On Thursday, July 24, the Senate appropriations subcommittee with jurisdiction over health research funding released its draft appropriations legislation for fiscal year (FY) 2015. Health services research fared well in the draft bill, in which the subcommittee proposed increases for the National Institutes of Health (NIH), the Agency for Healthcare Research and Quality (AHRQ), and the Centers for Disease Control and Prevention (CDC). Yet, though the legislation looks promising–all things considered–its potential to ever see the light of a vote does not.

Within the bill, the Labor, Health and Human Services, Education and Related Agencies Subcommittee provides details on what should be funded, at what level, and how. Some important notes that are relevant to health services research include:

  • AHRQ Budget Authority. AHRQ has historically been funded through what is essentially a “tap” on other health agencies’ budgets, making the agency vulnerable as the fiscal belt has tightened and as lawmakers have sought to fund other pressing priorities. The Senate subcommittee would, for the first time in decades, provide AHRQ with its own budget authority, providing significant stability for the agency. AcademyHealth, through the leadership of the Friends of AHRQ and the Friends of NCHS (the National Center for Health Statistics) coalitions, initiated the “Mind the Tap” campaign to educate lawmakers and staff about the evaluation tap and the important work funded by it, including AHRQ, NCHS, the Assistant Secretary for Planning and Evaluation (ASPE), and the Office of the National Coordinator for Health Information Technology.
  • Investigator-Initiated Research. AcademyHealth has long advocated for balance in AHRQ-funded research (IIR)–both what is funded, and how. At our recommendation, lawmakers have for many years targeted funding for investigator-initiated research grants at AHRQ to balance investments in intramural research and contracts. Again this year, the subcommittee proposes maintaining this targeted funding of $45 million and notes the importance of true IIR while urging AHRQ to avoid being too prescriptive in awarding these funds:

    “The Committee believes that IIR should not be targeted to any specific area of health services research in order to generate the best unsolicited ideas from the research community about a wide variety of topics.”
  • Commission on Scientific Standing. The subcommittee proposes $1 million for the National Academy of Sciences to establish a “Blue Ribbon Commission on Scientific Standing.” The Commission would discern American public opinion on, understanding of, and faith in scientific research and make recommendations for how to improve scientific literacy and enhance Americans’ views about science.

Just as important as what is in the bill is what is not. The bill does not include restrictions on the use of research, or prohibitions on comparative effectiveness research and health economics. AcademyHealth has been watching for such troubling language closely, since it first appeared in a draft House appropriations spending bill two years ago.

The release of the draft spending bill provides some transparency into the priorities of the Senate subcommittee with jurisdiction over health spending. However, it’s about all we can expect to see for the remainder of this Congress. The Senate Appropriations Committee cancelled its full committee markup of this spending bill among concerns about Affordable Care Act (ACA)-related amendments. The House has not–and likely will not–scheduled a markup of its health spending bill given the political sensitivities surrounding it (e.g., ACA, Title X funding, etc.).

With the month-long August recess upon us, lawmakers will not take any further action on the FY 2015 spending bills until they return in September, at which point they are expected to pass a stop-gap continuing resolution to keep the government running at current levels until December. Whether or not Congress will be able to negotiate an actual spending bill for the Department of Health and Human Services (HHS)–or will take the easy way out with a year-long continuing resolution–will largely depend on which party retains control of the Senate after the mid-term elections.

For a copy of the Senate’s draft legislation, click here, and for a copy of the report, click here. A summary of the subcommittee’s funding allocations can be found here.



Earlier this week, I had the pleasure of participating in TEDMED’s “Facing the Facts of Childhood Obesity” Google Hangout, part of the community’s Great Challenges of Health and Medicine series, which convenes individuals from various disciplines to explore “20 of the most complex, multifaceted, and insufficiently understood challenges to the health and health care of Americans.”

As a pediatrician and a passionate advocate for advancing the nation’s health, I was thrilled to join Risa Lavisso-Mourey, Nancy Brown, Don Schwarz, and Elissa Epel for this conversation. As tends to happen when I’m in a room full of great minds, I came away with my wheels churning and with our mission to improve health and health care through the application of evidence reaffirmed. Reflecting on this discussion, I want to emphasize one point I made during the Hangout that I find critical to the field of health services research more broadly:

To build a culture of health, we must first build a “culture of learning.”

To clarify, when I say “culture,” I mean an expectation, a new normal, where every innovation, every intervention, every program, and every policy is monitored and evaluated to establish whether it is actually delivering the intended impact. A new normal where every actor engaged in a program or policy development—whether a provider, program manager, policymaker, or participant—naturally asks, “How will we know if this intervention worked? How will we know that we had the effect we intended to have?”

It is only in a culture of learning that we will be able to scale up and spread those interventions that do work, adapting them to the many diverse communities in which they’re needed and—just as importantly—discarding those which do not. This will maximize our valuable, and not to mention already limited resources, to the benefit of better health and health care.

However, to accomplish this fundamental shift in thinking, we need to become better at building bridges between our scientific/evidence communities and our policy/practice communities. You’ll note that I made ‘communities’ plural, and I do so intentionally. Currently, there are too many silos within the science community; they’re bounded by disciplines and sectors, and the same is true for practice and policy.

What the obesity epidemic, both child and adult, makes abundantly clear is that we must work across these silos to succeed. We, as health services researchers, must not only bridge the traditional evidence and policy/program divide, which is already far too wide, but we must also create a vibrant, expansive, and mutually supportive community of evidence producers. We need to expand our proverbial “toolkit” of measures and study designs to enable more real-time knowledge generation, helping to drive mid-course corrections rather than [click to continue…]



On Tuesday, July 15, the Coalition for Health Funding hosted its annual Public Health 101 congressional briefing. During this year’s briefing, “Faces of Austerity: How Budget Cuts Hurt America’s Health,” longtime AcademyHealth member Glen P. Mays, F. Douglas Scutchfield Endowed Professor in Health at the University of Kentucky, spoke on the economic impact of cuts to public health funding.

The new work presented by Dr. Mays complemented his 2011 study, published in Health Affairs, which demonstrated that investments in local public health departments improved rates of preventable causes of death, including infant mortality, cardiovascular disease, cancer, and diabetes. That study, too, saw public health having a greater impact in low-resource communities.

As Dr. Mays noted during the briefing, historically, the U.S. public health system is a great success story. However, public health receives only 3 percent of the $2.3 trillion spent on health care. He cautioned that recent cuts to the chronically underfunded system could prevent public health from doing its traditionally “invisible” work to increase life expectancy, prevent disease and death, and contribute to healthier communities.

Among the statistics provided during his presentation, Dr. Mays noted that, between 2006 and 2012, the average community in the United States lost roughly 5 percent of its public health protection, including efforts to monitor community health status, investigate and control disease outbreaks, and educate the public about health risks and prevention strategies. Those hardest hit experienced reductions of more than 25 percent. When looking at the numbers, research reveals that the communities that experienced the largest increases in unemployment and the largest reductions in public health spending during the economic recession saw the most severe fall in local public health delivery. Also related to unemployment, the research found that a doubling of unemployment rate was associated with a 6.3 percent decline in the availability of public health activities in the average community. As drastic as these cuts appear at their surface, Dr. Mays told attendees that their full impact is yet to be recognized.

Public health is operating under the tyranny of short-term thinking. A desire to reduce funding now is resulting in shortsightedness when it comes to the future of the United States health care system. When considering the mounting list of demands and challenges facing health care today, including increasing costs and an aging population, continued cuts will do more harm than good. Despite what policymakers may think, “Cuts to the nation’s health are certainly not trivial,” said Dr. Mays. “Research shows they will have a direct impact.”

Read more about Dr. Mays’s research in the one pager “Evidence Links Public Health Services to Stronger Communities,” and follow along with his team’s research through his blog.



When tort reform comes up in discussions of health policy, it’s almost always pitched as a way to reduce health care spending in general. I’ve written extensively on how this seems very unlikely, given what we know from data and evidence. Changing physician behavior is hard, and the threat of lawsuits is not the only motivator in how physicians order tests or do procedures.

That said, there are many other questions. Such as how might malpractice reform change the supply of physicians? And would it be more likely to move high or low quality physicians? A recent study published in the Journal of Law and Economics is on point:

Malpractice reforms tend to reduce physicians’ liability for harming patients. Because these reforms are passed at the state level, the costs of harming patients vary widely by geographic location. In this paper, I test whether malpractice reforms affect where physicians choose to practice and whether physicians who relocate in response to reforms are particularly prone to commit malpractice. Because a state’s own reforms cannot separately distinguish moral hazard from adverse selection, and because those reforms are likely to have direct effects on measures of malpractice via the legal market, I focus attention on neighboring states’ reforms.

This study looked at how reforms passed in adjacent states affected physician movement, since it’s much easier to move from one state to another right across a border. The analysis got down to the county level to look at ease of moving when a neighboring state passed a law making malpractice lawsuits harder.

The first analysis looked at whether doctors relocated their practices after a nearby state changed its malpractice laws. The second analysis examined the how changes to nearby states’ malpractice laws changed the local rates for malpractice insurance. The authors felt that this was a decent proxy for detecting whether doctors who remained or moved were more or less likely to have been sued in the future.

The first analysis found that physician migration was related to nearby changes to malpractice laws. The study found that the supply of doctors decreased about 4.4% when a neighboring state passed tort reform with caps on non-economic damages. It appears that physicians are more likely to practice in states with reforms than states without.

The second analysis was also interesting. If a state passing malpractice reform caused the malpractice rates in neighboring areas to go up, that would imply that higher risk doctors remained, and lower risk doctors left the area. If rates went down in neighboring areas, then it would imply that it was the high risk doctors who moved.

The latter was seen. When states passed tort reform with caps on non-economic damages, malpractice rates in neighboring areas dropped 4.5%. Moreover, the sensitivity analyses showed that it’s unlikely that this is the result of certain specialties moving. It seems that physicians who are more likely to commit malpractice are the ones most likely to move.

Now, I admit that it’s hard to know what the actual damages and risks are here. Malpractice is still very uncommon, and these changes aren’t huge. But when policymakers argue that passing tort reform will increase the physician supply, they should know both the magnitude of that difference, and the quality of the physicians they might attract. This study gives us a little more information on both those questions.



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Along with many others, I’ve argued for years that journal publication is an inadequate dissemination strategy. Blogging about the work can help, but that’s not all one could do. What is the most one could reasonably do to disseminate one’s work or that of one’s field?

The answer to that question depends on the assets one has to deploy. For my part, I can tweet, blog, write a piece for a major media company, and/or facilitate others doing so. My full dissemination strategy would include all these approaches. There’s a nice way to organize them to convey how they relate to one-another, and how they work together to help a diverse audience find all the information they want and are able to handle, as shown and described below.


At the top (though we could turn it upside down), there are tweets and their cousins, Facebook status updates and the like. These have low information content, as conveyed by the small area they occupy at the top of the chart. But, they also have the potential for the widest reach, in general. If written well enough (which is not hard), they’re easily understandable and shareable, with modification if one wishes. Most anyone can tweet and tweet well (or update a Facebook status). It’s how things “go viral,” to any degree.

But to what should one link in a tweet? Certainly one could link to a journal article one on the issue or point one is attempting to promote, but that’s not going to go very far. A journal article is often literally inaccessible by being gated (OK, anyone can pay the ~$35, but nobody will) or what amounts to the same thing—written in technical language and way too long and (I’m sorry to say) boring for all but highly motivated scholars to read.

No, ideally one should link to a short summary that puts the work in the relevant policy or social context. That’s what people most want to know. What’s the point? Why should I care? Why is this important right now? And, yeah, how will this help me win an argument with my crazy uncle?

The next level down the pyramid, to which a tweet might ideally link, is an online column. It’s far longer than a tweet: more information, but still digestible in a few minutes and by a non-expert audience. About 700 words is near ideal. It makes the substantive policy or social point, leaning on evidence (one hopes), but without saying a great deal about that evidence, though more than a tweet, clearly. Most people who don’t care to delve deeply into the evidence, but want to know its social import, will stop here. Dissemination reach can be large (e.g., if the column is in a major publication, and in that case, the reach could exceed that of tweets).

That column could simply reference specific research papers. But, in my view, a more compelling, evidence-based argument is based on something like a comprehensive review of the evidence. So, the next level down is a literature review. The column might reference this. It’s all about the evidence, but in summary form and organized to help the reader understand it in total. It has a lot of content: it could be well over 1,000 words long, and often much longer than that. It could attempt some translation of that evidence into language more accessible to a wider audience, particularly if it’s on a blog. For the vast majority of people interested in evidence, this is the last stop. Reach will almost surely be less than a major-media column or tweets.

Finally, there’s the literature itself, upon which the literature review obviously relies. It’s voluminous, and not necessary organized in any coherent way. Only experts tread here, so reach is low beyond the field. But the literature is the foundation. Without it, nothing above follows: no evidence-based lit review, column, or tweets. It’s the fundamental product, but it can’t reach its full potential without help from other dissemination approaches.

I’ve deployed this hierarchy of dissemination tactics before, sometimes with the help of colleagues. (And, to be sure, I’m not the only one tweeting about my columns, posts, and literature.) For example, last week’s focus on the cost-effectiveness of contraception used all levels of the hierarchy, as illustrated below: Adrianna McIntyre (and others, including myself, of course) tweeted, I wrote a New York Times’ Upshot column, Daniel Liebman wrote a literature review for The Incidental Economist, and, of course, the research base was already in place.

hierarchy with stuff

Of course there are other dissemination tactics. Aaron puts out some amazing Healthcare Triage videos on evidence. Other organizations would write reports, convene meetings, call policymakers and stakeholders, and so forth. Some write books, give keynote addresses before large audiences, … You get the idea.

It’s worth thinking about how the dissemination tactics available to you or your organization fit together and work in concert. Viewing and using them as disjoint tools may not maximize results.

Acknowledgement: I thank Bill Gardner for his email feedback on my early thoughts that led to this post.

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.



In a prior post I explained how I was in agreement with the suggestion in a commentary [4] by Rebecca Russ-Sellers, Jerry Youkey, Ronnie Horner that health services researchers should learn more about the practice of medicine. As I mentioned, the authors, along with Matthew Hudson published a series of commentaries about remaking health services research (HSR), and that I did not agree with all of their ideas. In this post, I’ll push back on some of them. (For the reader’s convenience, full references and links to all their commentaries to date are at the end of this post.)

In [1], citing the fact that there are still racial and ethnic disparities in health care and predicting the failure of the accountable care organization model, the authors claim HSR has not achieved its potential. To be sure, we should strive for greater achievement, but the continued existence of disparities and the anticipation of failure not yet realized is hardly a sound or complete basis for assessing HSR.

Still, the authors believe there is trouble in the field, and the heart of it is that it is not patient-focused enough.

[H]ealth services research, even when it investigates comparative effectiveness or is otherwise focused on patient-centered outcomes, is methodologically targeted to the “average” patient in a population of patients. [...] The average patient seldom exists in the reality of medical practice; it is a statistical concept with certainty to result in the wrong care at the wrong time or in the wrong way with the wrong outcomes for many patients.

This echos a complaint articulated by Trisha Greenhaigh and colleagues and addressed by Bill Gardner on TIE.

You may think that the problem is that the evidence-based clinicians got off on the wrong foot by oversimplifying the patients when they developed their algorithms [or guidelines]. Maybe so, but this is almost unavoidable. The reason is that evidence-based medicine might also be called “medicine guided by statistical learning from data” and it is hard to learn anything from statistical data unless you can simplify your problem to some degree.

Ultimately one has to average over some number of patients to learn anything from data. Of course every patient is unique, but one cannot learn without generalizing (or “simplifying”) to some extent.

Aaron Carroll made a similar point at The Upshot in discussing medical guidelines.

Some doctors [...] believe that patients should be treated as individuals, and think that guidelines, and evidence-based medicine, are too “cookbook,” remove doctors from the equation, treat patients all the same, and result in missed opportunities for better care. [...]

[But] guidelines aren’t meant to tell you how to take care of every patient. They’re meant to tell you how to take care of specific patients. They tell you that for certain patients who meet certain criteria, there is a best way to practice.

But a physician still must decide when a patient doesn’t meet the criteria, and if not, must treat that patient using judgment and experience. Guidelines don’t cover everything, but we should allow them to cover what they can.

I’m all for pushing the envelope on patient-centeredness, but one must recognize that there are limits and that those limits do not doom HSR or evidence-based medicine.

I’ll conclude with one a last point from [2] that rubbed me the wrong way.

[T]he preferred study is designed to minimize the impact on the provider in providing care to the patient and on the patient who is there to receive care.

Here too, one must recognize reasonable limits of this ideal. Sometimes studies must be disruptive to be both informative and to move the system in the direction in needs to go. We cannot presume that the status quo is ideal, after all. For example, Atul Gawande’s interventions to encourage the use of checklists were disruptive! They inconvenienced providers! But they also improved care. The same might be said of interventions to promote shared decision making.

Of course, all things being equal, we don’t want to inconvenience providers or patients. But we tolerate some degree of it for the greater good (e.g., medical education means that less experienced practitioners do some of the health care delivery). It cannot be any other way, and that’s not the fault of HSR. That’s the nature of collecting evidence.


1. Horner RD, Russ-Sellers R, Youkey JR. Rethinking health services research. Med Care. 2013;51:1031–1033.

2. Sinopoli A, Russ-Sellers R, Horner RD. Clinically-driven health services research. Med Care. 2014;52:183–184.

3. Russ-Sellers R, Hudson M, Youkey JR, et al. Achieving effective health service research partnerships. Med Care. 2014;52:289–290.

4. Russ-Sellers R, Youkey JR, Horner RD. Reinventing the health services researcher. Med Care. 2014;52:573-575.

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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In a series of special commentaries published in the journal Medical Care [1-4], Rebecca Russ-Sellers, Jerry Youkey, Ronnie Horner, and Matthew Hudson raised some provocative ideas about how health services research ought to be reoriented. I found myself agreeing with some of their suggestions and in strong disagreement with others. In this post, I’ll cover some of their ideas I think make sense. In a subsequent post, I’ll push back against a few that I think do not.

I read their most recent commentary [4] first, so I’ll begin there. (For the reader’s convenience, full references and links to all their commentaries to date are at the end of this post.) The premise, established in the first three commentaries [1-3] is that health services research (HSR) has underachieved, failing to identify “effective or efficient approaches to the provision of health care.” I don’t fully agree with that premise, but it’s important not to be too defensive. Some valuable things can be learned by withstanding a bit of critique.

Indeed, I think the authors are on to something in writing,

[A]t the heart of the current underachievement is the pervasive lack of clinical awareness of the prototypical health services researcher. Although the majority of health services researchers do not possess the medical doctorate, the issue is not so much lack of medical credentials as it is that the perspicacious health services researcher needs an understanding of the full context in which medicine is practiced. This context includes not only the physical setting of the clinic, but the fiscal and policy pressures and, most of all, the patient-provider covenant that is at the center of medical practice.

I cannot think of a good reason why greater understanding of the practice of medicine would not improve the work of a health services researcher. I don’t mean (and neither do the authors) that every HSR practitioner need to be able to perform open heart surgery. Heavens no! But knowing just enough to be able to make one’s way through at least some of the clinical studies one encounters in, say, the New England Journal of Medicine or the Journal of the American Medical Association is important.

Why? Because we’re supposed to be in an age of ascendance of evidence-based medicine. HSR practitioners should be participants in this enterprise, if not at or near the center of it. And at the center, it is about medicine and how it’s delivered.

For this reason, I encouraged the community to beef up its understanding of medical science in a 2013 post on this blog. I still have not come across a course in any HSR-relevant program that teaches basic concepts of medicine for social scientists. (If you’re aware of one, let me know.) I wrote,

Does it strike you as odd that we are training students to be experts in health care delivery, organization, and policy without at least offering the opportunity for them to learn some details about medical science? It’s a bit like an engineer not knowing Newton’s laws. Maybe this made sense some time in the past, but given the current emphasis on evidence-based care and comparative effectiveness research, I think it is time that even health services researchers, health economists, and anybody who claims to be a health policy expert knew more about medical science. [...]

We all, as health services researchers, need to get up to speed. If we’re going to talk the “evidence-based medicine” talk, we’ve got to walk the walk.

In that post, I went on to suggest ways you can get yourself up to speed, even without a course, though that would be better. Likewise, Russ-Sellers and colleagues [4] argue that students and practitioners of HSR should participate in a practicum in which they are immersed in the clinical environment, experiencing “first-hand the organization, management and operation of, say, a general practice clinic or an operating room.”

This sounds great to me. Sign me up. (But also pay my salary during my immersion please!)


1. Horner RD, Russ-Sellers R, Youkey JR. Rethinking health services research. Med Care. 2013;51:1031–1033.

2. Sinopoli A, Russ-Sellers R, Horner RD. Clinically-driven health services research. Med Care. 2014;52:183–184.

3. Russ-Sellers R, Hudson M, Youkey JR, et al. Achieving effective health service research partnerships. Med Care. 2014;52:289–290.

4. Russ-Sellers R, Youkey JR, Horner RD. Reinventing the health services researcher. Med Care. 2014;52:573-575.

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.



I have long argued that the Affordable Care Act (and health care reform in general) has been about improving access. More specifically, it’s been about the uninsured. The ACA’s main raison d’ etre was to reduce the number of uninsured in the United States.

By that metric, the ACA appears to be working. As Sarah Kliff wrote yesterday on Vox, citing new work from Gallup:

The evidence is pretty overwhelming at this point that Obamacare has driven down the uninsured rate. Data from Gallup, the Commonwealth Fund, Robert Wood Johnson Foundation/Urban InstituteRAND Corporation and the Kaiser Family Foundation all have similar findings. Namely, that millions more people have insurance than before Obamacare’s insurance expansion.

It’s early, yes, and there’s still some ways to go, but it’s a start. Let’s look more closely at the latest from RWJF and the Urban Institute, “The ACA and America’s Cities: Fewer Uninsured and More Federal Dollars“:

This report estimated the effect of the Affordable Care Act (ACA) on 14 large and diverse cities: Los Angeles, Chicago, Houston, Philadelphia, Phoenix, Indianapolis, Columbus, Charlotte, Detroit, Memphis, Seattle, Denver, Atlanta, and Miami.

Among the seven cities in states that have expanded Medicaid, the ACA will likely decrease the number of uninsured by an average of 57 percent. City by city, the reduction is projected to vary between 49 percent in Denver and 66 percent in Detroit by 2016. New federal spending on health care from 2014 to 2023 would range from $4.1 billion in Seattle to $27 billion in Los Angeles.

Among the seven cities in states not expanding Medicaid, the ACA will likely decrease the number of uninsured by an average of 30 percent. The decrease would range from 25 percent in Atlanta to 36 percent in Charlotte by 2016. New federal spending due to the ACA from 2014 to 2023 would increase by between $1.9 billion in Atlanta and $9.9 billion in Houston

I’ve spent a significant amount of time talking about how the Medicaid expansion, or lack thereof in certain places, will leave many in the coverge gap. This report confirms that. But it’s important to note that even in cities where the Medicaid expansion is not taking place, the levels of uninsurance are expected to drop an average of 30%.

That’s not an insignificant amount. Remember that about 50 million Americans were considered uninsured before the ACA went into play. A 30% drop would constitute 15 million Americans achieving coverage.

Of course, in cities where the expansion is occurring, gains are even more dramatic. It’s expected that in those areas, the number of uninsured will drop by 57%.

The report estimates that if the remaining seven cities expanded Medicaid, then the levels of uninsured will drop by more than 50% in every city except Houston. In my own city of Indianapolis, which looks more likely to expand the program in the last month or so, it appears that the number of uninsured could drop by more than 55%, instead of the less than 30% expected without an expansion.

This sill isn’t universal coverage, though. Upwards of 25 million people in the United States will still be uninsured. Many of them will be undocumented immigrants. Some will be people who are still too poor to afford insurance. And some will be people who choose not to buy insurance and pay the mandate “tax” instead.

Things won’t be perfect. But with respect to the numbers of uninsured in the United States, things will certainly be improved. We won’t be done with health care reform, but for those who have been struggling to improve access for decades, it’s a big start.





Howard Koh, the Assistant Secretary for Health for the U.S. Department of Health and Human Services, has written a viewpoint (with colleagues) that was recently published in JAMA. In it, he details how the United States is moving toward achieving the health goals set forth in Health People 2020. What is Healthy People?

Healthy People provides science-based, national goals and objectives with 10-year targets designed to guide national health promotion and disease prevention efforts to improve the health of all people in the United States.  For three decades, Healthy People has established benchmarks and monitored progress over time…

Healthy People 2020 contains about 1,200 objectives in 42 Topic Areas designed to serve as this decades framework for improving the health of all people in the United States.

We have data for about a third of the decade, so it seems an appropriate time to check in and see how we’re doing. If you read the JAMA piece, and I encourage you to do so, you would likely come away feeling pretty good. After all, as Koh and colleagues report, 14 of the leading 26 indicators have shown improvement. This is surely a good thing. But even when we see improvement, there’s still a long way to go.

The percent of adults receiving screening for colorectal cancer went from 52% to 59%. But the goal is 75%. The percent of adults with hypertension under control went from 44% to 49%. But the goal is 61%.  the percent of kids receiving all their vaccines went from 44% to 69%. The goal is 80%. Injury deaths are down; preterm births are down. Adolescent drug use is down and adult cigarette smoking is down. Both have room to move, though.

Some goals have been met. The air is much cleaner, and fewer kids are exposed to secondhand smoke. The homicide rate is below projections. Adults are exercising, too. All this is good.

But a number of goals have seen little or no improvement. Obesity among both adults and children is steady to up. Vegetable consumption has not improved. Binge drinking remains a problem in adults, and smoking remains steady in adolescents. The percent of people insured and who had a primary care provider remains relatively unchanged. Diabetes is still poorly controlled.

And some things have gotten worse. Suicide is actually more common than it was before. So are adolescents reporting major depressive episodes. Fewer people are seeing the dentist than before, too.

I understand the administration’s desire to make things look good. I really do. But improving in 54% of metrics is barely more than half. In terms of a grade, I don’t see how that’s much better than an F. The things we’re failing on are of critical importance. We’re talking about obesity, nutrition, diabetes, alcohol, and cigarette use. We’re talking about depression and suicide. These are not minor issues. They are major problems.

An important aspect, and one often overlooked, is that we too often lack an evidence base for making things better. We know where we are, and we know where we want to be, but we’re not all in agreement as to how we should get there. More research needs to be performed. More data needs to be gathered. We need to study solutions, and to promote those that work. This is some of the critical work that health services research can do.

I’m glad to see that we’re holding ourselves accountable. I’m glad to see we’re getting feedback early and often. But we have a long way to go to make the nation healthier.




The last day of the AcademyHealth Annual Research Meeting wrapped up with a half day of presentations that included the Best of ARM: Part Two and a late-breaking abstract session on the early performance of the Affordable Care Act (ACA). Although it’s hard to believe another ARM has come and gone, we leave energized about the amazing work that people in our field are producing and its potential to positively shape the U.S. health care system.

Best of ARM: Part Two

Today’s Best of ARM: Part Two session highlighted high-level research findings worthy of further discussion. Expert discussants Tom Ricketts, David Auerbach, and Donald Taylor broadened the implications and meanings of the papers.

Conducted as a collaborative discussion, Rickets, Auerbach, and Taylor each provided their analysis among the abstracts Failing to Choose Wisely: Lack of Treatment De-intensification in Older Patients with Diabetes; Nurse Value Added and Patient Outcomes in Acute Care; The Changing Role of RNs in Pioneer ACOs;  and How Do Health Policy Researchers Perceive and Use Social Media to Disseminate Science to Policymakers? They then welcomed the abstracts’ authors to the stage to continue the conversation. Audience members were encouraged to ask questions of both the discussant and the author. Some of the Q&A session addressed challenges and opportunities of using big data warehouses, the role of the media in study titles, the idea of “good nurses,” and differences in magnet vs. non-magnet hospitals.

Late-Breaking Abstract Session: The ACA and Early Performance

The following late-breaking abstracts chosen for this special session discussed early evidence and experience associated with the Affordable Care Act (ACA):

  • Consumers’ early care experiences using Health Insurance Marketplace qualified health plans: Preliminary findings from California
    Brandy Farrar, American Institutes for Research
  • ACO Characteristics Associated with Quality Performance
    Taressa Fraze, Geisel School of Medicine
  • Early Impact of Affordable Care Act Subsidies on Labor Market Supply
    Cameron Kaplan, University of Tennessee Health Science Center
  • Experience with ACA Open Enrollment: Lessons for 2015
    Stephen Zuckerman, Urban Institute

Zuckerman kicked the session off by describing the ACA’s open enrollment and discussed its implications for 2015. Key among his findings were that costs were often perceived as a barrier for uninsured adults seeking coverage. Using 2014 as an indicator, there are many things to take into account for 2015′s open enrollment. Improving health insurance literacy may encourage participation and improve the ability of consumers to make informed choices; even if you build it, people may not come (many uninsured aren’t ready to obtain coverage, and some may question its value); and some people merely need people to help them, not just websites.

Kaplan’s work demonstrated that the way subsidies are designed may lead to labor market impacts. Based on preliminary analysis, estimated health insurance subsidies were associated with decreases in hours worked, and impacts were significantly greater in places with higher health insurance premiums.

Following the presentation of Kaplan’s work were Farrar and Fraze, who discussed Californians’ experiences using the state’s marketplace and emerging trends in Accountable Care Organizations (ACOs) and potential narratives as to why they’re occurring, respectively. Their work is not yet available for public distribution.

Update on Federal Payment Reform at CMMI and Responses from the Marketplace

This session focused on new payment models and reflected how the changing landscape of federal payment reform is influencing current and future programs in the marketplace. Moderated by William Shrank, this panel provided [click to continue…]