By Dana Connors, AcademyHealth

Year two, under our belts. Concordium 2016, a practical health data rodeo, once again successfully brought together health data lassoers, ropers and bronco riders in the form of data scientists, informaticians, researchers, patients and their representatives, clinicians, policymakers and other experts to address the changing field of health data analytics, and bring about delivery system transformation. The health care landscape is changing rapidly, both in implementation and from the policy perspective as we emphasize the importance of quality over quantity. The concept of a learning health system is cropping up all over the country, but no one knows quite yet what that means or how delivery systems will look.

While there are plenty of cow-pokes in the field investigating the pastures they intuitively sense are greener, Concordium 2016 attendees provide this turbulent landscape with strategy and tactics to manage the wild west of big data production and utilization. The data sheriffs are officially in town and they are doing their best to provide governance and leadership to achieve interoperability of resources and quality of records. This year’s panel presentations, posters, and demonstrations pioneered new tools and techniques working to manage data siloes and implement analytics, which will yield meaningful and fruitful results in outposts across the country.

However, the deal is not sealed. Concordium’s Challenge Workshops were a big hit with the town folk this year, as they highlighted work in progress and publications still in draft form. These town hall type meetings offered an environment where all participants could add their two cents to influence the direction of cutting edge projects and publications. Leaders who presented their work will use these diverse perspectives to refine the work they are doing in their own systems, and will soon disseminate it for the benefit of our entire health care system.

This diversity of perspective is a hallmark of the Concordium meeting, and the variety of attendees was an indicator of a new dawn in democratic decision making in health care. For a good part of our health care history it has been the physician alone who has dictated health care planning and outcomes. No one looking at the wealth of patient data and patient reported experience today believes that this system led to beneficial outcomes for the people requiring care. We are especially proud of the broad representation from patients, caregivers, and consumers who were present, and we are pleased that Concordium 2016 was accredited by Patients Included for the second year in a row for our focus on including patient, caregivers and consumers in the planning, execution and presentation of the meeting. At Concordium 2016 patients and their representatives got their say, and we are confident that all citizens of our present health care wild west will have an opportunity to shape the order of a new landscape.

This is our manifest destiny, folks. We’ll be using big data for years to come, and establishing the rules to guide our work and manage usage, without hurting each other in the process, is our present challenge. We are still roaming free, but civilized solutions are in sight, and the folks at Concordium 2016 got down to the difficult tasks of thinking through, communicating, and shaping our path to get there. We may witness some political shoot-outs in the near future, but Crystal City served as a quiet range for cultivating collaboration, and we are confident that the right folks are successfully working together to transform the face of health care.


Dana E. Connors serves as the project manager for the Electronic Data Methods (EDM) Forum, an AcademyHealth project supported by the Agency for Healthcare Research and Quality (AHRQ). In addition to programmatic development for the Concordium meeting, he nerds out on budgets, contracts and project work plans.  He is helping to manage the continued growth of eGEMS, an open access journal of the EDM Forum focused on using electronic health data to advance research and quality improvement and supports stakeholder outreach, collaborative projects, and the sustainability efforts of the EDM Forum.


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Every time health care reform comes up for debate, I see people arguing about whether a publicly or privately funded system would be better. The Affordable Care Act, in an attempt to forestall this debate, decided to split the baby, and give half of its newly insured beneficiaries public insurance (Medicaid) and half private insurance (insurance exchanges). But this isn’t really true. Yes, the half of people getting expanded Medicaid are getting public insurance, but the vast majority of people getting private insurance are also getting public funds (subsidies) in order to purchase their private insurance.

In other words, even though we expanded private insurance, we’re doing it with taxpayer dollars. Overall, the reduction in the uninsured was due to mostly public spending, with relatively little private spending overall. This isn’t rare in the US health care system. A recently released policy brief from the UCLA Center for Health Policy Research, “Public Funds Account for Over 70 Percent of Health Care Spending in California“, explains this quite well.

If you just look at a simple analysis of Medicaid, Medicaid, and CHIP, you might find that about 45% (or less than half) of total US health care spending is public. But that ignores a ton of health care spending that is also paid for with public funds outside those programs. In an effort to document the different, researchers looked at health care spending in California. They included four major public funding categories:

  1. Payments for public health insurance programs (like Medicare and Medicaid)
  2. Government payments for health insurance coverage for public employees (like me at Indiana University, for instance)
  3. Tax subsidies for employer-sponsored insurance and those purchasing exchange plans who earn less than 400% of the poverty line
  4. County health care expenditures

Everyone accounts for #1 in their analyses. Most people also account for #4. Too many ignore #3, though. The tax expenditures for employer-sponsored health insurance are massive in the US, and the exchange subsidies aren’t cheap either. Almost everyone ignores #2, though. All the people who work for the government, who work for public schools, or the police department, etc. all get private insurance, but you (taxpayers) are paying for it. People like me! I’m grateful to you, by the way, but I’m “on the public dole” as much as anyone in this respect.

In California, health care expenditures in 2016 are estimated to be more than $367 billion. That’s one state. Let that sink in for a minute. But much of that is public health expenditures. About 27% are from Medi-Cal/Healthy Families. About 20% is Medicare. The tax expenditures for employer-sponsored private insurance are 12%. though. Public spending for private insurance is 4%, county health expenditures are 3%, ACA  exchange subsidies are about 2%, and “other” government programs are about 3%. Add all that up, and public health expenditures in California are almost $261 billion, or about 71% of all health care spending.

What’s left for private? About 16% of spending is employer shares of premiums, 6% is employee shares of premiums, 4% are out-of-pocket spending for covered benefits, and 3% are premiums for individually purchased plans.

Some caveats: California spends a bit more in public funds than the rest of the country. Their Medicaid expenditures are a bit higher, as their 33% of the state being on Medicaid is higher than the national average. They also have a bit more in tax expenditures for employer-sponsored private health insurance than the national average. The national average for public share of health care spending is 65%, not the 71% they have.

But even that might give some pause. Even nationally, more than two-thirds of health care spending is being done by taxpayers, through public funds. We may have a “private” health insurance system. But much, much more of it is being paid for through public funds than many think.



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For two days, Concordium 2016 brought together the best and brightest in the fields of health data and delivery system transformation. The meeting showcased innovation and emerging science and promoted collaboration in an effort to improve health.

The conference kicked off with welcome remarks from AcademyHealth’s President and CEO Dr. Lisa Simpson and Senior Director Erin Holve, and Director of the Agency for Healthcare Research and Quality, Dr. Andy Bindman.

Key takeaways from selected sessions are recapped below by AcademyHealth staff:

Opening Plenary: Right-Sizing Measurement for Health Care
Moderator: Eduardo Sanchez, American Heart Association ; Panelists: Santi Bhagat, Physician-Parent Caregivers; Helen Burstin, The National Quality Forum; Darshak Sanghavi, OptumLabs

Monday’s opening plenary tackled how to measure achievements in providing better health at lower costs. Each panelist provided a different perspective and focused their comments on different measurements and tools being used by the field, including those that add value to care and those that do not. Several common themes emerged, including a discussion around the number of measures; the alignment of measurement’s purpose to improve health, and the need to look at health outcomes from a large population level. Dr. Bhagat represented the patient community and reminded attendees of the importance of recognizing health inequities in all demographics.

The panel’s Q&A included conversation about the deimplementation of low value care, the neglect of access in the conversation about quality health, and effective measurements.

This session aligned with AcadmeyHealth’s commitment to addressing quality and value in health care.

Meaningful Use: Developing Computer Algorithms to Identify Potential Adverse Events from Electronic Medical Record Data

Moderator: James Naessens, Mayo Clinic; Discussants: Earl Etienne, Howard University and Jonathon Nebeker, University of Utah School of Medicine and Department of Veterans Affairs; Speakers: James Moriarty, Mayo Clinic and Hongfang Liu, Mayo Clinic.

This panel positioned existing approaches for detecting hospital adverse events (HAE) that are based on manual chart review or administrative data against the rapid adoption of electronic medical records (EMRs) and the accelerated advance of health information technology (HIT). The panel discussed their efforts to detect HAEs by applying advanced analytics on EMRs offering a potentially powerful alternative to either administrative data or labor-intensive manual chart reviews for HAE surveillance.
Discussion topics included:

  • Data that is deliberately missing from the patient chart must be taken into account when investigating HAEs
  • Natural Language Processing (NLP) as a way to incorporate chart reviews into the EMR
  • Why utilization and publication of NLP have not increased in recent years

This session aligned with AcademyHealth’s pursuit to improve patient care through evaluation and management of adverse events, and incorporates the use of patient data and HIT in quality improvement.

Multi-Sector Community-Based Data Sharing Collaborations
Moderator: Peter Eckart, Illinois Public Health Institute; Panelists: Alison Rein, AcademyHealth; Karen Hacker, Allegheny County Health Department; Melinda Buntin, Vanderbilt University, Nashville, TN

Data Across Sectors for Health (DASH) and the Commmunity Health Peer Learning Program (CHP) joined forces once again at Concordium for a presentation on their collaboration project, All In: Data for Community Health. The session began with an overview of DASH and the CHP Program and their commitment to sharing information across sectors in order to build capacity drive community health improvement through the All In network. The overview was followed by presentations from two communities: the Allegheny County Health Department and the Nashville Infant Mortality Project. The Q&A session touched on the factors of motivation for collaboration and evidence-based community interventions.

This session, and the CHP Program, align with AcademyHealth’s belief that both the production and use of evidence from health services and policy research can improve health, health care, and public health.

Lunch Plenary: Leadership, Data Science, and Culture Change in Health
Chair: David Chambers, National Cancer Institute; Panelists: Bechara Choucair, Trinity Health, former Commissioner of the Chicago Department of Public Health; Vivian Lee, University of Utah School of Medicine; Glenn Steele, xG Health Solutions

Over lunch, attendees heard from a panel of leaders from different settings including academia, government and the private sector. The panel highlighted panelists’ leadership and culture change challenges and successes in delivery system transformation efforts. Discussion on the panel ranged from the philosophical – how to combine purpose, mastery and autonomy to motivate physicians – to the specific – publicly posting patient satisfaction data to improve quality and using social media to encourage reporting of food borne illnesses.

Questions from the audience included:

  • How can systems work with patients to ensure their perspective is included in culture change efforts?
  • What is the responsibility of the health care system to help patients develop appropriate goals that encourage quality care?
  • What are the best methods for disseminating innovations to others?

This session aligned with AcademyHealth’s mission to move knowledge into action by drawing on the expertise of a vibrant and diverse community.

Telehealth: An Idea Whose Time Is Still Coming?

Chair: Margo Edmunds, AcademyHealth; Panelists: David Cattell-Gordon, the University of Virginia; Neal Sikka, the George Washington University Hospital; Bernadette Loftus, he Permanente Medical Group

With the telehealth market growing fast, consumers are beginning to expect health care professionals to use the same technologies that other industries are already using, including videoconferencing, mobile apps, and web portals. But there are still a lot of myths and misperceptions among providers about what it takes to provide remote services to patients, and many providers have been slow to adopt these new technologies. In this session, three early adopters of telehealth shared their experiences with telehealth, including how and why they got started, what services they provide, and fielded questions from the audience.

Questions from the audience included:

  • How do telehealth methods affect the patient-provider relationship and what can be done to ensure that relationship remains effective?
  • What role should patient satisfaction metrics play in measuring the effectiveness of telehealth services?
  • How can telehealth extend the number and capacity of caregivers who might otherwise lose their ability to contribute?

This session aligned with AcademyHealth’s efforts to address the needs and concerns of the filed in a changing environment for health and the health care system.

Unleashing the Power of Patient Registries through Harmonized Outcomes: An Early Test of the Outcomes Measure Framework in Atrial Fibrillation
Moderator: Elise Berliner, Agency for Healthcare Research and Quality; Speakers: Richard Gliklich, Better Outcomes; Paul Wallace, AcademyHealth; Lara Slattery, American College of Cardiology

In the panel’s opening, Dr. Berliner explained that there is currently significant variation in both the types of information collected and the types of outcomes measured in patient care, even within a given clinical area. Therefore, the Agency for Healthcare Research and Quality (AHRQ) is attempting to address fragmentation and variation by supporting a more harmonized and standardized approach to defining outcome measures and usage by developing a patient registry. The conceptual foundation for this work lies in the AHRQ-funded development and refinement of the Outcomes Measure Framework (OMF), a conceptual model for classifying outcomes relevant to patients and providers across most conditions. The Challenge Workshop was used as a forum to test the feasibility of using the OMF for classifying and ultimately harmonizing outcome measures by applying it to a clinical area test case – atrial fibrillation (AFib).

Question/discussion topics included:

  • Do the relevant outcome measures for AFib fit within the OMF?
  • Are there ‘cross-cutting’ outcome measures that are relevant for AFib (i.e., outcome measures that are also used in other condition areas)?
  • What is the “right” level of clinical specificity for data definitions? What are the tradeoffs in achieving consistency versus meeting individual registry needs?

This session aligned with AcademyHealth’s work to minimize data silos and improve health outcomes through appropriate identification and efficient use of patient data.

Exchanging Data to Improve Population Health: Infrastructure Protection Meets Consumer Protection
Moderator: Robin Strongin, Amplify Public Affairs, LLC Panelists: Peter Levin, Amida Technology Solutions; Kshemendra Paul, White House Information Sharing & Access Inter-agency Policy Committee

This concurrent session shed light on the bright spots in health and information sharing despite persistent barriers and public concerns. Kshmendra Paul discussed the evolution of open data in government and the many interactions between the health community and the Department of Health and Human Services. Peter Levin emphasized the move to value-based care and how data sharing will feature in that shift. This interactive panel was followed by a vibrant Q&A session, during which participants asked questions about:

  • The challenges in achieving interoperability because of concerns over security and privacy
  • Linking criminal justice and health data
  • The shift from a confrontational relationship to an aligned one between insurers and patients

This session aligned with AcademyHealth’s organizational goal to advance the science of health services and policy research production and use.

Day two brought more data-related challenges and opportunities to the fore with sessions on access, practical considerations of large data projects and the use of storytelling to communicate complicated data.

Plenary: No Wrong Door: Improving Health Access Across Sectors
Moderator: Gilbert Salinas, Rancho Los Amigos National Rehabilitation Center Panelists: Karen Hacker, Allegheny County Health Department; Ivor Horn, Seattle Children’s Hospital; and Jerry Krishnan, University of Illinois Hospital and Health Sciences System

Day two’s lunch plenary focused on the role of data and service integration in improving health access and optimization across sectors. Gilbert Salinas framed the conversation with a call for greater attention to metrics and data collection around underserved communities, and an evaluation of how the health industry is performing around disability competent care. Panelists provided examples of the difficulty behind integrating social determinants of health in efforts to optimize health. Common themes included health care access, trust issues within data sharing partnerships, and challenges associated with government inaction. The Q&A included discussion around community leadership in health system reform and social influencers of health.

This session aligned with AcademyHealth’s belief that diverse perspectives lead to richer and more nuanced understanding of issues related to health and the performance of the health system.

Implications of Health Policy for Research and Clinical Practice

Moderator: Richard Dutton, US Anesthesia Partners; Speakers: Natalia Chalmers, DentaQuest Institute; Prashila Dullabh, NORC at the University of Chicago; Jonah Geddes, Oregon Health & Science University; Jill Huppert, AHRQ.

This panel explored the (often unintended) consequences of developing a data stream and managing it. An example of work done across the dental network in Maryland, Kentucky, and Rhode Island was presented and showed increase use of emergency rooms as a safety net for oral care. Panelists also explored emergency department practice decisions and guidelines for screening cervical cancer in young adults.

Question/discussion topics included:

  • When you take on a large data intensive project, how are you able to manage the costs and realize utility?
  • When representing complicated information to patients and their surrogates, it is important to make information accessible and meaningful.
  • Do guidelines really lead to practice change? Yes, it looks like they do in hospital settings, but less locally.

This session aligned with AcademyHealth’s work to explain and inform policy implications in practice and in the development of research.

Plenary: We’re All Data Consumers: Personal Health Technology and Storytelling
Chair: Erin Holve, AcademyHealth; Panelists: Anjali Jain, the Lewin Group; Amy Abernethy, Flatiron Health; Megan O’Boyle, Phelan-McDermid Syndrome Foundation

Big or small, all data is personal. The final session of this year’s Concordium acknowledged that science and evidence are most effective when they reflect individual stories and experiences. Panelists represented varied viewpoints highlighting the roles of clinicians, patient advocates, and researchers in bringing data, data use and its impact together. Comments from the panel and the audience highlighted challenges of conducting and translating science in reliable and valid ways while paying careful attention to lived experiences of individuals.

Topics discussed included:

  • What is the key ingredient to narratives that work?
  • How does data completeness (or incompleteness) affect our ability to translate science in compelling ways?
  • What role does professional training or patient education play in getting more meaningful data that results in more powerful stories?

This session aligned with AcademyHealth’s goal to promote the visibility and relevance of health services and policy research.


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As I documented in my previous post, syringe exchange programs (SEPs) reduce the spread of infectious diseases (like HIV and hepatitis B and C), promote drug treatment among injection drug users, and save money. The savings come, in large part, from averted health care spending — treating HIV and hepatitis B and C is expensive — much of which would otherwise be borne by public programs. (Half of people with AIDS are on Medicaid, for example.)

So, on financial grounds alone, SEPs are in taxpayers’ interest. This and other benefits of SEPs have been known for decades. Yet, the law prohibits use of federal funds to purchase clean syringes for SEPs, though, as of this year, it does allow support for other aspects of SEPs. Many states and municipalities also restrict SEP operations. On what grounds?

Neil Hunt and colleagues summarized criticisms of drug use harm reduction approaches, including SEPs. Among them, many opponents of SEPs think they don’t work or will promote drug use, contrary to the evidence.

It’s entirely possible, of course, that some policymakers and segments of the public are unaware of or misunderstand the research on SEPs. But, that’s not the whole story. Injection drug use is considered by many to be not just unhealthy but immoral. For this reason, injection drug users, like the broader population with substance use disorders, are often stigmatized. A negative attitude toward them can promote willful misunderstanding or biased interpretation of research on harm reduction of drug use.

In an insightful analysis of the politics and policy of SEPs, Elizabeth Bowen explained the misapplication and marginalization of research. In doing so, she adopted the framework of William Gormley, which illuminates key aspects of morality-driven politics and policy that differ from, say, economically-driven ones. The framework characterizes policy issues along two dimensions: salience and complexity (see figure below).


SEPs are at the intersection of two public health issues: injection drug use and infectious disease. These have potentially large and feared effects on individuals, their families, and communities. Therefore, they — and SEPs — are salient in a way that, say, the manner in which motor vehicles are inspected is not. At the same time, SEPs are simple — the exchange of used for clean injection equipment. They are readily grasped in a way that, say, the patent regulation is not.

Bowen explains that for highly salient and low complexity issues like SEPs, values and emotions tend to dominate over science. (It’s the morality, stupid.) From politicians to journalists to citizens, on such issues everyone has an opinion. We both care deeply and we are not confused about what policy is on the table. Why bring evidence to bear when our gut tells us what’s right? It’s very easy to slip into a “data-free zone.” Moreover, when policy is morality, not economically, driven, what does it matter whether it saves money or not?

Morality-driven policies, including those governing SEPs, abortion, the death penalty, and sex education are never settled. Even when a law is passed or a high court rules, the debate goes on. They perpetually garner media attention and are the focus of symbolic legislative action, like passing bills that have no policy impact but serve to “send a message” or to force legislators to pick a side.

Where does that leave research and researchers? Sean Allen, Monica Ruiz, and Allison Rourke documented the role of evidence in SEP policy change in three cities: Baltimore, Philadelphia, and Washington DC. Research was used differently in each case.

Baltimore’s legalization of SEPs in 1994 followed, perhaps, the most hospitable policy environment for SEP research. Allen, Ruiz, and Rourke wrote,

Baltimore primarily used research evidence in an instrumental manner to directly facilitate and guide policy change. One interviewee captured this instrumental use of research evidence as follows: “… I think Maryland was able to … fend off bad stuff and make policy decisions based on science.”

This is evidence-informed policymaking at its best. It doesn’t always go so smoothly. Sometimes advocates for change need to use research differently and do more work.

For example, in Philadelphia, policymakers were initially not ready to hear the evidence. So, research played a different role there in supporting legalization of SEPs in 1992. After an illegal SEP commenced in 1991, efforts were first made to change public opinion about it.

Activists accepted that policy change may be best achieved by first changing public opinion about SEPs and then empowering constituencies to put political pressure on legislators to change policy. [...] This indirect, conceptual application of research evidence was illustrated by an interviewee who stated, “… you educate community, then you educate constituencies that eventually pressure politicians or, or vote for politicians.”

Though Congress eventually permitted municipal funding of SEPs in DC in 2007, the debate exemplifies how research is frequent misused or ignored on morality-driven issues.

[O]pponents’ use[d] evidence [...] out of context, misinterpreting research findings, or selectively picking language from research articles that they thought supported their claims. [...] Interviews suggested this unwillingness was derived from persons’ fears [...] and based on moral ideologies. [...] “It is possibly the most crazy-making thing about this issue … [Politicians] [...] saying, ‘I don’t care what the data say, I won’t have it’.”

The lesson for researchers is that their work can make in impact, even on morality-driven issues. But it may require more elaborate application than communicating facts to policymakers. Because elected officials, or those whose jobs rely on them, need simple messages that convey cultural alignment with their constituents, sometimes the culture needs to change before policy can. For some issues, communicating research to broad, lay-audiences may help support the cultural change that’s prerequisite to policy change.

Austin B. Frakt, PhD, is a health economist with the Department of Veterans Affairs, an Associate Professor at Boston University’s School of Medicine and School of Public Health, and a Visiting Associate Professor with the Department of Health Policy and Management at the Harvard T.H. Chan 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, Boston University, or Harvard University.


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By Megan Collado, AcademyHealth

Amid coverage of Olympic feats and the presidential election, two questions have grabbed health policy headlines as summer concludes: 1) Will the ACA marketplaces remain competitive? and 2) Will health insurance be affordable? In particular, decisions by major US health insurance companies, like Aetna, to leave the health insurance marketplaces established under the Affordable Care Act (ACA) signal concerns about whether there will be sufficient competition to promote affordable plans for consumers. Reports of premium increases have raised questions about affordability, although for many, these increases may be offset by marketplace subsidies.

To answer these and other related questions, the Robert Wood Johnson Foundation created the Policy-Relevant Insurance Studies (PRIS) program in 2015. This program, managed by AcademyHealth, seeks to fund quick turnaround, empirical research studies that examine highly policy-relevant questions related to health insurance markets. The 2015 PRIS grantees examined a diverse array of topics, including: Medicaid expansion and the effect on personal finances, self-insurance in the small group market, the ACA’s risk adjustment mechanism, and the ACA smoking penalties.

The second round of funding under this program was announced in early 2016, and seven grants were recently awarded. Many of the grantees will address the pressing questions around competition and affordability on the ACA marketplaces.

For example, Christine Buttorff at RAND Corporation will examine the potential consequences of the current ACA tax credit structure and the implications of changes in the benchmark plan on consumers’ ability to afford continuous coverage.

Maria Polyakova at Stanford University will consider affordability of marketplace plans from another important angle—risk protection. She will assess the extent to which financial risk protection from out-of-pocket spending varies across marketplace plans and develop methods to convey the level of risk protection provided by plans to the public.

Other 2016 PRIS grantees are examining issues related to competition and stability in the marketplaces. Stan Dorn at the Urban Institute will address risk selection during special enrollment periods to identify whether current risk adjustment mechanisms adequately adjust for higher-risk enrollees. David Howard at Emory University will assess the impact of provider-led plans on competition and explore whether these plans have lower premiums than plans marketed by traditional insurers.

At AcademyHealth, we believe that policies that affect health and the performance of the health system should be informed by the best and most relevant evidence. To that end, we are working with all of the PRIS grantees to ensure their findings reach policymakers and other decision makers working on these issues. We bring grantees to Washington, D.C., to brief staff at relevant agencies, and we prepare syntheses of published research to highlight key findings and implications for policy.

With the 2017 open enrollment period on the horizon, health insurance affordability remains a critical concern for the remaining uninsured, and the competitiveness of the marketplaces goes hand-in-hand with the availability of high-value, affordable insurance products. The 2016 PRIS grantees are poised to contribute important evidence to further our understanding of competition and affordability on the ACA marketplaces. Stay tuned.
Megan Collado, M.P.H., is a senior manager at AcademyHealth, where she co-directs and supports a number of Robert Wood Johnson Foundation grantmaking programs and is the Project Director of an AHRQ-sponsored conference grant that convenes policy audiences to discuss the evidence and future research needs related to health care costs, financing, organization and markets. 



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Syringe exchange programs (SEPs) provide free, sterile injection equipment to injection drug users and collect their used equipment. SEP’s primary purpose is to reduce the blood borne infectious disease like HIV and hepatitis B/C, all of which are disproportionately prevalent among injection drug users. Some programs also offer other services (e.g., condom distribution, infectious disease testing and prevention education) and can be a gateway to drug treatment programs. The preponderance of evidence suggests that, for all these things, they work and that they’re cost effective or even cost saving. Let’s review.

Improving Injection-Related Practices. Many studies show that injection drug users who visit SEPs use safer injection practices.

  • A meta-analysis of 47 studies by Ksobiech (2003) found that needle sharing and borrowing declined among SEP visitors.
  • Hagan et al. (1993) interviewed over 204 users of a Takoma, Washington SEP. They reported no change in injection frequency, but a decline in injections with used equipment.
  • After Vancouver increased its distribution of clean syringes, it experienced 40% declines in syringe borrowing and lending, according to Thomas Kerr et al. (2010).

Reducing Blood Borne Viral Infection. Safer injection practice is a process measure. Does it translate into reduced incidents of infectious disease among injection drug users? There’s a lot of evidence it does.

  • Hurley et al. (1997) compared changes in rates of HIV infection among injection drug users in 29 cities with SEPs to 52 cities without them. In those with SEPs, the HIV infection rate fell an average of 5.8% per year compared to a 5.9% annual increase in those without SEPs.
  • Hagan et al. (1995) studied injection drug users who did and did not use a Tacoma, Washington area SEP — one of the first to open in the late 1980s. Not using the SEP was associated with six and seven times greater risk of hepatitis B and C infection, respectively. However, this was a relatively small study, with only about 50-60 subjects, depending on outcome.
  • A much larger study — of over 1,600 subjects — by Des Jarlais et al. (1996) found that injection drug users who didn’t visit a New York City SEP in the early 1990s were over three times more likely to contract HIV, compared to those who did visit one.
  • Kwon et al. (2012) estimated that, among injection drug users, SEPs in Australia reduced cases of HIV and hepatitis C by between 34-70% and 15-43%, respectively.
  • For the WHO and in a separate, similar paper, Wodak and Cooney (2006) reviewed and assessed the SEP research literature, concluding that SEPs reduce HIV infection substantially.
  • HIV incidence fell after Vancouver increased its distribution of clean syringes (Thomas Kerr et al. 2010).
  • According to a study by Ruiz et al. (2016), when the ban on municipal funding of SEPs in DC lifted, the number of incident HIV cases among injection drug users fell 70%. (See the figure just below.)

DC ban lift

Not Increasing Injection Drug Use. A significant concern among many is that the provision of free, clean injection equipment will promote injection drug use. The research says it won’t.

  • That’s the conclusion from the literature review by Wodak and Cooney (2006) who wrote, “[A]fter almost two decades of extensive research, there is still no persuasive evidence that NSPs increase the initiation, duration, or frequency of illicit drug use or drug injecting.”
  • Hagan et al. (2000) found that, relative to those who had not visited a SEP, Seattle-area injection drug users who had were more likely to report a reduction or cessation in injection.
  • Guydish et al. (1993) compared San Francisco drug treatment admissions two years before to two years after SEP implementation (1987-1990). According to the study, SEPs were not associated with increasing drug use (overall or injection-based) or needle-sharing behavior. However, “[n]eighborhoods without needle-exchange sites showed a greater increase in proportion of admissions for injection drug use, and in frequency of injection, over time.”
  • In an analysis of about 5600 San Francisco injection drug users over 5 years, Watters et al. (1994) found that frequency of injection fell and average age of injection drug users rose as a higher proportion of them used SEPs. These findings do not support the hypothesis that SEPs promote greater injection drug use.

Promoting Drug Treatment. SEPs are an effective way to reach a population in need of drug treatment.

  • Wodak and Cooney (2006) conclude that there is reasonable evidence that they increase recruitment into drug treatment programs.
  • Hagan et al. (2000) found that “[n]ew exchange users were five times more likely to enter methadone treatment and ex-exchangers were 60% more likely to remain in methadone treatment over the 1-year study period.”
  • Among Baltimore injection drug users, those that had attended a SEP were more likely to enter a drug treatment program, according to work by Strathdee et al. (1999).

Cost-Effectiveness. In their literature review, Wodak and Cooney (2006) conclude, “a number of careful studies in several developed countries and some transitional countries have demonstrated convincingly that NSPs are cost-effective.” However, they’re more than that — they’re cost saving.

  • Lurie et al. (1988) calculated that if the HIV prevalence rate among injection drug users were above 2.1% then SEPs would be cost-saving. (In the U.S., 3.6% of injection drug users have HIV.)
  • According to Holtgrave et al. (1998), providing every injection drug user with all the clean needles he or she would avert enough HIV cases to be cost saving.
  • Laufer (2001) estimated that New York State SEPs cost about $21,000 per averted HIV case in 1996. Because the lifetime costs of HIV exceed this amount, the program was cost saving. (Today, lifetime costs of an HIV infection are about $380,000.)
  • Lurie and Drucker (1997) estimated that a national implementation of SEPs would avert up to nearly 10,000 HIV infections, saving over three-quarters of a billion dollars in current dollars.
  • Ruiz et al. (2016) estimated that a policy change that permitted use of Washington DC municipal funds for SEPs saved the city over $44 million in averted HIV cases.
  • In their study of Australia’s SEPs, Kwon et al. (2012) calculated that a dollar invested in them returned $1.3 to $5.5 in averted health care spending.
  • A SEP in Ontario saved four times more than it cost, according to Gold et al. (1997).
  • Cabasés and Sánchez (2003) estimated that a SEP in Spain was saved more than it spent, again due to averted HIV cases.
  • Nguyen et al. (2014) found that for additional SEP funding in the US between $10 to $50 million per year, 194–816 HIV infections would be averted, translating into a return on investment between 7.58–6.38. (See the figure just below.)


Some studies differ. It is important to acknowledge that findings contrary to some of the above exist. For this reason, in a review of reviews, Palmateer et al (2010) found “insufficient” and “tentative” evidence to support effectiveness of SEPs in preventing hepatitis C and HIV transmission, respectively. This, however, is not the same thing as concluding SEPs do not reduce transmission. Additionally, as discussed in Wodak and Cooney (2006), studies that don’t find SEPs effective in preventing transmission of these diseases are more likely to have been conducted in settings in which injection drug users have legal access to syringes through local pharmacies. “[I]n settings with [SEPs] but without additional legal access to sterile injecting equipment, there were no negative or null findings,” they wrote. This only reinforces the idea that access to clean needles by some mechanism — SEPs and legal sale at pharmacies among them — is an effective means of improving public health and saving downstream health care costs.

Austin B. Frakt, PhD, is a health economist with the Department of Veterans Affairs, an Associate Professor at Boston University’s School of Medicine and School of Public Health, and a Visiting Associate Professor with the Department of Health Policy and Management at the Harvard T.H. Chan 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, Boston University, or Harvard University.


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By Gilbert Salinas, M.P.A., Rancho Los Amigos National Rehabilitation Center and Los Angeles County Department of Health Services

Before you settle in to read this blog post, do me a favor and check your smartphone. Are you tracking your steps? Fitbit recommends10,000 steps a day. Are you going to hit that? I’ll check mine, too. It’s evening as I write this and…my app has recorded zero steps.

But that’s not because I lead an unusually sedentary lifestyle. Today, I actually speed pushed over two miles before going to work, pushed to and from my car, rounded on patients and went to the market after work. The reason I have zero steps logged is because the app can’t track my movement in my wheelchair.

I share this example to illustrate the critical aspect of the patient perspective. While technology does hold a lot of potential for improving health outcomes and the patient experience – even for transforming health care as we know it –it can’t do any of that without considering the patient. When you have a goal as big as transforming health care, you need all of the help you can get.

As a former community advocate working on violence prevention, I am all too familiar with the common disconnect between health care and the rest of the world. When I made the switch to health care about 10 years ago, I found myself continually bringing community aspects into the discussion. We must consider the experiences of our patients, where they play, pray and live. I don’t think we can be effective without that holistic perspective.

That’s why I’m looking forward to attending Concordium early next month where people from across diverse sectors will gather to talk about how data and knowledge can transform health care. When I attended and spoke at the inaugural Concordium meeting last year, I was struck by the variety of perspectives invited and welcomed during the conference and the creative energy that resulted.

I found myself attending sessions with physicians using electronic medical records in innovative ways to help their patients, informatics experts talking about predictive analyses, and policy works highlighting challenges and solutions to issues like patient privacy. In between sessions, I would get caught up in conversations in the hallway with people such as a developer working on a new app to increase health literacy or a fellow patient opening up to share tips and advice related to my own health journey. It was unlike many other meetings I’d attended where people are segregated by area of expertise.

The best part was that these relationships and connections extended beyond the confines of the conference center. After the meeting, I was invited to help new colleagues I met at the meeting as they worked on a national strategy to connect information systems and access integrated data from different sectors to improve communities’ capacity to improve health. This wasn’t just feel-good networking; this was real action. I’m looking forward to see what will come out of this year’s meeting.

With health care changing faster than ever, we need to be sure we’re not leaving anyone behind. We need more opportunities like Concordium, where we bring diverse perspectives together to think critically about how we collect data, how we use data, and how we work to continually improve that process. We need everyone at the table for this discussion so that we can hold each other accountable to the high standard of improving health and health care for everyone.

I hope I’ll see you there as well. There is still time to register. We can compare our fitness apps in between sessions. I’ve found some good ones that accurately track my activity, so come prepared!

Gilbert Salinas is the Chief Clinical Officer at Rancho Los Amigos National Rehabilitation Center (RLANRC), as well as the interim Director of Performance Improvement for Los Angeles County Department of Health Services (LA DHS). He also serves on the Concordium Advisory Committee and is a speaker at Concordium 2016.


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By: Andrea S. Rodriguez Lebron, AcademyHealth

Over the past ten years, access to healthcare has been a main topic of discussion in the United States. Passage of the Affordable Care Act (ACA) expanded access to more affordable health insurance for many Americans, though uncertainty remains over patients’ ability to gain timely access to care within their network, particularly for individuals purchasing insurance sold through Markeplaces established by the ACA. A recent study in Health Affairs explored this issue of network adequacy for insurance plans sold inside and outside insurance Marketplaces. Authors found that gaining timely access to primary care providers is challenging regardless of where the plan was purchased and attribute many of these issues to errors and inconsistencies in provider listings within the networks.

In the study by authors Haeder, Weimer, and Mukamel, researchers posed as “secret shoppers” to simulate and compare the experiences of health insurance consumers in California with plans in two different markets: (1) the Covered California insurance Marketplace, and (2) equivalent “mirrored” plans sold outside of the Marketplace. Using provider directories, the secret shoppers acted as potential patients and called 70 physician offices in each of the five California insurance Marketplace pricing zones studied. For all calls, one of the secret shoppers presented with insurance through the Marketplace, and the other with a plan outside the Marketplace. In half of the calls, shoppers asked for a physical and in the other half, for appointments due to illness.

The authors found that securing an appointment with a provider was difficult regardless of plan type; secret shoppers with the study had a less than 30% chance of successfully securing an appointment with any randomly selected provider within his or her network. While patients with commercial plans fared better than those with Marketplace plans, these results were often not statistically significant and were overshadowed by larger issues of access seen in both plan types. The authors noted that the average wait time to get an appointment for an illness was eight to 12 days in both plans. Although this was half the wait time to schedule a physical, the authors noted that this was concerning given that many patients presenting with acute conditions are in need of timely care. The authors suggested that many of these problems could be attributed to inaccurate provider directories that list either incorrect or out-of-date information about providers participating in a particular network.

In their conclusion, the authors noted that “access to health insurance is not necessarily synonymous with access to healthcare services.” Though the study reveals important issues around network adequacy for patients in both Marketplace and commercial plans, it also highlights the related issue of network listing inaccuracies. Authors suggest that their findings in California may be generalizable to other states, and that there is a need for future research to explore the impact of required improvements to network accuracy (e.g., regular, timely updates to network listings) and network capacity on access to care. Although the ACA has made strides in providing expanded access to affordable health insurance, these study findings suggest that barriers around timely access to care remain.

Andrea S. Rodriguez Lebron was an Intern at AcademyHealth supporting the Translation and Dissemination Institute through her involvement with the Evidence Roadmap and Rapid Evidence Reviews projects. She is also an MPH candidate at Columbia University’s Mailman School of Public Health.



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I spend a fair amount of time talking about how social determinants of health come into play, with respect to health care outcomes. I also talk a lot about things that don’t work, and therefore constitute waste in that they don’t affect outcomes positively, and cost money. But there are some aspects of health care (many, in fact) that do matter, and when research points that out, it’s worth highlighting. In a recent BMJ paper, a number of researchers investigated how surgeon specialization was associated with operative mortality in the United States:

Objective: To measure the association between a surgeon’s degree of specialization in a specific procedure and patient mortality.

Design: Retrospective analysis of Medicare data.

Setting: US patients aged 66 or older enrolled in traditional fee for service Medicare.

Participants: 25 152 US surgeons who performed one of eight procedures (carotid endarterectomy, coronary artery bypass grafting, valve replacement, abdominal aortic aneurysm repair, lung resection, cystectomy, pancreatic resection, or esophagectomy) on 695 987 patients in 2008-13.

Main outcome measure: Relative risk reduction in risk adjusted and volume adjusted 30 day operative mortality between surgeons in the bottom quarter and top quarter of surgeon specialization (defined as the number of times the surgeon performed the specific procedure divided by his/her total operative volume across all procedures).

Eight procedures were studied among more than 25,000 surgeons and almost 700,000 patients. Surgeons were ranked by the number of times they performed a specific procedure as a percentage of their total procedures. This was called “specialization”, and was a measure of how much surgeons devoted their activities towards a specific procedure.

The hypothesis was that surgeons who specialize more on a specific procedure might be better at it. The outcome of interest was the relative risk reduction in 30-day operative mortality between the most-specialized and least-specialized surgeons, after adjusting for risk and volume.

There were four cardiovascular procedures studied, and in all of them, a surgeon’s specialization predicted operative mortality. The risk reductions ranged from 46% (valve replacement), to abdominal aortic aneurysm repair (42%), to carotid endarterectomy (28%), to coronary artery bypass grafting (15%). For two of the four cancer resection procedures, specialization was also associated with reduced operative mortality – lung resection (28%) and cystectomy (41%).

What was interesting was that the predictive power of specialization was independent of the number of times that a surgeon performed a procedure. In fact, for five of the procedures – carotid endarterectomy, valve replacement, lung resection, cystectomy, and esophagectomy – the risk reduction from specialization was greater than that from volume of procedures. In other words, it mattered more that surgeons focused their time on a specific procedure than that they did a lot of them.

It’s not that volume didn’t matter. It did. But specialization mattered more than volume a great deal of the time. And even when volume mattered, specialization accounted for much, if not all, of the variability of 30-day mortality outside of volume.

This is important, both at an individual level and at a societal one. Often, when selecting a surgeon to perform a specific procedure, we are concerned with how many of them they do each year. It makes sense to us that surgeons who do a lot of one type of procedure will be better at them. This study would caution us to consider further how much they specialize in that procedure. It’s not just how many times they do it each year, but also how much they focus on that procedure as a percentage of their total practice.

Moreover, as we think about how we make changes in delivery systems to improve outcomes, we might consider encouraging physicians to specialize in certain types of procedures more. We certainly do that already at some level (ie not everyone does heart transplants). But we might consider doing it more, at least as something we might study in the future.



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Many health insurance Marketplace shoppers have a lot of choices — more than those of us with employer-sponsored coverage. For states participating in, the average number of plans offered for 2016 coverage is 48. After learning, from a recent study, how little help is available for most Marketplace consumers, I’m sure I’d be highly challenged and frustrated by the task of choosing among this many plans.

After all, choosing coverage is hard. As I’ve written in several, prior posts, many consumers make mistakes in doing so. But they can do a better job if they have the right tools. For example,

Eric Johnson [...] conducted a series of experiments on people similar to those who would shop for marketplace coverage. Each study participant was asked to presume he’d use a certain amount of health care and, based on that, to choose the lowest-cost plan from among eight choices, which varied by premium, doctor co-pay and deductible. Only 21 percent could accomplish this task, a figure not statistically different from chance. [...]

But when study subjects were provided with a tutorial or with a calculator that revealed the full cost of each plan, or if they were placed in the lowest-cost plan by default (from which they could voluntarily switch), their chance of selecting the cheapest plan was much higher, upward of 75 percent in some experiments.

But, not many Marketplaces provided tools and features like this for the 2016 coverage year (or earlier years). I know from experience how useful they could be. Because I am eligible to participate in the Federal Employees Health Benefits Program (FEHBP) I have more choices than most workers, though less than half as many as Marketplace shoppers. The several times I looked over my 20 or so choices I yearned for two things: (1) to filter out plans that did not include the doctors and hospitals my family prefers and drugs we take; (2) to rank order remaining plans by expected total cost to me (premium plus out of pocket costs) if my family’s health care use remained about the same or if it grew substantially (e.g., if I or a family member got very sick).

Lacking those tools, I have stuck with my current plan for years. Switching, even though it might save me money, always seems like too much work and risk. So, I really feel for Marketplace shoppers.

For several years, Charlene Wong and other researchers at the University of Pennsylvania’s Leonard Davis Institute have examined the choice architecture of state Marketplaces. Last year, they found only a few that provided some of the tools consumers need. For example, only three states offered cost estimators. Recently, Wong and colleagues looked at what tools were available for selecting plans for 2016. Among their findings:

  • Estimates of total out of pocket costs were available only from two (of 13) state Marketplaces — California and Kentucky — during the “real” shopping phase. However, during “window shopping,” such a tool was not available in California but was available for, Connecticut, District of Columbia, and Minnesota. (The “real” shopping phase is when consumers actually establish an account to select an enroll in plans; “window shopping” can be done before account creation.)
  • Eight state Marketplaces (out of 13) and offered an integrated provider lookup (to readily find in-network providers without going to plan-specific websites), but only one could sort on provider inclusion and two could filter on it.
  • Neither nor any state Marketplace offered an integrated drug lookup during the real shopping phase, but Colorado did so during window shopping.
  • Two Marketplaces — Massachusetts and Rhode Island — provided some indication of network size.

Overall, these (and other results) represent progress form prior years. However, it may be confusing and inconvenient for consumers that some of platforms that provide certain tools only do so in the real or window shopping phases, but not both.

The authors wrote,

In the window-shopping experience, for example, the number of Marketplaces that offered total cost estimators increased from zero in the first enrollment period to five in the third, including for the first time. More Marketplaces had integrated provider lookups (there were three in the first enrollment period and eight in the third) and pop-up definitions (five and nine, respectively).

Most sites have continued to list plans by the premium amount. However, compared to previous enrollment periods, in the third period more sites were experimenting with alternative orders, including by estimated total out-of-pocket spending or with best-fitting or silver-tier plans first—especially for consumers who qualified for tax credits and cost-sharing reductions.

This is good, but more could be done. To be fair, it is not trivial to provide these tools. It requires planning, design, and implementation. That all costs money that some states may not have. Things will likely improve in future years. already announced that for the 2017 plan year, consumers will be able to select from “Simple Choice plans” that have a uniform structure, aiding comparisons. For example, deductibles and cost sharing won’t vary across the plans (within metal tier).

Another way to make progress on helping consumers is to learn more about how they select plans and to what extent different tools help them do so. That could be done with data from Marketplaces or about their choices and how they make them. To date, such data are not available.

Austin B. Frakt, PhD, is a health economist with the Department of Veterans Affairs, an Associate Professor at Boston University’s School of Medicine and School of Public Health, and a Visiting Associate Professor with the Department of Health Policy and Management at the Harvard T.H. Chan 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, Boston University, or Harvard University.


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