the midwestern United States. The primary care work group included the family medicine and primary care internal medicine departments. The study was reviewed and approved by the Institutional Review Board.

Patient Population The target enrollment for the study was set at 50 independent-living elderly adults (aged ≥60 years) who were enrolled in the local CTP. The determination of eligibility for the CTP required stratification of patients during hospitalization using the Elders Risk Assessment (ERA) index, which was developed to identify elderly patients who are at high risk for an emergency department visit or a hospital readmission.20 Patients who were newly enrolled in the CTP were targeted for participation in this study.

Each patient was reimbursed $25 as compensation for the time commitment required for the completion of the study. Patients were offered enrollment in the CTP during their hospitalization if they were empaneled in the primary care work group, resided within a 20-minute drive, and were predicted to be at risk for high healthcare utilization (ie, had an ERA index score of ≥16). The study coordinator recruited participants for the study and obtained informed consent during hospitalization or via a telephone call shortly after discharge from the hospital.

Patients were randomly assigned to either the intervention group or to the usual care group by a study coordinator. Randomization was completed during the phone call by the study coordinator, who opened a sealed envelope that contained an indication of which group the patient was assigned to.

The study statistician used a random number generator to determine the allocation sequence. The trial was unblinded (ie, the participants and the investigators were aware of the intervention), and the patients received a telephone call from the pharmacist if they were randomized to the intervention group. However, all outcomes were assessed while blinded to the intervention or the usual care group allocations.

herbal medications taken. This systematic review of medications included the identification, resolution, and prevention of drug-related problems, including adverse events or the use of potentially inappropriate medications.

In addition, the electronic medical record was investigated for potential prescribing omissions. This review was the foundation for the phone consultation with the patient to ensure medication optimization. Decisions were based on the pharmacist’s clinical judgment after considering practice guidelines, 2 clinical support databases (Truven Health Analytics’ Micromedex21 and Wolters Kluwer Lexi-Drugs22), or the highest-quality evidence available, as well as patient preferences. Recommendations were communicated by the pharmacist via a secure messaging function within the electronic medical record to the CTP provider for review on completion of the phone consultation.

The study included 5 pharmacists—2 had delivered the interventions and 3 performed the analysis; all the pharmacists had pharmacy doctoral degrees and were required to complete an MTM certification program.

The usual care group was defined as the preexisting CTP without pharmacist intervention. Patients enrolled in the CTP during their hospitalization received a home visit by a nurse practitioner within 3 business days after their discharge. As part of the visit, the nurse practitioner reviewed the patient’s medications and made changes as deemed appropriate. The changes were implemented directly or were discussed with the patient’s primary care provider, depending on clinical judgment. Follow-up telephone calls at scheduled intervals were implemented, depending on the needs of the individual patients.

The study coordinators functioned only in a research capacity, independent of the pharmacist intervention or usual care groups. They performed recruitment and obtained consent from participants. They collected patient characteristics at baseline within 7 days of hospital discharge and at 5 weeks after the intervention with a follow-up phone call. The information collected by the study coordinator included demographic factors, such as age, race, marital status, medication adherence, and patient-­ reported hospital or emergency department utilization.

Data Collection The intervention group received an MTM consultation with a pharmacist by telephone, preferably within 3 (and up to 7) business days after hospital discharge. This intervention was developed using successful methods of pharmacist integration during care transitions,11,12 while complementing the services of an existing CTP, to assess the impact on the quality of medication use. The pharmacist obtained the necessary information and clinical assessments from each patient’s electronic medical record to complete a comprehensive review of all prescription, nonprescription, and

Outcome Measures Two independent pharmacists assessed the medication quality indicators for each patient at baseline after hospital discharge (before pharmacist intervention and/or the nurse practitioner home visit) and at 30 days after discharge.

The primary outcome was to identify potentially inappropriate medications with the STOPP criteria and potential prescribing omissions using the START criteria.

The secondary outcomes included an assessment of medication utilization quality with the Medication Appropriateness Index (MAI), a 10-item instrument used to further as-

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Figure Study Population Diagram 222 recently discharged high-risk elderly patients screened by study coordinator

197 patients excluded: 68 not interested 62 residing in nursing home 19 unable to reach 15 dementia 33 other

25 patients eligible for randomization

13 patients randomized to pharmacist intervention

12 patients randomized to usual care

2 patients excluded: 1 death 1 withdrew from study

1 excluded because of death

22 patients completed the study from baseline to 30-day follow-up

sess each prescribed medication.23 Modifications to the MAI were similar to those used previously in another study.24 The assessment, which was reduced to 3 items to minimize interview burden, was based on the following questions: 1. Is there an indication for the drug?

2. Is the medication effective for the condition?

3. Is there unnecessary duplication with other drugs?

For the STOPP and START assessments, the medications involved included routinely administered systemic drugs other than topical treatments. The MAI assessment was applied to systemic drugs (other than over-the-counter or topical treatments) that were used on a regular basis.

Additional secondary end points included an assessment of healthcare resource utilization within 30 days of discharge, defined by (1) emergency department visits, (2) hospital readmissions, and (3) the composite of emergency department visits and hospital readmissions.

These outcomes were self-reported during the 5-week follow-up telephone call from the study coordinator.

Medication adherence was determined by utilizing an adapted Morisky Medication Adherence Scale (MMAS)

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at baseline and at the 5-week follow-up phone call.25 The traditional MMAS was adapted to be a global assessment on medication adherence, in lieu of specific disease state medication adherence. The drug therapy problems that were identified during the pharmacist intervention were categorized using standard MTM definitions.26 The study data were managed using Research Electronic Data Capture (REDCap) tools that are hosted at our institution.27 REDCap is a secure, web-based application designed to support data capture for research studies, providing (1) an intuitive interface for validated data entry, (2) audit trails for tracking data manipulation and export procedures, (3) automated export procedures for seamless data downloads to common statistical packages, and (4) procedures for importing data from external sources.

Statistical Analysis The START and STOPP scores were calculated for each patient. The possible scores ranged from 0 to 22 for the START criteria and from 0 to 65 for the STOPP criteria. Using the standard deviation estimates of 2.1 and 1.6 for the START and STOPP scores,28 respectively, a total sample size of 25 patients would allow the detection of mean between-group differences of 1.7 and 1.3, respectively, with 80% power.

The statistical methods used to compare the groups were the Wilcoxon rank-sum test for continuous or discrete ordinal variables and the Pearsonâ&#x20AC;&#x2122;s chi-squared test for discrete nominal variables. In all cases, 2-tailed P values of <.05 were considered statistically significant.

The continuous data are reported as the median (interquartile range), and the categorical data are reported as the frequency and percentage of the group represented.

The data analysis was generated using SAS version 9.2 for UNIX (SAS Institute, Inc; Cary, NC).

Results Of the 222 patients eligible for the study, 197 patients were excluded from participation because they were either uninterested, were residing in a skilled nursing facility, unable to reach, had a clinical diagnosis of dementia or a terminal illness, or were unable or unwilling to provide informed consent (Figure). Of the 25 patients who were randomized to the MTM intervention (N = 13) or to usual care (N = 12), 2 died (1 from each cohort) and 1 patient in the intervention group voluntarily withdrew from the study.

Baseline patient characteristics are listed in the Table in the Appendix (see www.AHDBonline.com). Table 1 compares baseline and 30-day follow-up outcomes for the 2 study cohorts. The study participants were predominantly male, white, and married, with a median age of approximately 84 years. At baseline, the patients in the pharmacist-intervention group used a median of 17 (interquartile

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Table 1 A ssessment of 25 Recently Discharged, High-Risk Elderly Patients at Baseline and at 30-day Follow-up Baseline Characteristic Total medications listed on home medication list, median (IQR) Total required daily doses, median (IQR) Prescription medications assessed, median (IQR)

30-day follow-up visit Pharmacist intervention Usual care (N = 11) (N = 11) P value

Pharmacist intervention (N = 13)

Usual care (N = 12)

P value

17 (12-20)

15.5 (13-18.5)

.96

18 (12-20)

17 (13-18)

.95

17 (14.5-20.5)

13.8 (12-18)

.59

15.3 (11-20.5)

14 (12-21)

.97

9 (6-11)

8.5 (7.5-10.5)

.68

9 (5-12)

8 (8-11)

.87

3 (2-4)

.59

3 (2-4)

3 (2-4)

>.99

3 (2-5.5)

.98

5 (2-5)

4 (3-6)

.59

.16

1 (9)

2 (18)

.53

10 (91)

9 (82)

1 (9)

0 (0)

10 (91)

11 (100)

3 (3-4) OTC/herbal medications assessed, median (IQR) Topical/as-needed medications excluded, 4 (2-6) median (IQR) Do you sometimes forget to take any of your medications?

Yes, N (%)

4 (31)

1 (8)

No, N (%)

9 (69)

11 (92)

Over the past 2 weeks, were there any days you did not take your medications?

Yes, N (%)

1 (8)

0 (0)

No, N (%)

12 (92)

12 (100)

.33

.31

Have you ever cut back or stopped taking your medication without telling your doctor because you felt worse when you took it?

Yes, N (%)

2 (15)

0 (0)

No, N (%)

11 (85)

12 (100)

.16

2 (18)

0 (0)

9 (82)

11 (100)

.14

When you travel or leave home, do you sometimes forget to bring your medications?

Yes, N (%)

1 (8)

0 (0)

No, N (%)

12 (92)

12 (100)

Yes, N (%)

12 (92)

11 (92)

No, N (%)

1 (8)

1 (8)

.33

0 (0)

0 (0)

11 (100)

11 (100)

10 (91)

11 (100)

1 (9)

0 (0)

1 (9)

0 (0)

10 (91)

11 (100)

>.99

Did you take all of your medications yesterday? .95

.31

Do you sometimes stop taking your medications because you feel they are no longer needed?

Yes, N (%)

0 (0)

1 (8)

No, N (%)

13 (100)

11 (92)

.29

.31

Taking medication every day is a real inconvenience for some people. Do you ever feel hassled about sticking to your medication plans?

Yes, N (%)

1 (8)

0 (0)

No, N (%)

12 (92)

12 (100)

.33

2 (18)

0 (0)

9 (82)

11 (100)

10 (91)

10 (91)

1 (9)

1 (9)

.14

How often do you have difficulty remembering all of your prescribed medications?

Never or rarely, N (%)

12 (92)

10 (83)

Once in a while, N (%)

1 (8)

2 (17)

.49

>.99

MMAS score 0, N (%)

0 (0)

1 (8)

0 (0)

0 (0)

1, N (%)

7 (54)

9 (75)

8 (73)

9 (82)

2, N (%)

3 (23)

0 (0)

2 (18)

1 (9)

3, N (%)

3 (23)

2 (17)

0 (0)

1 (9)

4, N (%)

0 (0)

0 (0)

0 (0)

0 (0)

5, N (%)

0 (0)

0 (0)

0 (0)

0 (0)

6, N (%)

0 (0)

0 (0)

1 (9)

0 (0)

.14

.65

IQR indicates interquartile range; MMAS, adapted Morisky Medication Adherence Scale; OTC, over-the-counter.

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Table 2 Primary and Secondary Outcomes for 25 Recently Discharged, High-Risk Elderly Patients at 30-Day Follow-Up Baseline Pharmacist intervention (N = 13) N (%)

Usual care (N = 12) N (%)

0

6 (46)

2 (17)

1

5 (38)

5 (42)

2

1 (8)

3 4

30-day follow-up visit

P value

Pharmacist intervention (N = 11) N (%)

Usual care (N = 11) N (%)

P value

.09

5 (45)

2 (18)

.26

4 (36)

6 (55)

3 (25)

1 (9)

2 (18)

1 (8)

1 (8)

1 (9)

0 (0)

0 (0)

1 (8)

0 (0)

1 (9)

0

5 (38)

5 (42)

4 (36)

6 (55)

1

6 (46)

5 (42)

4 (36)

3 (27)

2

1 (8)

2 (17)

0 (0)

0 (0)

3

1 (8)

0 (0)

3 (27)

2 (18)

4

0 (0)

0 (0)

0 (0)

0 (0)

0

11 (85)

8 (67)

10 (91)

10 (91)

1

2 (15)

4 (33)

1 (9)

1 (9)

8 (73)

10 (91)

Outcome STOPP medications on the patient’s list

START medications missing from the list .91

.44

MAI criterion 1 (no indication) .29

>.99

MAI criterion 2 (medication not effective for condition) 0

9 (69)

10 (83)

1

2 (15)

1 (8)

1 (9)

0 (0)

2

1 (8)

1 (8)

1 (9)

1 (9)

3

0 (0)

0 (0)

1 (9)

0 (0)

4

0 (0)

0 (0)

0 (0)

0 (0)

5

1 (8)

0 (0)

0 (0)

0 (0)

9 (82)

10 (91)

.42

.31

MAI criterion 3 (unnecessary duplication of other drugs) 0

11 (85)

8 (67)

1

1 (8)

4 (33)

1 (9)

1 (9)

2

0 (0)

0 (0)

1 (9)

0 (0)

3

1 (8)

0 (0)

0 (0)

0 (0)

NA

NA

2 (18)

1 (9)

9 (82)

10 (91)

1 (9)

1 (9)

10 (91)

10 (91)

.40

.55

30-day hospital readmission Yes

NA

No

.53

30-day emergency department visit Yes

NA

NA

NA

No

>.99

Composite 30-day emergency department visit or hospital readmission Yes

NA

NA

No

NA

2 (18)

1 (9)

9 (82)

10 (91)

.53

MAI indicates Medication Appropriateness Index; NA, not applicable; START, Screening Tool to Alert Doctors to the Right Treatment; STOPP, Screening Tool of Older Persons’ Prescriptions.

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Table 3 D rug Therapy Problems Identified During Pharmacist Intervention Drug therapy problems, N

Descriptiona There is no valid medical indication for the drug therapy at this time

4

Multiple drugs are being used for a condition that requires single-drug therapy

2

The medical condition is more appropriately treated with nondrug therapy

0

Drug therapy is being taken to treat an avoidable adverse reaction associated with another medication

1

Drug abuse, alcohol use, or smoking is causing the problem

0

A medical condition requires the initiation of drug therapy

7

Preventive drug therapy is required to reduce the risk for a new condition

3

A medical condition requires additional pharmacotherapy to attain synergistic or additive effects

0

The drug is not the most effective for the medical problem

1

The medical condition is refractory to the drug

0

The dosage form of the drug is inappropriate

2

The drug is not effective for the indication being treated

0

The dose is too low to produce the desired response

7

The dosage interval is too infrequent to produce the desired response

1

The drug interaction reduces the amount of active drug available

0

The duration of drug therapy is too short to produce the desired response

0

The drug causes an undesirable reaction that is not dose related

3

A safer drug is required because of risk factors

7

A drug interaction causes an undesirable reaction that is not dose related

0

The dosage regimen was administered or changed too rapidly

0

The drug causes an allergic reaction

0

The drug is contraindicated because of risk factors

1

Additional laboratory monitoring is recommended to prevent adverse drug reaction

12

The drugâ&#x20AC;&#x2122;s dose is too high

0

The dosing frequency is too short

0

The duration of drug therapy is too long

1

A drug interaction occurs, resulting in a toxic reaction to the drug

0

The dose of the drug was administered too rapidly

0

The patient does not understand the instructions

1

The patient prefers not to take the medication

0

The patient forgets to take the medication

1

The drug is too expensive for the patient

1

The patient cannot swallow or self-administer the drug appropriately

0

The drug is not available for the patient

0

b

Total drug therapy problems/total medications assessed among 13 patients

55/191 (28.8%)

Drug therapy problems unresolved at 30 days after discharge

24 (43.6%)

Adapted from Brown TR, ed. Handbook of Institutional Pharmacy Practice. 4th ed. Bethesda, MD: American Society of HealthSystem Pharmacists; 2006. b Denotes addition to standard definitions of drug therapy problems.26 a

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range, 12-20) medications compared with 15.5 (interquartile range, 13-18.5) medications in the control group.

As shown in Table 1, the total number of medications and the number of required daily doses were not significantly different between the 2 groups at baseline and at 30-day follow-up. The between-group differences in medication adherence were also not significant. At the 30-day follow-up, no significant differences were found between the pharmacist-intervention and usual care groups in the number of STOPP medications or missing START medications (Table 2).

The secondary outcomes of the modified MAI assessment and the 30-day rates of emergency department visits, hospital readmissions, or the composite of both showed no significant differences between the 2 groups.

Table 3 summarizes the drug therapy problems that were identified by the MTM consultation, which represented the pharmacist intervention. Our results show that 24 (43.6%) of the 55 identified drug therapy problems persisted at the 30-day follow-up (Table 3).

Discussion We found no difference between the 2 groups in medications meeting the STOPP or START criteria. A similar study used a retrospective chart review to evaluate similar medication quality parameters, including the START and STOPP criteria, in elderly veterans.28 That study found a significant decline in the STOPP score from 1.2 at their initial home-based primary care visit and the 0.895 score at their follow-up visit (P = .001).28 A major factor that might have affected the results of this study was the implementation rate of the pharmacistâ&#x20AC;&#x2122;s recommendations. The patients were reassessed at 30 days after hospital discharge by review of the electronic medical record to determine the status of their medication therapy problems compared with baseline. There were 55 drug therapy problems identified by the pharmacist at baseline, and 43.6% remained unresolved 30 days after discharge (Table 3). This suboptimal rate might have reduced the impact of the pharmacistâ&#x20AC;&#x2122;s interventions and the subsequent statistical differences between the 2 groups.

A 2013 systematic review concluded that the level of collaboration between the general practitioner and the pharmacist regarding medication review yields higher implementation rates of medication recommendations.29 A few of the key elements of collaboration to improve the recommendation implementation rate included sharing of the medical records, recruitment of patients by the provider, and a case conference between the provider and the pharmacist.29 Although we were unable to discern a significant difference in our study, the number of STOPP criteria medications identified is concerning. The pharmacist

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identified 28 medications that met the STOPP criteria among all 25 patients at baseline, with 17 (68%) patients being prescribed at least 1 inappropriate medicine. This prevalence is higher than the 35% to 57% found previously by researchers who evaluated the inappropriate use of medications in elderly patients.16,24 Medication underuse was also common, with 20 START criteria medications missing among all 25 patients at baseline, which represents 15 (60%) patients with at least 1 missing medication. This rate of medication underuse is similar to the 63% that was found in previous research,30 suggesting that the underuse of appropriate medications is common. The secondary outcomes were not significantly different between the 2 groups, with 3 (13.6%) of the 22 patients available at the 30-day follow-up reporting an emergency department visit or a hospital readmission since the initial discharge.

These results are similar to our previously published readmission rates after care transitions.31 The results from our elderly cohort showed that each patient was taking approximately 9 prescription medications, suggesting an association with an increased number of inappropriate medications. Steinman and colleagues demonstrated the frequency of inappropriate medication use increases with the total number of medications taken. However, the frequency of potential prescribing omissions does not vary with the total number of medications taken.24 Our study demonstrated a fairly balanced percentage of potentially inappropriate medications versus potential prescribing omissions (approximately 68% vs 60%, respectively).

Our findings suggest that the implementation of a telephonic MTM consultation into an already resource-intensive, comprehensive CTP may not represent the optimal integration strategy. One area of potential further research is to identify specific patient populations that derive the most benefit from a pharmacist-provided MTM program during care transitions.

Limitations The primary limitation to the study is the small sample size, which yielded inadequate statistical power to allow us to draw definitive conclusions. Our initial intervention included an in-home assessment by the study coordinator to perform the baseline functional measurements. This requirement limited patient recruitment, and the intervention was modified to perform all baseline and follow-up assessments via telephone. However, this modification did not significantly improve patient recruitment. Thus, this study can be considered preliminary, and its data can be regarded as hypothesis-generating.

In addition, the pharmacistâ&#x20AC;&#x2122;s intervention was part of a multifaceted pilot CTP, and it is difficult to discern the absolute impact of this integration.

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Several other methodologic limitations deserve notation. The 3 MAI-derived subscales that identify medications that are not indicated, are ineffective, or are duplicative have not been independently validated as standalone measures. However, this combination has been used in previous research,24 and each of the 3 items has excellent intrarater and interrater reliability.23,32 Notably, 2 of the 12 patients who were randomized to the usual care group had participated in MTM in the past 12 months. These 2 patients might have confounded the results, and might have introduced bias between the 2 treatment groups.

Finally, the study was conducted at a single center, which might have also limited the results.

Conclusion Although many studies have examined methods to improve care transitions from a hospital to home, an optimal standard of practice has not yet been determined.

Utilizing screening tools such as START, STOPP, or MAI may be helpful in transitioning patients, but it is also important to recognize the individual needs of each patient. Inappropriate medication use and underuse were common within the elderly cohort in our study. Although pharmacist-provided MTM consultation did not demonstrate a statistically significant benefit, the negative findings may be attributable to a lack of statistical power because of the small sample size or to the suboptimal integration into the care model. Future research should include a method to identify the specific patients who would benefit most from intervention by a pharmacist. n Acknowledgments The authors would like to thank Stephanie M. Quigg, Betty A. Wirt, and Ivana T. Croghan, PhD. Author Disclosure Statement Dr Haag, Dr Davis, Dr Hoel, Dr Armon, Dr Odell, and Mr Dierkhising reported no conflicts of interest. Dr Takahashi is on the Medical Board of Axial, LLC.

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10. Centers for Medicare & Medicaid Services. Medication therapy management. http://cms.gov/Medicare/Prescription-Drug-Coverage/PrescriptionDrugCov Contra/MTM.html. Accessed January 23, 2014.

11. Dudas V, Bookwalter T, Kerr KM, Pantilat SZ. The impact of follow-up telephone calls to patients after hospitalization. Am J Med. 2001;111(9 suppl 2):26S-30S. 12. Jack BW, Chetty VK, Anthony D, et al. A reengineered hospital discharge program to decrease rehospitalization: a randomized trial. Ann Intern Med. 2009;150:178-187.

13. Stewart S, Pearson S, Horowitz JD. Effects of a home-based intervention among patients with congestive heart failure discharged from acute hospital care. Arch Intern Med. 1998;158:1067-1072.

14. Koehler BE, Richter KM, Youngblood L, et al. Reduction of 30-day postdischarge hospital readmission or emergency department (ED) visit rates in highrisk elderly medical patients through delivery of a targeted care bundle. J Hosp Med. 2009;4:211-218.

15. Zillich AJ, Snyder ME, Frail CK, et al. A randomized, controlled pragmatic trial of telephonic medication therapy management to reduce hospitalization in home health patients. Health Serv Res. 2014;49:1537-1554.

16. Gallagher P, O’Mahony D. STOPP (Screening Tool of Older Persons’ potentially inappropriate Prescriptions): application to acutely ill elderly patients and comparison with Beers’ criteria. Age Ageing. 2008;37:673-679.

17. Petrarca AM, Lengel AJ, Mangan MN. Inappropriate medication use in the elderly. Consult Pharm. 2012;27:583-586.

18. Barry PJ, Gallagher P, Ryan C, O’Mahony D. START (screening tool to alert doctors to the right treatment)—an evidence-based screening tool to detect prescribing omissions in elderly patients. Age Ageing. 2007;36:632-638.

19. Gillespie U, Alassaad A, Hammarlund-Udenaes M, et al. Effects of pharmacists’ interventions on appropriateness of prescribing and evaluation of the instruments’ (MAI, STOPP and STARTs’) ability to predict hospitalization— analyses from a randomized controlled trial. PLoS One. 2013;8:e62401.

20. Crane SJ, Tung EE, Hanson GJ, et al. Use of an electronic administrative database to identify older community dwelling adults at high-risk for hospitalization or emergency department visits: the elders risk assessment index. BMC Health Serv Res. 2010;10:338.

21. Truven Health Analytics. Micromedex 2.0. www.micromedexsolutions.com.

Accessed December 8, 2011.

22. Wolters Kluwer. Lexi-Drugs. http://online.lexi.com. Accessed December 8, 2011.

23. Hanlon JT, Schmader KE, Samsa GP, et al. A method for assessing drug therapy appropriateness. J Clin Epidemiol. 1992;45:1045-1051.

24. Steinman MA, Landefeld CS, Rosenthal GE, et al. Polypharmacy and prescribing quality in older people. J Am Geriatr Soc. 2006;54:1516-1523.

25. Morisky DE, Ang A, Krousel-Wood M, Ward HJ. Predictive validity of a medication adherence measure in an outpatient setting. J Clin Hypertens (Greenwich). 2008;10:348-354.

26. Cipolle RJ, Strand LM, Morley PC. Pharmaceutical Care Practice: The Clinician’s Guide. 2nd ed. New York, NY: McGraw-Hill; 2004.

27. Harris PA, Taylor R, Thielke R, et al. Research electronic data capture (REDCap)—a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42: 377-381.

28. Brahmbhatt M, Palla K, Kossifologos A, et al. Appropriateness of medication prescribing using the STOPP/START criteria in veterans receiving homebased primary care. Consult Pharm. 2013;28:361-369.

29. Kwint H-F, Bermingham L, Faber A, et al. The relationship between the extent of collaboration of general practitioners and pharmacists and the implementation of recommendations arising from medication review: a systematic review. Drugs Aging. 2013;30:91-102.

30. Shrank WH, Asch SM, Adams J, et al. The quality of pharmacologic care for adults in the United States. Med Care. 2006;44:936-945.

31. Takahashi PY, Haas LR, Quigg SM, et al. 30-day hospital readmission of older adults using care transitions after hospitalization: a pilot prospective cohort study. Clin Interv Aging. 2013;8:729-736.

32. Fitzgerald LS, Hanlon JT, Shelton PS, et al. Reliability of a modified medication appropriateness index in ambulatory older persons. Ann Pharmacother.

1997;31:543-548.

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STAKEHOLDER PERSPECTIVE

A Systematic Approach to Medication Therapy Management in Elderly Patients with Chronic Diseases Can Improve Outcomes

By James T. Kenney, Jr, RPh, MBA Manager, Specialty and Pharmacy Contracts, Harvard Pilgrim Health Care, Wellesley, MA

M

edication therapy management (MTM) is an effective way to assess the current medication use and educational needs of a patient. Transitioning care from a healthcare facility to the outpatient setting is a critical point in the treatment process of patients with chronic diseases. The article by Haag and colleagues highlights the importance of proper education and counseling to help patients understand their therapy needs, and the importance of adhering to treatment recommendations.1 The small sample size of the study, however, might have contributed to the lack of differences between the study groups: still, this endeavor points to key challenges for providers, patients, and health plans in the attempt to improve health outcomes by delivering safe and effective medications while enhancing patient quality of life.

PROVIDERS: There are many opportunities to identify problems with medication use. A major concern in older patients is inappropriate medication use that can lead to hospitalizations, falls, fractures, or other events that can lead to morbidity. The complex drug regimens, multiple diseases, and cognitive challenges in elderly patients all contribute to the risk for adverse events from pharmacotherapy. Drug interactions are common when using 2 or 3 prescription or over-the-counter drugs. The Screening Tool of Older Personsâ&#x20AC;&#x2122; Prescriptions scores showed that 68% of patients had at least 1 inappropriate medication in their drug regimen.1 This suggests a need for provider education to improve the understanding of these agents and avoid prescribing them in the elderly. Similarly, the Screening Tool to Alert Doctors to the Right Treatment indicated that 60% of patients were missing at least 1 medication.1 These statistics highlight the need for a comprehensive approach to MTM that will involve all stakeholders in the delivery system to achieve quality drug therapy.

Missed medications can lead to serious adverse outcomes, including disease exacerbation, medication changes by the provider because of a perceived lack of efficacy, and wasted dollars spent on inappropriately used drugsâ&#x20AC;&#x201D;all of which creates significant gaps in care.

PHARMACISTS: This study provides insight into

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potential opportunities for clinical pharmacists, community pharmacists, and institutional pharmacists to help achieve improvements in drug treatment. Haag and colleagues note that even after 30 days, many problems related to drug therapy were still unresolved.1 A systematic approach is needed to effectively target patients in this 30-day window for interventions that will address these problems.

These gaps in care increase the risk for an adverse event, promote poor outcomes, and drive up healthcare expenses.

I was surprised to read that the telephonic approach used by the authors did not offer benefits to the patients over the standard-of-care approach in a care transitions program.1 We know from other studies that interventions can have a positive effect on outcomes in the treatment of chronic diseases. The Asheville Project demonstrated the effectiveness of direct patient counseling by community pharmacists when diabetic patients showed significantly lower hemoglobin A1c values after targeted, direct counseling from their community-based pharmacists.2 PAYERS: To increase the level of medication management and improve access to MTM services, it may be time to consider compensation to pharmacists for these services, provided that there is documentation of true clinical and financial benefits to the patients and/or the health plan. An effective MTM program can improve health, prevent undesired clinical outcomes, and save scarce resources that may be applied to new and innovative treatments for chronic diseases.

PATIENTS: In addition, patients need to become more engaged in their own care through effective health and wellness programs, counseling, and formal disease education. These activities can be combined with an effective MTM program to ultimately affect poor health and deliver consistent improvements in health outcomes. n 1. Haag JD, Davis AZ, Hoel RW, et al. Impact of pharmacist-provided medication therapy management on healthcare quality and utilization in recently discharged elderly patients. Am Health Drug Benefits. 2016;9(5):259-267.

2. Cranor CW, Bunting BA, Christensen DB. The Asheville Project: long-term clinical and economic outcomes of a community pharmacy diabetes care program. J Am Pharm Assoc. 2003;43:173-184.

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REVIEW ARTICLE

Hospital and Health Plan Partnerships: The Affordable Care Act’s Impact on Promoting Health and Wellness Michelle Vu, PharmD candidate; Annesha White, PharmD, PhD; Virginia P. Kelley, MBA; Jennifer Kuca Hopper, MS; Cathy Liu, PharmD candidate BACKGROUND: The Affordable Care Act (ACA) healthcare reforms, centered on achieving the Centers for Medicare & Medicaid Services (CMS) Triple Aim goals of improving patient care quality and satisfaction, improving population health, and reducing costs, have led to increasing partnerships between hospitals and insurance companies and the implementation of employee wellness programs. Hospitals and insurance companies have opted to partner to distribute the risk and resources and increase coordination of care.

OBJECTIVE: To examine the ACA’s impact on the health and wellness programs that have resulted from the joint ventures of hospitals and health plans based on the published literature.

METHOD: We conducted a review of the literature to identify successful mergers and best practices of health and wellness programs. Articles published between January 2007 and January 2015 were compiled from various search engines, using the search terms “corporate,” “health and wellness program,” “health plan,” “insurance plan,” “hospital,” “joint venture,” and “vertical merger.” Publications that described consolidations or wellness programs not tied to health insurance plans were excluded.

Noteworthy characteristics of these programs were summarized and tabulated.

RESULTS: A total of 44 eligible articles were included in the analysis. The findings showed that despite rising healthcare costs, joint ventures prevent hospitals from trading-off quality and services for cost Stakeholder Perspective, reductions. Administrators believed that partnering would allow the companies to meet ACA standards page 278 for improving clinical outcomes at reduced costs. Before the implementation of the ACA, some employers had wellness programs, but these were not standardized and did not need to produce measurable results. The ACA encouraged improvement of employee wellness programs by providing funding for expanded health services and by mandating quality care. Successful workplace health and wellness Am Health Drug Benefits. programs have varying components, but all include monetary incentives and documented outcomes.

2016;9(5):269-278 CONCLUSION: The concurrent growth of hospital health plans (especially those emerging from vertical www.AHDBonline.com mergers and partnerships) and wellness programs in the United States provides a unique opportunity for employees and patient populations to promote wellness and achieve the Triple Aim goals as initiated Received July 12, 2015

by CMS.

Accepted in final form February 10, 2016

KEY WORDS: accountable care organization, Affordable Care Act, health and wellness programs, health insurance plan, healthcare reform, partnerships, joint ventures

T

he growing number of partnerships between hospitals, outpatient care providers, and academic medical centers has been attributed, at least in

Ms Vu is a graduate student, College of Pharmacy, Mercer University, Atlanta, GA; Dr White is Assistant Dean for Assessment, UNT System College of Pharmacy and Assistant Professor, Department of Pharmacotherapy, University of North Texas, Fort Worth; Ms Kelley is Benefits Director, Piedmont Healthcare, Atlanta, GA; Ms Kuca Hopper is Manager, Piedmont Healthcare, Atlanta, GA; Ms Liu is a graduate student, College of Pharmacy, Mercer University.

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Disclosures are at end of text

part, to the healthcare reform initiated by the Affordable Care Act (ACA), which rewards hospitals for improving patient health outcomes and reducing healthcare costs.1 For example, under the Medicare program for accountable care organizations (ACOs), any reduction in cost growth (as well as any losses) will be shared with Medicare, depending on the quality of care delivered.2 These reforms represent a departure from fee-for-service models, which incentivize payment for a volume of services, to value-based models, which reimburse based on quality-­ of-care measures. In response to various incentives and increased efforts to reform, many hospitals and health

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KEY POINTS The ACA has led to increased mergers and partnerships between hospitals and insurance companies. ➤ This article reviews the impact of the ACA on health and wellness programs associated with joint ventures of hospitals and health plans based on the published literature. ➤ A total of 44 eligible articles were included in this analysis. ➤ Despite rising healthcare costs, joint ventures prevent hospitals from trading-off quality and services for cost reductions. ➤ The ACA encourages enhancement of existing employee wellness programs by providing funding for expanded services and mandating quality care. ➤ Successful employee wellness programs have different components, but all include monetary incentives and documented outcomes. ➤ The growth of wellness programs provides an opportunity to promote the Triple Aim goals outlined by CMS, which could improve healthcare outcomes in the country. ➤

systems have opted to partner to distribute the risk and resources, increase coordination of patient care, and provide higher-quality services.3 Hospitals opt for mergers and partnerships for several reasons. The ACA’s healthcare reform stresses the Triple Aim goals, introduced by the Centers for Medicare & Medicaid Services (CMS), of improving patient care quality and satisfaction, improving population health, and reducing costs.4 CMS planned to cut payment to hospitals with poor patient outcomes by 1%, from October 2014 through September 2016, a decision that affects approximately 14% of hospitals in the United States.5 To meet these demands, hospital administrators have been seeking to diversify their patient populations, upgrade technologies, and increase access to capital through joint ventures.

A joint venture is a partnership in which 2 parties share risks and profits, as well as administrative power, to innovate.3 Joint ventures are more flexible than mergers, with the parties remaining more independent. A merger is a partnership in which 2 parties combine, sharing assets as well as debts, for a competitive market advantage.

Mergers and joint ventures allow participating parties to combine clinical and/or management strengths and gain greater geographic coverage, which increases access to more patients for federal reimbursement.3,6 Restructuring, similar to repurposing assets, is a natural conse-

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quence of joint ventures and could reduce excess capacity at the city level, which would further reduce costs.

An ACO is a group of healthcare providers and/or suppliers of services (eg, hospitals, physicians, payers) that voluntarily work together to coordinate patients’ healthcare to improve overall patient health and healthcare while reducing costs, in turn producing a more streamlined method of healthcare delivery.2 A 2012 joint venture between Piedmont and WellStar healthcare systems resulted in the Georgia Health Collaborative, which focuses on ACOs and innovative healthcare delivery. This partnership was much aniticipated in the state7 and allowed for the formation of a new insurance plan—Piedmont WellStar Health Plan (PWHP)—to accommodate the increased population coverage and Medicare recipients.8 Medicare Shared Savings mandates reporting of quality measures to receive payment as preventive health, as well as requirements covered by PWHP’s wellness program, including immunizations, disease screenings, and disease management improvements.2 The administrators of the respective organizations at PWHP believed that partnering would allow the companies to meet ACA standards for improving clinical outcomes at reduced costs, and offer a greater financial buffer for future healthcare reform.8 PWHP also emphasizes that joint ventures will allow for implementation of disease prevention and care management programs, with higher quality at lower costs, which is funded by the Prevention and Public Health Fund of the ACA.7,9 With this goal of improving the health of patient populations, this joint venture is paving the way for a care model centered on patients and healthcare professionals.

In addition to improving patient care, specific ACA provisions have encouraged hospitals to focus on the well-being of their employees.10 Before the ACA was passed, some employers had wellness programs (ie, preventive measure activities) in which participants were awarded for adopting healthy lifestyles.11 However, these programs were not standardized and did not need to produce measurable results to comply with federal standards.

The ACA encourages implementation of employee wellness programs by establishing the Prevention and Public Health Fund, which includes other preventive goals of funding community health services and waiving preventive service costs (eg, immunizations, cholesterol screenings, flu shots).9 In 2011, $10 million in ACA funds was distributed by the US Department of Health & Human Services (HHS) to help establish and improve employee wellness programs. The ACA also mandated quality reporting from health insurers to monitor the programs’ effectiveness.

CMS’s final rule, “Incentives for Nondiscriminatory Wellness Programs in Group Health Plans,” outlines the

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types of wellness programs and their incentive structures.11 In 2013, the US Department of the Treasury, the Department of Labor, and the HHS issued a joint final ruling that further increased ACA provisions for employee programs.11 The final ruling categorized programs by their type of incentives: participatory or contingent on health. Participatory programs are focused mainly on education and health screenings, and rewards (if any) are not tied to participants’ health outcomes.

Health-contingent programs offer incentives for participants to improve health factors and are subdivided into action-only incentives (rewards are issued for enrolling in activities such as diet and exercise) and outcomes-based incentives (rewards are issued for demonstrating improvement in health-screening results). For the latter type, the legislation has increased the amount of outcomes-based rewards from 20%, set by HIPAA regulations, to 30% of the employer employee’s cost for the health plan. For programs with tobacco-reduction goals, the legislation increases ACA’s incentives to 50% coverage of healthcare costs. These increased efforts to fund preventive efforts have increased the development of employee wellness programs.11 Although leaders of hospitals and health plans cite many benefits to partnering and the subsequent development of health and wellness programs,3,7,8 there is controversy about whether these structures, supported by ACA reforms, benefit all related parties (physicians, employees, and patients) by lowering costs and improving healthcare quality. Joint venture and merger deals have engendered noteworthy antitrust disputes within federal and state courts because of posited anticompetitive effects.12 Some economic studies based on outcomes of heightened consolidation activity in the 1990s and early 2000s suggest that such concentration of the healthcare market will result in higher costs for patients.13,14 For example, in 2013, the Federal Trade Commission (FTC) blocked hospital mergers in Illinois and Ohio,3 and would have blocked the merger between Palmyra Park Hospital and Phoebe Putney Health System in Georgia if state legislations had not nullified the federal mandate.15 For health and wellness programs, an investigation of UMPC MyHealth,16 and a review by the RAND Corporation,17 have demonstrated varying significance of health benefits and are inconclusive on cost-effectiveness.1 Although the trend toward partnerships between hospitals and health plans is increasing, as is the consequent development of health and wellness programs, it is unclear whether this trend is positive or negative.

The ACA reforms have incited rapid growth of joint ventures and mergers, as well as health and wellness programs within the healthcare marketplace. However, evidence is inconclusive on whether these partnerships

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and wellness programs are contributing to the Triple Aim of improving patient care, improving population health, and reducing costs.4 Piedmont/WellStar emerged as a novel entity in the shifting healthcare environment.

It is one of the first vertical partnerships in the country between a hospital and a health plan that implemented a reformed employee health and wellness program. This combination represents a unique opportunity to promote health and wellness.

The primary objective of our study was to examine the impact of ACA-related reforms on the development of health and wellness programs once a joint venture is established between a hospital and a health plan. The secondary objective was to summarize the literature on effective health and wellness programs and provide examples of successful joint ventures and mergers.

Methods We conducted a review to identify successful joint ventures, mergers, and health and wellness programs. Journal articles, newspaper articles, press releases, and legislative reports were collected from PubMed, Galileo, EBSCO­host, and Google Scholar. Key search terms were “employee,” “corporate,” “health and wellness program,” “health plan,” “insurance plan,” “hospital,” “vertical venture,” “joint venture,” and “merger.” Details for individual partnering entities and wellness programs were obtained by searching hospital websites. Articles selected for review were published between January 2007 and January 2015.

Articles pertaining to joint ventures and mergers had to be published online, in the United States, between 2007 (in anticipation of the ACA) through January 2015 (first-year benchmark of Piedmont/WellStar, a joint venture employee wellness program). Articles were excluded from the review of successful wellness programs if they involved topics related to acquisitions, wellness programs not tied to insurance plans, patients and nonemployee populations, studies conducted in nonhospital settings, and articles lacking a report on health outcomes. ACOs formed outside of joint ventures or merger agreements were not included in this study. The bibliographies of the articles were reviewed, and cited sources were obtained if relevant.

Data collected and analyzed included partnership location, partnership type, population size, partnership date, and demographics and program outcomes of the health and wellness programs.

Results Joint Ventures A total of 44 articles met the inclusion criteria. Analysis of these articles showed that the rationale related to risks and benefits of joint ventures associated with mar-

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ket consolidation and anticompetitive effects have changed since hospital mergers of the 1990s.18 In addition, growth in hospital prices has been declining over the past decade, from 5.8% in 2003 to 1.5% in 2013.18 The number of hospital joint ventures increased substantially in 2010 and 2011, which was attributed in part to preparation for the ACA reforms.3 According to a survey published in 2013 of 306 hospital referral regions, 60% of hospitals in 2013 were affiliated with health systems, representing a 7% increase over 10 years.1 The increase in joint venture and acquisition activity correlated with decreased demand for inpatient services, as evident by reductions in the length of hospitalization.18 According to a 2013 study by the Center for Healthcare Economics and Policy, from 2007 to 2011 there have been 245 hospital mergers, with the majority consisting of the acquisition of 1 or 2 entities.19 Of the 333 mergers, approximately 33% were reported to the FTC, and only 4 were challenged in court. Furthermore, joint venture and acquisition activity overall only involved 12% of hospitals, contrary to the perceptions of “mega-consolidation” within the healthcare market.19 Most joint ventures and mergers can be categorized as either vertical or horizontal partnerships.1,12 A horizontal partnership is a consolidation of businesses that provide the same service (eg, a hospital partnering with another hospital). By contrast, a vertical partnership is a consolidation of businesses that provide different services.1,13 For example, a hospital and a health insurer launching a joint health plan, such as Piedmont/WellStar, represents a vertical joint venture. Vertical joint ventures had been unprecedented before the recent healthcare reforms of the ACA, because of conflicting interests (eg, hospitals bill insurance plans for patients’ charges). However, the ACA reform’s incentives to reduce costs and offer accountable care have fostered this unique collaboration.

Examples of Successful Joint Ventures and Mergers In addition to Piedmont/WellStar’s partnership, 7 other entities have formed vertical joint ventures or mergers (Table 1), including Mount Sinai Medical Center and Continuum Health Partners (New York City); MedStar Health and Southern Maryland Hospital Center (Clinton); Highmark Health Services and West Penn (Pittsburgh); Aetna and Inova (Northern Virginia); Health First and Florida Hospital (Florida); Dartmouth-Hitchcock, Elliot Hospital, and Harvard Pilgrim Health Care (New Hampshire); Anthem Blue Cross plus 7 California hospital systems (California); and Tufts Health Plan and Granite Health (New Hampshire).6,20-30 Kern Medical Center and Kern Health Systems may establish a vertical merger in California.31

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Innovation Health represents a novel type of joint venture between a hospital system and a health plan, Inova and Aetna, respectively.24,25 The joint venture was launched to enroll members in North Virginia, allowing them access to local Inova providers and to Aetna providers nationwide. Payment reform from the ACA was given as a motivating factor to form this partnership: a unique health plan that aligns incentives among physicians, patients, the health plan, and the health system to improve quality and lower cost of care.29 The health plan follows the traditional fee-for-service model by charging premiums per enrollee, and it incentivizes value-based care by sharing cost reductions with physicians. The aim of this incentive is to reduce patient premiums long-term by aligning incentives with healthcare providers. Furthermore, the health plan believes that joint ventures will allow for an easier transition from fee-for-service to accountable care payment models, combining resources to invest in information technology and communication infrastructure. This venture has been active for 3 years and provides coverage to residents of North Virginia.29 Similarly, the merger of Highmark with West Penn, known as Allegheny Health Network (AHN), provided the basis for Piedmont/WellStar’s partnership and joint health plan.7,32 This Pennsylvania collaboration initiated the Accountable Care Alliance and, through this initiative, physicians from AHN’s 7 hospitals worked with Highmark to set new standards for patient care and safety, identify best medical practices, and upgrade technology to improve care coordination.32 Highmark based the AHN’s model for patient care on its patient-centered medical home program, a collaboration with a separate ACO, in which providers communicate and share responsibility for a patient’s health quality. The Accountable Care Alliance is expected to expand to include Highmark providers outside of AHN, which would increase patients’ access to providers and specialists. The joint venture has benefited both parties, with the West Penn Allegheny Health System recently reporting its first profit in 3 years.33 The most recent joint venture, Tufts Freedom Health, involves the 5-hospital health system, Granite Health, and an insurer, Tufts Health Plan, to administer Tufts Freedom Health Plan exclusively to New Hampshire residents.30 Leaders from both entities aim to provide greater care coordination and quality care, with Granite Health’s initiatives centered on improving health outcomes through shared data-driven population health management and administrative efficiencies and product innovation from Tufts Health Plan.

Representing one of the innovative services focused on improving quality care, wellness-focused health plans

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Table 1 V ertical Partnerships Established Through January 2015 Resulting health partnership Base location

Participants

Partnership launch date

Insurer/hospital

Type

MedStar Health/Southern Maryland Hospital Center21

Merger

MedStar Southern Maryland Hospital Center

Clinton, MD

10 hospitals 258 physicians 27,000 employees

December 2012

Highmark/West Penn22,32

Merger

Allegheny Health Network

Pittsburgh, PA

7 hospitals 1700 physicians 17,000 employees

July 2013

Continuum Health Partners/ Mount Sinai6

Merger

Mount Sinai Health Systems

New York, NY

3500 certified, licensed beds July 2013 12 freestanding ambulatory surgical centers 6600 physicians 36,000 employees

Piedmont/WellStar7,8,20

Joint venture

Georgia Health Collaborative

Atlanta, GA

10 hospitals 900 physicians 19,600 employees

November 2012

Inova/Aetna24,25,29

Joint venture

Innovation Health

Falls Church, VA

Aetna 5400 hospitals 587,000 physicians

October 2013

Inova 5 hospitals 3720+ physicians Health First/Florida Hospital23,26

Joint venture

Florida Hospital Ormond Beach, FL 17 hospitals Care Advantage 3000 physicians (administered by Health First)

August 2013

Dartmouth-Hitchcock Medical Center, Elliot Hospital, and Harvard Pilgrim Health Care27

Joint venture

Elevate Health

Manchester, NH, and Wellesley, MA

January 2014

Joint Anthem Blue Cross, venture Cedars-Sinai, Good Samaritan Hospital, Huntington Memorial Hospital, MemorialCare Health, PIH Health, Torrance Memorial Health, and UCLA Health28

Anthem Blue Cross Vivity

Los Angeles and 7 hospital systems Orange County, CA

September 2014

Joint venture

Tufts Health Freedom Plan

Watertown, MA, and Concord, NH

January 2016

Tufts Health Plan and Granite Health30

have been launched for employees and patients.30 Reflecting the trend of integrating provider and payer, some hospitals are planning to start their own insurance plans for their patient populations, either by self-insuring or through partnering.20 A 2011 survey of hospital leaders demonstrated that 20% of the 100 hospitals surveyed intend to market their own insurance plan. In 2010, approximately 10% of community hospitals nationwide either owned or were part of health systems that owned health plans.20 For example, Florida Hospital had planned to launch its own insurance, but because of cost and time barriers, it was believed that strategically partnering with

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17 hospitals 4000 physicians 50,000 employees

5 hospital systems

Health First Health Plans would be more efficient, reflecting the advantage of shared resources within a joint venture.23 This partnership and others reflect the increasing interest of hospitals and health plans in becoming more patient-centered service providers. Entities also recognize the importance of improving care through wellness programs.

Wellness Programs In recent years, more companies have been providing employee health and wellness programs. According to a 2011 report of the American Hospital Association, 86%

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Action-based Incentives linked Yes to health insurance: health spending account with up to $550 per employee (dependent on health profile)

l

NA indicates not available.

11,200; 20% identified as high-risk

Wellbucks; credits redeemed for gift cards and other rewards

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Sentara Healthcare– Northfolk, Optima Healthcare VA Partnership38,39

Omaha, NE 5700 Nebraska Medical Center37,40,42

For high-risk participants only, an extra $460 annual reduction in premium for disease-management activities

Goal-specific activities; emphasis on coaching

• Smoking cessation • Nutrition • Physical activity • Disease management (emphasized)

NA • Smoking cessation • Nutrition • Physical activity (emphasized) Participationand action-based Yes

Cleveland, OH Cleveland Clinic35,36,40

Health insurance premium discounts

Increase in premiums is delayed if employees meet the program’s goals • Smoking cessation • Weight management and nutrition • Physical activity Outcomes-based Yes Health insurance rebates

Location

Target employee population Incentive type

Voluntary participation Reward type

Program components

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Hospital

Table 2 D emographics and Structures of Some Successful Hospital Health and Wellness Programs

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of the nation’s hospitals have an employee wellness program and are promoting a “culture of health,” involving leadership, incentives, 2-way communication, program diversity, and/or outcomes documentation.10 Most employee wellness programs target obesity and smoking,10,34 the leading causes of preventable death in the United States, and the greatest cost to insurers. Depending on the type of incentive (participation-based or health outcomes–based), employee participation rates and health outcomes vary.11 A literature review conducted by the US Department of Labor and the HHS, “Current Use of Wellness Programs and Economic Impacts,” supports (but not definitively) the belief that most such programs contribute to lowering insurance costs and improving employee morale and health.11 However, a RAND study showed that results from these programs (only 50% of which were evaluated formally by employers) produce negligible savings and health improvements: in a 3-year period, the average weight loss was approximately 1 pound per employee.17 A 5-year observational study of a wellness program examined by the University of Pittsburgh Medical Center (UPMC) involved a matched-control analysis of more than 4000 employees.16 Although results showed an increase in overall costs, the cost reduction for the high-risk groups was significant. The majority of employees maintained or reduced their health risks.16 Table 2 and Table 3 summarize several examples of successful hospital wellness and health programs, including Cleveland Clinic, Nebraska Medical Center, and Sentara Healthcare–Optima Healthcare. Although they vary in size and activities, their best practices for profitable wellness programs are similar and include risk stratification of employees, targeted interventions, substantial monetary incentives, and employee-­ centered care.35-38 Smoking cessation and physical activity are among the areas targeted. Sentara and Cleveland Clinic demonstrated improved health outcomes, as measured by lower health risks, reduced smoking rates, and screening values. Sentara and Nebraska Medical Center realized cost-savings through their wellness programs. The Sentara-Optima partnership reflects the strategic advantages of joint ventures; Sentara wished to build on Optima’s existing MyLife and MyPlan programs with added care coordination to form the Mission Health wellness program.39 The clinical and financial success of Mission Health is evidenced by its disease manage-

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Table 3 O utcomes of Some Successful Hospital Health and Wellness Programs Participation rate

Hospital

45%

Cleveland Clinic35,36,40

Monetary outcomes

Effectiveness Blood pressure lower in 2011 than in 2008a

Other features

NA

• Partnerships with Curves and Weight Watchers • Requires employees to log weight and body measurements online

Mean smoking rate declined from 15.4% to 6.8% Nebraska Medical Center37,40,42

63%

N/A

Spent $4117 per employee vs the national average of $8376

• Tailors activities and education programs to employee population’s health risks • Contracts with SimplyWell to maintain a wellness portal • Offers diverse incentives

Sentara Healthcare– Optima Healthcare Partnership38,39

>50% participation among high-risk employees

Critical health risks were maintained or improved for 87% of monitored participants

ROI of $6 per dollar invested vs the national average of $3

• High financial rewards, high ROI • Successful diseasemanagement program

Percentage of change not specified.

NA indicates not available; ROI, return on investment.

a

ment outcomes and the high ratio of return on investment (ROI) of 6:1.39 Approximately 7% of hospital wellness programs surveyed by the American Hospital Association have measured their ROI, and less than 50% have measured health outcomes.10 Therefore, because most programs are less than 3 years old and lack ROI data, controversy still exists on the effectiveness of these programs in improving population health and reducing costs.18 However, the average ROI ratio of successful programs ranges from 2:1 to 3:1 compared with 3:1 in corporate settings.34 Notwithstanding the dispute on the effectiveness of these employee programs, to mitigate rising healthcare and program implementation costs, a trend within the hospital community links employee wellness programs with health insurance.10

Discussion Several case studies of joint ventures and mergers suggest that anticompetitive effects increase costs for comparable services but that overall the cost benefits of merging are dependent on characteristics of the hospital and the market.1 Moreover, it has been suggested that price analyses based on healthcare consolidations in the 1990s do not accurately apply to the current healthcare environment, which is marked by emphasis on the Triple Aim goals and the shift of health stewardship to the patient.18 Moreover, antitrust actions from the FTC have not been a barrier: less than 2% of reported partnerships have been challenged in court.18 The novel partnerships between hospitals and health plans that are now emerg-

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ing are very different from the horizontal joint ventures that occurred before implementation of the ACA. Most vertical joint ventures and partnerships have formed since 2011. For the novel entities, health outcomes data are currently insufficient to determine their effect on improving patient care, improving population health, and reducing costs, especially within the context of joint wellness programs.18 For 1 Triple Aim goal, that of improving patient care satisfaction, the American Hospital Association recommends engaging employees first, and then tailoring program incentives and goals.10 Within the value-based payment model, improving population health and reducing costs are aligned, achieving patient population-based health goals by targeting highrisk, high-utilization groups.

However, given this trend of increasing partnerships and rising healthcare costs, healthcare executives believe that joint ventures prevent hospitals from trading-off quality and services for cost reductions and risk of closure.7 Therefore, these partnerships provide a structure to achieve the Triple Aim of improved patient care, cost containment, and population health.4 If these entities can meet these goals, especially through demonstrating cost-savings and improved health outcomes, they will be rewarded for their innovation through the ACA’s value-based payment models that share risks and cost-savings among healthcare partners.

Although ACA provisions for Medicare Shared Savings have incentivized employee wellness programs, other federal programs, particularly Medicare Part D, currently do not reimburse for wellness or preventive health inter-

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ventions. Accurate and detailed documentation of the cost-effectiveness of Medicare Shared Savings may encourage Medicare Part D to expand to wellness reimbursement based on the joint stakeholder incentives. If well-structured incentives from Medicare Shared Savings are tied to wellness outcomes, health systems could use this model for future wellness programs, and more healthcare practitioners (including pharmacists) could have more opportunities to participate in wellness promotion.

Before the ACA, some employers had wellness programs, but these programs were not standardized and did not need to produce measurable results. The ACA encourages improvement of employee wellness programs by providing funding for expanded health services and mandated quality reporting. The increase in compensation of health-contingent programs from 20% to 30% of wellness program costs reflects the shifting paradigm toward value-based care.11 Employee wellness programs have implemented more patient-centered interventions, including health portals, counseling on lifestyle choices, and prospective referral services for at-risk groups.

Successful workplace health and wellness programs have varying incentive structures, but all include monetary incentives and documentation of costs and/or health outcomes. The Mission Health and UPMC MyHealth programs support the belief that disease management programs and targeted wellness services for high-risk populations can result in substantial cost-savings. Therefore, focusing on a select group of high-cost patients and designing methods of documenting cost-savings at the start of the wellness program is a best practice for achieving lower healthcare costs. Corporate wellness professionals and health outcomes organizations recommend best practices to establish a wellness program40 and to generate and synthesize healthcare evidence for adequate cost-effective analysis.41 These recommendations should be followed for merged organizations to adequately assess health outcomes, produce adequate ROI, and determine the true health values realized from health and wellness programs.

For the initial stages of their new health plans, hospital executives state that launching reinvented employee wellness programs represents an opportunity not only to adapt to new federal quality-based incentives and penalties, but also to test the efficacy and cost-savings of these interventions before expanding them to their patient populations.8 Piedmont and WellStar’s partnership and joint wellness-centered health plan represent a model that addresses the Triple Aim of improved patient care, cost containment, and population health. Although most wellness programs currently allow access to only local employee populations, the potential expansion of Aetna and Inova’s Innovation Health and the alliance of Highmark and

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West Penn indicate a trend toward integrated patient care among providers and insurers on a national scale.

Conclusion The combination of funding from the ACA to offset initial investment costs of a wellness program plus incentives from CMS’s value-based payment models to realign care models and document quality measures have incited innovation in employee wellness programs within vertical joint ventures and mergers. Although there are startup costs for providing employee wellness programs, partnering entities foresee increased value in providing more health benefits because of the lack of detailed documentation and the novelty of the models identified (incentivized employee wellness programs and vertical joint ventures and mergers): the degree of benefits realized from these costs is yet to be determined.

Future research on wellness programs of joint ventures or mergers should include high-quality study designs that focus on the Triple Aim objectives. Patient-centered goals and focus groups should be elicited for continuous feedback on program designs. These studies should include matched-control and intervention groups, stratified by risk, to assess the impact of wellness programs, and primary outcomes should entail documenting costs as well as health outcomes. In addition, studies should demonstrate cost-savings from meeting Medicare Shared Savings quality measures and document the impact of healthcare professionals on quality care for reimbursement purposes. Such research would help expand value­based care models and foster new opportunities to promote health and wellness. n Author Disclosure Statement Dr White is a consultant to Baxter, Keryx, Prium, and GVK Biosciences. Ms Vu, Ms Kelley, Ms Kuca Hopper, and Ms Liu reported no conflicts of interest.

References

1. Cutler DM, Scott Morton F. Hospitals, market share, and consolidation.

JAMA. 2013;310:1964-1970.

2. Centers for Medicare & Medicaid Services (CMS), HHS. Medicare Program; Medicare Shared Savings Program: Accountable Care Organizations. Proposed rule. Fed Regist. 2014;79:72760-72872.

3. Dixon Hughes Goodman. What hospital executives should be considering in hospital mergers and acquisitions. White paper. Winter 2013. www.dhgllp.com/ res_pubs/Hospital-Mergers-and-Acquisitions.pdf. Accessed July 3, 2014.

4. Stiefel M, Nolan K. A guide to measuring the Triple Aim: population health, experience of care, and per capita cost. Institute for Healthcare Improvement Innovation Series white paper. 2012. www.ihi.org/resources/Pages/IHIWhite Papers/AGuidetoMeasuringTripleAim.aspx. Accessed June 19, 2015.

5. Rau J. Medicare cuts payment to 721 hospitals with highest rates of infections, injuries. Kaiser Health News. December 18, 2014. http://kaiserhealth news.org/news/medicare-cuts-payments-to-721-hospitals-with-highest-rates-ofinfections-injuries/. Accessed April 2, 2015.

6. Hartocollis A. 2 hospital networks agree to merge, raising specter of costlier care. New York Times. July 16, 2013. www.nytimes.com/2013/07/17/nyre gion/2-hospital-networks-agree-to-merge-raising-specter-of-costlier-care.html ?ref=mountsinaimedicalcenter&_r=2. Accessed April 20, 2015.

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7. Miller A. Piedmont-WellStar alliance shakes up marketplace. Georgia Health News. November 12, 2012. www.georgiahealthnews.com/2012/11/pied mont-wellstar-forming-alliance/. Accessed June 26, 2014.

8. Miller A. Piedmont-WellStar alliance to launch health plan. Georgia Health News. December 17, 2012. www.georgiahealthnews.com/2012/12/piedmontwellstar-alliance-launch-health-plan/. Accessed June 27, 2014.

9. Anderko L, Roffenbender JS, Goetzel RZ, et al. Promoting prevention through the Affordable Care Act: workplace wellness. Prev Chronic Dis. 2012; 9:E175.

10. American Hospital Association Long-Range Policy Committee. A call to action: creating a culture of health. January 2011. www.aha.org/research/cor/ content/creating-a-culture-of-health.pdf. Accessed June 24, 2014.

11. Internal Revenue Service, Department of the Treasury; Employee Benefits Security Administration, Department of Labor; Centers for Medicare & Medicaid Services, Department of Health and Human Services. Incentives for nondiscriminatory wellness programs in group health plans. Final rule. Fed Regist. 2013;78:33157-33192.

12. Braun CJ, Short F. Going vertical: the hospital-health insurer merger. Paper presented at the Antitrust in Healthcare Conference; May 3-4, 2012; Arlington, VA. www.mintz.com/DesktopModules/Bring2mind/DMX/Download.aspx ?EntryId=1495&PortalId=0&DownloadMethod=attachment. Accessed June 24, 2014.

13. Dafny L. Estimation and identification of merger effects: an application to hospital mergers. J Law Econ. 2009;52:523-550.

14. Gaynor M, Town R. The impact of hospital consolidation—update. The Synthesis Project, policy brief no 9. June 2012. www.rwjf.org/content/dam/ farm/reports/issue_briefs/2012/rwjf73261. Accessed August 1, 2014.

15. Federal Trade Commission. Hospital Authority and Phoebe Putney Health System settle FTC charges that acquisition of Palmyra Park Hospital violated U.S. antitrust laws. Press release. August 22, 2013. www.ftc.gov/news-events/ press-releases/2013/08/hospital-authority-and-phoebe-putney-health-sys tem-settle-ftc. Accessed July 3, 2014.

16. Parkinson MD, Peele PB, Keyser DJ, et al. UPMC MyHealth: managing the health and costs of U.S. healthcare workers. Am J Prev Med. 2014;47:403-410.

17. Mattke S, Liu H, Caloyeras JP, et al. Workplace wellness programs study: final report. 2013. www.rand.org/content/dam/rand/pubs/research_reports/ RR200/RR254/RAND_RR254.pdf. Accessed December 29, 2014.

18. Guerin-Calvert ME, Maki JA. Hospital realignment: mergers offer significant patient and community benefits. January 23, 2014. www.fticonsulting. com/~/media/Files/us-files/insights/reports/hospital-realignment-mergers-of fer-significant-patient-and-community-benefits.pdf. Accessed July 3, 2014.

19. Center for Healthcare Economics and Policy, FTI Consulting; American Hospital Association. How hospital mergers and acquisitions benefit communities. September 18, 2013. www.aha.org/content/13/13mergebenefitcommty.pdf.

Accessed July 3, 2014.

20. Wilde Mathews A. Hospital systems branch out as insurers. Wall Street Journal. December 16, 2012. www.wsj.com/articles/SB10001424127887324677 204578183041243834084. Accessed June 3, 2015.

21. MedStar Southern Maryland Hospital Center. MedStar merger. www. medstarhealth.org/msmhc/our-hospital/medstar-merger/. Accessed July 2, 2014.

22. PR Newswire. Highmark Health Services forms Accountable Care Alliance to improve care and health outcomes for Western Pennsylvania residents. Press release. July 18, 2013. www.prnewswire.com/news-releases/highmark-healthservices-forms-accountable-care-alliance-to-improve-care-and-health-out comes-for-western-pennsylvania-residents-216008621.html. Accessed July 1, 2014.

23. Evans M. Hospitals seeing benefits of partnering with insurance companies.

Vital Signs blog. Mod Healthc. August 28, 2013. www.modernhealthcare.com/ article/20130828/blog/308289999. Accessed July 12, 2015.

24. Accountable Care Solutions from Aetna. Innovation Health approved to

offer health insurance plans in Virginia. Press release. October 3, 2013. www. aetnaacs.com/innovation-health-approved-offer-health-insurance-plans-vir ginia. Accessed June 24, 2015.

25. Kliff S. Aetna and Inova unveil joint venture for improved, cost-effective health care. Washington Post. June 22, 2012. www.washingtonpost.com/busi ness/economy/2012/06/22/gJQAOyoGvV_story.html. Accessed June 22, 2015.

26. Florida Hospital. Florida Hospital Care Advantage opens office in Ormond Beach. Press release. October 7, 2013. www.floridahospital.com/news/flori da-hospital-care-advantage-opens-office-ormond-beach. Accessed June 24, 2015.

27. Harvard Pilgrim Health Care. ElevateHealth. www.harvardpilgrim.org/ portal/page?_pageid=213,2673992&_dad=portal&_schema=PORTAL. Accessed July 11, 2015.

28. Abelson R. Hospitals and insurer join forces in California. New York Times.

September 17, 2014. www.nytimes.com/2014/09/17/business/hospitals-and-in surer-join-forces-in-california.html. Accessed July 11, 2015.

29. American Medical Association. Insurer-hospital venture paves way toward accountable care. American Medical News. July 10, 2012. www.amednews.com/ article/20120710/business/307109997/8/. Accessed June 22, 2015.

30. Wells B. Tufts Health Freedom Plan, Granite Health leaders: why we teamed up for Tufts Health Freedom Plan in New Hampshire. Becker’s Hospital Review. January 27, 2016. www.beckershospitalreview.com/payer-issues/tuftshealth-freedom-plan-granite-health-leaders-why-we-teamed-up-for-tuftshealth-freedom-plan-in-new-hampshire.html. Accessed June 20, 2016.

31. Burger J. County proposes Kern Medical Center-Kern Health Systems merger. Bakersfield Californian. June 5, 2014. www.bakersfield.com/ news/2014/06/05/county-proposes-kern-medical-center-kern-health-sys tems-merger.html. Accessed July 3, 2014.

32. Allegheny Health Network. Our locations. www.ahn.org/locations. Accessed January 7, 2016.

33. Kutscher B. Rivals UPMC, West Penn Allegheny report improving financials. Modern Healthcare. February 7, 2015. www.modernhealthcare.com/arti cle/20150207/MAGAZINE/302079951. Accessed June 24, 2016.

34. Baicker K, Cutler D, Song Z. Workplace wellness programs can generate savings. Health Aff (Millwood). 2010;29:304-311.

35. Cleveland Clinic. Cleveland Clinic Employee Health Plan. www.cleve landclinic.org/healthplan/wellness.htm. Accessed June 23, 2014.

36. Klein E. Health care’s brave new world of compulsory wellness. Bloomberg View. October 12, 2011. www.bloomberg.com/news/articles/2011-10-13/healthcare-s-brave-new-world-of-compulsory-wellness-ezra-klein. Accessed July 2, 2014.

37. Nebraska Medicine. Making healthcare work. 2011. www.nebraskamed. com/article/100/making-healthcare-work. Accessed July 2, 2014.

38. Optima Health. Managing the wellness gap: Sentara Healthcare and Optima Health demonstrate a five-year trend of bending the healthcare cost curve downward while improving employee health. www.optimahealth.com/well nesspayoff/Pages/default.aspx. Accessed July 2, 2014.

39. Optima Health. The wellness payoff: an exceptional model for improving employee health and achieving unparalleled savings. Podcast. www.optima health.com/wellnesspayoff/Pages/podcasts.aspx. Accessed July 2, 2014.

40. Larson J. The ROI of hospital employee wellness programs. AMN Healthcare. March 18, 2011. www.amnhealthcare.com/the-roi-of-hospital-employ ee-wellness-programs/. Accessed June 23, 2014.

41. International Society for Pharmacoeconomics and Outcomes Research.

ISPOR Good Practices for Outcomes Research index. www.ispor.org/workpa per/practices_index.asp. Accessed April 25, 2015.

42. 100 great hospitals in America 2016: Nebraska Medicine—Nebraska Medical Center (Omaha, Neb.). Becker’s Hospital Review. May 5, 2016. www.becker shospitalreview.com/100-great-hospitals-in-america-2016/nebraska-medi cine-nebraska-medical-center-omaha-neb-16.html. Accessed June 24, 2016.

Stakeholder Perspective next page

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STAKEHOLDER PERSPECTIVE

Measurable Clarity in Healthcare Is Needed So Those Who Use the System Could Achieve a State of Well-Being

By F. Randy Vogenberg, PhD, RPh Partner, Access Market Intelligence and National Institute of Collaborative Healthcare, Greenville, SC

EMPLOYERS/COMMERCIAL HEALTH PLANS: By default, most of the joint ventures in wellness since 2010 among the entities studied by Vu and colleagues1 would have been centered on efforts initiated by the Affordable Care Act (ACA) or the Centers for Medicare & Medicaid Services (CMS). This, and that few employers are willing to publish their collaborations in the medical literature, creates an inherent bias in the effort discussed by Vu and colleagues. Nevertheless, the authors’ conclusions correctly reflect the wide variation in workplace health and wellness programs, the reliance on financial carrot-stick incentives, and the lack of rigorous standards in program evaluation.

One of the biggest mistakes in partnerships between hospitals and health insurance plans has been a primary reliance on CMS criteria and goals to be used with commercial plan populations. The poor history of execution, application of provider incentives, and innovation limits on CMS imposed by Congress significantly curb the direct application of the so-called reforms used in public sector programs to private sector plans. Furthermore, most commercial plan benefit designs are different from Medicare or are nearly in public exchange plans.

For example, the continued difficulty in determining value in commercial plan–sponsored employee healthcare is the topic of an article about the value of investment regarding wellness efforts that clearly underscores the need for improved health risk assessment data for employers.2 It also provides employers’ insights into the positive impact of reducing costs, absenteeism, and the prevalence of disease, and of increasing productivity.

These efforts are beginning to coalesce under the concept of well-being, a broader and higher level construct than plain health and wellness. Well-being may emerge as the best metric to assess economic and clinical outcomes through broader metrics that make sense to executives or board members in all organization sizes.

PATIENTS: Patients are assessing and reacting to

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providers, hospitals, and insurers according to the spectrum of covered benefits and services available to them.

That primarily means that, despite the availability of covered wellness services (eg, immunizations), patients are confused about what, when, and how a service is covered when they decide to access that service (eg, a flu shot).

And the concern is not always about coverage; it may be about how the health delivery system and the benefits administration communicate at the time of service.

Incentives are hard to execute when a multidecade­old national care delivery system shifts from fee for service that focuses on acute care services to fixed reimbursement that focuses on preventive care. Given these seismic shifts, it is not surprising to reach the conclusion that Vu and colleagues identified when viewing the system from a patient perspective. The needs and interests of patients are shifting at the same time that the reimbursement system is being jolted by CMS, and ACA benefits are being mandated. Millennials access and utilize the healthcare system different from the Greatest Generation, and the sandwich baby boom generation is caught in the middle of these trends, while advocating for its own view of care delivery.

Clearly, the health and wellness trend has emerged as important to patients, providers, and purchasers of care.

It is in the interpretation of meeting the needs, wants, and desires of one patient at a time that we are most likely to figure out a clear strategy in the future. Healthcare has evolved to be complex and difficult from a patient perspective, so the arbiters of healthcare need to resolve the complexity, potentially eliminate the middlemen, and provide measurable clarity to those who use the system to achieve a state of well-being. n 1. Vu M, White A, Kelley VP, et al. Hospital and health plan partnerships: the Affordable Care Act’s impact on promoting health and wellness. Am Health Drug Benefits. 2016;9(5):269-278.

2. Livingston S. Going after value in employee health. Crain’s Benefits Outlook; Summer 2016. www.businessinsurance.com/assets/pdf/issues/CBOsummer2016. pdf. Accessed July 6, 2016.

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ORIGINAL RESEARCH

Oncologist Support for Consolidated Payments for Cancer Care Management in the United States Siva Narayanan, MSc, MHS; Emily Hautamaki, MPH

Stakeholder Perspective, page 289

Am Health Drug Benefits.

2016;9(5):280-289 www.AHDBonline.com Received February 1, 2016 Accepted in final form April 28, 2016

Disclosures are at end of text

BACKGROUND: The cost of cancer care in the United States continues to rise, with pressure on oncologists to provide high-quality, cost-effective care while maintaining the financial stability of their practice. Existing payment models do not typically reward care coordination or quality of care. In May 2014, the American Society of Clinical Oncology (ASCO) released a payment reform proposal (revised in May 2015) that includes a new payment structure for quality-of-care performance metrics.

OBJECTIVES: To assess US oncologists’ perspectives on and support for ASCO’s payment reform proposal, and to determine use of quality-of-care metrics, factors influencing their perception of value of new cancer drugs, the influence of cost on treatment decisions, and the perceptions of the reimbursement climate in the country.

METHODS: Physicians and medical directors specializing in oncology in the United States practicing for at least 2 years and managing at least 20 patients with cancer were randomly invited, from an online physician panel, to participate in an anonymous, cross-sectional, 15-minute online survey conducted between July and November 2014. The survey assessed physicians’ level of support for the payment reform, use of quality-of-care metrics, factors influencing their perception of the value of a new cancer drug, the impact of cost on treatment decision-making, and their perceptions of the overall reimbursement climate. Descriptive statistics (chi-square tests and t-tests for discrete and continuous variables, respectively) were used to analyze the data. Logistic regression models were constructed to evaluate the main payment models described in the payment reform proposal.

RESULTS: Of the 231 physicians and medical directors who participated in this study, approximately 50% strongly or somewhat supported the proposed payment reform. Stronger support was seen among survey respondents who were male, who rated the overall reimbursement climate as excellent/ good, who have a contract with a commercial payer that reimburses for dispensed oral cancer drugs, or who practice in a hospital setting. The use of at least 1 quality-of-care metric was more common among respondents participating in an accountable care organization (ACO) than among those not participating in an ACO (92.6% vs 83.2%, respectively; P = .0380). The most common metric used by the physicians in their practice setting was patient satisfaction scores (60.1%). Accountability for delivering high-quality care was supported by 74.9% of respondents; those who practice in a hospital setting were twice as likely as those in private practice to support accountability for quality of care (81.3% vs 67.6%; odds ratio, 2.1; P = .0176).

CONCLUSION: Support for ASCO’s payment reform proposal is mixed among oncology physicians and medical directors, underscoring the importance of continuous and broader engagement of practicing physicians around the country via outreach and dialogue on topics that impact their clinical practices, as well as providing education or awareness activities by ASCO to its membership.

KEY WORDS: ASCO, cancer care, consolidated payments, oncologists, patient-centered oncology payment model, payment reform, provider perspectives, quality-of-care metrics

Mr Narayanan was Senior Vice President, Global Evidence, Value & Access, Ipsos Healthcare, when this study was conducted, and is now Executive Vice President, Market Access Solutions, LLC, Raritan, NJ; Ms Hautamaki is Senior Research Manager, Global Evidence, Value & Access, Ipsos Healthcare, Washington, DC.

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he cost of cancer care in the United States continues to rise, in part as a result of the aging population and improvements in diagnosis, treatment, and survival. These costs are projected to reach $173 billion in 2020, representing a 39% increase from 2010.1 Steadily increasing costs put pressure on payers and

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healthcare providers to develop innovative strategies to control costs. It is also increasingly recognized by various healthcare stakeholders, including providers, payers, and patient advocates, that the current reimbursement system needs refinement to adequately address the breadth of services that are involved in cancer care today.2,3 Furthermore, traditional fee-for-service payment models tend to reward volume and seldom support care coordination or the management of chronic disease. Bundled, risk-based, and episode-of-care−based payment systems have been evolving and are taking shape.4,5 The American Society of Clinical Oncology (ASCO) has undertaken steps to assist physicians with treatment decision-making, assessment of treatment value, and evaluation of quality of care.

To facilitate shared decision-making between physicians and patients, ASCO has developed tools designed to guide the assessment of comparative value of interventions. In 2015, ASCO released its value framework that provides a formula for calculating a drug’s net health benefit score based on clinical benefit and toxicity, which is then considered in conjunction with cost.6 Earlier, in 2013, ASCO released a list of 5 top tests, procedures, and treatments whose value is not supported by available evidence.7 ASCO identified potential barriers faced by oncologists in their ability to provide high-quality care while controlling costs for payers.8 These barriers include undue dependence of practice revenue on administration of drugs in the office; lack of incentive to prescribe less expensive drugs; lack of compensation for patient education and care coordination, including management of patient communications by telephone or e-mail or via a nonphysician member of the practice; insufficient compensation for initial visits, which may reduce access for new patients; lack of consideration of quality of care in providers’ compensation; and lack of compensation for clinical trial participation and management.8 In May 2014,8 ASCO released a proposal (which was revised in May 20159) titled the “Patient-Centered Oncology Payment: Payment Reform to Support Higher Quality, More Affordable Cancer Care,” consisting primarily of new payment types in exchange for practice accountability for delivering high-quality care.9 The new proposal involves 4 payment types, including (1) New Patient Treatment Planning ($750 per patient), (2) Care Management During Treatment ($200 per patient per month), (3) Care Management During Active Monitoring ($50 each month for each patient during treatment holidays and for up to 6 months after the end of treatment), and (4) Participation in Clinical Trials ($100 per month for each patient while treatment is underway and for 6 months afterward for trials in which practice support is not available).9

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KEY POINTS The cost of cancer care in the United States continues to rise, putting pressure on oncologists to provide high-quality, cost-effective care while preserving the financial stability of their practice. ➤ In May 2014, ASCO released a payment reform proposal that includes quality-of-care measures and was revised in May 2015. ➤ Using responses from 231 oncologists/hematologists and medical directors, this study analyzed the use of quality-care metrics in oncology and the impact of new drugs on treatment decisions. ➤ The use of at least 1 quality-of-care metric was more common among those involved in an accountable care organization than other types of practice. ➤ The most common quality-care metric used by respondents was patient satisfaction scores. ➤ Overall, almost 75% of respondents support accountability for delivering high-quality care. ➤ Oncologists who practice in a hospital setting were twice as likely as those in private practice to support accountability for quality of care. ➤ The survey reveals mixed support among oncologists and medical directors involved in oncology for the proposed payment reform from ASCO. ➤

At the time of our study in 2014, a fifth payment was included in ASCO’s proposal, for Transition of Treatment (for treatment planning and patient education, when a patient begins a new line of therapy or ends treatment without an intention to continue).8 This item was removed from the revised proposal released subsequently by ASCO in May 2015.9 Billing for other services, including evaluation/management, chemotherapy infusions, advanced care planning, and testing/imaging, may be generated to the payer, as they currently are.9 In return for this proposed payment structure, the oncology practice would be accountable for delivering high-quality care, demonstrated by performance on several quality-of-care metrics, including emergency department visits and hospital admissions related to complications of treatment, following evidence-based guidelines for treatment patterns and end-of-life care, and following ASCO-defined quality standards.9 A provider payment reform that encourages multi­ stakeholder engagement and rewards improvements in quality of care and patient outcomes while reducing costs may prove beneficial. The purpose of this present study was to assess the attitudes and perspectives of oncologists in the United States about the proposal, their level of

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support for the patient-centered oncology payment (PCOP), and to determine current use of quality-of-care metrics, factors influencing oncologists’ perception of the value of a new cancer drug, the influence of cost on treatment decision-making, and their perceptions of the overall reimbursement “climate” (ie, ease of billing payers for services and receiving appropriate payment) for their practice and patient case mix.

This study was undertaken to assess US oncologists’ perspectives on and support for ASCO’s payment reform proposal, and to determine their use of quality-of-­ care metrics, factors influencing their perception of value of new cancer drugs, the impact of cost on treatment decisions, and the perception about reimbursement modalities.

Methods Physicians and medical directors who specialize in medical oncology or hematology/oncology in the United States, who had practiced for at least 2 years, and managed the care of at least 20 patients with cancer were randomly invited, from a commercial online physician panel, to participate in a cross-sectional survey. The physician panel was created and maintained by a specialized third-party agency, and was designed to include a diverse set of physicians in a range of geographic and practice settings.

The physicians had given consent to be contacted to solicit their interest in participating in research using online data collection platforms. Invitations to participate in this research survey were sent to a random sample of oncologists in the existing panel. The physician and medical directors represented hospital-based and private practices in the United States.

The survey consisted of questions related to demographic and practice characteristics; factors shaping perceptions of value for new cancer drugs (namely, clinical efficacy, impact on quality of life, safety and tolerability, and cost-effectiveness); influence of treatment cost, payer reimbursement policies, and patient out-of-pocket costs when making prescribing decisions; perceptions of use of cost-effectiveness and comparative effectiveness data by payers when deciding reimbursement of drugs; opinions of the most pressing issues facing the future of oncology care in the United States; and level of support for each new payment and the value-based adjustments in ASCO’s proposal for PCOP. Respondents were asked to identify the metrics they use to measure and track quality of care from the following list: Commission on Cancer (CoC) standards, patient satisfaction scores, Quality Oncology Practice Initiatives (QOPI), Physician Quality Reporting System (PQRS), adherence to clinical pathways, ASCO’s Can-

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cerLinQ, and other metrics (ie, metrics from the National Accreditation Program for Breast Centers, American College of Radiology, or any homegrown dashboard).

Questions related to influence of the overall drug costs and patient out-of-pocket drug costs on prescribing decisions were adopted from a survey conducted by Neumann and colleagues in 2010.10 Each component of the ASCO proposal was described briefly in the survey, using text from the PCOP. The survey also solicited unstructured verbatim feedback on the ASCO proposal.

The survey required approximately 15 minutes to complete, and the respondents were assured of anonymity and confidentiality. No personally identifiable information was collected. The respondents were compensated nominally, per fair market value, for their time to complete the survey. The study was conducted between July and November 2014.

Study results were analyzed descriptively, with unadjusted statistical differences between groups assessed using chi-square tests for discrete variables and t-tests for continuous variables. Logistic regression models were constructed to assess factors supporting each of the main payment models described in the payment reform proposal. P values of less than .05 were considered significant in all analyses.

Results A total of 231 physicians (oncologists or hematologists) and medical directors responded to the invitation and completed the survey. Characteristics of the respondents and their practices are listed in Table 1. Medical directors accounted for 13.0% of the respondents. Approximately two-thirds (67.5%) of respondents specialized in hematology/oncology and 32.5% in medical oncology.

The average duration of physicians’ practice was 15.3 years; 59.3% of the participants were aged 30 to 49 years.

Slightly more than half (53.2%) of the participants practice in an academic, community, or Veterans Administration (VA) hospital; 46.8% are part of a group or solo private practice; 40.7% participate in an accountable care organization (ACO); and 88.7% use electronic health records (EHRs). Only 6.9% of the participants rated the current reimbursement climate as “excellent,” and only 18.2% rated the financial status of their practice’s cancer program as “excellent.”

Participants who rated the overall financial status of their cancer program as excellent or good had practiced for fewer years than those who rated it otherwise (14.1 vs 17.1 years; P = .0069); males were more likely than females to rate it as excellent or good (62.3% vs 42.5%; P = .0206).

Medical directors were more likely than physicians to rate the overall reimbursement climate as excellent or good (60.0% vs 35.3%; P = .0096), as were participants whose

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Table 1 C haracteristics of Respondents and Practices Characteristics of respondents and practices Role

Respondents, N (%) or mean (SD)

Physician

201 (87.0)

Medical director

30 (13.0)

Specialty

Characteristics of respondents and practices Medicaid

Respondents, N (%) or mean (SD) 14.4 (± 13.3)

State Children’s Health Insurance Program (CHIP) Military or Veteran health benefits

1.6 (± 4.7)

Indian Health Service

0.2 (± 1.0)

2.9 (± 8.2)

Hematology/oncology

156 (67.5)

No insurance

4.1 (± 6.6)

Medical oncology

75 (32.5)

Other

0.1 (± 1.4)

Practice duration, yrs

15.3 (± 8.2)

Age, yrs

Practice has an onsite pharmacy

162 (70.1)

Practice has infusion chairs onsite

221 (95.7) 102 (44.2)

205 (88.7)

30-39

63 (27.3)

40-49

74 (32.0)

Practice has a contract with a commercial payer that reimburses for dispensed oral cancer drugs Currently participate in an ACO

50-59

61 (26.4)

Currently use EHR system

60-69

32 (13.9)

Region

70+

1 (0.4)

Sex

94 (40.7)

Northeast

68 (29.4)

Midwest

52 (22.5)

Male

191 (82.7)

South

73 (31.6)

Female

40 (17.3)

West

38 (16.5)

Race

Perception of overall reimbursement climate

White

144 (62.3)

Excellent

16 (6.9)

Asian

47 (24.7)

Good

73 (31.6)

Black or African American

2 (0.9)

Satisfactory

93 (40.3)

Native Hawaiian or Pacific Islander

1 (0.4)

Not very good

45 (19.5)

Other

5 (2.2)

Prefer not to answer

22 (9.5)

Bad

4 (1.7)

Perception of the financial status of the cancer program

Practice setting

Excellent

42 (18.2)

Academic/university hospital

82 (35.5)

Good

94 (40.7)

Community hospital

40 (17.3)

Satisfactory

77 (33.3)

Group private practice

96 (41.6)

Not very good

17 (7.4)

Solo private practice

12 (5.2)

Bad

1 (0.4)

Veterans Administration

1 (0.4)

Practice is adding new technologies/services to improve revenue Yes 93 (40.3)

Patients (approximate) per insurance type Private insurance

42.6 (± 16.3)

No

67 (29.0)

Medicare

34.0 (± 15.9)

Don’t know

71 (30.7)

ACO indicates accountable care organization; EHR, electronic health record; SD, standard deviation.

cancer programs have a contract with a commercial payer that reimburses for dispensed oral cancer drugs (48.0% vs 31.0%; P = .0083). Physicians who rated the reimbursement climate favorably had a larger mean volume of patients per physician (748 vs 370 patients; P = .0004).

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Use of Quality-of-Care Metrics The most common quality-of-care metric used by respondents was patient satisfaction scores (60.1%), followed by QOPI (42.9%), adherence to clinical pathways (35.5%), PQRS (34.6%), CoC standards (23.8%), other

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Table 2 U se of Quality-of-Care Metrics Used Among Respondents Respondents, N (%) or mean (SD) 139 (60.1)

Quality-of-care metric used Patient satisfaction scores Use EHR system

128 (62.4)a

Do not use EHR system Quality Oncology Practice Initiatives

11 (42.3) 99 (42.9)

Adherence to clinical pathways

82 (35.5)

Physician Quality Reporting System

80 (34.6)

Commission on Cancer standards Other

55 (23.8) 25 (10.8)

CancerLinQ

6 (2.6)

None or not sure

30 (13.0)

Use ≥1 quality-of-care metrics

201 (87.0)

Participate in an ACO

87 (92.6)b

Do not participate in an ACO Perception of effectiveness of the organization’s quality measurement and tracking procedures, in terms of improving quality of care, outcomes, and cost-savings Highly effective

114 (83.2)

36 (15.6)

Somewhat effective

152 (65.8)

Somewhat ineffective

29 (12.6)

Very ineffective

10 (4.3)

Unsure Approximate percentage of patients with cancer in the practice for whom the physician generally adhered to NCCN guidelines or pathways Approximate percentage of patients with cancer in the practice who have documented clinical or pathologic staging before initiation of first course of treatment Participate in an ACO Do not participate in an ACO

4 (1.7) 76.4 (± 21.4) 84.2 (± 23.3) 80.3 (± 25.7)c 86.8 (± 21.1)

Rank the top 3 most pressing issues facing the future of oncology care in the United States Increasing costs of drug prices

160 (69.3)

Growing demand for cancer care services

131 (56.7)

Cost and payer pressures

123 (53.3)

Provider burnout

88 (38.1)

Anticipated workforce shortages

64 (27.7)

Racial disparities in access to quality cancer care

35 (15.2)

Access to quality cancer care for rural populations

34 (14.7)

Ineffective health information technology

24 (10.4)

Gaps in racial and ethnic diversity in the workforce

16 (6.9)

Other

6 (2.6)

None of the above 4 (1.7) P = .0482. b P = .0380. c P = .0389.

ACO indicates accountable care organization; EHR, electronic health record; NCCN, National Comprehensive Cancer Network; SD, standard deviation. a

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Perception of Value of a New Cancer Treatment On a scale of 1 to 4, with 1 being the most important and 4 being the least important, respondents ranked clinical efficacy as the most important factor when considering the value of a new cancer drug (mean score, 1.4), followed by impact on quality of life (mean score, 2.69), safety and tolerability (mean score, 2.71), and cost-effectiveness (mean score, 3.2; Figure 1).

Perception of Oncology Care Landscape The cost of cancer drugs reportedly influenced prescribing decisions “quite a bit” or “a lot” for 28.1% of participants; patient out-of-pocket costs were said to influence prescribing decisions “quite a bit” or “a lot” for 48.5% (Figure 2). In addition, 37.7% of participants reported that payer reimbursement policies limited their ability to offer certain therapies to their patients “quite a bit” or “a lot.”

Overall, 26.8% and 22.1% of the respondents rated the use of cost-effectiveness and comparative effectiveness data, respectively, by payers for reimbursement decisions as negative or neither positive nor negative.

According to the survey results, the most pressing issues facing oncology care today are increasing costs of drug prices (69.3%), growing demand for cancer care services (56.7%), and cost and payer pressures (53.3%), provider burnout (38.1%), and anticipated workforce shortages (27.7%) (Table 2).

Support for Proposed New Payments Approximately half of the respondents “strongly” or “somewhat” supported the proposed payments in the PCOP (Figure 3).9 New Patient Treatment Planning payments were strongly or somewhat supported by 46.7%; Care Management During Treatment payments

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Figure 1 Factors Shaping Perceived Value of a New Cancer Drug n 1 - Most important 100% 90%

5.6% 6.9%

80%

13.9%

n 2

n 3

19.5%

n 4 - Least important

21.2% 53.6%

70% 34.2%

39.4%

60% 50% 40%

73.6%

19.5%

30%

38.5%

32.0%

20%

15.6%

10% 0%

Clinical efficacy

9.1%

6.1%

Impact on quality of life

Safety and tolerability

11.3% Costeffectiveness

Figure 2 Key Influences on Prescribing Decisions 60% “Quite a bit” or “a lot”

(10.8%), and CancerLinQ (2.6%); 13.0% stated that no quality-of-care metrics were used or “not sure” (Table 2).

Overall, 81.4% of respondents stated that their organization’s quality measurement and tracking procedures were “somewhat” or “highly” effective in terms of improving quality of care, outcomes, and cost-savings. On average, physicians reported that they followed the National Comprehensive Cancer Network guidelines/pathways for an average of 76.4% of their patients; 84.2% of their patients reportedly had documented clinical/pathologic staging before initiation of treatment (86.8% among non-ACO respondents vs 80.3% among ACO respondents; P = .0389). The use of at least 1 metric was more common among respondents participating than those not participating in an ACO (92.6% vs 83.2%; P = .0380). The use of patient satisfaction scores was more common among respondents using than those not using EHRs (62.4% vs 42.3%; P = .0482).

48.5%

50%

37.7%

40% 30%

28.1%

20% 10% 0%

Costs of cancer drugs influence prescribing decisions

Patient out-of-pocket Payer reimbursement drug costs influence policies have influenced prescribing decisions prescribing decisions

by 57.2%; Care Management During Active Monitoring payments by 54.5%; Transition of Treatment payments by 54.1%; and Participation in Clinical Trials payments by 74.9%. Support for the payments was stronger for respondents who rated the overall reimbursement climate as “excellent” or “good” than for those who rated it “satisfactory,” “not very good,” or “bad” (Figure 4).

Among those who rated the reimbursement climate as excellent or good (vs those who rated it otherwise), 55.1% supported New Patient Treatment Planning payments (vs 41.6%; P = .0452); 66.3% supported Care Management During Treatment payments (vs 51.4%; P = .0261); 65.2% supported Care Management During Active Monitoring payments (vs 47.9%; P = .0103); 60.7% supported Transition of Treatment payments (vs 50.0%; not significant); and 73.0% supported Participation in Clinical Tri-

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Support for ASCO’s Patient-Centered Oncology Figure 3 Overall Payment’s Proposed New Payments n S trongly oppose

n S omewhat

100% 17.8%

90% 80%

13.4%

70% 60%

n Neutral n S omewhat

oppose

n S trongly support

support

2.2% 2.2%

7.4%

8.7%

7.8% 5.7%

25.9%

32.0%

29.8%

8.2%

8.7%

20.7%

29.4%

22.1%

50% 40% 30%

32.8%

43.3%

38.5%

40.7% 45.5%

20% 10% 0%

13.9%

13.9%

16.0%

New patient payments

Treatment month payments

Active monitoring month payments

13.4% Transition Clinical trial of treatment payments paymentsa

Not included in the May 2015 revision of the proposed patientcentered oncology payment model.

a

Support for the Patient-Centered Oncology Payment’s Figure 4 Proposed New Payments, by Perception of Overall Reimbursement Climate Perception of overall reimbursement climate:

n E xcellent/good n S atisfactory/not very good/bad

“Strongly” or “somewhat” support

80%

73.0% 66.3%

70%

76.1%

65.2% 60.7%

60% 50%

55.1%

51.4%

50.0%

47.9%

41.6%

40% 30% 20% 10% 0%

New patient payments

Treatment month payments

Active monitoring month payments

Transition Clinical trial of treatment payments paymentsa

Not included in the May 2015 revision of the proposed patientcentered oncology payment model.

a

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als payments (vs 76.1%; not significant). Support for all proposed payments was marginally higher among respondents who rated the financial status of their organization’s cancer program as excellent or good compared with those who rated it as satisfactory, not very good, or bad; however, the difference was not significant.

Logistic regression analysis using backward elimination was performed to assess factors contributing to support (strongly/somewhat support vs neutral or strongly/ somewhat oppose) for each main payment type described in the reform proposal. The characteristics considered in this analysis are listed in the Appendix (see www.AHDBonline.com).

The logistic regression analysis showed that male respondents generally reported greater support for the new payments than female respondents, including New Patient Treatment Planning payments (odds ratio [OR], 2.4; P = .0259); Care Management During Treatment payments (OR, 3.6; P = .0010); Care Management During Active Monitoring payments (OR, 2.1; P = .0389); and Transition of Treatment payments (OR, 2.2; P = .0263).

Respondents having a contract with a commercial payer that reimburses for dispensed oral cancer drugs were more likely to support the proposed payment types than others, including New Patient Treatment Planning (OR, 2.6; P = .0006); Care Management During Treatment (OR, 1.9; P = .0388); Care Management During Active Monitoring (OR, 1.8; P = .0391); and Transition of Treatment (OR, 1.9; P = .0232).

Race (white vs nonwhite) was a significant factor for supporting payments for Care Management During Treatment (OR, 1.9; P = .0283) and Care Management During Active Monitoring (OR, 1.8; P = .0487). Respondents who practice in an academic/community hospital or VA facility were more likely than those in group/solo practice to support payments for Care Management During Treatment (OR, 2.0; P = .0216) and Participation in Clinical Trials (OR, 2.0; P = .0218). Respondents who use EHRs were more likely to support payments for Participation in Clinical Trials (OR, 2.4; P = .0466).

Support for Accountability for Quality of Care Accountability for delivering high-quality, evidence-based, patient-centered care, with payments slightly increasing or decreasing based on quality metrics, was supported by 74.9% of respondents. Respondents who practice in an academic, community, or VA hospital were twice as likely as those in group or solo private practice to support accountability for quality of care (81.3% vs 67.6%; OR, 2.1; P = .0176).

Value-based adjustments were supported by approximately 50% of the respondents. Specifically, 54.6% strongly or somewhat supported rating oncology practic-

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es based on the degree of collection and reporting key standard quality measures and performance against benchmarks; 52.4% strongly or somewhat supported rating oncology practices based on level of use of existing pathways and adherence to pathways over time; and 45.9% supported rating practices based on patients’ risk-adjusted rates of oncology-related emergency visits.

(Value-based adjustments were not included in the May 2015 revision of the PCOP.)

Qualitative Analysis At the end of the survey, respondents were asked to provide qualitative feedback on ASCO’s PCOP, including their overall thoughts, whether they disliked any components of the proposal and the reasons for this, and whether there are any areas for improvement. A thematic analysis of the qualitative responses was conducted to determine whether they responded generally positively, negatively, neutrally, had no opinion, or were unsure or needed more information on the overall proposed payment-reform policy and its different components.

Overall, 210 (90.9%) respondents provided qualitative feedback; 49.5% responded generally positively regarding the PCOP, 30.5% were unsure or neutral, and 20.0% felt generally negatively about the policy. The top reasons for feeling generally positively related to the proposal’s ability to control costs and to standardize measurements of quality of care in oncology. Some of these respondents felt that the proposal does not go far enough to rein in costs of drugs and imaging procedures, but generally thought that it is a step in the right direction.

The top reasons for a generally negative attitude toward the policy related to perceived lack of consideration of the complexity of treating individual patients, and lack of focus on reimbursement for diagnosis and initiating care for patients who continue their care with a different practice subsequently. Some respondents noted that the ASCO proposal could make it difficult to remain in private practice, or that it would affect patients’ ability to access newer treatments.

Discussion Our research reveals that support for the ASCO PCOP is generally mixed, with a greater level of support coming from oncologists who already consider the current reimbursement climate or the current financial status of their practice to be positive. However, nearly 75% of the respondents appeared to appreciate the need to be held accountable for delivering high-quality, evidence-based, patient-centered care. Despite such views, only approximately 50% of the sample supported value-based adjustments that involve rating practices based on their performance against benchmarks, adherence to

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treatment pathways, and risk-adjusted rates of oncology-related emergency visits. Thus, it is not surprising that these value-based ratings were removed from the 2015 version of the PCOP proposal.

Although more than 80% of respondents stated that the standard quality-of-care measures used by their oncology practice were somewhat or highly effective in improving quality of care, outcomes, and cost-savings, the established metrics for quality of care generally are underutilized. Patient satisfaction scores were not used consistently, even in sites without an EHR system, and more than 10% of respondents were not aware of any quality-of-care metrics used by their practice.

These findings reinforce the need for improving the evaluation of quality of care in oncology to strengthen care delivery and outcome evaluation. Various efforts may pave the way for better implementation and reporting of quality metrics, including the proliferation of ACOs; regulations set forth by the Centers for Medicare & Medicaid Services (CMS), which require ACOs to meet specific quality performance standards to participate in the Shared Savings Program; and interactions between ACOs’ quality reporting and other CMS initiatives, particularly the PQRS, Physician Value-Based Payment Modifier, and the EHR Incentive Program.11 These efforts may further influence the support for, and adoption of, effective payment reforms such as ASCO’s PCOP, which ties payment to performance.

However, for oncology practices that remain unaffiliated with ACOs, an appropriate incentive and support structure must be enacted to encourage adoption of relevant quality metrics and reporting among these practices.

Increasingly, oncology practices are burdened with administrative hurdles to providing quality care to cancer patients while maintaining the financial stability of their practice.2 This is supported by our respondents’ input on the key issues facing the future of oncology care in the United States, namely, cost and payer pressures; increasing drug prices; growing demand for cancer services; provider burnout; and workforce shortages.

Overall, 28% of respondents identified the cost of drugs as a key influence on their prescribing decisions. A similar proportion (27%) rated drug cost-effectiveness as “1” or “2” on a scale of 1 (most important) to 4 (least important) while rating the factors that constitute “value” for a new cancer drug; 48% of respondents reported patient out-of-pocket costs as another key factor influencing their prescribing decisions. These views are consistent with the ongoing debate on shifting more of the economic burden to patients.12-15 Empowering practices with up-to-date information on care modalities, clinical pathways, and payer reimbursement, while recognizing and compensating for the com-

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plexity of individualized oncology care delivery, may help sustain the viability of oncology practices in the United States, and community practices in particular. Finally, an optimal payment-reform model should address the diverse needs of provider stakeholders in the United States.

These results reflect mixed support for the proposal, underscoring the importance of continuous and broader engagement of practicing physicians from diverse settings around the country via outreach and dialogue on topics that affect their clinical practices.

Limitations Although the random sample of oncologists was from across the United States, encompassing academic and community-based practices, the oncologists who chose to respond to our survey may differ from those who did not.

An online survey has several limitations. Physicians who participate in online panels and complete online surveys tend to be young; 27% of respondents in this study were aged <40 years, whereas the 2014 oncology practice census data from ASCO reported only 16% of oncologists aged <40 years.16 In addition, compared with 2014 national averages of practice census data reported by ASCO,16 our study had a higher proportion of female respondents, oncologists who practice in an academic or university setting, and ACO participants.

Furthermore, ASCO membership status was not assessed in our study. It is possible that such affiliation could have influenced respondentsâ&#x20AC;&#x2122; perceptions of the ASCO payment reform proposal.

Conclusion Through this study, we attempted to describe the views of real-world practicing oncologists toward a payment reform proposal that would have implications on their daily practice. These results reflect mixed support for the proposal, underscoring the importance of continuous and broader engagement of practicing physicians from diverse settings around the country via outreach and dialogue on topics that affect their clinical practices, as well as educa-

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tion and awareness activities from ASCO and other policy-shaping organizations to their constituents. n Author Disclosure Statement The authors did not receive any financial support for this study. Mr Narayanan has received research grants from GlaxoSmithKline, Vertex, Sun, Celgene, Johnson & Johnson, Teva, and Bayer. Ms Hautamaki has received research grants from Vertex, Merck, Sun, Celgene, and GlaxoSmithKline.

References

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2. Zweigenhaft B, Bosserman L, Kenney JT Jr, et al. Defining value in cancer care: AVBCC 2013 Steering Committee report. Am Health Drug Benefits.

2013;6:236-246.

3. Ginsburg PB. Achieving health care cost containment through provider payment reform that engages patients and providers. Health Aff (Millwood).

2013;32:929-934.

4. Delisle DR. Big things come in bundled packages: implications of bundled payment systems in health care reimbursement reform. Am J Med Qual. 2013; 28:339-344.

5. Miller HD. From volume to value: better ways to pay for health care. Health Aff (Millwood). 2009;28:1418-1428.

6. Schnipper LE, Davidson NE, Wollins DS, et al; for the American Society of Clinical Oncology. American Society of Clinical Oncology statement: a conceptual framework to assess the value of cancer treatment options. J Clin Oncol.

2015;33:2563-2577.

7. Schnipper LE, Lyman GH, Blayney DW, et al. American Society of Clinical Oncology 2013 top five list in oncology. J Clin Oncol. 2013;31:4362-4370.

8. American Society of Clinical Oncology. Consolidated payments for oncology care: payment reform to support patient-centered care for cancer. May 2014. www.asco.org/sites/www.asco.org/files/consolidatedpaymentsforoncologycare_ public_comment_final_dk.pdf. Accessed August 28, 2015.

9. American Society of Clinical Oncology. Patient-centered oncology payment: payment reform to support higher quality, more affordable cancer care. May 2015. www.asco.org/sites/www.asco.org/files/asco_patient-centered_oncology_ payment_final_2.pdf. Accessed August 28, 2015.

10. Neumann PJ, Palmer JA, Nadler E, et al. Cancer therapy costs influence treatment: a national survey of oncologists. Health Aff (Millwood). 2010;29: 196-202.

11. Centers for Medicare & Medicaid Services. Quality measures, reporting and performance standards. www.cms.gov/Medicare/Medicare-Fee-for-Service-Pay ment/sharedsavingsprogram/Quality-Measures-Standards.html. Accessed January 26, 2016.

12. Tefferi A, Kantarjian H, Rajkumar SV, et al. In support of a patient-driven initiative and petition to lower the high price of cancer drugs. Mayo Clin Proc.

2015;90:996-1000.

13. Zirkelbach R. Focusing on only 1% of spending will not solve nationâ&#x20AC;&#x2122;s health care challenges. July 23, 2015. Catalyst. http://catalyst.phrma.org/focus ing-on-only-1-of-spending-will-not-solve-nations-health-care-challenges. Accessed April 16, 2016.

14. Dusetzina SB, Winn AN, Abel GA, et al. Cost sharing and adherence to tyrosine kinase inhibitors for patients with chronic myeloid leukemia. J Clin Oncol. 2014;32:306-311.

15. Bestvina CM, Zullig LL, Zafar SY. The implications of out-of-pocket cost of cancer treatment in the USA: a critical appraisal of the literature. Future Oncol.

2014;10:2189-2199. Erratum in: Future Oncol. 2015;11:544.

16. American Society of Clinical Oncology. The state of cancer care in America, 2015: a report by the American Society of Clinical Oncology. J Oncol Pract.

2015;11:79-113.

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STAKEHOLDER PERSPECTIVE

Implementing Payment Reform in Oncology: Benefits and Challenges

By Byron C. Scott, MD, MBA Associate Chief Medical Officer, Truven Health Analytics, an IBM Company, Chicago, IL

C

ancer continues to be a very high-profile disease and is the second leading cause of death in the United States.1 With the passage and implementation of the Affordable Care Act (ACA), all healthcare stakeholders—including patients, payers, and physicians who may be affected by any final payment reform implementation—have an increased focus on major diseases such as cancer. Clinical oncologists have also been monitoring the impact of the ACA. Narayanan and Hautamaki present a thorough review of oncologists’ and medical directors’ perspectives and support for the American Society of Clinical Oncology (ASCO) proposal for payment reform.2 PATIENTS: The most important stakeholder in any payment reform discussion is the patient. Every reader of this journal most likely knows a family member or friend who has been diagnosed with and received treatment for cancer. Because patients are the most important stakeholders and the ultimate payers in healthcare, any payment reform related to quality of care must address issues that affect the patient. This includes improving the quality of care and finding cost-effective treatment protocols, given the increasing cost of copays and deductibles for patients, especially those dealing with cancer. Even with the growing trend of addressing value in oncology, discussing patients’ perceived satisfaction with their care and well-being is critical to any quality measurement.

PAYERS: With the ever-rising cost of cancer care, payers have a significant interest in payment reform in oncology, because high-quality care and lower costs are their ultimate goals. As the US population ages, the

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federal government as a payer is becoming increasingly relevant in the Medicare population. For large employers, cancer care is becoming more important, because in addition to the aging population, people are remaining in the workforce longer and are deferring retirement to an older age. Unlike previous decades, with their employees spending extra years in the workforce, employers are currently being challenged by the increasing costs of cancer care.

PHYSICIANS: Although not an oncologist myself, during my 25-year career as an emergency physician caring for patients with cancer in the emergency department, I have had tremendous respect for clinical oncologists and their very challenging job. ASCO has a considerable responsibility in representing oncology as a specialty organization. With the push for value-based reimbursement, any quality-of-care metric must be designed to improve outcomes for patients based on evidence-based medicine, must ensure that oncologists are fairly reimbursed for the comprehensive care they provide during a patient’s treatment, and should not increase the workload of physicians. Recognizing the need to not create extra work for physicians is important, because the demand for oncologists will most likely continue into the foreseeable future, and we cannot afford to build barriers that could lead to physician labor shortages. n 1. Centers for Disease Control and Prevention National Center for Health Statistics. Leading causes of death. Updated April 27, 2016. www.cdc.gov/nchs/ fastats/leading-causes-of-death.htm. Accessed July 11, 2016.

2. Narayanan S, Hautamaki E. Oncologist support for consolidated payments for cancer care management in the United States. Am Health Drug Benefits. 2016; 9(4):280-289.

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