Placebos raise ethical quandaries, as highlighted by a PLOS ONE study published last summer. At their heart is the notion that placebos only work if patients are deceived as to what they really are (inert). However, another PLOS ONE study suggests that this may not be so.

To elicit views on physicians’ use of placebos, Felicity Bishop, Lizzi Aizlewood, and Alison Adams conducted eleven focus groups, collectively including 58 people residing in England (18 men, 40 women, 19-80 years old). Discussions centered on vignettes presented by the investigators in which placebos were variously prescribed to patients with either a serious or mild condition (terminal cancer or a cold) and with or without deception. The ensuing discussions raised the core ethical tension: should doctors tell the full truth about what placebos are when prescribing them (if at all), or is it OK for them to deceive patients in an attempt to maximize (positive) placebo effects?

This ethical tension rests on two beliefs: (1) To many, “placebo” means “ineffective.” And, (2) there is some benefit merely from thinking one is receiving an effective treatment, in the mere expectation of an effect. Therefore, should a physician disclose that she is prescribing a placebo to a patient holding these beliefs, they act to cancel each other out. One can’t think one is receiving an effective treatment if one is also told that one is receiving a “placebo,” synonymous with “ineffective.” (An exception arises if one disbelieves one’s physician, but that is probably rare among patients who actively seek treatment.)

The idea that the placebo effect can only be harnessed by physicians who deceive patients is an uncomfortable principle to endorse. Who wants to be deceived? On the other hand, there are circumstances in which employing the placebo effect is the best a physician can do to help a patient feel better (i.e., no other therapy would be more effective). Who doesn’t want to feel better?

Not surprisingly, people are torn between wanting to feel better (the consequentialist view) and wanting to preserve control over their care (respecting autonomy). Quotes from the focus groups highlight this tension:


“The point is do I get better? I don’t really care how it happens, to be honest.”

Respecting autonomy:

“I would be furious, I have to say, if I did go to the GP and wanted – needed medication and [...] then find afterwards that it had been a placebo, without my permission, I would want to sue, I would be so angry.”

A few situations dodge the consequentialist-autonomy dilemma. First, when placebos were viewed as ineffective, their use was judged unacceptable by focus group participants. Deception for snake oil and quackery is not OK. Second, some participants thought placebos were a less acceptable use of public and personal resources for minor conditions, like colds, that would resolve on their own. Third, offering placebos to children was viewed as more uniformly appropriate. It was acknowledged that parents do this all the time, with “magic kisses,” and the like. Finally, with informed consent, use of placebos in clinical trials was also felt to be appropriate.

Discussion also turned to the possibility of placebo prescribing without deception.

Some focus groups suggested that careful use of language might resolve the dilemma: if doctors are vague or tentative in how they describe placebos then they might be able to use them to elicit placebo effects without directly lying to patients. In other words, some participants suggested that careful wording (or ‘‘fudging’’ the truth) could be a way of avoiding ‘‘blatant’’ lies and thus rendering placebo-prescribing acceptable.

Could this, or even more straight-forward disclosure, ever work? A study by Ted Kaptchuk and colleagues suggest it’s possible. They conducted a three-week randomized controlled trial (RCT) comparing an open-label (no deception) placebo (N=31) to no-treatment controls (N=39) for patients with irritable bowel syndrome (IBS). The placebo nature of the “treatment” group was disclosed to patients by explaining that it was inactive (an inert substance) like a sugar pill. Further, patients were told that the placebo effect is powerful, that the body can respond to it, a positive attitude helps, and faithfully taking the placebo is critical.

Results after 21 days are summarized in the following figure. In brief, the investigators found statistically significant and clinically meaningful improvements in various measures of IBS symptoms in the open-label placebo group, relative to the no-treatment controls. (A separate study on depression also found encouraging but limited improvements from an open-label placebo.)

IBS placebo

What is unclear from this study is whether the placebo effect would have been even larger if it was closed-label (relying on deceit). However, the authors noted that their open-label placebo response was larger than typical closed-label placebo responses in other IBS studies.

Including use of medications for conditions for which they cannot help (e.g., antibiotics for viral infections), placebos are frequently prescribed. And prior work has found that patients, by and large, don’t mind, without much detail on how they think though the ethical dilemmas. The American Medical Association’s code of medical ethics advises that placebos be used only if a patient provides informed consent. This could put too much emphasis on autonomy if it completely ruins the placebo effect, under the presumption it relies on deceit.

But at least two studies, noted above, suggest we can have our autonomy and our placebo effect too. This is not enough work to convince me that’s generally true, but it’s an interesting possibility.

Austin B. Frakt, PhD, is a health economist with the Department of Veterans Affairs and an associate professor at Boston University’s School of Medicine and School of Public Health. He blogs about health economics and policy at The Incidental Economist and tweets at @afrakt. The views expressed in this post are that of the author and do not necessarily reflect the position of the Department of Veterans Affairs or Boston University.


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NHPC Day 1: At a Glance

by Lindsey Horan on February 9, 2015

The National Health Policy Conference, this year celebrating its 15th anniversary, covers the issues that will define the policy and practice agenda in 2015. Monday’s dynamic sessions revealed the intricacies and complexities of what Congress and the administration face in the year to come, but left panelists and attendees feeling optimistic about the role health services research and health services researchers could play in the policy debate.

Here, you will find a quick recap of some of the day’s sessions from AcademyHealth staff:

Administration’s Plenary on Health Policy Priorities: “The Reward is Worth the Work”

William Corr, Deputy Secretary of the United States Department of Health and Human Services, kicked off the 2015 National Health Policy Conference (NHPC), noting that it’s a historic time to work in the health care field. The transformation, he said, is due in large part to health services researchers, who are helping to create a foundation of research and knowledge for the administration to build upon and pave the path for advancement. Deputy Secretary Corr spent much of his session highlighting the progress made by the administration and states to move millions of Americans into health care coverage, while also noting there is still more work to be done:

“For the sake of our health, our wallets and our economy, we need to go further…We have a responsibility to lead.” He told attendees that the United States isn’t going to be able to fix the health care system unless we make it better and smarter, something in which individuals of all political parties and ideologies have a stake [and something we at AcademyHealth would say requires the contributions of health services research]. “We all have a stake in more access to quality, affordable health care,” said Corr, adding that there was a deep commitment to building on the current health care momentum and writing the next chapter.

Plenary: State Health Policy

With the second open enrollment period closing on February 16, states continue to experiment with new innovations to expand coverage and improve access, quality and cost. This session, moderated by Dan Crippen of the National Governors Association featured Rita Landgraf, Delaware Department of Health and Social Services; Nico Gomez, Oklahoma Health Care Authority; and Brian Neale, Office of the Governor, Indiana.

Speakers discussed varying initiatives to address state-specific challenges and expand coverage in Delaware, Oklahoma, and Indiana, and they agreed that there is a great opportunity for states to use innovations to improve coverage and access. Speakers also agreed on the need to bring all of the players to the table to discuss coverage, payment, and care delivery issues and to create a lean operation and avoid duplication of effort. Nico Gomez stated “…we need to use opportunities to bring everyone to the table to make changes.” 

Another important goal of state strategy that speakers discussed is empowering consumers. Landgraf giving consumers an ownership in health care so that they understand the value of health insurance and access. 

This session highlighted the important role that states have in creating innovations to address changes and expansions brought on by the Affordable Care Act and the idea that states should work together to share ideas, challenges, and solutions. Brian Neale summarized the approach by saying, “When states have the opportunity to work with one another to create best practices, everyone wins.” 

By leveraging multiple state resources, population health, the workforce, payers, employers, technology and more, participants believe that states can achieve success in expanding coverage and achieving the triple aim. Landgraf encouraged attendees to “look innovatively and leverage across the spectrum.”

Late Breaking Session: U.S. Health System Preparedness: Lessons from Ebola & Other Threats

Dr. Nicole Lurie, the Assistant Secretary of Preparedness at the U.S. Department of Health and Human Services moderated a panel on the recent Ebola outbreak and the state of the nation’s public health infrastructure. Dr. Lurie commented on the interconnectedness of the world and the crucial dependence on the efficiency and efficacy of the public health and health care system in order to combat public health threats. 

The recent outbreak exposed healthcare gaps in preparedness procedures and day-to-day infection control processes and begs the question, “what are the roles and responsibilities of the public health and health care system in confronting threats?” Dr. Michael Stoto of Georgetown University compared the Ebola response in New York and Dallas. He asserted that, while systemic breakdowns occurred in Dallas, New York City prepared its institutions, and was able to effectively treat an Ebola case and quarantine individuals who were exposed. 

Dr. Bryce Gartland, Emory University, provided remarks on the importance of adequate funding in order to sustain an appropriate state of readiness Additionally, the importance of communicating risk appropriately is key to the success of systemic response. 

Dr. Jeff Levi, Trust for America’s Health, tied the perspectives together by illustrating that policymakers ramp up resources after adverse events, which eventually dwindle, weakening the necessary infrastructure— including the public health workforce; response training and resources; and the ability of the healthcare system to treat. 

The ACA Punch List: Top 5 Things that Congress Needs to Fix in the ACA

The sentiment coming out of this Monday session is that the Affordable Care Act (ACA) is complicated—and panelists may argue even that is an understatement. Despite varying political ideologies and affiliations, panelists Joseph Antos, Sabrina Corlette, Jon Kingsdale, and Judith Solomon did have a common thread: a deep understanding of the health care system and how the ACA can affect it, noted moderator Timothy Jost.

Although there was some overlap between some panelists—one overlay being the dire need for the legislation’s simplification—viewpoints varied on which components were most important and in need of fixing. These ranged from eliminating surcharge rates based on tobacco use and providing plans with greater health incentives to cover more primary and chronic disease management pre-deductible (Sabrina Corlette, who focused solely on private market reform) to fixing the “family affordability glitch” (Judith Solomon) to computing different tax credits and eliminating extra plans “that serve to confuse” (Jon Kingsdale) to fixing the subsidies and eliminating the mandates (Joe Antos). Ultimately, Jost said, “Repealing the ACA is no more possible than removing the interstate highway system;” at this point, the question is how to amend it, and panelists gave members of  the audience much to think about in that respect. 

Lunch Plenary: Separating the Buzz from the Boon in Population Health

Elizabeth Bradley of Yale University and co-author of The American Health Care Paradox kicked off the luncheon plenary with a discussion on health care spending in the United States as compared to Scandinavian countries, and provided recommendations on what we can do to address the paradox. 

Bradley compared the ratio of health care spending to social services spending in the United States and in the OECD countries: from 2000-2009, for every one dollar spent on health care, the United States spends about 90 cents. For every one dollar spent on health care, OECD countries spend two dollars on social services. 

Countries with higher ratios of social to health spending have statistically better health outcomes. The difference, she suggested, can be attributed to history: in the United States, health care and social service sectors grew up from independently from one another and where as health care grew into a marketable commodity, social services were conceived of being “for the poor.” In Europe, the two sectors were knit together from the beginning.

To address this paradox, Dr. Bradley stressed the importance of debunking the popular American myth that health equals health care. By driving a culture shift on what drives health, separating health from health care, and incentivizing collaboration, we can begin to unravel the paradox of the U.S. health care system.

She highlighted the success of small, individual, champion-led programs, which led to improved outcomes for their populations and encouraged the mobilization of collaboration for health nationally. In addition, she called for common metrics for health care and social providers to measure public spending in order to report on results. 

Following her presentation, Dr. Bradley participated in a panel discussion with Chris Koller, Milbank Memorial Fund and Alan Weil, Health Affairs. Koller emphasized the importance of primary care in improving population health and bridging the gap between health and social services. Weil emphasized the need for new tools and pathways to build capacity for health care organizations to do community-based, population health work. 

Expanding the “Ownership” of the Social Determinants of Health

This session discussed the evolving nature of partnerships and new perspectives on the return on investment (ROI) for non-health sector investments in improving the social determinants of health, and the trans-disciplinary research required to continue to build the evidence base for action.

Dr. Ana Diez Roux, Drexel University, presented rationale for building the evidence base in order to understand the implications of social determinants of health. Dr. Diez Roux urged the audience to consider what place-based factors explain why individual characteristics related to health are spatially patterned.

Building on theme of “place matters,” Amy Gillman, Local Initiatives Support Corporation, presented the community development movementdriving investments to low-income communities to improve the quality of life for all residents. For example, in the Eastern North neighborhood of Philadelphia, an investment in several local programs e.g. a credit union, lead to a 12% reduction in poverty.

Dr. Eduardo Sanchez, American Heart Association, discussed the “upstream promotion of health” to improve the cardiovascular health of individuals, with critical attention to how an individual’s location affects their ability to establish heart-healthy behaviors.  Dr. Sanchez elucidated that low education level and racial segregation contribute as equally, if not more, as tobacco use to poor heart health.

Dr. Alonzo Plough, Robert Wood Johnson Foundation, moderated the session and lead with a call to action to all stakeholders to enable every member of society to make healthy choices through greater resource equity, in order to build a culture of health.  

HSR Impact Award Presentation

Day one of the NHPC ended with the presentation of the HSR Impact Award, an annual award presented to health services research that has made a clear impact on health policy and practice. This year’s award was presented to Jonathan P. Weiner, Dr. P.H., of The Johns Hopkins Bloomberg School of Public Health by Helen Burstin, chief scientific officer of The National Quality Forum, on behalf of his and his colleagues’ groundbreaking work on The Johns Hopkins ACG Case-Mix System.

This model has gained international acceptance as a standardized risk adjustment tool for health services and outcomes research. AcademyHealth congratulates Dr. Weiner and his colleagues on this well-deserved achievement.

Private Sector Health Care Transformation Plenary

Today’s final plenary examined how exactly private-sector payers, provider systems, and recent or new entrants into health care are reshaping the way care is delivered and financed.

Jeffrey Kang from Walgreens Co. discussed how his organization is responding to consumer needs through providing convenience, simplicity, and affordability. According to Kang, providing these characteristics lead to both a simple transactional relationship with a consumer and engagement in other health care channels such as digital health and chronic condition care services.

Innovative technology and technological assistance for both providers and consumers was a reoccurring theme during the plenary. David Notari of Innovation Health stated the importance of providing consumers with the tools necessary to compare prices and make firm decisions in the health care market place, an important factor in achieving better health, higher quality and lower costs. Aparna Higgins, AHIP, further built on this theme by explaining that giving providers data on patients is critical to helping them better manage their practices as well as exchanging health information through access to online portals.

This session was moderated by Susan Dentzer from the Robert Wood Johnson Foundation. 

Adjunct Meetings and Day Two 

This evening’s adjunct meetings include:

  • Student Networking Event
    6:30-8:30 p.m. | President’s Sports Bar & Grill | Renaissance Washington, D.C. Downtown Hotel
  • Disparities Interest Group Networking Happy Hour
    7:00-8:30 p.m. | Penn Quarter | Renaissance Washington, D.C. Downtown Hotel

Tomorrow morning’s adjunct meetings include:

We will update this post with links to presentations as they become available. In the meantime, we hope you enjoy your second day of the NHPC. Be sure to follow us and add to the conversation on Twitter @AcademyHealth, #nhpc15.


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Paying for quality, not quantity is getting to be almost cliche. Recently, the Obama administration doubled down, however, announcing ambitious targets for Medicare payments to be “tied to” quality in the future. Unfortunately, the evidence behind such programs working continues to elude us. This week, two studies were published in JAMA that add to my skepticism. The first, “Association of Hospital Participation in a Quality Reporting Program With Surgical Outcomes and Expenditures for Medicare Beneficiaries“:

Importance  The American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) provides feedback to hospitals on risk-adjusted outcomes. It is not known if participation in the program improves outcomes and reduces costs relative to nonparticipating hospitals.

Objective  To evaluate the association of enrollment and participation in the ACS NSQIP with outcomes and Medicare payments compared with control hospitals that did not participate in the program.

Design, Setting, and Participants  Quasi-experimental study using national Medicare data (2003-2012) for a total of 1?226?479 patients undergoing general and vascular surgery at 263 hospitals participating in ACS NSQIP and 526 nonparticipating hospitals. A difference-in-differences analytic approach was used to evaluate whether participation in ACS NSQIP was associated with improved outcomes and reduced Medicare payments compared with nonparticipating hospitals that were otherwise similar. Control hospitals were selected using propensity score matching (2 control hospitals for each ACS NSQIP hospital).

Main Outcomes and Measures  Thirty-day mortality, serious complications (eg, pneumonia, myocardial infarction, or acute renal failure and a length of stay >75th percentile), reoperation, and readmission within 30 days. Hospital costs were assessed using price-standardized Medicare payments during hospitalization and 30 days after discharge.

Researchers looked at a decade of data for hundreds of hospitals which did (and did not) participate in the American College of Surgeons National Surgical Quality Improvement Program. Specifically, they looked at whether 30-day mortality, complications, and readmission changed in participating hospitals. They looked at costs as well.

After controlling for patient factors and secular trends, they found no differences at all in outcomes before enrollment, and 1, 2, and 3 years after enrollment. No difference in 30-day mortality (4.5% before, 4.3% after. No difference in complications (11.0% before, 11.1% after). No difference in readmissions (12.8% before, 13.3% after). Mean total Medicare payments didn’t change either.

Some surgical outcomes did improve over the study, but these occurred in all hospitals, even those not in the program. It appears that the quality-based feedback didn’t make a difference.

The second study, “Association of Hospital Participation in a Surgical Outcomes Monitoring Program With Inpatient Complications and Mortality“:

Importance  Programs that analyze and report rates of surgical complications are an increasing focus of quality improvement efforts. The most comprehensive tool currently used for outcomes monitoring in the United States is the American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP).

Objective  To compare surgical outcomes experienced by patients treated at hospitals that did vs did not participate in the NSQIP.

Design, Setting, and Participants  Data from the University HealthSystem Consortium from January 2009 to July 2013 were used to identify elective hospitalizations representing a broad spectrum of elective general/vascular operations in the United States. Data on hospital participation in the NSQIP were obtained through review of semiannual reports published by the ACS. Hospitalizations at any hospital that discontinued or initiated participation in the NSQIP during the study period were excluded after the date on which that hospital’s status changed. A difference-in-differences approach was used to model the association between hospital-based participation in NSQIP and changes in rates of postoperative outcomes over time.

Exposure  Hospital participation in the NSQIP.

Main Outcomes and Measures  Risk-adjusted rates of any complications, serious complications, and mortality during a hospitalization for elective general/vascular surgery.

This study looked at surgical outcomes at hospitals also participating, and not participating, in this program. Specifically, they looked at elective surgery to look at rates of complications and mortality from 2009 to 2013. More than 100 hospitals took part, with more than 345,000 hospitalizations. The most common procedures were hernia repairs, bariatric surgery, mastectomy, and cholecystectomy. After controlling for other factors, once again there were no differences between hospitals in the quality programs and those out of them with respect to complications, serious complications, or mortality.

From the accompanying editorial:

The most likely explanation for the findings of these 2 studies is that end-results information, although necessary for improvement, is not sufficient, and that the skills necessary to make effective changes in processes and cultures do not yet pervade US hospitals, to say the least. Both research groups speculate about that as a reason for their results. As Osborne et al suggest, “Changing physician practice requires complex, sustained, multifaceted interventions, and most hospitals may not have the expertise or resources to launch these effective quality improvement interventions.”

I agree. I’ve said so before, and I’ll say it again. I think the problem with our quality metrics is that we use the ones that are easy to measure, not the ones that “matter”. Getting information is also just the first step. Using it to change behavior and practice requires infrastructure, time, and money. We routinely underestimate how much more than just “data” is necessary. As long as we continue to do so, I fear many of the announcements we see about “paying for quality, not quantity” will amount to sound and fury.



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The Ebola epidemic is a stark reminder that the United States needs a multi-pronged strategy to ensure vigilance and capacity to respond to all health threats. A late-breaking session, “U.S. Health System Preparedness: Lessons from Ebola & Other Threats” has been added to the 2015 National Health Policy Conference agenda for February 9 at 11:00 a.m. ET. The session will be moderated by Dr. Nicole Lurie, Assistant Secretary of Preparedness and Response, U.S. Department of Health and Human Services. On site registration is still available.

On November 3, 2014 the Institute of Medicine in partnership with the National Academy of Science convened experts and stakeholders for Research Priorities to Inform Public Health and Medical Practice for Domestic Ebola Virus Disease (EVD): A Workshop. AcademyHealth research assistant Danielle Robbio prepared the following reaction to the event.


The recent epidemic of Ebola has thrust public health preparedness back into the spotlight. The disease has spread rapidly and dangerously across West Africa (Guiena, Liberia, Sierra Leone, Nigeria and Senegal) and cases have been confirmed in the United States. As media attention and scrutiny dies down, the opportunity exists to examine the three core functions of public health (i.e., assessment, policy development, and assurance). The field of health services research, and its sub-discipline, public health services and systems research (PHSR), is positioned to address the systems-level challenges posed by this unique threat. PHSR investigates the public health system’s organizational structure, financing, and processes, and could point to strategies for addressing the spread and treatment of a transnational disease, as well as chronic threats to America’s health.

The 2014 IOM workshop  convened experts from all arenas—virologists, wildlife specialists, public health officials and physicians—in order to identify research priorities to prevent further spread and future outbreaks. (Read the full brief here.) In kicking off the event, Dr. Lurie noted “We do believe that it’s possible to help to foster research during a response to inform practice and also to ensure that guidance in the future is based on the most current and best available science and to make sure that data are gathered before they are lost.”

(For more on the importance of studying real-time events, and methodological considerations for researching public health emergency preparedness system capacities, see:Getting from What to Why: Using Qualitative Methods in Public Health Systems Research)

Ultimately, this outbreak has sparked a nationwide re-examination of the unique role of governmental public health. How will the public health system respond to a transnational disease outbreak? How should it respond? And, more broadly, how should the public health infrastructure adapt to meet new population health challenges?

Given this increased scrutiny, the field of PHSR has the opportunity to revisit the three core functions of public health and address the systems issues raised in the workshop i.e., impact of Ebola on healthcare settings and procedures, household and mass transit risks, and vulnerabilities in the health care safety net. PHSR provides evidence that practitioners need to answer these questions, evaluate successes, identify best practices, and most important, learn from failures.


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Use and abuse of opioid medications and attendant problems have grown tremendously since the late 1990s or so, fueling a quadrupling of deaths from opioid pain relievers between 1999 and 2010. Well aware of the growing problem, state governments and federal agencies have attempted a range of remedies. A recent, NEJM-published study by Richard Dart and colleagues offers evidence that they may have helped, in a way, but may have also encouraged a shift from painkiller use to heroin.

Attempts to address the opioid painkiller abuse epidemic are numerous. Some examples include:

Many other state laws regulating access to and dispensing of opioid painkillers are found at this CDC page.

Perhaps the increased attention to the opioid problem is penetrating clinical practice. Catherine Hwang and colleagues published results in JAMA Internal Medicine of a survey of 420 primary care physicians, examining their attitudes and perceptions of use and abuse of prescription drugs. The vast majority (85-90%) reported that drug abuse is a “big” or “moderate” problem and that opioids are over-prescribed. Yet, nearly half said they were prescribing them less than one year ago.

Richard Dart and colleagues used the collection of data sources that comprise the Researched Abuse, Diversion, and Addiction-Related Surveillance (RADARS) System to assess use and abuse of opioid painkillers from January 2002 through December 2013. They also obtained measures of heroin use from the National Poison Data System and the National Survey on Drug Use and Health, prescription volume from IMS Health, and population data from the 2000 and 2010 U.S. Census.

The authors found that prescriptions of opioid painkillers grew from 47 million in first quarter of 2006 to 62 million in the fourth quarter of 2012. However, since then, prescriptions dispensed has trended downward to 60 million in the final quarter of 2014. Provided this recent downward trend of prescriptions written isn’t adversely affecting those for whom use for pain would be appropriate, this is good news. Overuse may still exist, but its growth may have abated.

opioid prescriptions

One notable exception to the trend suggested in the chart above is from the College Survey Program. The authors’ analysis of that data set found that the rate of nonmedical opioid painkiller use increased from 0.14 per 100,000 college students in 2008 to 0.35 by the end of 2013.

As prescriptions for opioid painkillers have leveled off, heroin use has increased. For example, data from the National Poison Data System show that the rate of heroin use accelerated in late 2010. At the same time, abuse of extended-release OxyContin decreased. Other data sources included in the RADARS are consistent with these findings, with the notable exception of the College Survey Program.

abuse rate

It is possible that those who would have otherwise abused OxyContin switched to heroin. But it’s also possible some of them used other opioid painkillers not shown in the chart above. However, death rate evidence suggests a more systemic substitution of heroin for opioid painkillers since 2010. Opioid painkiller deaths increased from 2002-2006, plateaued, and then decreased from 2009-2013. In contrast, heroin deaths were flat until 2010, and then increased.

The forgoing evidence suggests that policy interventions may have had their intended impact, though we can’t prove that. The authors wrote, for instance, that “studies show that the introduction of a less desirable formulation of oxycodone can rapidly decrease demand for that formulation.” At the same time, they may have encouraged substitution of heroin for opioid painkillers, which certainly is not their intent. “[I]t seems likely that the reformulation of extended-release oxycodone in 2010 has contributed to the increase in reported heroin use,” the authors wrote.

Whether it’s heroin or painkillers, we’re still in the midst of an opioid epidemic. Policy interventions may be helping, but the myriad sources for opioids, as well as accommodations for appropriate use, complicates efforts to address the problems they create.

Austin B. Frakt, PhD, is a health economist with the Department of Veterans Affairs and an associate professor at Boston University’s School of Medicine and School of Public Health. He blogs about health economics and policy at The Incidental Economist and tweets at @afrakt. The views expressed in this post are that of the author and do not necessarily reflect the position of the Department of Veterans Affairs or Boston University.


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The Common Rule is undoubtedly one of the most significant governing documents in research today, with jurisdiction over human research subjects and Institutional Review Boards, or IRBs. Human subjects research protections and relating policies are critical to the public good, and have the potential to dramatically impact the conduct of research. As such, they are of the utmost importance to AcademyHealth and its members. In late 2014, two different comment opportunities surfaced that had the potential to affect human subjects research, and AcademyHealth had a responsibility to respond on behalf of the field.

Disclosing Reasonably Foreseeable Risks in Research Evaluating Standards of Care

In October, the Office for Human Research Protections (OHRP) announced the invitation of public comments on its Draft Guidance on Disclosing Reasonably Foreseeable Risks in Research Evaluating Standards of Care. Within the draft guidance, OHRP specifically addressed what risks to subjects are presented by research evaluating standards of care, and which of these risks are reasonably foreseeable and should be disclosed to prospective research subjects as part of their informed consent.

As written, AcademyHealth felt the guidelines would have a negative effect—both on the ability to develop critically needed knowledge and on the likelihood of patients enrolling in studies that would provide them with more information on risks and benefits than they currently receive as part of routine care. There is important work being done to clarify public attitudes on consent in this type of research, and if OHRP were to implement this draft, the participation of those patients representative of the intended target population could be jeopardized.

The full set of comments can be found here.

Use of a Single Institutional Review Board for Multi-Site Research

In December the National Institutes of Health (NIH) released a request for comments on the Draft NIH Policy on the Use of a Single Institutional Review Board for Multi-Site Research.

AcademyHealth believes the proposed revision from NIH will speed the initiation of studies by reducing administrative burdens to scientific innovation and progress while simultaneously assuring the rigorous and potentially enhanced protection of human subjects.

The full set of comments can be found here.

AcademyHealth continues to monitor for comment opportunities that would advance our field, promote the interests of our members, and ultimately contribute to the improvement of health and health care. Continue to monitor our work through the AcademyHealth blog and on the advocacy portion of our website.


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As I posted previously, many studies have pointed to technology as a principal driver of health care spending growth. Those studies also credit third party payment (i.e., insurance) and income for some of the blame too. More interesting, coverage, income, and technology interact; their intersection is explored in a few papers summarized below.

The 2009 paper in Health Affairs by Shelia Smith, Joseph Newhouse, and Mark Freeland is one of the sources for the chart above. (See this post for additional detail.) In it, the authors note that “interrelationships among technology, income, and insurance are strong,” which makes “it difficult to assign specific quantitative magnitudes to each factor.”

There’s an obvious way in which insurance and income interact with health care technology: they broaden financial access to it. Income does so directly. The more money you have the more you can buy. Insurance does so by spreading technology’s cost across individuals, not all of whom require access to the same types and amount of it at the same time (or in the same year). Insurance has an income effect.

There’s a more subtle way insurance and income interact with technology. Smith et al. put their finger on it. “[T]he rate of technological innovation is influenced by the size of the market, which in turn is influenced by income and insurance.” The size of the market is influenced by insurance in three ways: (1) The absolute or relative size of the population covered, (2) the level of coverage insured people tend to have, and (3) the manner in which insurers (public or private) pay providers.

Burton Weisbrod’s fascinating 1991 paper, “The Health Care Quadrilemma,” may have been the first to deeply contemplate the insurance-technology nexus. In it, he explained “how the expansion of health insurance has paid for the development of cost-increasing technologies, and how the new technologies have expanded demand for insurance.” Weisbrod recognized that the key linkage is the research and development (R&D) process:

(1) The amount of resources going into the R&D process, and its direction, during some time interval, depend in part on the mechanisms expected to be used to finance the provision of health care in future periods, when the fruits of the research process become marketable. This is simply to say that R&D is influenced by expected utilization, which depends on the insurance system. Reciprocally, (2) the demand for health care insurance depends, in part, on the state of technology, which reflects R&D in prior periods. These relationships help to explain why (3) long-run growth of health care expenditures is a by-product of the interaction of the R&D process with the health care insurance system.

Though I want to focus principally on how insurance affects R&D, Weisbrod also discussed the reverse direction: how R&D affects insurance. For example, he pointed to advances in fertilization technology that increased demand for coverage of it. In 1988, five states mandated coverage of certain fertilization technology. Just one year later, that number was up to nine; today it’s 15. More generally, Weisbrod argued that health care technology that increases the mean and variance of health care expenditures tend to increase demand for insurance.

Coverage affects R&D by changing how providers are paid. Pressures to contain cost, as codified by new payment systems (e.g., bundled payments, ACOs) can affect R&D by shaping the medical market differently from prior payment systems. Retrospective payment, Weisbrod argues, sends the message, “Develop new technologies that enhance the quality of care, regardless of the effects on cost.” Prospective (whether bundled or capitated, though to different degrees) payment sends the message, “Develop new technologies that reduce costs, provided that quality does not suffer too much.” (Italics original in both cases.)

Note that cost reduction in the latter case is from the perspective of the provider, not society. The sense of cost reduction pressure is different under bundled payments (lower per episode costs, but not fewer episodes) than under annual capitation (lower overall costs, but only within the year). As the CBO pointed out, “Even when technological innovation leads to a decline in the cost of a given service, net spending rises if the use of services increases sufficiently.”

Examples of how coverage and payment shaped technology can be found in a number of studies, including Weisbrod’s:

  • When Medicare dialysis reimbursement was capped, newly developed equipment cut session time in half, saving labor costs (Weisbrod).
  • When chochlear implants became less profitable after “application of the DRG-pricing system [t]he 3M Company, the manufacturer of the first FDA-approved single-channel cochlear implant model, halted research” on a more advanced model (Weisbrod).
  • Prospective pricing has increased the expected profitability of drugs that can substitute for more costly treatments (e.g., beta blockers instead of coronary bypass surgery and cimetidine instead of ulcer surgery) (Weisbrod).
  • Policies by the CDC and Medicare in the early 1990s that increased coverage and use of certain vaccines, and a vaccine injury fund introduced in 1986 that protected manufacturers from lawsuits, encouraged 2.5 times more new vaccine clinical trials per year for each affected disease (Finkelstein).
  • The introduction of Medicare and Medicaid are associated with 40-50% more US-based medical equipment patenting, relative to other US patenting and foreign medical equipment patenting (Clemens).
  • Implementation of Medicare’s drug benefit is associated with increases in preclinical testing and clinical trials for drug classes most likely affected by the policy (Blume-Kohout and Sood).
  • Lower reimbursement by Medicaid programs for the care of pregnant women is associated with slower NICU adoption (Freedman, Lin, and Simon).

The basic point is the size of the market for technology with different characteristics is influenced by coverage. And, as Daron Acemoglu and Joshua Linn showed, market size matters. They exploited changing U.S. demographics (principally aging) to show that a 1% increase in a drug category’s potential market size leads to a 6% increase in number of new drug entry in that category (4% brand and 2% generic). Their findings suggest that pharmaceutical R&D anticipates changes in market by 10-20 years, reflecting the time it takes to develop and bring a new drug to market.

Today, coverage is increasing, and changing in generosity. Payment systems are in flux. Though the existing research is hardly rich enough to permit us to make precise predictions about what these changes will do, we can be confident they are shaping the future of health care technology.

(See also related, largely theoretical, work by Garber, Jones, and Romer and Baumgardner.)

Austin B. Frakt, PhD, is a health economist with the Department of Veterans Affairs and an associate professor at Boston University’s School of Medicine and School of Public Health. He blogs about health economics and policy at The Incidental Economist and tweets at @afrakt. The views expressed in this post are that of the author and do not necessarily reflect the position of the Department of Veterans Affairs or Boston University.


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One of the main points of the Affordable Care Act was to make sure that people with chronic conditions could not be discriminated against. For many, many years, people who had medical problems had difficulty getting insured, and if they could, policies could cost exorbitant amounts of money. This isn’t because insurance companies were evil. It’s because their business model forced them to individually rate plans. Someone who had a chronic condition would be much more expensive to care for, and a bad bet as a customer.

But the ACA forced plans to be sold with community ratings. No longer could insurance companies ask about your medical history before offering you a plan. They could only ask your age, if you smoke, where you live, and whether or not you wanted to insure just you, or your family.

As I’ve discussed before at the Incidental Economist, though, insurance companies are very, very good at what they do. These same rules apply to Medicare Advantage plans, and those plans have still sometimes managed to find ways to attract more healthy customers and dissuade less healthy ones.

A recent NEJM Perspective piece argues that this same thing might be going on under the ACA:

There is evidence, however, that insurers are resorting to other tactics to dissuade high-cost patients from enrolling. A formal complaint submitted to the Department of Health and Human Services (HHS) in May 2014 contended that Florida insurers offering plans through the new federal marketplace (exchange) had structured their drug formularies to discourage people with human immunodeficiency virus (HIV) infection from selecting their plans. These insurers categorized all HIV drugs, including generics, in the tier with the highest cost sharing.

The complaint alleges that insurance companies in some states are structuring their drug formularies in such a way as to discourage patients with HIV from signing up. There’s no argument that patients with HIV can be expensive. Therefore, discouraging them as customers can be a financial plus. The authors of the NEJM piece performed a little experiment:

To explore the implications of this practice, we analyzed adverse tiering in 12 states using the federal marketplace: 6 states with insurers mentioned in the HHS complaint (Delaware, Florida, Louisiana, Michigan, South Carolina, and Utah) and the 6 most populous states without any of those insurers (Illinois, New Jersey, Ohio, Pennsylvania, Texas, and Virginia; for details, see the Supplementary Appendix, available with the full text of this article at We examined the plans with the lowest, second-lowest, median, and highest premiums on the “silver” level in each state, analyzing formularies and benefit summaries to assess cost sharing for nucleoside reverse-transcriptase inhibitors (NRTIs), one of the most commonly prescribed classes of HIV medications. We chose this example because HIV is associated with high insurance costs, requires lifelong treatment, and is treated with an expensive and disease-specific class of medications. We defined adverse tiering as placement of all NRTIs in tiers with a coinsurance or copayment level of at least 30%. In estimating enrollees’ average annual medication costs, we used the negotiated drug price paid by Humana, which makes its prices available online.

Basically, they looked at plans offered in the exchanges to see whether they made certain commonly used medications for HIV expensive for beneficiaries due to increased co-pays or co-insurance. They found that enrollees in adverse tiered plans had a yearly cost per drug that was almost $4900, versus about $1600 in non-adverse tiered plans. About half of the adverse tiered plans had a deductible that was drug specific, compared to fewer than 20% of other plans.

Bottom line, someone with HIV would pay more than $3000 a year in a adverse tiered plan versus another plan.

If you’re an insurance company, it is good business to cover healthier people and have other companies cover sicker ones. If they can’t individually rate, they may find other means try and preferentially attract and repel certain customers. Future regulations can help ensure this doesn’t happen. Medicare D, for instance, designates some classes of drugs as “protected” and mandates that patients have access to them in all plans.  Other options can be considered as well.

One of the most popular, and most successful, components of the ACA was to make health insurance and care more accessible to those with chronic conditions. We need to make sure that continues, policymakers may need to shore up holes that remain in the law.



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I’ve written favorably about reference pricing in the past. But it’s important to be forthcoming about its limitations, or those of any payment strategy. Several recent publications, which I summarize below, highlight some of ways reference pricing could fall short.

First, let’s review what reference pricing is and what it can do. In a post on The Incidental EconomistNicholas Bagley and I briefly explained,

With reference pricing, insurers set the price they’re willing to pay for a given service or procedure, typically pegging it to a price at which it can be obtained at good quality—the reference price. A policyholder can then obtain that service or procedure at zero out-of-pocket cost at any provider willing to match that price. For providers that charge more, the policyholder—not the insurer—pays the difference.

You’ll find more discussion of reference pricing in the JAMA Surgery Viewpoint by Terry Shih and Justin Dimick, who add some of the history. A reference pricing drug “program was first implemented in Germany in 1989 and has been widely adopted in many European countries, Canada, and New Zealand.” They wrote that Safeway has implemented reference pricing for colonoscopy, laboratory and imaging tests, arthroscopy, herniorrhaphy, cholecystectomy, and cardiac catheterization.

In a prior post on this blog, I reported on some encouraging results from a study of reference pricing. The California Public Employees’ Retirement System (CalPERS) and its enrollees saved $3.1 million in 2011 by using reference pricing for knee and hip replacement surgery.

Before implementation of reference pricing by CalPERS, roughly an equal share of patients chose low- and high-price hospitals for knee or hip replacement surgery. [... After reference pricing, a]lmost 65% chose low-price hospitals and 35% high price hospitals by 2012. [In addition,] CalPERS high-price hospitals dramatically lowered their prices.

CalPERS’ achievement of savings was a function of the degree of competition in the market: patients had choices about where to receive knee and hip replacement surgery. Crucially, such choice is only meaningful when it is sufficiently abundant and patients are aware of price and quality differences among providers, as Uwe Reinhardt recently noted.

[G]reater transparency about prices and quality in health care are not helpful if the relevant market for health care is monopolized. Transparency can promote savings and encourage better quality only if there are enough competing entities that provide health care in a market. It is a point that is sometimes overlooked but is an essential ingredient for patients to benefit from knowing the price and quality of the health care services they purchase.

Reference pricing is different from network contracting in this way. For the latter, the insurer makes a judgement about price and quality, including in its covered network only providers that meet its criteria. So only the insurer need know about prices and quality. In the former, it’s patients that decide, so it is paramount that they have access to price and quality information.

Though reference pricing and network contracting are different, one would expect a similar price dynamic in a sufficiently competitive market. If offering lower prices and better quality is required to obtain a contract with an insurer who can deliver high volume (like CalPERS), provider organizations will tend to respond in much the same way to network contracting as they do to reference pricing: reducing prices and increasing quality to secure greater volume. For the Federal Trade Commission, Keith Brand, Christopher Garmon, and Martin Gaynor made this point.

We believe there is little difference between the price reduction and quality improvement incentives associated with narrow network health plans compared with reference pricing health plans. A health insurer could create a narrow network plan to give providers an incentive to reduce their prices and improve their quality in exchange for inclusion in the network and the increased patient utilization associated with this inclusion. Alternatively, the health insurer could create a reference pricing health plan and set a relatively low reference price that would mimic the incentives and utilization of the narrow network plan. The only difference between the two plans is that, in the former, providers compete in price and quality to be included in the network, while in the latter, providers compete directly for the patients.

They go on,

Lost in the discussion is the possibility that some patients may prefer to delegate the responsibility for selecting low-price, high-quality providers to their insurance company instead of shouldering the burden of evaluating the relative price and quality of various providers.

This is a good point, though it doesn’t suggest which arrangement is better. To the extent there is heterogeneity of preferences, there’s a role for both reference pricing and network contracting.

Finally, Chapin White and Megan Eguchi analyzed the potential savings from reference pricing based on data from 528,000 active and retired nonelderly autoworkers and their families in 19 midwestern markets.

If reference pricing were applied to a [broad] set of so-called “shoppable” inpatient and ambulatory services [those that can be scheduled in advance at more than one provider and with available price data], potential savings would be [] roughly 5 percent of total spending.

The authors consider this “modest,” and it is relative to the typical benchmark of 30% of health care spending for which we receive no value. However, it’s very unlikely we’ll ever find and agree to implement a single (or just a few) reforms that add up to 30% savings. In that context, a handful of reforms, each of which trims a few percentage points is a more realistic goal. In my view, something like 5% savings from reference pricing is enough to warrant attention.

Reference pricing, like every reform idea or payment system, has strengths and limitations. We should acknowledge both.

Austin B. Frakt, PhD, is a health economist with the Department of Veterans Affairs and an associate professor at Boston University’s School of Medicine and School of Public Health. He blogs about health economics and policy at The Incidental Economist and tweets at @afrakt. The views expressed in this post are that of the author and do not necessarily reflect the position of the Department of Veterans Affairs or Boston University.


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Although we often focus on the Affordable Care Act’s Medicaid expansion and insurance exchanges, it’s important to remember that the majority of people in the United States still get their coverage from employer sponsored health insurance.

To put things in perspective, it’s worth remembering that less than 7 million people, or 2% of Americans, are covered by insurance exchange plans. Even when we hit the CBO projected 25 million people in a few years, that’s still less than 10% of nonelderly people in the United States.

Employer sponsored plans, however, cover more than 150 million people, or almost 60% of the non-elderly US population. They shouldn’t be forgotten when we discuss what’s happening with spending and reform. Recently, the Commonwealth Fund published a report which allows us to discuss what’s going on with such insurance – “National Trends in the Cost of Employer Health Insurance Coverage, 2003-2013”.

Confirming what we’ve seen from Kaiser Family Foundation data, the average family plan cost (in premiums) more than $16,000 in 2013, up 73% from 2003. Single coverage cost, on average, more than $5500, and has gone up 60%.

Many predicted that the regulations that forced family plans to start allowing children to stay on them until age 27 would force premiums to go up more than normal. But, along with overall health care spending, premiums have risen more slowly on average since the ACA was passed (4.1% per year) than before it was passed (5.1% per year). In the last few years, plans at large firms grew more slowly than those at small firms (4.0% versus 4.3%).

A concerning trend, however, has been that even though premiums have been increasing more slowly than before, they are still increased faster than family income. Remember that premiums rose 73% for families in the decade 2003-2013. In that same time period, median family income only rose 16%. That means that while premiums cost families only 15% of their income in 2003, they cost families 23% in 2013.

While most economists would argue that, in the end, employees bear the full costs of their insurance plans, the direct contributions of employees have only increased as well. In 2003, employees contributed 17% of their premium costs; in 2013, this rose to 21%. Such contributions rose from 2% of income to 4% of income over that period.

I recently wrote about underinsurance over at The Upshot, and the contributions that higher deductibles play in that discussion. Even in employer sponsored plans, that applies. Deductibles more than doubled from 2003 to 2013. In fact, in 2003, just over half of employer sponsored plans had a deductible at all. In 2013, that number had risen to more than 80%. The deductible for a family in a small firm averaged $3761 in 2013. In a large firm, it was still $2307.

In 2013, the average deductible for a single person plan was 5% of median income. That’s the definition of underinsurance. That means the average person getting an individual plan from an employer in 2013 was underinsured.

That’s on top of premiums, and also doesn’t include other forms of cost-sharing like copays and co-insurance.

There’s a lot of good news in the reports of recent health care spending slowdowns. There’s also good news in the reduction of the number of Americans who are uninsured. But we shouldn’t neglect the majority of Americans who get their coverage through employer sponsored plans. Many, if not most, are still exposed to large out of pocket spending, and they’re paying a lot of money in premiums. There’s still a lot of work to do to get this under control.



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