“As the national organization working with the producers and users of evidence to improve health and the performance of the health system, and the home of the EDM Forum, AcademyHealth has long been a champion for data liberation and a catalyst for its use in decision making and quality improvement,” said AcademyHealth President and CEO, Dr. Lisa Simpson. “As hosts of the Health Datapalooza, we’ll build on our work in this area to shape an agenda that engages the broad community of data liberation champions — patients, advocates, researchers and delivery system and industry leaders — in focused discussions about how we turn data into evidence, and evidence into actions that improve health outcomes.”


Read full release on the AcademyHealth website.



A few weeks ago on October 1st, the switch from ICD-9 diagnosis and procedure codes to ICD-10 became mandatory for all HIPAA-covered entities. ICD-10 is already used by most (if not all) other developed countries, and has been for years. The number of available codes under ICD-10 will increase by nearly 5-fold, and will provide more precision and detail regarding a patient’s condition and the health encounter. For example, diagnosis codes indicating an injury will typically provide more information about the location of the injury, its cause, as well as whether the health encounter is the initial encounter to treat the injury or a subsequent encounter. Most agree that ICD-10 will allow for a more accurate representation of patients’ conditions, and likely will be accompanied by fewer coding errors. Some are concerned about the impact the new coding system could have on quality assessments (and hence reimbursement), as well as the cost associated with its implementation and continued use, but almost everyone agrees the change is necessary.

For researchers who utilize claims-based administrative data, the switch to ICD-10 will present different types of opportunities and challenges than it does for healthcare providers. It is widely assumed that the increased detail and accuracy provided by ICD-10 will translate into more accurate and precise research, which is obviously good for researchers. At the same time, along with a series of validation studies that will be needed to demonstrate the sensitivity and specificity of the new codes, good crosswalks will also be needed to allow for consistency in methods across research that utilized ICD-9 to that which will utilize ICD-10.

Some crosswalks for individual codes have already been developed, including by CMS, the Agency for Healthcare Research & Quality, (AHRQ) and the American Academy of Professional Coders, (AAPC). Some of these have shown that while many codes have a direct mapping between ICD-9 and ICD-10, other codes do not have a clear mapping, and still others have no mapping at all. There may be no remedy for this. But, what is perhaps more important than a crosswalk for individual codes is to develop a crosswalk for estimates (of incidence, prevalence, rates of outcomes, etc.) produced by the individual codes, especially given that many diseases and health events are typically defined by a set or group of codes instead of by the presence of a single code.

It may not be possible to identify methods whereby rate estimates produced using ICD-10 codes are identical to those produced by ICD-9 codes, although the AHRQ Healthcare Cost an Utilization Project has produced a Clinical Classifications Software for ICD-10. However, perhaps duplicating rates should not be the goal: after all, maybe the increased detail allowed by ICD-10 codes will produce estimates that are different – but more accurate – than those that were possible using ICD-9 codes. However, it will be crucial that we understand the differences so that we can make valid comparisons between rates produced by ICD-9 codes versus those produced by ICD-10 codes, and can identify how much of an observed difference over time is due to the new codes, and how much is due to actual changes in the underlying health status of the population being studied.

For obvious reasons, longitudinal studies that span October 2015 will need to face this issue head-on, since these studies will track rates from before October 2015 (when ICD-9 was used) to after the implementation of ICD-10 codes. But cross-sectional analyses that utilize only data from October 2015 and later will also need to address the ICD-9 to ICD-10 switch. When these studies compare their results to those of previously published literature, much of those results (at least initially) will be based on ICD-9 codes, and therefore will require that the authors be able to accurately assess how much the differences they see may be due to the switch in coding methods.

For most researchers, the typical time-lag associated with claims-based data means that we will not have to deal with these issues directly for at least a year or more. However, now is the time when we should be thinking about how we will address these challenges so that we can take full advantage of the benefits provided to us by ICD-10. Additionally, as research utilizing ICD-10 codes begins to emerge here in the US, it will be important to keep these issues in mind when assessing and critiquing the quality of these studies.


DSC_0048Craig Solid, PhD, is owner and principal of Solid Research Group, LLC, an organization that helps shape healthcare delivery and national healthcare policy by quantifying and disseminating results of health research and quality improvement initiatives. For over 15 years, Dr. Solid has helped healthcare organizations discover effective treatments for disease, improve the quality of care delivery, and increase efficiency and effectiveness. Dr. Solid is a member of the American Medical Writers Association.




I write about incentives to change behavior quite a bit. Sometimes, it’s to acknowledge that it might work. Other times, it’s to question if it might not. But there’s no question that incentives do have the potential to help people achieve goals. A new study in JAMA tries to tease out to whom we should be directing those carrots.

David Asch and colleagues recognize that financial incentives both to patients and physicians are being used more and more often. But research often is lacking on how those function in practice. They wanted to see how incentives could be used to help patients with a high level of cardiovascular risk lower their low-density lipoprotein (ie bad) cholesterol.

They set up a four-group randomized controlled trial in a number of primary care practices. They enrolled both primary care physicians as well as patients. Patients were eligible if they had a 10-year Framingham risk score of 20% or higher with an LDL level of at least 120 mg/dL or a risk score of 10%-20% with an LDL of at least of 140 mg/dL. They were able to blind those gathering data for the study, but not the participants, obviously.

Doctors were eligible for $256 for each patient who met a quarterly goal (up to $1024 per patient per year). This money was kept separate from their other salary, so that it could be easily identified as part of this initiative.

Patients were incentivized differently. Each day, they had a 10% chance to win $10, and a 1% chance to win $100, but only if they had taken their medication the day before. If they were completely adherent, they could potentially win (on average) about $1022 per year. Information about compliance was uploaded automatically from electronic pill bottles. The daily drawings also reinforced the idea that medication needs to be taken every day.

One group was physician incentive only, as described above, and one group was patient incentive only. A third group had both physician and patient incentives, but at half the value of the individual incentive groups. A fourth group received no incentives and served as the control.

The outcome measure of interest was the change of LDL level one year out. Simple as that. The results, however, were interesting.

Patients in the control group wound up lowering their LDL levels by just over 25 mg/dL, which shows how just being in a study can have an impressive effect on health. People in the patient-incentive-only arm saw a reduction of the exact same amount. They didn’t seem to work at all. Patients in the physician-incentive-only arm saw a reduction by just under 28 mg/dL which wasn’t significantly different from control either. In the joint incentive arm, however, the average reduction was 33.6 mg/dL, which was significant.

In other words, incentivizing either group alone didn’t appear to do much at all, with respect to lowering LDL values. But incentivizing both, even though the money spent was no greater, had a significant effect.

I’ve been down on physicians incentives at times because I don’t think they’ve been shown to have the effects people sometimes attribute to them. But this study is interesting. It shows that by focusing either on patients or providers alone, we might not do much good. Focusing on both, however, seems to work. It has the added benefit of also aligning with many of the models of ideal care, where doctors and patients work together to achieve better health. Something to think about.




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As AcademyHealth’s #SaveAHRQ Tweet Day is underway, it’s appropriate to stop and reflect on the tremendous gain in visibility the Agency for Healthcare Research and Quality (AHRQ) has received–not only by those in the health community, but also by those on Capitol Hill.

Last week, under the leadership of Senator Richard Blumenthal, a dear colleague letter in support of AHRQ—its first-ever—was circulated in the United States Senate.

Senator Blumenthal, along with Sens. Brown (OH), Franken (MN), Markey (MA), and Warren (MA) urged their Senate colleagues to work with the House of Representatives on the fiscal year (FY) 2016 appropriations bill to protect and preserve funding for AHRQ with a $364 million investment, expressing concern about the 35 percent cut to the agency in the Senate’s bill approved by the Committee on Appropriations and the House bill’s proposed funding elimination:

“Finding innovative and affordable new ways to deliver health care is one of the most important investments we can make as a nation. AHRQ is the only federal agency whose sole focus is to generate reliable and credible information on how to deliver the best possible care, at the greatest value, with the best outcomes. In this regard, AHRQ is an integral pillar of the federal health research continuum, and sits at a critical intersection—generating evidence to support the needs of delivery systems dedicated to providing quality care, and the needs of patients and payers who want to understand the actual performance of the delivery system.”

To read the full text of the letter, click here.

AcademyHealth appreciates the leadership of Sen. Blumenthal and his colleagues to preserve the funding of AHRQ and the critical health services research it supports.

As we thank our champions, we ask that you do too. Please take a moment during this #SaveAHRQ Tweet Day to express your gratitude to Sens. Blumenthal, Brown, Franken, Markey, and Warren and their efforts to #SaveAHRQ!


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“We’re at the junction of crisis and success, and what we do over the next several years will hopefully determine which way we go.” – Dr. Edward Septimus, Hospital Corporation of America

We continue to see staph infections, specifically Methicillin-resistant Stephylococcus aureus (MRSA) infections, weave their way into national news. And the reason is an alarming one: MRSA infection is caused “by a type of staph bacteria that’s become resistant to many antibiotics used to treat ordinary staph infections,” as described by the Mayo Clinic.

Most recently, New York Giants tight end Daniel Fells contracted the antibiotic resistant condition MRSA and was in danger of losing his foot and required multiple surgeries to rid his body of the infection. Although the bacteria isn’t problematic most of the time, it can quickly become deadly. According to the CDC, in 2013 nearly 10,000 people died from MRSA infections in the United States.

During the panel “Combating Antibiotic-Resistant Bacteria (CARB): AHRQ’s Role and Activities in the White House-Mandated National Enterprise” at the 2015 Agency for Healthcare Research and Quality (AHRQ) Research Conference, co-hosted with AcademyHealth, Dr. Edward Septimus noted that we’re in the perfect storm, experiencing antibiotic resistant conditions at more alarming rates and seeing decreased investment. What’s more is that investments in antibiotics may no longer be enough. Whereas antibiotics were “miracle drugs” in the past, in this decade Septimus asks if we’re seeing the rise of the post-antibiotic area.

In September 2014, in response to President Obama’s request, the President’s Council of Advisors on Science and Technology (PCAST) released its Report to the President on Combating Antibiotic Resistance, in which the council makes recommendations on what steps the federal government could take to tackle this crisis. The recommendations included in the report were: ensure strong federal leadership; effective surveillance and response for antibiotic resistance; fundamental research; clinical trials with new antibiotics; increase economic incentives for developing urgently needed antibiotics; improve stewardship of existing antibiotics in healthcare; limit the use of antibiotics in animal agriculture; and ensure effective international coordination.

To make the best of these recommendations, research needs to be conducted so the federal government has a sense of what works best, for whom, under what circumstances, and at what cost. Enter health services research—and AHRQ.

One area where AHRQ is focusing its CARB efforts is in that of MRSA. These studies, funded by AHRQ, could profoundly change the way we deliver care:

The STOP SSIs (Study to Optimally Prevent Surgical Site Infections) Project

The STOP SSIs project, funded under an AHRQ ACTION I contract, is a collaboration between The Joint Commission, the University of Iowa, and the University of Maryland aimed at determining whether screening, decolonization (an attempt to remove S arureus or MRSA or both from an individual known to be ‘colonized’), and selective use of cefazolin and vancomycin can substantially reduce S. aureus (the number one pathogen associated with SSIs) SSI rates. Surgical site infections are the number one health care-associated infection (HAI) related to increased length of stay and higher health care costs, with estimates ranging from 30-50 percent, and S. aureus is the most common reason for readmission after surgery.

Prior to the STOP SSIs Project, the effectiveness of this approach—referred to by researchers as an evidence-based bundle—had not previously been compared to the effectiveness of the bundle’s standalone elements or to the effectiveness of no bundle. Focusing specifically on patients undergoing cardiac or orthopedic operations, researchers found that a bundle comprising of the screening, decolonization, and targeted prophylaxis was associated with a modest decrease in complex S aureus SSIs. Specifically, researchers found that, per 10,000 operations, 36 cases of complex S aureus occurred for the preintervention versus 21 for the intervention period. Results of this study were recently published in JAMA.

The REDUCE MRSA (Randomized Evaluation Decolonization vs. Universal Clearance to Eliminate Methicillin-Resistant Staphylococcus aureus) Trial

AHRQ’s REDUCE MRSA Trial, which was conducted in the largest inpatient health system in the United States, examined which method was most effective overall for eliminating the presence of MRSA in cultures in intensive care units (ICUs). Would the use of special soaps and nose ointments reduce bacteria on the body during periods of high risk for infection—i.e., decolonization—or would screening and isolating those who tested positive be more effective?

A three arm cluster-randomized trial of the prevention strategies revealed that universal decolonization was the most effective intervention to reduce MRSA infections; it led to a 37 percent reduction in MRSA clinical cultures and a 44 percent reduction in all-cause bloodstream infections, according to AHRQ. Furthermore, the study found that universal decolonization was highly cost effective. As reported in the implications of the REDUCE MRSA trial, “Compared with screening and isolation, universal decolonization was estimated to save $171,000 and prevent nine additional bloodstream infections for every 1,000 ICU admissions.”

The PROTECT Project

The final project discussed, AHRQ’s PROTECT Trial, focuses on health care-associated infections in nursing homes. The 3 million nursing home residents in the United States experience 2-3 million preventable HAIs each year, resulting in more than 150,000 readmissions and 380,000 deaths. To date, trials have focused on hospitals, despite the growing number of infections occurring outside the hospital. The purpose of this project was to determine how generalizable we can be outside of the ICU and, if so, whether those steps are feasible and practical.

In the PROTECT Project, supported by AHRQ, researchers will enroll 28 nursing homes to evaluate the ability of routine bathing with antiseptic soap and routine use of topical nasal antiseptic to prevent multi-drug resistant organisms and readmissions due to HAIs.

*The Agency for Healthcare Research and Quality has been negatively targeted (for elimination by the House and for a 35 percent funding reduction by the Senate) in fiscal year 2016 appropriations. The health services research it supports is critical to improving the health research enterprise. Learn more and help #SaveAHRQ by visiting the AcademyHealth website.



The Obama administration recently made news by announcing that the number of people expected to obtain insurance under the exchanges will fall far short of previous projections. Specifically, they are now expecting about 10 million people to enroll in private exchange plans in 2016, compared to the 13 million that were previously thought might enroll not long ago.

Why so many fewer? Many have speculated as to the reasons behind this difference, but it doesn’t make sense to guess when we can just ask. The Commonwealth Fund did just that in their most recent Affordable Care Act Tracking Survey. Specifically, they analyzed responses from people who visited the exchanges, but did not decide to enroll in any insurance plans. About 25% of working-age adults had visited the marketplaces to shop for health insurance by Spring of 2015. About half of them eventually purchased health insurance, enrolling in a private plan about twice as often as Medicaid.

The good news is that, contrary to many people’s fears, young people were not under-represented in enrollees. More than a third of people signing up for insurance were 19-34 years old. Many of them qualified for Medicaid, but more than 30% of those who bought private plans were in the age group, as well.

The most important factor noted in the selection of a plan was the cost of the premium (41%). Next most common was the amount of the deductible and copayments (25%). This means that, in some way, the cost of health insurance was the most important factor in choosing a plan for two-thirds of people enrolling in the marketplace.

About 22% of people noted that their biggest concern was the size of their network, and whether their provider of choice was covered in a plan they were considering. That said, of those who had the option of choosing a cheaper plan with a narrower network, more than half decided to go that route.

When considering those who did not choose to enroll, more than half (57%) reported that they could not find a plan that they could afford.More than a third (38%) reported that they found the process difficult or confusing. And 43% found that they were not eligible to enroll in Medicaid or financial assistance. Many of the latter were likely in states that did not participate in the Medicaid expansion, meaning that they were too poor to qualify for subsidies, and could not afford private coverage without them.

The cost of insurance is still the main driver of uninsurance. This could be fixed with more generous subsidies, but such a change is unlikely to occur anytime soon. Increasing uptake of the Medicaid expansion would also make a difference, but that, too, is politically fraught, especially in an election year.

There are other options, however. People who received personal assistance in shopping for plans were much more likely to obtain them. Almost 80% of those who had help eventually signed up for coverage, versus 56% of those who didn’t. This may be because, without help, it’s very hard to make decisions. About half people who didn’t obtain coverage reported that it was difficult to compare premium costs. More than that had difficulty understanding differences in benefits covered, potential out-of-pocket costs, and who might be in and out of networks.

This could also be a problem with information dissemination. More than half of the people who didn’t enroll because of the cost of insurance were eligible for subsidies. It’s not clear whether the subsidies were just inadequate, or whether they understood  they were eligible at all. If the latter is the case, then – again – providing assistance might improve the chance that people might sign up for insurance plans. Doing so makes sense, given how bad people are at choosing health plans in general.

That’s the crucial thing to consider here. It is becoming abundantly clear that the Affordable Care Act has significantly reduced the numbers of the uninsured in the United States. It’s also becoming clear that there is still much work to be done to reduce those numbers further. There are many steps we can take to make sure that more people sign up for insurance. Whether we choose to do so is up to those implementing the policy,



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The Obama Administration is making a strong push to increase access to medication-assisted treatment (MAT) for addiction to opioids. In this and a prior post, I am reviewing evidence from previous MAT access expansion measures.

An estimated 2 million Americans abuse opioids, leading to $55.7 billion in social costs in 2007. In the 2000s, two laws aimed to make a dent in the problem by changing the accessibility of treatment for opioid dependence.

In 2000, the Drug Addiction Treatment Act (DATA) permitted qualified physicians to prescribe buprenorphine and related opioid substitution medications to up to 30 patients at one time and outside of opioid treatment programs like methadone clinics. The work of Andrew Dick and colleagues, which I described in a prior post, characterized the resulting expansion in access to substitution therapy.

In a subsequent paper published in Milbank Quarterly, the same authors (plus one more) assessed the association an Office of National Drug Control Policy Reauthorization Act of 2006 provision that permitted an increase in the number of patients to whom certain office-based physicians could prescribe buprenorphine at one time, from 30 to 100. The increase was available to physicians upon application, if they were actively treating patients with buprenorphine and had already been authorized for a year to prescribe it—so-called, “waivered” physicians because they held a waiver from the the registration requirements of the Controlled Substances Act.

Consequently, after 2006, two kinds of waivered physicians existed: “30″ and “100,” corresponding to the number of patients to whom they could prescribe buprenorphine under the law. Stein et al. studied how changes over time in numbers of 30- and 100-waivered physicians related to changes in grams of buprenorphine prescribed (both per capita), in urban and rural counties. They also examined the association of buprenorphine prescribing volume with numbers of methadone-dispensing opioid treatment programs and non-methadone dispensing substance abuse treatment facilities per capita.

The two charts below, which I made from data in the authors’ Table 1, show the growth in 30- and 100-waivered physicians over years 2004-2011 and by urban (blue) and rural (red) county status. The first chart shows substantial growth in 30-waivered physicians, from 3,293 in 2004 to 15,007 in 2011. 30-waivered physicians grew proportionally more in rural than urban counties over time, but from a much smaller base.


The chart just below shows that there were no 100-waivered physicians before 2007, as is expected since the law didn’t allow it. In 2007, there were 2,132 100-waivered physicians, growing to 5,403 in 2011. Proportional growth in rural counties was much larger than in urban ones (about doubling in urban counties but growing almost four-fold in rural ones), but, again, urban counties started with a much higher base.


Not shown in my charts, but included in the authors’ Table 1, the numbers of opioid treatment programs through which and substance abuse treatment facilities at which patients received buprenorphine grew over this period as well. Both started from a small base (71 of the former and 246 of the latter in 2004), and exceedingly small in rural counties (9 and 25, respectively). They experienced four-to-five-fold growth by 2011, across both county types.

Grams of buprenorphine dispensed was not consistently statistically significantly related to number of 30-waivered physicians, opioid treatment programs, or substance abuse treatment facilities. In the few years for which there was a statistically significant relationship for 30-waivered physicians, the results were small and negative, perhaps because relatively few 30-waivered physicians opt to dispense buprenorphine despite being authorized to do so.

However, 100-waivered physicians had a large, statistically significant relationship with grams dispensed in urban and rural counties in all but one year (the 2007, rural result was not statistically significant), as shown in the chart below, which I made from data in the authors’ Table 3. With the exception of 2007 and in urban counties, grams dispensed per 100-waivered physician was about 400 in urban counties and 500 in rural ones, in all years.

grams per phys

The authors put these numbers in clinical context:

Because the recommended daily dose of buprenorphine for treating opioid use disorders ranges is 16mg/day, with a maximum of 24mg/day (5.8 to 8.8 grams per year), our findings indicate that 24 (in 2007) to 45 (in 2011) additional patients received buprenorphine treatment per 100-patient waivered urban physician, assuming these physicians prescribe on the higher end of the daily dosage and individuals are treated for an entire year. For rural areas, assuming that waivered physicians prescribe on the higher end of the recommended daily dosage, our findings indicate that 57 additional patients received buprenorphine treatment per 100-waivered rural physician.

Scaling these figures up by the number of 100-waivered physicians in 2011, about 230,000 additional patients received treatment in urban areas and 15,000 in rural ones, assuming no substitution away from other means of treatment. The authors wrote,

Since buprenorphine’s approval, its availability from an increasing number of waivered physicians and substance abuse treatment facilities [refref] has raised the number of individuals receiving buprenorphine [refref] and often for the longer durations associated with improved outcomes. [...]

At the same time, more widely available buprenorphine can also have significant downsides, including medical emergencies due to ingestion by children [ref] diversion, and illicit use.

They found that,

The 2006 legislation allowing appropriately waivered physicians to treat more patients appears to have contributed to a substantial increase in the use of buprenorphine, which is encouraging at a time when a recent spike in heroin and illicit prescription opioid painkiller use has reinforced the importance of facilitating access to effective opioid agonist therapies.

As we combat the problematic use of opioids in America, it’s worth keeping in mind that efforts to reduce use in the first place don’t always help those already dependent. Policies that expand access to treatment are worthwhile complements.

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 or Boston University.


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The Obama Administration is making a strong push to increase access to medication-assisted treatment (MAT) for addiction to opioids. In this and a subsequent post, I will review evidence of prior MAT access expansion measures.

Treatment for opioid dependence is worth the cost but under-provided. Part of the problem is poor access to programs that offer substitution therapy like methadone or buprenorphine, particularly in rural areas. Policy can help. A 2000 law permitted an expansion of substitution therapy, and a recent study documented a substantial, subsequent increase in access to treatment for opioid dependence.

In 2000, the Drug Addiction Treatment Act (DATA) permitted an expansion of opioid substitution therapy. It did so by providing waivers from the registration requirements of the Controlled Substances Act to physicians so they could prescribe buprenorphine and related substitution treatment medications outside of opioid treatment programs like methadone clinics. Prior to DATA, substitution treatment was only available in treatment programs. In Health AffairsAndrew Dick and colleagues described the growth in and geographic distribution of opioid treatment programs and waivered physicians who could prescribe substitution therapy, from 2002-2011.

In their analysis, the authors characterized a county as having a shortage of treatment programs or waivered physicians if the number of providers per capita in the county was in the lowest decile among all counties or in the second-lowest decile and had high treatment need. Treatment need “was a function of the number of opioid related overdose deaths, heroin prices, and socioeconomic and demographic characteristics,” described in detail in an online appendix. A treatment shortage county was one that had both a waivered physician and opioid treatment program shortage.

The following chart from the paper shows that the percent of counties with treatment shortages dropped from about 50% to about 10% between 2002 and 2011. Nearly the entirety of this drop was due to waivered physicians, not treatment programs, suggesting a strong effect of the Drug Addiction Treatment Act.


As the following chart shows, reduction in treatment shortage varied by county urban/rural status. More urban counties saw greater reductions in shortages, relative to more rural ones.

shortages by county

Despite these gains in access to opioid substitution therapy, only 2.2% percent of physicians were waivered—and only 3% of primary care physicians—as of 2012. So, there is ample room for greater access, and particularly in rural areas.

Greater access to and care for opioid dependence is at least cost effective and some work shows it to be cost savings. Methadone treatment  reduces hospitalization and emergency department use and limits the spread of HIV by reducing the use and sharing of needles. Analyzing New England states, the Comparative Effectiveness Public Advisory Council found that as access to treatment increased so did savings to society, saving money in the long run. New England states could save $1.3 billion by expanding treatment of opioid-dependent persons by 25 percent, the Council found.

This all suggests that the Drug Addiction Treatment Act improved access to cost-effective and even cost-saving care. However, as Andrew Dick and colleagues point out, there are other barriers to access might require further policy development. These include stigma, un/under-insurance, managed care/behavioral health treatment requirements, among others.

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 or Boston University.


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On Tuesday night, the new coalition the Friends of NIMHD (National Institute on Minority Health and Health Disparities), housed at AcademyHealth, hosted a welcoming reception for new NIMHD Director Dr. Eliseo J. Pérez-Stable. In his role, Dr. Pérez-Stable will oversee the Institute within the National Institutes of Health (NIH) responsible for leading scientific research to improve minority health and eliminate health disparities—this includes not only the research component, but also ensuring a diverse research workforce, spreading research information, and fostering collaborations and partnerships. This mission is all done in support of the health system’s collective efforts to achieve the three aims of better care, smarter spending, and healthier people.

Much progress has been made in this space, but much remains to be done. Specifically, greater strides need to be made to address disparities in health care.

A positive first step was the transition of the National Center on Minority Health and Health Disparities to the NIMHD, an Institute at NIH; this move signaled to the community a more prominent focus on minority health and health disparities on the federal government agenda.

The Agency for Healthcare Research and Quality (AHRQ) is another entity that has recognized this need and acted upon it when, earlier this year, it changed the format of its Congressionally-mandated National Healthcare Quality and Disparities Report (QDR) to make the content easier to understand and more actionable for patients, physicians, policymakers, and care providers. The report now also tracks measures that align with the National Quality Strategy (NQS)—mandated by the Affordable Care Act (ACA)—since the NQS sets national priorities for health care quality improvement and the QDR tracks quality, access and disparities. The two go hand-in-hand.

In addition to releasing just the mandated report, AHRQ concurrently published QDR Chartbooks, which provide information on individual measures, such as rural health care and women’s health care, and the QDR Data and Tools, which allow users to drill down into the quality and disparities measures on both the state and national levels and which provide snapshot summaries of what’s happening across various measures.

For example, here in Washington, D.C. the performance of the District across all quality measures ranks in the “Average” range:

ahrq blog


Image Source: District of Columbia, State Snapshot, National Healthcare Quality and Disparities Reports, Agency for Healthcare Research and Quality, http://nhqrnet.ahrq.gov/inhqrdr/District%20of%20Columbia/snapshot/summary/All_Measures/All_Topics

To determine why D.C. received this ranking, AHRQ allows users to “Review Underlying Data,” which shows the rating under various quality measures (e.g., Hospice patients who received the right amount of medicine for pain, children ages 19-35 months who received 3 or more doses of polio vaccine). Users can see which measures achieved the benchmark, which were close to the benchmark, and which were far from the benchmark. The measures are also broken down by Race and Ethnicity.

As panelist Sabrina Matoff-Stepp, Health Resources and Services Administration, said during her presentation at the 2015 AHRQ Research Conference, co-hosted by AHRQ and AcademyHealth, data tells the story not only of a specific population (e.g., women), but also the story of the population to whom we’re comparing them, whether it be individuals of a different gender or racial/ethnic group.

Overall this story has a positive attribute; key findings from the 2014 QDR demonstrate that the nation has made progress in improving the health care delivery system to achieve the aims of better care. The QDR’s strength lies in that it identifies for policymakers and health care delivery organizations the system’s strengths and weaknesses, or where there is room for improvement (whether within specific populations or in the way care itself is being delivered).

At the end of the day, “Our data is only as good as what we do with it,” as Matoff-Stepp said. The QDR provides a solid foundation for those who work day in and day out to improve the health care system, giving them tools to better understand where gaps exist and thus, equipping them with the information they need to tackle those issues moving forward.

To access the 2014 QDR and its supporting materials, visit the AHRQ website.

*The Agency for Healthcare Research and Quality has been negatively targeted (for elimination by the House and for a 35 percent funding reduction by the Senate) in fiscal year 2016 appropriations. The health services research it supports is critical to improving the health research enterprise. Learn more and help #SaveAHRQ by visiting the AcademyHealth website.




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Patterns of opioid use and abuse changed in a big way around the end of 2010. What changed and why?

You may be old enough to recall answers to those questions from my post in February in which I described work by Richard Dart and colleagues. Using a variety of data sources, they found that after an abuse-deterrent form of OxyContin was released in August 2010, OxyContin abuse plummeted and heroin use picked up. Abuse-deterrent OxyContin is resistant to crushing and dissolving, operations that users can employ to achieve a faster, more intense high.

more recent study, published in April, supports these findings with different data. Marc Larochelle and colleagues, publishing in JAMA Internal Medicine, examined a cohort of over 31 million non-elderly, adult patients with coverage from a large insurer from 2003 through 2012.

They note that the release of reformulated OxyContin was just one of two opioid changes to occur in late 2010. In addition, propoxyphene was withdrawn from the market. (Propoxyphene is the active ingredient in the narcotic pain reliever Darvon and was frequently abused.) Their analysis assesses the independent effects of these two changes on prescribing and the joint effects on overdose, as observed in claims data.

Their effects were substantial and closely coincided with moderation in prescribing of other immediate-release and long-acting opioid medications. The chart below shows the collective impact, and others in the paper tease apart prescribing by agent. (The tall, thin region surrounded by dotted lines indicates the period during which reformulated OxyContin was released and propoxyphene withdrawn. MED = morphine-equivalent dose, a means of normalizing all opioids to an equivalent basis.)


Prescription opioid overdose also exhibits a structural break, as shown in the chart below.


Heroin overdoses, which had been on the rise, picked up steam.


As these results make clear, the authors mention, and as articulated more fully in the accompanying commentary by Hillary Kunins, abuse-deterrent formulations and withdraws of highly abused narcotics painkillers are only a partial solution to the opioid epidemic.

Additional public health policies that promote judicious opioid prescribing can reduce population overdose risk. Judicious use means favoring nonopioid or nonpharmacologic approaches to pain management and, if opioids are used, prescribing the lowest possible opioid dose for the shortest amount of time necessary to control pain. These strategies need to be strengthened along with the introduction of abuse-deterrent formulations of long-acting opioids. Promising public health approaches include prescription drug monitoring programs, pain clinic regulation, insurer and pharmacy benefit manager policies, and promulgation of guidelines.

Finally, there are proven, cost effective (even cost saving) methods of reducing the harm substance use disorders can cause.

To amplify individual health care professionals’ efforts, policy and structural approaches can increase availability and appeal of the full continuum of services, including treatment with effective pharmacotherapeutic agents (eg, methadone and buprenorphine) as well as harm reduction services (eg, naloxone distribution and access to sterile injection equipment).

Yet, as recently shown by Brandan Saloner and Shankar Karthikeyan in a JAMA letter, risk-adjusted treatment rates over the past decade or so for patients with opioid abuse disorder have remained flat.

It’s gratifying to see that we can influence opioid abuse, though disheartening to see that when we cut off one avenue, it pops up somewhere else. Something big happened in 2010, but it wasn’t enough.

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 or Boston University.


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