Written by Erin Holve, PhD, MPH, MPP, Senior Director, AcademyHealth

How can research go beyond traditional discovery, peer review and publication? How can it better resonate with stakeholders such as policymakers, business leaders and health systems administrators, who can take groundbreaking clinical data and implement innovative solutions that transform health and improve patient outcomes?

These questions have partially inspired a redesign of the EDM Forum’s brand, which for five years has driven collaboration among researchers and diverse stakeholders who create data, methods and evidence to shape the next generation of learning health systems. The redesign, which features sleek, modern branding, will further connect the dots between how electronic data can enhance research and quality improvement initiatives, opening the door to build relationships with new audiences.

The task to extend the reach of research and new evidence to improve health isn’t new.

An article in The Guardian in November 2014 delved into what steps can be taken to make relationships between researchers and policymakers more fruitful. Some of the conclusions in the article focused on the need for researchers to be clearer about their focus, improve their engagement techniques, network, and implement an active media presence.

Similarly, AcademyHealth’s Translation and Dissemination Institute tackled a similar topic last year during its Lessons Seminar, which explored, in part, how other industries communicate hard-to-digest information. Their findings can be found in a recent publication, “Moving Health Services Research Into Policy and Practice: Lessons from Inside and Outside the Health Sector.” Some of the conclusions in the final report focused on communicating research more effectively, establishing personal relationships, and using storytelling and social media to improve engagement with target audiences.

Linking clinical data with its practical application in hospitals or in policy isn’t an overnight reality. However, by improving how we present and communicate data, through better visuals and engaging channels, we can maximize the impact of research and achieve even greater collaboration.

This week during Health Datapalooza, I will be available to talk about the EDM Forum’s rebrand and refreshed approach to galvanizing new audiences, and making research into inspirational and aspirational assets for a variety of stakeholders. On June 2, from 3:35-4:05 pm, I will deliver a presentation on the EDM Forum rebranding, eGEMs and other collaborative projects at Exhibit Hall Booth #407.



Whether or not they expanded Medicaid, states are always looking for ways to reduce program costs and improve care for their enrollees. Often, a small number of Medicaid beneficiaries account for a large proportion of the costs – and those same enrollees are the ones who could benefit most from better coordination of their care.

But how can a state actually figure out how to best target their limited resources?

A recent three-part webinar series featuring members of the AcademyHealth State University Partnership Learning Network, as well as leaders from other states, discussed examples of each state’s own experience identifying the target population, implementing interventions, and then evaluating those programs employed to help improve the health of Medicaid enrollees.

Together, participants outlined an approach that both starts and ends with data:

Identification. First and foremost, states need to identify the specific populations or individuals within Medicaid that are driving costs up. Agreeing on the definitions of “high-utilizers”, “high-needs”, and “high-cost” is a critical first step and should not be overlooked. Identification must begin with collecting the pertinent data, including determining what gaps in data availability or quality may hinder the process. Once a state has the necessary data, using analytical and modeling tools to learn who the high-cost Medicaid enrollees are, where they live, and what types of services they are (or aren’t) using will help states focus on targeted interventions.

Intervention. Using the results of predictive modeling and analytics, states can create evidence-based targeted programs to drive specific outcomes. An intervention may be small and local, like a program to reduce emergency department use at an urban hospital, or it may be a large, multifaceted statewide initiative like a birth outcome program to reduce early elective delivery and premature births.

Evaluation. Finally, evaluation efforts bring a state back to data, asking whether the program or initiative is truly reducing costs, creating better health outcomes, and delivering the best return on investment for the Medicaid program. Rapid-cycle evaluation is becoming more common for states to be able to quickly learn whether a particular program is working.

The webinar series is archived here.

About the AcademyHealth’s State-University Partnership Learning Network
The mission of the State-University Partnership Learning Network is to support evidence-based state health policy and practice. To do this, the Learning Network brings together state Medicaid agencies and university research centers to learn from and with one another around specific, partnership defined initiatives. More information about the Learning Network and the webinar slides are available on AcademyHealth’s website.



For scientists, or those who aspire to think like one, the National Geographic piece by Joel Achenback titled “Why Do Many Reasonable People Doubt Science” is likely a painful read. But, as Achenback discusses, there’s a scientific basis for scientific doubt, one that not even scientists can fully avoid.

The gist is that we’re social animals. (Yes, even the introverts.) We belong to tribes—composed of our circle of friends, our family, our colleagues, our community or church members, and the like—whether we choose to recognize it or not. Tribal affinity can trump objective interpretation and unbiased presentation or dissemination of evidence.

Let me be concrete: My tribe recycles. Its members believe climate change is real and human-driven. We think parents should vaccinate their children. We’re not fans of processed food. And so on.

It’s not perfect, but I like my tribe. I was born into it, and I’ve made a comfortable life among its people, some of whom I care about deeply. I don’t want to upset them. I don’t want them to think badly of me either. So, what do I do with evidence on the matters above, among others?

It’s natural—even rational—that I’m predisposed to accept, highlight, and discuss evidence that is consistent with my tribe’s identity. Sure, maybe I explore and entertain counterpoints. Maybe I even see merit in them (well, some of them). But the field is tilted in what I’m likely to reveal about where I stand, or even what I entertain only to reject, to members of my tribe, if not more publicly. I’m probably even tricking myself as to what’s true, at least some of the time and for some issues.

This is Dan Kahan’s “identity-protective cognition” at work. Even if I could avoid it, can I be sure that I am? Can you? I really doubt it. Not even deeper engagement with evidence is sure to unbias.

Studies back that up. For example, in one study, Kahan and colleagues found that political orientation can overwhelm correct interpretation of data even among highly numerate individuals. In their intriguing study, such individuals could correctly interpret data when they were presented as pertaining to a topic that isn’t politically charged, like how well a skin cream works. But, when the data were said to represent something politically charged, like the relationship between a gun ban and crime, they suddenly misinterpreted it in a way that aligned with their political views. You’ll find other work on this theme at The Cultural Cognition Project.

This is enough to make one despair and overreact: If people are going to believe whatever they want, no matter the data, is science and evidence irrelevant? The answer is surely “no.” Other work shows that facts can attenuate bias, but only so much.

But there’s another reason to value science. It clearly has affected the human condition enormously, and largely for the better (in my view). The fruits of science have helped more than double our achievable lifespans, provide levels of control over our environment (think agriculture and transportation) and facility in interacting (think Internet and cell phones) that could not have been dreamed of decades ago. At a less grand level, honest debate over evidence does inform policy. I see it happen at the Comparative Effectiveness Public Advisory Council meetings I participate in, for example.

Moreover, it may be possible to at least somewhat protect oneself from one’s tribal instincts. To improve the chances one’s view is defensible, Bill Gardner suggests that we seek the best arguments from worthy adversaries from different tribes.

[Y]ou have to tackle the best version of the argument you hope to defeat. [...] You should also seek identity threat. You need to expose yourself to people who fight by the rules, and who can and will beat the intellectual crap out of you.

This is useful advice, so long as we understand that to get at the truth, the outcome of interest is light of knowledge not heat of battle. And yet, heat can be alluring and is often highlighted in the media.

In a recent paper, Matthew Nisbet and Declan Fahy examined the media’s role in conflicts over interpretation of scientific evidence. The tendency for media to cover the “political angle” or to “balance” stories with opposing views—without resolving which one is more consistent with the body of evidence—swiftly moves attention away from light to heat. Such politicization of scientific subject areas encourages the public to heed their tribal instincts even beyond their subconscious tendencies. Nisbet and Fahey take heart in the rise of explanatory, data-driven journalism now found at The Upshot, 538, Vox, and elsewhere, suggesting that the more knowledge-based products they provide might help attenuate tribalism. Whether they’re right or not, a focus on knowledge as opposed to debate is probably a necessary condition.

Better still is greater participation in dissemination by researchers and directly on such sites. (Aaron and I write regularly for The Upshot on health care research and policy, for instance, along with other scholars who write on other subjects.) As Dahlia Remler pointed out, such arrangements can disseminate knowledge more cheaply than financially struggling media could do on its own, because academics do not require a salary and benefits (just a relatively modest fee) to produce occasional pieces.

Quality journalism is a public good. While it was once cross-subsidized by selling sports coverage and classified ads, the Internet and other technology put a stop to that. Now, like most public goods, quality journalism is poorly sustained by the market. So, it makes sense to use higher education, an already financed public good, to support quality journalism, an under financed public good. That idea was just one of the reasons Don Waisanen, Andrea Gabor and I advocated Academic Journalism—a lot more journalism done by people with full-time academic salaries.

If scholars partner with media organizations to disseminate knowledge and do so by engaging the best alternative, identity-threatening interpretations, we might just learn something. It won’t change the world overnight, but it isn’t likely to make it worse.

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.



When I was a resident, one of my mentors recommended that I buy this new handbook on evidence-based medicine by David Sackett. In the last decade or so, I’ve purchased maybe ten copies of this book. None remain in my possession. I keep loaning them out and no one ever returns them.

I remember the first time I read it, which isn’t long. It was as if someone was pulling back the curtain, explaining to me how the practive of medicine would be if everyone was logical. When do you order a test? How do you interpret? How do you make decisions? What do all those numbers in the literature actually mean?

The book came with laminated cards that summarized the chapters. I used to carry them around the hospital with me, pulling them out whenever I thought a decision we were making wasn’t evidence-based. I don’t think that made me very popular with all of my attending physicians, but I know it made me a better doctor.

David Sackett is the father of evidence-based medicine. His texts are widely regarded as the first and last word on the subject, and his many manuscripts on the topic are as relevant today as they were when he wrote them.

It saddened me this week to learn that he had died. Not because he hadn’t led a good and full life. An obituary at the BMJ this week lays out in detail many amazing facts about him that I didn’t know. For instance, twenty years after completing his training, he repeated his residency in medicine because he felt that he “wasn’t a good enough doctor”. I can honestly say that there’s not enough money in the world to get me to do that. He must have been an amazingly humble man.

Many things I did know, however. With Drummond Rennie, he published the Users’ Guides to the Medical Literature, still THE reference book on the subject. He wrote a book on Clinical Epidemiology in the 80′s, which is still “the bible of evidence based medicine.” He was the founding editor of Evidence Based Medicine and the first chair of the Cochrane Collaboration. I knew he had “retired” even before that EBM handbook found its way into my library. But as with many amazingly productive researchers, retirement was a relative thing for him. After quitting clinical practice, he set up a research and education center in Canada where he continued to teach, research, and write about randomized clinical trials. Just a few years ago, he published a three part series on how to say “no” in order to succeed professionally. Any of my mentees would recognize much of what he wrote, because I’ve been living it and preaching it ever since.

As I wrote this piece, I realized that – once again – I seem to be without a copy of his EBM handbook. I went to Amazon to get a new copy, and discovered that just recently, he had published a book on evidence based mentorship in academic medicine. I immediately ordered one. It seems that even now, I still have much to learn from Dr. Sackett.

I also learned that his EBM handbook now seems to be out of print. I spent a little extra to get myself a copy from a third-hand seller. I won’t be lending this one out.




I’m a huge supporter of information technology. I’ve spent almost my entire career creating systems in order to improve outcomes for pediatric patients. But that doesn’t mean I don’t carry a healthy skepticism for how much of a difference HIT is actually making in practice. The evidence for how much health information exchanges are impacting care is somewhat equivocal as well. A new study is being discussed as showing HIEs can significantly reduce hospital admissions. It’s worth reviewing in detail. “The potential for community-based health information exchange systems to reduce hospital readmissions“:

Background Hospital readmissions are common, costly, and offer opportunities for utilization reduction. Electronic health information exchange (HIE) systems may help prevent readmissions by improving access to clinical data by ambulatory providers after discharge from the hospital.

Objective We sought to determine the association between HIE system usage and 30-day same-cause hospital readmissions among patients who consented and participated in an operational community-wide HIE during a 6-month period in 2009–2010.

Methods We identified a retrospective cohort of hospital readmissions among adult patients in the Rochester, New York area. We analyzed claims files from two health plans that insure more than 60% of the area population. To be included in the dataset, patients needed to be continuously enrolled in the health plan with at least one encounter with a participating provider in the 6?months following consent to be included in the HIE system. Each patient appeared in the dataset only once and each discharge could be followed for at least 30?days.

Readmissions are one of the most popular metrics being promoted as a measure of quality in the health care system. Measures which might reduce such readmissions would be welcome, as payments might depend on keeping reasmissions to a minimun.

Some have postulated that a lack of information might drive a number of admissions. Doctors might put patients into he hospital because they don’t have a clear picture of what’s going on, or because they think patients might need tests or checks that they are unaware have already been done. With better information, therefore, some readmissions might be prevented. If HIEs can deliver this information, then they might be a means to achieve better quality.

This study was a retrospective cohort analysis of patients in two health plans who live in Rochester, New York. To be included in the cohort, patients had to be continuously enrolled and have been seen at least once by a participating provider in the last six months. The main outcome of interest was whether a patient was readmitted to the hospital within 30 days of being discharged. The main predictor of interest was whether a provider had accessed patient information in the HIE in the month after discharge.

The researchers found that patients whose information was accessed by a provider had significantly lower odds (aOR 0.43) of readmission when compared to patients whose information was not accessed. They further estimated that the reduced readmissions for the health system were just over $600,000.

On its face, these findings seem like great news, for patients, for HIEs, and for the health care system. But there are some reasons to take them with a grain of salt. This is an observational study, and causality cannot be assumed. We don’t know that the HIE is what led to a reduction in readmissions. This is also a study of a relatively small set of patients in a health care market that is reasonable contained.

The larger issue is one of confounding, however. It’s entirely possible that accessing the HIE could be a marker for a more attentive physician, a more robust medical home, or a patient who was being managed more closely. In that case, the HIE isn’t the cause of the reduced readmission – it’s merely a signal that better care was occurring. This is important, because the creation and maintenance of HIEs is not insubstantial. They take time, money, and a large amount of effort.

Pretty much all of these issues are noted in the discussion of the manuscript, so none of these are to fault the paper or the authors. But some are over-interpreting this study to “prove” that HIEs are a success. Almost all of want them to be. But the siren song of HIT that improves access, reduces spending, and improves quality has lured many before with promises that have failed to achieve their potential.

This study shows that it’s very possible that HIEs could lead to improved quality and increased savings. Whether they are truly the cause of these findings will need further work with more robust, prospective work.


From the editors: Learn about more new health information technology research at AcademyHealth’s 2015 Annual Research Meeting and discuss health information exchanges with delivery system leaders at AcademyHealth’s inaugural Concordium conference.



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A recent Academy Health blog post explored the relationship between the number of physicians accepting Medicaid patients and the number of children who were able to access care without being turned away or having their care delayed. The author deduced a simple, yet important point: More doctors=better access for kids; better reimbursement=more doctors.

As researchers continue to explore these and other issues in Medicaid policy, it is vital that research findings are timely, relevant, and presented in ways that are useful for policymakers. It comes as no surprise that an important first step in making research relevant is understanding the priorities and evidence needs of the intended research user. This is the premise underlying a recent AcademyHealth report highlighting the research and data gaps that policymakers and analysts identify as key to informing Medicaid policymaking over the next several years. The report, “Improving the Evidence Base for Medicaid Policymaking,” is the second in AcademyHealth’s Listening Project series, which seeks to identify areas where new or better evidence could help inform timely issues in health policy and health care delivery. The Medicaid-focused report is informed by interviews with more than 50 Medicaid policymakers, researchers, and other stakeholders from across the country. Across the interviews, respondents consistently noted several areas where new or better evidence could help inform their decision-making or that of their colleagues. For example, respondents saw a role for the research community in helping them:

  • Understand the health and budgetary implications of Medicaid expansion versus non-expansion;
  • Implement strategies for driving quality and value through payment and delivery system reform;
  • Develop targeted strategies for serving high-cost, high-need enrollees, such as dual eligibles and individuals with mental health and substance use disorders;
  • Identify opportunities for better coordination among Medicaid programs and social services agencies, public health departments, and the criminal justice system;
  • Determine what benefits and services best match the needs of specific groups of enrollees; and
  • Explore the role of community health workers, peer support specialists, and other alternative health care providers in serving Medicaid enrollees.

In addition to outlining high-priority research needs, the report offers advice from the policymaking community for researchers seeking to produce more policy relevant work. Some of this advice we’ve heard many times before, such as the importance of communicating research results in clear, concise language and disseminating findings in multiple formats, such as a peer-reviewed publication accompanied by a shorter brief. In addition, many respondents noted the importance of understanding states’ unique political environments, budget constraints, and other contextual factors that can affect the production and use of research – a point that is not unique to Medicaid. In another piece of advice, several respondents encouraged researchers to put study findings in the context of existing literature as a way of helping policymakers and other audiences understand the study’s contribution to the current evidence base.

A product of Academy Health’s Translation and Dissemination Institute, the report is supported by the Robert Wood Johnson Foundation and the Medicaid and CHIP Payment and Access Commission. It follows an earlier Listening Project report focused on the evidence needs of Medicare policymakers, and precedes a 2016 report that will highlight opportunities for researchers to help inform pressing issues in safety net care.

In response to these needs, AcademyHealth today released the first in a series of Evidence Roadmaps that take a closer look at the evidence needs identified in the Medicaid report. The Roadmap explores how best to integrate physical and behavioral health services for Medicaid enrollees, especially for those with serious mental illness. Medicaid enrollees with both types of needs are often among the program’s most costly and medically complex.The Roadmaps are intended to help policy analysts and other research users better understand whether a perceived research gap represents an actual lack of evidence, or failure to effectively disseminate existing evidence to the policy arena. Nine Roadmaps created in response to findings from the Medicare-focused Listening Project were released earlier this year.

View complete findings from the Medicaid Listening Project here, and stay tuned for additional Roadmaps resulting from this work.


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The National Heart, Lung, and Blood Institute (NHLBI) has released a Request for Information on its Strategic Visioning process that intends to “shape the scientific priorities of the Institute and guide [its] funding strategies over the next decade.”

For this collective planning effort, NHLBI is taking a creative approach—using crowdsourcing to invite individuals and organizations to help identify the most compelling questions and critical challenges that NHLBI must tackle in order to take full advantage of emerging scientific opportunities and new approaches for promoting health and reducing and preventing disease. Through NHLBI’s crowdsourcing platform Strategic Visioning Forum, participants may:

  • Browse existing Questions/Challenges;
  • Submit your own ideas for Questions/Challenges;
  • React to ideas by voting on Questions/Challenges; and
  • Comment on and discuss Questions/Challenges with others in the community.

As one of the main funders of health services research, NHLBI is an important partner for our community. If you or your organization operates in this space, we encourage you to submit a question or challenge before May 15.

You may also submit questions and challenges through an email form or through regular mail. More information on how to participate can be found on the NHLBI website.

If you do submit, we’d love to hear what you believe to be the preeminent questions and challenges facing the field. Let us know in the comments section below!


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It’s an incorrect, but convenient, shorthand to say that the ACA establishes state-based health insurance markets. Actually, the markets are finer grained than that. Each state can decide the number and configuration of coverage regions that will exist within its borders, and insurers must elect whether to offer plans on a region-by-region basis.* Across a region, for a given plan, premiums and benefits are fixed.

These within-state regions are the real markets. Do their sizes and configurations matter?

According to work by Michael Dickstein and colleagues, released in an NBER working paper, they do. This is intuitive. If there is some fixed cost of entry that’s largely independent of the number of potential consumers (market size), then an insurer should be more willing to enter a bigger market vs. a smaller one. (Such fixed costs could include those for marketing or for customer service centers, for instance.) Maybe bigger markets are better for competition and consumers.

But, what if a region’s geographic extent includes areas with different types of consumers or different kinds of provider markets? What if there are some consumers in one part of the region that are harder to satisfy than in others with the kinds of products the insurer is good at offering, say? Or what if one part of the region has a dominant hospital system that demands higher prices than in other parts of the region with less provider concentration? Given the constraint that a plan’s premiums and benefits are fixed over a region, some insurers might be less inclined to enter even a populous region that includes a subset of potential customers they cannot satisfy or areas where network establishment is too expensive. For them, the effective market is smaller than it appears.

Dickstein et al. examined insurers offering products in 33 of the 36 states that use healthcare.gov for their exchange. (The three states that use healthcare.gov they didn’t include — Alaska, Nebraska, and Idaho — were dropped for technical reasons.) All told, their data encompass 2,388 counties from 398 coverage regions, representing about 66% of the approximately eight million people who enrolled in an exchange plan during the 2013-2014 open enrollment period. For analysis of premiums, the authors examined those for the second-cheapest silver rated plan for a 51-year-old.

There is considerable variation in coverage regions across states. Some states, like Florida, allow each county to be its own coverage region. That state has 67 coverage regions. Texas divides its 254 counties into only 26 coverage regions, however.

Further focusing on smaller, 1,157 rural counties, the authors divided them into groups based on the size of the population of counties with which these rural counties are grouped into coverage regions. They found that the greater the population of a coverage region, the greater number of insurers offer plans and with lower premiums. But, with another analysis at a regional level, they found that as a coverage region grows in geographic extent, the opposite holds: less entry and higher premiums. If the latter is an indicator of greater heterogeneity of customers or provider markets, both sets of results are consistent with the intuition offered above.

Being grouped in a region with a large urban county increases the expected number of entrants by between .6 and .8 insurers. The bundling also leads to an average decrease in annual premiums of between $200 and $300. [... However,] controlling for population, increasing land area from the 25th to 75th percentile leads to a decrease in the log
number of entrants of between 6.5 and 15 percent. Premiums increase 7.0 to 8.3%.

These findings tell us that how states define regional markets matters, particularly how bundling rural counties with others affects market outcomes. In general, a bigger market promotes competition. But, the kind of bigness matters too: a market with a lot of consumers is good, but one very large in geographic extent is self defeating. That could be because of heterogeneous consumer preferences over wide areas and/or bundling more concentrated provider markets with ones less so.

These are interesting findings. Given our reliance on markets in the U.S. health system, and the benefits of competition, it’s worth understanding how best to organize them to encourage better market outcomes.

* It is possible for insurers to offer products only within a subset of counties in coverage regions, but only in rare circumstances, like when establishing an adequate network is not feasible. By email, Dickstein told me that of the 186,566 plans region-plans on healthcare.gov, only 3% are not offered in all counties in a region. “These are mostly ‘network plans,’ as the number goes down to 1% for PPO/EPO and up to 5% for POS/HMO,” he wrote.

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.

From the editors: AcademyHealth’s 2015 Annual Research Meeting features several sessions on marketplaces. To view the sessions, access the online agenda and search ‘marketplace’ in the search box.


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Place Matters

by Academyhealth on May 5, 2015

Written by Darrell J. Gaskin and Thomas A. LaVeist

On April 10, 2015, the Agency for Healthcare Research and Quality (AHRQ) released the latest version of the National Quality and Disparities Report, a Congressionally-mandated report that uses more than 40 national data sources and more than 250 measures to describe annual trends in access, quality, and disparities in health care.

There is clearly some good news. Coverage is increasing, particularly among blacks and Hispanics. After years with higher uninsurance rates compared to whites, the drop in uninsurance rates in 2013-2014 was 26.4 percent to 15.9 percent for blacks, and 40.3 percent to 33.2 percent for Hispanics. This trend indicates that the Affordable Care Act (ACA) is succeeding in making affordable coverage available for millions of newly-insured Americans so they can access health care when they need it.

In other good news, disparities have been eliminated for some health services, including immunization. Black and white children receive the measles-mumps-rubella vaccine at similar rates, and American Indian children receive hepatitis B vaccines at similar rates as other children. Hispanic and white adults who are obese received nutrition counseling and advice to eat fewer high-fat foods at the same rates–an improvement over 2004 figures showing half of white and 4 out of 10 Hispanics received similar counseling.

Quality of care also improved for most of the priorities in the National Quality Strategy (NQS), but overall quality and racial/ethnic disparities varied widely across the states and showed that some gaps were closing, while others were growing. For example, income-related disparities in two measures related to diabetes and joint symptoms grew larger.

Public reporting is vitally important to monitor progress toward meeting the national goal of eliminating disparities. But reporting at the national level cannot possibly capture the fact that differences in exposure to health risks and access to resources vary depending on where people live. Short distances on maps can translate to large differences in life expectancy.

Racially segregated communities — where many blacks and Hispanics live — tend to present greater health risks, partly because of higher poverty rates and also because of the lack of resources needed to live healthy lives (e.g., quality health care, healthy foods, and safe recreation). These communities have suffered for decades as a result of systematic under-investment by both the public and private sectors. Consequently, residents in these communities experience higher rates of mortality and chronic conditions. They have less access to medical care and use fewer health care services. Baltimore is a prime example of these health inequities. For example, out of 100 counties in a recent study, Baltimore ranks in the bottom 10 for income mobility for poor children.

AcademyHealth members are at the forefront of tracking and understanding disparities. They are developing and evaluating models and strategies to reduce and eliminate disparities. Some of this research will be on display at the Annual Research Meeting (ARM) in Minneapolis, MN, June 13-16, 2015. The Disparities Interest Group begins this discussion with a pre-conference meeting that will focus on the role of “place,” (both social and environmental) on health and possible solutions to reduce or eliminate health care gaps and health disparities. Presentations will introduce innovative methodological approaches in health equity research on health outcomes, health care delivery, health care quality, and health policy.

The ARM program also features several sessions addressing health care disparities. In particular, there will be a session based on AcademyHealth’s Diversity Roundtable recommendation that focuses on the role of place-based policies and diversity in reducing health disparities. We will follow this session with discussions on the 30-year anniversary of the historic “Heckler Report” on minority health and health care disparities. Taken together, these sessions will provide evidence about how much has been accomplished and how much remains to be done.

Darrell J. Gaskin, Ph.D., is Deputy Director, Center for Health Disparities Solutions and Associate Professor, Johns Hopkins University Bloomberg School of Public Health, and Vice Chair of the AcademyHealth Board of Directors.

Thomas A. LaVeist, Ph.D., is Director, Hopkins Center for Health Disparities Solutions and William C. and Nancy F. Richardson Professor in Health Policy, Johns Hopkins University Bloomberg School of Public Health


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This post was written by Gerry Fairbrother, Ph.D., a Senior Scholar at AcademyHealth.

The United States spends more than 2.5 times as much on health care as its peer nations and yet it constantly suffers from inferior health. A new article in Pediatrics, titled Higher Cost, But Poorer Outcomes: the US Health Disadvantage and Implications for Pediatrics, highlights the factors responsible for the United States’ health care disadvantage, comments on implications for policy, practice, and research, and proposes a call to action. The article, based on a symposium exploring the findings of an Institute of Medicine (IOM) Report on relative health disadvantages between the United States and peer nations, includes research I worked on with other professionals in my field, including Lisa Simpson, Astrid Guttman, Jonathan Klein, Pauline Thomas, and Allison Kempe.

The original IOM report found at that all of these nations, including the United States, have sufficient national wealth to support a variety of health and social services policies and programs to address the health needs of their populations. Yet a pervasive disadvantage exists for the United States’ population beginning at birth and affecting all age groups. The substantially higher rates of infant mortality, below average birth weight, and preterm birth have been known for years. What is perhaps less well known is that this disadvantage continues through childhood and adolescence. For example, United States adolescents have higher all-cause mortality, including mortality from injuries and violence. Additionally, obesity among United States adolescents is more than twice the mean and the prevalence of diabetes is in the top third, compared with peer nations.

My colleagues and I agree that reversing the sub-optimal health outcomes in the United States will require a wide-range of policy solutions at all levels of government. One of the difference in policies and spending between the United States and other peer nations is that the latter spend much more than the United States on social services such as education, home visiting, maternity leave, and food security. In response, we call for recalibrating spending for health and social welfare, with greater investments in social services that have been proven protective in other peer nations such as high-quality early care and education, or for those that support families with young children, such as paid parental leave, subsidies, income transfers and other social programs.

My colleagues and I also recommend additional focus on the establishment of cross-sectoral governance such as the ones in Canadian provinces and Western Europe, with linkages established between health, welfare, education and other social services. Critical to achieving this this type of governance is cross-sectoral linked data and research refocused on the most leading causes of mortality and morbidity. In addition, focus on translational research that informs that development of effective policy and system and service intervention is needed.

Together, we acknowledge that generating action to address the United States health disadvantage will not be easy. First, there needs to be a collective understanding that the United States health care system is not the greatest in the world, but rather one of the worst among high income countries when health outcomes are measured. Public awareness of this and even outrage may be necessary to spur policy action. In addition, it is clear that solutions for improving health for children will require solutions outside of the health care sector.

It is a tragedy for all Americans, especially children, that the health of Americans does not meet the standards that exist in peer countries. Given the evidence, the question becomes, “what will we do about it?”

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