Health services research produces evidence that can have a transformative effect on healthcare quality and value, but the real promise of this information is in what happens after the research project ends. Moving knowledge into policy and practice is a key component of AcademyHealth’s mission, and can be seen in the regular presence of dissemination and implementation (D&I) science as a track at the Annual Research Meeting, in the conduct of AcademyHealth programs and projects, and in the formation and programing around our Translation and Dissemination Institute.

In fact, D&I research was woven throughout the 2016 Annual Research Meeting (ARM) in Boston, with sessions touching upon new methods in moving evidence to action as well as how individuals in health care and beyond are working to tackle obstacles to effective dissemination. Below is a sampling of the D&I-related sessions hosted at ARM.

Entrepreneurship in Bridging Evidence, Policy and Practice: A Conversation

As moderator Michael Gluck began, entrepreneurs tend to share characteristics: they have an idea for something new; embrace the idea of “disruption;” are willing to take risks, acting even when the outcome isn’t assured; and are flexible, able to operate in an environment of ambiguity.

This discussion-formatted session featured four individuals who have been successful at bridging the gap between evidence and policy. Each of the panelists was motivated by a frustration with the status quo and a desire to disrupt it:

  • Robin Strongin (Disruptive Women) wanted to innovate across the decision chain and demonstrate how social media, namely a blog of diverse women working across law, bench science, and health care, could be used to leverage information and exchange ideas about the health care information being released.
  • Karen Wolk Feinstein (Pittsburgh Regional Health Initiative) was frustrated working in a health care environment with no grounding in safety science and engineering and used the Turner “Knowledge Network” model as inspiration for new organizational alignment, staff education, and unity.
  • Gregg Gonsalves (Treatment Action Group) triggered a social movement of “normal people” who took on federal agencies after becoming fed up with the incredibly slow drug approval process, but then identified a gap of information in the drug market and made it the group’s mission to expand and accelerate research and community engagement; and
  • Ran Balicer (Clalit Research Institute) overcame an organizational mindset against research to create an evidence-based and evidence-oriented practice to enhance efficiency, provide clinicians with a better understanding of their workloads, and ensure alignment with the organization’s priorities.

The conversation was robust and captivating, with panelists urging attendees to break down walls, let people in from the outside, be interdisciplinary, first tackle the “critical points,” and, let passion be their guide.

Direct Observation Methods for Dissemination and Implementation Research

This engaging, didactic workshop, hosted by the Innovation Station, featured three researchers who provided an introduction into direct observation, a quantitative and qualitative method used in health services research and implementation science that can provide researchers with direct insight into the environment being studied. Direct observation involves continuously or instantaneously watching a given environment for better understanding of processes. It can capture routinized, unconscious behaviors, provide (work/life) context of the staff or clinic, document a process, behavior or interaction, illustrate what’s happening in a program or complement quantitative data.

Using a clip of documentary “The Waiting Room” as a simulation of real life, Megan McCullough, Bo Kim, and Gemmae Fix allowed participants the opportunity to experience direct observation for themselves. Teams then huddled together to examine the footage from different lenses and highlight what was important as well as to identify the research questions that could be answered from the footage.

To continue the conversation about D&I Science, join us at the 9th Annual Conference on Dissemination and Implementation in Health, December 14-15, 2016.




By: Danielle Robbio, AcademyHealth

In a time of significant health care transformation, many health insurers and health care providers are moving toward payment models based on the quality of care rather than the quantity in an effort to attain the Triple Aim of better care, smarter spending, and healthier people. The U.S. Department of Health and Human Services is working toward having 90 percent of Medicare payments tied to quality by 2018, and, at the state level, many are exploring a variety of new payment approaches through State Innovation Models funded by the Center for Medicare and Medicaid Innovation (CMMI).

While these payment reform efforts have a clear tie to the smarter spending aspect of the Triple Aim, what about their impact on people’s health? Right now, most of these value-based payment models, as they’re known, focus on clinical services and specifically focus on the needs and outcomes of a particular health care provider’s patients, a health plan’s enrollees, or the purchaser’s employee subscribers. Other payment models focus on a targeted sub-population of individuals with a defined clinical condition, such as patients with diabetes or depression. As such, payment and financing models are not yet adequately supporting community-wide, that is, geographically-based, population health. The incentives in these models do not yet reward health care providers for creating healthy communities, nor do they incentivize other sectors—transportation, housing, education—for population health improvements.

In light of this disconnect between payment reform and community-wide population health, AcademyHealth, with support from the Robert Wood Johnson Foundation, is leading a new effort called Payment Reform for Population Health to identify where momentum and opportunities exist to close the gap. As a neutral broker of information, AcademyHealth supports the generation of new knowledge and the transfer of knowledge into action. Supported by a broad and diverse network of researchers, policymakers, and practitioners, AcademyHealth is uniquely positioned to collaborate and facilitate connections, create shareable resources, and co-create strategies for using payment reform to support population health improvement.

This cross-team, multidisciplinary effort brings together AcademyHealth’s experts in payment reform, population and public health, health care data management, and research and analytic methods to identify where payment reform and population health intersect (to learn more about the project team, click here).

Past RWJF-supported initiatives as well as state and federal-led demonstrations have shown that payment reform efforts supporting population health improvement face persistent challenges. Yet, the team has observed encouraging innovations in the Population Health Community of Practice during the past year and by those expected to come from the recently-launched Office of the National Coordinator funded Community Health Peer Learning Program. Beyond AcademyHealth, the team is also looking to the innovative work of others, such as the Health Care Payment Learning and Action Network (LAN). These programs and networks illustrate the on-going efforts of health systems and other stakeholders to innovate and implement successful population-focused interventions.

One of the hallmarks of this Payment Reform for Population Health initiative is its emergent approach. Because working emergently with complex issues requires ongoing attention to multiple levels of change, AcademyHealth has set up processes that support adaptation to the changing context. We have also committed to supporting discovery and knowledge sharing through strategic collaboration with those already improving population heath as well as with those developing and implementing alternative payment models. Specifically, an in collaboration with our Guiding Committee, practitioners, and other key stakeholders, we will work to:

  • leverage and learn from efforts underway and work to support and enhance their activities;
  • assist in the spread of ideas, knowledge and evidence; and
  • support those initiatives to overcome persistent, yet surmountable barriers to achieve success.

After conducting structured interviews with 18 experts and convening our first in-person Guiding Committee meeting, we’ve already identified several barriers to payment reform for population health, including:

  • multiple definitions of population health;
  • the complexity of how various payment models can impact social determinants of health;
  • misalignment of financial incentives;
  • lack of appropriate data;
  • lack of adequate outcomes measures;
  • insufficient evidence for which population health initiatives might have the greatest impact;
  • inability to replicate and scale innovations across various communities; and
  • the lack of a business case or return-on-investment for such activities.

Next steps include digging deeper into these challenges and working to identify and disseminate promising solutions to overcome shared challenges.

Stay tuned here, at the AcademyHealth blog, for updates on our initiative’s progress and emerging findings. If you are doing related work, please contact Enrique Martinez-Vidal; we’d like to include you in our efforts!

Danielle Robbio, is a research associate on the Public and Population health team where she works to bridge the gap between public health and health care.




For over 30 years, AcademyHealth’s Annual Research Meeting (ARM) has been the premier forum for health services research, where attendees gather to discuss the health policy and health system implications of research findings, sharpen research methods, and network with colleagues from around the world. This year’s meeting in Boston was the largest one yet with more than 2,900 attendees and included 150 sessions with more than 700 speakers and nearly 1,500 posters.

In this post-ARM series, blog posts will summarize key takeaways from sessions on four hot topics:

  1. Data and methods: Dealing with increased volume, variety and velocity of data
  2. The Affordable Care Act: Evaluating the latest in health care reform
  3. Translation and dissemination: Moving evidence into action
  4. Race, ethnicity and health

This is the second post:

While provisions of the Affordable Care Act (ACA) began taking place in 2010, some of the most significant aspects of the law have taken effect in the last two years. Recently several in the health services research community have shared thoughts evaluating the ACA. Even President Obama has weighed in. This year’s Annual Research Meeting (ARM) was no different, with several sessions including late-breaking research on topics including coverage, access, quality and cost of care in a post-ACA world.

Late-Breaking Session: Does the Health System Have Enough Capacity in the Era of Health Reform?

These late-breaking abstracts examined capacity across a variety of settings and patient populations. Daniel Polsky presented research showing increased access to primary care and Megan Cole presented on improved quality in community health centers. Other papers drilled down to capacity for specific areas of care, such as dental coverage. Amber Willink’s research found that less than half of all Medicare beneficiaries had any dental coverage and Cameron Kaplan’s paper found that ACA tobacco penalties lead to lying and under-enrollment amongst this population. Caitlin Crowley presented research on the health center workforce that found that 95 percent of health centers have at least one clinical vacancy. Questions from attendees focused on how access has changed over time and how differences in service type and location might affect usage and volume.

Late-Breaking Session: New Evidence on Medicaid and Private Insurance Coverage Expansions

This session highlighted key findings from late-breaking research on public and private health insurance expansions under the ACA. Research presented by John Graves revealed new dynamics of U.S. health insurance. Benjamin Sommers presented research comparing three states’ (Arkansas, Texas and Kentucky) changes in utilization and health. Overall, researchers found positive downstream effects after expansion, whether via Medicaid or a private option as was the case in Arkansas. Affordability, preventative care and self-reported health outcomes all increased while reliance on emergency department care decreased. Joseph Thompson presented findings on Arkansas’ private option showing a clear benefit between Arkansas and neighbor states without expansion. Stacey McMorrow presented a study looking at the ACA’s effect on employee-sponsored and private insurance found that coverage expansions may have reduced churn between public coverage and uninsured status among low-income adults. Chima Ndumele presented results from a study showing no Medicaid quality erosion based on capacity constraints caused by expansion. Comments and questions from the audience focused on opportunities for further research looking at affordability and cost-sharing subsidies effects as well as comparisons with non-managed care plans.

The Impact of the ACA on Coverage

Research presented in this session examined which particular parts of the ACA have had a positive benefit on coverage and where challenges remain. While there are several incentives to encourage people to sign up for health insurance, research presented by Benjamin Sommers found that 2014 coverage gains were more sensitive to the percent subsidy than the premium dollar amount, and the mandate penalty had little effect. Other research looked at some adverse impacts of other provisions of the ACA such as Erin Trish’s data on small businesses self-insuring to avoid community rated premiums and Lisa Dubay’s presentation on the “family glitch,” which prevents some families from receiving marketplace tax credits because one adult has access to affordable work-only employer coverage. Questions from attendees focused on Kristin Kan’s research findings about a lack of access to pediatric subspecialty care and Lucas Higuera’s projections that the proposed Cadillac tax for employers to pay on high-cost health insurance plans would result in employers substituting increases in health insurance benefits with increases in wages.

The Impact of Coverage Options on Access, Quality and Health

Research in this session looked at how competing coverage plans are impacting individuals’ access to care, quality of care, and health outcomes. One study, presented by Sandra Decker, looking at the impact of Medicaid expansion on access to care and health found significant gains in insurance coverage, primary care visits, and specialist care visits in expansion states compared to non-expansion states, but no significant changes in self-reported physical or mental health. Chima Ndumele reported that plans that stay in the marketplace perform better in terms of quality than those that leave, but that there is no effect of plans leaving on those that stay. A third study from Sara McMenamin analyzed policy options to limit patient cost-sharing for prescription drugs noting that as of the beginning of this year, there were 16 states that have enacted legislation on this topic. In a study looking at high deductible health plan (HDHP) impacts presented by James Wharam, researchers found that women with HDHP experienced delays from diagnoses to treatment. In a similar concerning finding, Jennifer Lewey presented research showing that among commercially insured patients with chronic medical conditions, switching to a HDHP was associated with a significant and immediate decrease in adherence to evidence-based medications.




Integrated delivery systems (IDSs) are vertically integrated health service networks that include physicians, hospitals, post-acute services, and sometimes offer health insurance. In short, within a single organization, they provide a broad spectrum of coordinated inpatient and outpatient care. Kaiser Permanente is the quintessential example, but there are many other IDSs.

It has long been claimed that the greater care coordination provided by IDSs improve quality and outcomes at lower cost, in large part from elimination of duplication and unnecessary or avoidable care. A larger organization might, for example, streamline and consolidate common needs such as information technology and human resources, reducing costs. An integrated organization might more successfully implement quality improvement programs or might more frequently deliver the right kind of care, in the right setting, at the right time, improving outcomes.

Last year, for the National Academy of Social Insurance, Jeff Goldsmith, Lawton Burns, Aditi Sen, and Trevor Goldmith surveyed the evidence on IDS performance and conducted some additional analyses. Their conclusion:

[T]here is little evidence that integrating hospital and physician care has helped to promote quality or reduce costs. Indeed, there is growing evidence that hospital-physician integration has raised physician costs, hospital prices and per capita medical care spending. Similarly, hospital integration into health plan operations and capitated contracting was not associated either with clinical efficiency (e.g. shorter lengths of stay) or financial efficiency (e.g. lower charges per admission).

Their literature review included a 2006 study by Cuellar and Gertler that examined the effect of hospital-physician integration on costs, quality, and prices, using data from three states in the mid- to late-1990s. Overall, they found that integration does not reduce costs, but it increases prices by about 6%, with small improvements in quality. Integrated, large, nonprofit teaching hospitals, however, did not have higher prices and provided higher quality of care than non-integrated hospitals and other kinds of integrated ones. Working with Medicare data and also examining the mid- to late-1990s, Madison found that hospitals that employ physicians are associated with more procedures and higher expenditures, with no appreciable effect on outcomes.

Several more recent studies — also cited by Goldsmith et al. — have found hospital-physician integration associated with greater spending and higher prices. Baker, Bundorf, and Kessler examined a privately insured population between 2001 and 2007. They found that vertical integration increased hospital market share, prices, and spending, despite a small effect of reducing hospital admissions. With data from California spanning 2009-2012, Robinson and Miller found that physician organizations owned by local hospitals spend 10% more per patient than physician owned groups. When they’re owned by multi-hospital systems, they spend nearly 20% more. Two studies led by Gans found lower physician productivity associated with hospital employment, relative to physician-owned multi-specialty groups.

Hwang et al. conducted a systematic review of literature published between 2000 and 2011 on the effects of various kinds of physician integration on cost and quality. Only two peer-reviewed studies reviewed pertain to IDSs as defined here and compared their performance to non-IDS care.* Rittenhouse et al. found that hospital- or plan-owned physician practices were more likely to use evidence-based care. Similarly, Shortell et al. found that hospital or health plan affiliated medical groups were more likely to better manage care.

Carlin, Dowd, and Feldman examined changes in quality associated with two hospital acquisitions of three multispecialty clinics in the Minneapolis–St. Paul area. They found small improvements in cancer screening and appropriateness of ED use but also increased probability of ambulatory care sensitive hospital admissions when the acquisition disrupted prior physician-hospital admitting relationships.

Goldsmith et al. also examined 15 nationally prominent IDNs:


Among their analyses was a comparison of each of the IDN’s flagship hospital to its main in-market competitor. They found that flagship hospitals with no revenue at risk (meaning fully reimbursed for all costs) have 8% lower Medicare per case costs than their competitors. Those with revenue at risk (e.g., sponsor their own health plan, are capitated, or subject to a two-sided ACO model) are 20% more costly than competitors. They found no meaningful differences in clinical quality or safety scores for IDN flagship hospitals, relative to competitors, but the vast majority of IDN flagships had a higher case-mix adjusted cost per case and spent more on end-of-life care.

Why do IDNs fail to consistently reduce costs and spending and only intermittently or marginally improve quality? One explanation is that a larger and more diverse organization is more difficult to manage.

A major contributor to the performance problem is that diversification increases the firm’s size and complexity, which in turn increases the firm’s cost of coordination, information processing, and governance and monitoring.

Related to this explanation is that IDN formation is only a structural change. It doesn’t necessarily, by itself, make a positive impact on processes of care that would be necessary to consistently improve outcomes and efficiency. Another explanation is that IDNs may command greater market power and use it to increase prices in the commercial market. If it’s perceived to be a “must have” organization in plans’ networks, it may not need to work as hard on quality either. An NBER working paper by Baker, Bundorf, and Kessler found that patients who see a hospital-owned physician are more likely to visit high-cost, low-quality hospitals.

The trend is for greater integration between hospitals and physician practices. Prior work on IDNs does not provide confidence that this trend will produce better outcomes at lower costs.

*Hwang et al.’s definition of an IDS includes multi-specialty physician group practices that are not hospital owned whereas, this post defines an IDS as integration between physicians and hospitals.

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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For over 30 years, AcademyHealth’s Annual Research Meeting (ARM) has been the premier forum for health services research, where attendees gather to discuss the health policy and health system implications of research findings, sharpen research methods, and network with colleagues from around the world. This year’s meeting in Boston was the largest one yet with more than 2,900 attendees and included 150 sessions with more than 700 speakers and nearly 1,500 posters.

In this post-ARM series, blog posts will summarize key takeaways from sessions on four hot topics:

  1. Data and methods: Dealing with increased volume, variety and velocity of data
  2. The Affordable Care Act: Evaluating the latest in health care reform
  3. Translation and dissemination: Moving evidence into action
  4. Race, ethnicity and health

This is the first post:

ARM 2016: Dealing with increased volume, variety and velocity of data

It is no secret that the environment for health services research (HSR) is evolving rapidly, especially with significant changes in the volume, variety, and velocity of data available and an increasing number of opportunities for collaboration across sectors. In response, AcademyHealth is working to build an infrastructure of training, methods, and governance to support evolving and emerging data streams and to address relevant research questions in rigorous and novel ways.

Formulated from the best abstracts submitted to this year’s ARM, “Best of ARM: New Developments in Data and Methods That Will Transform Our Field Over the Next 5 Years” seeded a provocative discussion on transformational changes in data and methods. The 90-minute discussion highlighted impact, accomplishments, and challenges of using data and methods to improve the health care system and an overall culture of health among Medicare beneficiaries, patient-research, relationships and more.

The four presentation in this methods-focused panel included:

  1. The Impact of Suppressing Substance Use Data on Measures of Chronic Conditions, Hospitalization, and Spending Among Medicare Beneficiaries
    Hundreds of studies of the U.S. health care system each year rely on administrative claims data, like those in the Medicare program, to evaluate the efficiency of the health system, utilization patterns of patients, and quality of care. The presentation of this paper by Julie Bynum explained how the redaction of substance use data has constrained efforts to evaluate what works and what does not work for populations with mental illness or substance use disorders. As a result, Bynum noted, the health system has lost a vital source of information on some of the nation’s most vulnerable patients.
  2. Identifying Patients at High-Risk for Readmission Using Socio-Behavioral Patient Characteristics
    During his presentation, Amol Navathe presented and discussed automated methods for analyzing physician notes which could enable better identification of patients with high socio-behavioral needs who are at increased risk for readmission. This information, he indicated, could improve health system allocation of care management resources to the highest need patients.
  3. Initiative to Support Patient Involvement in Research (INSPIRE)
    This presentation focused on the INSPIRE initiative, which aims to identify training and support needs and synthesize existing tools and resources to meet those needs, while creating a network to help researchers and patients better connect and collaborate in patient-centered outcomes research (PCOR). Danielle Lavalle presented INSPIRE findings around how individual patients and researchers approach research partnerships and how organizations can develop infrastructure and resources that encourage and support patient-researcher relationships.
  4. Linking to Clinical Registrants with the All Payer Claims Database: A Powerful Source of Data to Reform Health Care
    This presentation focused on a New England patient-centered medical home (PCMH) program, and its use of two large databases to guide its efforts: the state’s all-payer claims database and a statewide clinical registry with primary care practice data. Amy Kinner explained that data from the two databases are being used to drive efforts with accountable care organizations and payment reform initiatives focused on the statewide population—an example that could potentially be applicable to the rest of the United States.

These four papers provided clear examples of the potential data and methods have to advance health care, health services research, and improve the overall culture of health. Panelists noted the importance of remembering that each community and patient is different, and studies should be designed to best fit the population in need.



So often, when we implement new policy, I wish we had better ways to capture its effects so that we could expand our knowledge base as to how decisions change health and health care. The Oregon Health Insurance Experiment, and its older brother the RAND HIE, were RCTs designed to look at how insurance affected utilization and health. While these were impressive studies, they had their flaws.

RCTs are hard to do, though; they’re also expensive. Sometimes, other designs are necessary. Recently, in Annals of Internal Medicine, Laura Wherry and Sarah Miller looked at how the Medicaid expansion has changed things. “Early Coverage, Access, Utilization, and Health Effects Associated With the Affordable Care Act Medicaid Expansions: A Quasi-experimental Study“:

Background: In 2014, only 26 states and the District of Columbia chose to implement the Patient Protection and Affordable Care Act (ACA) Medicaid expansions for low-income adults.

Objective: To evaluate whether the state Medicaid expansions were associated with changes in insurance coverage, access to and utilization of health care, and self-reported health.

Design: Comparison of outcomes before and after the expansions in states that did and did not expand Medicaid.

Setting: United States.

Participants: Citizens aged 19 to 64 years with family incomes below 138% of the federal poverty level in the 2010 to 2014 National Health Interview Surveys.

Measurements: Health insurance coverage (private, Medicaid, or none); improvements in coverage over the previous year; visits to physicians in general practice and specialists; hospitalizations and emergency department visits; skipped or delayed medical care; usual source of care; diagnoses of diabetes, high cholesterol, and hypertension; self-reported health; and depression.

As we’ve discussed many times before, only about half of states initially decided to join the Medicaid expansion. This meant that – in those states – anyone making less than 138% of the federal poverty line could get Medicaid. In other states, many poor people were out of luck. The law provided no subsidies to people earning less than the poverty line, and without new Medicaid, many had no affordable options for insurance.

This study sought to compare how adults who would qualify for the expansion compared to those in states with and without it. The researchers used data from the 2010 and 2014 National Health Interview Surveys to compare health insurance coverage, utilization, diagnoses of some illnesses, self-reported health, and depression. They used a quasi-experimental difference-in-difference design to compensate for secular changes as well as time-invariant differences in characteristics across all states. They excluded five states that already pretty much provided expansion-like coverage before 2014.

They found that, by the second half of 2014, adults in the expansion states had seen their health insurance coverage increase 7.4%; Medicaid coverage increased 10.5%. This isn’t surprising, as increased coverage was the main intent of the Affordable Care Act. Coverage was found to have “improved” as well (7.1%).

They also found that, in Medicaid expansion states, there were increased in physician visits (6.6%), hospital stays (2.4%), rates of diagnoses of diabetes (5.2%) and high cholesterol (5.7%).

Of course, this is an observational study. It’s possible that other confounders exist that are the reasons for these changes. These are also very short-term data. They also couldn’t find real differences in terms of access.

But, as I’ve discussed before, insurance coverage is just the first step in improving access. What this study adds are some data showing that expanding Medicaid through the ACA resulted in increased coverage, improved coverage, more physician visits, and more disease diagnosed.

It will be important for us to continue these types of studies as we move forward, to understand better the full impact of the ACA. But if future analyses continue to show improvements in coverage, utilization, and health from the Medicaid Expansion, it may become more difficult for the 19 remaining states to refuse it without offering alternative paths to the same achievements.


For more reading on the effects of the ACA, you might also enjoy both the HSR systemic review blog piece written earlier this week here on the AcademyHealth blog and the President’s recent JAMA article


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In this week’s special issue of JAMA, President Barack Obama declared the Affordable Care Act to be a success, highlighting “significant progress toward solving long-standing challenges facing the US health care system…”

But what does high-quality research by the health services research community show? Is the President’s assessment correct?

HSR, an official journal of AcademyHealth, just published the first systematic review that comprehensively summarizes early research findings on the impact of the Affordable Care Act on health insurance coverage in the United States. In a peer-reviewed publication available free online, authors Michael French and colleagues conclude that “research shows that the ACA has substantially decreased the number of uninsured individuals through the dependent coverage provision, Medicaid expansion, health insurance exchanges, availability of subsidies, and other policy changes. Affordability of health insurance continues to be a concern for many people and disparities persist… (but) Early evidence also indicates improvements in access to and affordability of health care.” You can read more here.


This post was provided by Patrick S. Romano, MD MPH, Co-Editor in Chief, Health Services Research (HSR), an official journal of AcademyHealth. Dr. Romano is Professor of Medicine and Pediatrics, UC Davis Division of General Medicine


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Tomorrow, the House Subcommittee on Labor, Health and Human Services, Education and Related Agencies will mark up its FY 2017 spending bill. In a victory for the #SaveAHRQ campaign, the Agency for Healthcare Research and Quality (AHRQ) is sustained in the bill – a vast improvement from last year’s proposed termination and the first time in four cycles that the House has preserved any funding for the agency at all.

Unfortunately, the House like the Senate, has proposed cuts for AHRQ which are not acceptable. The bill as written cuts AHRQ by just under $54 million (16 percent), bringing its discretionary budget to $280.24 million. Any of these cuts would be on TOP of the $30 million cut AHRQ sustained in FY 2016. The bill also decimates funding for the Center for Medicare and Medicaid Innovation (CMMI); rescinds significant funding for the Patient-Centered Outcomes Research (PCOR) Trust Fund – which compounds AHRQ’s cuts; and prohibits funding for any patient-centered outcomes research with appropriated dollars across the Department of Health and Human Services (HHS).

Taken together these cuts would be a significant blow to federally funded health services research and our nation’s ability to research and produce information on whether and how different interventions work for different patients in different settings. The cuts will make it harder for health care delivery organizations, policymakers, and the people they serve to make informed decisions about how to get the best, safest care while addressing costs and protecting patient safety.

As an advocate for the health services and policy research community and all the users of their findings in the public and private sectors, AcademyHealth is extremely disappointed with the proposed funding level for AHRQ and strongly opposed to the cuts at CMMI, the claw back of the PCOR Trust Fund, and the prohibition on discretionary funding for PCOR more generally. While we recognize that Congress is under extreme pressure to fund competing priorities whilst doing its best to keep the federal budget in check—reducing our ability to make health care safer, less complex and less costly is simply a foolish decision.

The Details

As noted above, AHRQ sustains a pretty hefty cut of just under $54 million (16 percent) in the House bill, bringing its discretionary budget to $280.24 million. The last time AHRQ’s base budget was close to this low was 2001, at $270 million (not adjusted for inflation). As a reminder, the Senate proposed a $10 million cut (3 percent). The agency’s current discretionary budget is $334 million.

Any proposed cuts in FY 2017 would be in addition to the $30 million cut AHRQ sustained in FY 2016.

The House “Labor-HHS” bill also rescinds $150 million from the PCOR Trust Fund. As mandated by the Affordable Care Act, up to 20 percent of the amount in the PCOR Trust Fund shall be used to support research capacity building and dissemination activities and of this amount, 80 percent may be used by AHRQ and 20 percent may be used by the Secretary of HHS.

AHRQ received approximately $90 million from the PCOR Trust Fund in FY 2016 in addition to its base discretionary budget. So the cut to the PCOR Trust Fund has additional implications for AHRQ’s program level budget, as well as that of the Patient Centered Outcomes Research Institute (PCORI).

Finally, the Labor-HHS bill prohibits the use of any discretionary funding to support patient-centered outcomes research, which would impact the portfolio of the National Institutes of Health, and it rescinds $7 billion from the Center on Medicare and Medicaid Innovation or CMMI.

What Happens Now

AcademyHealth encourages the health services research (HSR) community, the myriad users of HSR findings, and the Friends of AHRQ to contact their representatives on the House Subcommittee on Labor, Health and Human Services, Education and Related Agencies Appropriations to advocate for increased funding for AHRQ, the restoration of funding for CMMI and the PCORTF, and the removal of the ban on PCOR discretionary funding.

While funding for all health research is crucial, AcademyHealth believes that health services research is uniquely capable of helping the nation address the rising costs of health care and transform how we approach health and health care in this country. Every cut reduces our capacity to ensure patient safety, address waste and inefficiency, and ensure access groundbreaking treatments and prevention.

You can find a toolkit of resources to assist in educating policymakers about the important contributions of AHRQ on our website.

AcademyHealth will be following appropriations developments in the House and Senate closely, and stand ready to act on behalf of our members and the field. As we look to the future, we look not only to preserve AHRQ, but to save the critical health services research that can measurably improve health and healthcare in the nation.


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In four separate posts, Austin Frakt and Aaron Carroll from The Incidental Economist will describe their translation and dissemination process, specifically how they turn academic papers into interesting blog posts. Each of their posts will cover one of these questions:

  1. How do we read research papers?
  2. How do we decide what to write about?
  3. How do we make our posts interesting?
  4. How do we decide where to publish them?

This is the fourth post:

How do we decide where to publish a post?

Aaron: Austin and I publish in the same places, and I bet we think about them similarly. However, I also have to provide content to a video series: Healthcare Triage.

Anything I want up super-fast, goes on TIE. This includes any new studies that I want to get my thoughts out on immediately. TIE also gets my newsy rants, when I want to comment quickly on something in the blogosphere. I write like I think at TIE, with the least amount of concern for adapting to the audience. I assume readers at this point know what they’re getting.

If I think that what I want to say is more than just about a new study, if I think a real dive into context is necessary, then I consider the Upshot. Those columns are a lot more work. I do a mini-systematic review for many of those, really trying hard to make sure I don’t miss any research. That often takes more time than the writing.

I like to comment on new reports and analyses of more HSR-related items over at AcademyHealth. I also can be a bit more wonky over there. At the JAMA Forum, on the other hand, I will write about more medical things, especially if they are policy-oriented. If it’s going to affect physicians, then I’m going to JAMA.

A lot of this has to do with the expected audience. AcademyHealth readers tend to be more wonky, HSR-types. JAMA Forum readers include more docs and more of a still-sophisticated, but wider audience. TIE readers tend to be engaged, but even more diverse. But we expect at this point, they like what we like. The Upshot caters to the most public audience, and pieces there have to have wide appeal.

That leaves Healthcare Triage. HCT News (Fridays) usually gets adapted from posts I’ve done on TIE about individual studies. Traditional HCT episodes (Mondays) often get adapted from pieces I’ve written for other sites (Upshot, AcademyHealth, JAMA). Otherwise, I write them from scratch. I often get ideas for those from Tweets, emails, or comments. That audience is the most general, although often I’m surprised who watches. Writing a script isn’t much different than writing a post (I write like I speak), but I have to be more cognizant of breaking things into manageable chunks for the teleprompter.

Austin: Publishers have editors. They know (or should know) their audience or intended audience. They call the shots and set the style that should cater to that audience. Some editors are very specific and demanding. Some aren’t. This drives what works where.

Upshot posts should be evidence-driven, not political or opinion, and accessible to a non-expert audience. I only pitch material to The Upshot if it is relevant to a typical NYT reader. How will it inform or affect his/her life? The editors will come right back at me with this question if I haven’t answered it in a pitch. By now I know that and have learned the art of the pitch. I can’t remember the last time they rejected one.

If I want to write for researchers or policy wonks, AcademyHealth or TIE is the place. I can use some jargon. It isn’t important if the post is relevant to an average person’s daily life. It just needs to be relevant to health services or health economics research in some way. Actually, TIE is even broader. Really, I can (and do) write whatever I want there.

If I want to comment on policy or express opinion, JAMA Forum works. It’s still got to be substantiated and relatively jargon-free, but I can say what I think is right or wrong, if I wish.

It’s rare that I initially write a post for one site and then use a subsequent version of it elsewhere, but it has happened. I make sure nothing goes to waste. Everything I write gets published in some form somewhere. Also, when it makes sense to do so, I’ll write about the same work in different ways, for different sites and different audiences. See, for instance, this JAMA Forum post on the cost of Medicare Advantage and this Upshot post on competitive bidding in Medicare Advantage. Some of the same research arises, but in service to a different point.

I’ve noticed that some of my colleagues tend to think a column is a column and it can run anywhere. That’s not so. Style really matters and varies from place to place. Some of my colleagues send me drafts for TIE guest posts and some of them are all wrong. They’re not in TIE style (or even blogging style). I tell them. It’s my job. I’m one of the editors!

Aaron E. Carroll, MD (@aaronecarroll), is a professor of pediatrics at Indiana University School of Medicine. Austin B. Frakt, PhD (@afrakt), 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. Both blog about health economics and policy at The Incidental EconomistThe views expressed in this post are those of the authors and do not necessarily reflect the position of the Department of Veterans Affairs, Boston University, Harvard University, or Indiana University.


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In four separate posts, Austin Frakt and Aaron Carroll from The Incidental Economist will describe their translation and dissemination process, specifically how they turn academic papers into interesting blog posts. Each of their posts will cover one of these questions:

  1. How do we read research papers?
  2. How do we decide what to write about?
  3. How do we make our posts interesting?
  4. How do we decide where to publish them?

This is the third post:

How do we write posts people want to read?

Austin: There is not one answer. Each person wants a lot of things, and different people want different things. Here are five rules of thumb — things that usually improve posts.

First, one can rarely go wrong by writing less. Blog posts should usually be under 1,000 words, preferably closer to 700. But less is fine, so long as it clearly makes a point.

Second, and related, make a point. One is enough. It’s all people really want. Two is possible, but risky. People will only remember one. Three or more is nuts.

Third, and also related, don’t hide the ball. If you’ve got a point, come clean with it at or near the top. The academic style of belaboring the context and background is not engaging. You’ve got to work that in far more briefly and creatively after giving the reader a reason to read the post.

Fourth, keep the language simple and the jargon to a minimum. What “minimum” means varies by audience. It’s OK for a TIE or AcademyHealth post that’s directed at researchers and wonks to be a bit jargony. JAMA Forum language should be simpler. Upshot should be nearly jargon free.

Fifth, making it personal is usually helpful. I rarely succeed at this, but I do try. If I can think of a way to put myself in a post — tell a personal story that relates to the point — I do so. For example, one of my Upshot posts in 2014 began, “A confession: I am a health economist, and I cannot rationally select a health plan.”

Or, when I can’t make it personal, I try to make it relevant to others’ experiences. For example, one of my recent Upshot posts begins, “Aside from whatever a visit to the doctor costs you in money, it also costs you in time. A lot of it.” Devoting a big part of one’s day just to see a doctor is a common experience. Nobody likes it. That’s a reason to read the post.

Aaron: I have such a hard time getting people to believe this, but the truth is that writing is like any other skill. You get better at it the more that you do it. One of the reasons I committed to a blog in 2009 was that I wanted to become a better writer. It was a huge part of my job, and I wasn’t very good at it. I committed to getting up every day and writing 600-800 words, assuming that eventually, writing 600-800 words wouldn’t be a big deal. That happened.

A key for me was figuring out that writing doesn’t need to be complicated. The simpler the better. I don’t shoot for very long sentences or complex constructions. I write the way that I think I would talk. I think I succeed, because many people, when they meet me, tell me that talking to me is very much like reading my columns. I take that as a compliment.

Paragraphs should be kept short, for the most part. Posts aren’t novels, and you don’t want people getting bogged down.

I agree with Austin on the lack of jargon. I’m a doctor, and I constantly rebel against that. You will never see me write (or say) something like “elevated erythematous papules accompanied by severe pruritus” when I can simply say “hives”.

When I’m feeling fancy, I will try and start the post with some vignette or story that relates the column to me or something people can identify with. Here’s an example.

The most important advice I can give is to edit. I still go back and edit posts I wrote years ago. My writing is never perfect, and I’m always tinkering it. If you’re lucky in life, you get to work with editors who can help clean up your writing. I learn a ton from them all the time. You can also get people you trust to edit your pieces. I find Nicholas Bagley to be invaluable. I am never attached to my writing in such a way that I refuse edits or help. I find that editors generally tend to appreciate that, which hasn’t hurt my career.

Finally, write stuff that people will want to read. Make sure each post has a point. Make sure it’s interesting. Make sure it’s clear.

Always write with some idea in mind of where to publish. That’s the topic of our next post.

Austin B. Frakt, PhD (@afrakt), 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. Aaron E. Carroll, MD (@aaronecarroll), is a professor of pediatrics at Indiana University School of Medicine. Both blog about health economics and policy at The Incidental EconomistThe views expressed in this post are those of the authors and do not necessarily reflect the position of the Department of Veterans Affairs, Boston University, Harvard University, or Indiana University.


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