In welcome news for researchers, Congress is considering a bill that would stop CMS from deleting claims pertaining to substance use disorders from Medicare and Medicaid data. But the bill isn’t perfect. Federal privacy rules don’t just apply to CMS. They also prevent private payers—think here of employers and insurers—from sharing their data. And the bill as written doesn’t fix that.
That’s a big problem for the all-payer claims databases that have now been established in about sixteen states. To improve transparency and foster research, these databases are tasked with collecting claims data from public and private payers alike. The idea is to give state officials and researchers a comprehensive picture of what’s going on in the state’s health-care system.
Taking their lead from CMS, private payers have begun withholding substance use data from these databases. The gaps in the data will impede the effectiveness of these new databases, a particular concern in those New England states that hope to use them to address the growing heroin epidemic.
Austin and I have also learned that high-profile researchers lucky enough to work with private claims data have encountered obstacles to getting their hands on substance use data. Want to find out whether privately insured people shop around when they get treated for substance use disorders? Whether they’re more price-sensitive than when they’re seeking other kinds of treatments? Or whether HIV-positive employees stop taking their medication when prices go up? Forget about it.
At the risk of pushing our luck, Austin and I wanted to offer some slightly amended statutory language that would more comprehensively fix the problem:
In applying this section and part 2 of title 42 of the Code of Federal Regulations, the Secretary shall, by July 1, 2016, establish rules and regulations that will allow “third party payers,” as such term is defined under such part, to disclose patient identifying information to qualified researchers, subject to the privacy restrictions governing the disclosure of such information established in §2.52 of such part. In carrying out the previous sentence, the Secretary shall also, by not later than July 1, 2016:
(1) establish rules and regulations enabling “third party payers” to share patient identifying information with federal and state officials for the purpose of creating and maintaining a database of health-care claims, and authorizing those state officials to share such data with qualified researchers, subject to the privacy restrictions under §2.52 of such part; and
(2) restore access to qualified researchers of patient identifying information held by the Centers for Medicare & Medicaid Services for the programs under titles XVIII and XIX of the Social Security Act.
If you’ve got suggestions for how to improve this language, let me know via twitter, email, or in the comments (which we’ll leave open for a week).
Full disclosure: my son Noah played tackle football for a few years, and it was some of the most exciting kids’ sports we watched. I’ve been conflicted about the ongoing discussion about whether kids should be allowed to play tackle football. On the one hand, Noah and his teammates were so small that they didn’t hit each other with much force. And they loved playing. On the other, concussions are bad. Luckily, he “retired”, and I wasn’t forced to make a decision.
But I like to think I’m consistent in weighing risks and benefits. Others, however, advocate a “protect the children at all costs” approach.
In an NEJM Perspective piece this week, Kathleen Bachynski calls the AAP to task for its inconsistency with football:
At least 11 U.S. high-school athletes died playing football during the fall 2015 season. Their deaths attracted widespread media attention and provided fodder for ongoing debates over the safety of youth tackle football. In October 2015, the American Academy of Pediatrics (AAP) issued its first policy statement directly addressing tackling in football. The organization’s Council on Sports Medicine and Fitness conducted a review of the literature on tackling and football-related injuries and evaluated the potential effects of limiting or delaying tackling on injury risk. It found that concussions and catastrophic injuries are particularly associated with tackling and that eliminating tackling from football would probably reduce the incidence of concussions, severe injuries, catastrophic injuries, and overall injuries.
But rather than recommend that tackling be eliminated in youth football, the AAP committee primarily proposed enhancing adult supervision of the sport. It recommended that officials enforce the rules of the game, that coaches teach young players proper tackling techniques, that physical therapists and other specialists help players strengthen their neck muscles to prevent concussions, and that games and practices be supervised by certified athletic trainers. There is no systematic evidence that tackling techniques believed to be safer, such as the “heads-up” approach promoted by USA Football (amateur football’s national governing body), reduce the incidence of concussions in young athletes. Consequently, the AAP statement acknowledged the need for further study of these approaches. The policy statement also encouraged the expansion of nontackling leagues as another option for young players.
The AAP committee shied away from endorsing the elimination of tackling in youth football, because doing so would fundamentally change the way the game is played. Yet evidence indicates that tackle football in its current form is inconsistent with the AAP mission “to attain optimal physical, mental, and social health and well-being for all infants, children, adolescents and young adults.” Repetitive brain trauma can have serious short- and long-term consequences, including cognitive and attention deficits, headaches, mood disorders, sleep disturbances, and behavioral problems. To significantly reduce the incidence of brain trauma in young people, I believe that physicians should consider endorsing strategies that alter the way football is played.
I’d post the whole thing, but you should probably go over to the NEJM to read it. I’m still not sure where I stand on all of this, but I think her piece is well worth your time. I also think the AAP (and other groups) might need to think about being more consistent in their recommendations.
I feel like a lot of my blogging has been reactive this week. Someone says something, people get outraged, ask me what I think, and then I wind up here. So be it.
The CDC weighed in on alcohol and pregnancy yesterday. This should be relatively straightforward. It’s pretty widely believed that if a fetus is exposed to alcohol while in utero, it has a greater-than-zero risk of developing fetal alcohol syndrome. FASD is a collection of issues which include low birth weight and growth, and problems with organs such as the heart, kidney, and brain. Kids with FASD can have learning disabilities, communication issues, and a lower IQ. The problems can last a lifetime.
That said, there are a number of holes in our knowledge base that make preventing this difficult. No one knows how much alcohol is needed in utero for a child to develop FASD. No one knows when the exposure makes a difference. No one knows why some women can binge drink during pregnancy and have a normal child while others might drink much, much less and have a child with problems.
The American Academy of Pediatrics’s solution has been to declare that no amount of alcohol is safe during pregnancy, that there is no time during pregnancy that women can drink, and that no type of alcohol is ok. Although that’s not as widely accepted in other parts of the world, it’s felt like women in the US took that in stride without too much controversy. I know women who choose to drink the occasional glass of wine during pregnancy, but most women I know seem to abstain altogether during pregnancy.
Clearly, I don’t know a random selection of Americans, though. According to the CDC, about 10% of pregnant women report some alcohol use and about 3% report binge drinking in the last month. Pregnant women most likely to drink are 35-44 years old, not married, and college graduates. Those who report binge drinking in the last month say they did so between 4 and 5 times, more even than nonpregnant women.
I’m a “rate limiting step” guy. If we want to prevent FASD, starting with these women (who aren’t rare) might be a good start. Expanding to those who are still drinking alcohol might be the next place to go. But the CDC decided to go whole hog and recommend that no women who might possibly become pregnant should drink. This includes, of course, pretty much all women who have yet to go through menopause:
More than 3 million US women are at risk of exposing their developing baby to alcohol because they are drinking, having sex, and not using birth control to prevent pregnancy. About half of all US pregnancies are unplanned and, even if planned, most women do not know they are pregnant until they are 4-6 weeks into the pregnancy. This means a woman might be drinking and exposing her developing baby to alcohol without knowing it. Alcohol screening and counseling helps people who are drinking too much to drink less. It is recommended that women who are pregnant or might be pregnant not drink alcohol at all.
The subtitle of this article is, “Why take the risk?” and it’s part of a genre of “won’t somebody think of the children?” that leads to the “if just one child can be saved” thinking that winds up with the conclusion that all women should just be plugged into Matrix-style birthing chambers once they hit puberty, until they hit menopause. That’s clearly how you prevent anything from happening to a baby in utero, ever. Do I need to bring up cars? We do things every day, EVERY DAY, which increase the risk of death to children.
You need to weigh risks and benefits. What is the prevalence of FADS? Even the CDC can’t decide. In their Data & Statistics section, they say that some records can identify 0.2 to 1.5 infants with FADS for every 1000 births. A more recent study found 0.3 out of 1000 kids 7-9 years of age has FADS. Other in-person assessments found that 6-9 per 1000 kids might have a FADS.
But their new infographic proclaims that “Up to 1 in 20 US school children may have FADS.” Huh?
Moreover, their other infographic says that women who drink too much have a higher risk of injuries/violence, sexually transmitted diseases, and unintended pregnancy. That has caused the blogosphere to lose its s#$t, and I can’t blame them. The alcohol doesn’t CAUSE these things, and the CDC knows it. This is an association, and it’s part of a pathway, but the way they went about talking about it is being interpreted as victim blaming.
Why couldn’t the CDC just say that drinking too much causes you to lose control of your decision-making skills, which can lead to regret? For that matter, why is this part of the FASD discussion at all? It comes across as fear mongering about alcohol, period. If we go this route, why not just go back to Prohibition in an attempt to prevent FADS?
I get what the CDC is trying to say here. They’re saying that women can become pregnant if they’re having sex and not on birth control (true). Many women are pregnant and don’t know they are (true). If we want to limit the chance of a baby having FADS, we should try and limit the number of women who drink, thinking they’re not pregnant when they are (true). So women should think about being sexually active without birth control while they are still drinking alcohol in their life.
Unfortunately, that message didn’t get across. But before I blame the CDC completely, let me add that I don’t find the coverage by many in the media to be fair. Instead of trying to inform the public, talking about how the proper message should be getting across, too many are quick to use this as a “gotcha” moment to attack the CDC for their communication skills.
If we want to reduce FADS, and get the most bang for our buck, it’s worth starting with the too-many women who binge drink while they’re pregnant. Their fetuses are likely at highest risk. It’s probably worth talking to women who drink at all during pregnancy, to tell them we don’t know the amount or time that alcohol is safe, so that they can make an informed decision about drinking. It’s even worth telling women who are sexually active without birth control that if they think they might be pregnant, they should stop drinking.
Going beyond that with moralizing, shaming, complicating, and embellishing tactics likely doesn’t help.
No one gets better just from getting a mental health assessment. Screening and diagnosis only benefit a patient if the assessments lead to successful mental health treatment. In the current JAMA Pediatrics, Briannon O’Connor and her co-authors (I am one) report research on the care that adolescents receive after symptoms of depression are detected.
OBJECTIVE To determine rates of appropriate follow-up care for adolescents with newly identified depression symptoms in 3 large health systems.
DESIGN, SETTING, AND PARTICIPANTS In this analysis conducted from March to September 2014, structured data retrospectively extracted from electronic health records were analyzed for 3 months following initial symptom identification to determine whether the patient was followed up and, if so, whether treatment was initiated and/or symptoms were monitored. Records were collected from 2 large health maintenance organizations in the western United States and a network of community health centers in the Northeast. The study group included adolescents (N = 4612) with newly identified depression symptoms, defined as an elevated score on the Patient Health Questionnaire (10) and/or a diagnosis of depression.
MAIN OUTCOMES AND MEASURES Rates of treatment initiation, symptom monitoring, and follow-up care documented within 3 months of initial symptom identification.
We looked at follow-up care in some of the best health care systems in the country. We found major gaps in the care kids received.
RESULTS Among the 4612 participants, the mean (SD) age at index event was 16.0 (2.3) years, and 3060 were female (66%). Treatment was initiated for nearly two-thirds of adolescents (79% of those with a diagnosis of major depression; n = 1023); most received psychotherapy alone or in combination with medications. However, in the 3 months following identification, 36% of adolescents received no treatment (n = 1678), 68% did not have a follow-up symptom assessment (n = 3136), and 19% did not receive any follow-up care (n = 854). Further, 40% of adolescents prescribed antidepressant medication did not have any documentation of follow-up care for 3 months (n = 356). (Emphasis added.)
So about a third of adolescents who were identified with depression were not treated and of those who were treated, many did not have a follow-up visit or follow-up assessment that could assess treatment progress. Unfortunately, we couldn’t get data in this study that could tell us why the care didn’t occur.
This is bad. Follow-up care is important because the first mental health treatment a clinician tries may not work. Medication doses often need to be changed. Sometimes the particular form of psychotherapy proves unsuitable for the patient. Finally, although the benefits of anti-depressant medications for depressed adolescents likely outweigh the risks, the drugs can have side effects. Follow-up care is important to monitor whether young patients are safe.
When the US Preventive Services Task Force* considered whether adolescents should be screened for depression, they wrote that
The USPSTF recommends screening for major depressive disorder (MDD) in adolescents ages 12 to 18 years when adequate systems are in place for diagnosis, treatment, and monitoring. (Emphasis added)
I think they included the latter qualification because screening is pointless and wasteful if a positive screen does not lead to care. This study showed that systems that can reliably deliver follow-up care to adolescents are not in place even in good health care systems.
This doesn’t mean that we shouldn’t screen kids for depression. For one thing, many of the kids who were identified with depression did get treatment with follow-up care. What it means is that it’s not enough to screen. You have to fix the treatment and follow-up care systems too.
* See Aaron’s post here on the USPSTF’s recommendations about adult depression screening. The language I quote here is a draft of the Task Force’s proposed recommendation, but I believe it is likely to become part of the final language.
From JAMA Psychiatry, “Associations of Parental Depression With Child School Performance at Age 16 Years in Sweden“:
IMPORTANCE Depression is a common cause of morbidity and disability worldwide. Parental depression is associated with early-life child neurodevelopmental, behavioral, emotional, mental, and social problems. More studies are needed to explore the link between parental depression and long-term child outcomes.
OBJECTIVE To examine the associations of parental depression with child school performance at the end of compulsory education (approximately age 16 years).
DESIGN, SETTING, AND PARTICIPANTS Parental depression diagnoses (based on the International Classification of Diseases, Eighth Revision [ICD-8], International Classification of Diseases, Ninth Revision [ICD-9], and the International Statistical Classification of Diseases, 10th Revision [ICD-10]) in inpatient records from 1969 onward, outpatient records beginning in 2001, and school grades at the end of compulsory education were collected for all children born from 1984 to 1994 in Sweden. The final analytic sample size was 1 124 162 biological children. We examined the associations of parental depression during different periods (before birth, after birth, and during child ages 1-5, 6-10, and 11-16 years, as well as any time before the child’s final year of compulsory schooling) with the final school grades. Linear regression models adjusted for various child and parent characteristics. The dates of the analysis were January to November 2015.
MAIN OUTCOME AND MEASURE Decile of school grades at the end of compulsory education (range, 1-10, with 1 being the lowest and 10 being the highest).
I’ve written about depression many times before. Besides its devastating consequences to people who, themselves, are depressed, it also impairs their children. Prior work has shown that parental depression is associated with many detrimental consequences in early childhood, from a behavioral, social, and emotional standpoint. Long-term outcomes are less well understood.
This study sought to investigate the relationship between parental depression and school performance at 16 years of age in Sweden. Researchers examined a cohort of more than 1.1 million children born between 1984 and 1994. They gathered data from medical records from 1969 onward to see if their parents had a diagnosis of depression.
The main outcome of interest was the decile of school grades (1-10) at the end of compulsory education. They controlled for many things, like child characteristics including sex, birth year, birth order, and whether the child was part of a multiple birth. They accounted for pregnancy characteristics including maternal and paternal age, and maternal smoking during pregnancy. Family characteristics controlled for included parental education, disposable family income, parental region of birth, and parental alcohol abuse.
Both maternal and paternal depression at any time before the final compulsory school year were associated with worse school performance. Even after adjusting for all covariates, depression was associated with a reduction of almost half a decile. The effect was greater for girls than for boys.
There are limitations, of course. Depression that was never diagnosed would be missed. This is an epidemiological study, so causation is not assured, and other unmeasured confounding could be important.
We also don’t know whether the lower school performance is because children were affected by their parents’ depression, or because they, themselves, have problems because of genetic or familial predispositions.
Regardless, this study shows that parental depression is linked to long-term effects on children. Even depression when kids are young appears to be associated with worse school performance many years later. There are so many reasons to diagnose and treat depression, in both adults and children. This just might be one more.
If your home team is playing in the Super Bowl (looking at you, Denver Broncos and Carolina Panthers fans), the parties you attend could give you more than just heartburn, a hangover or temporary psychological discomfort.
They could give you the flu.
According to a new study published in the American Journal of Health Economics, the death rate from the flu is appreciably higher among those whose home team makes it to the Super Bowl.
This seemingly puzzling finding actually makes some sense. The Super Bowl occurs during the heart of flu season and is the reason many mingle at Super Bowl parties. And fans with their team in the big game are probably more likely to attend one.
The flu virus can spread whenever a person with it releases droplets of saliva — by coughing, sneezing or even talking — within six feet of someone without it. At a Super Bowl party, people are mingling closely.
The Super Bowl is far from the only event that increases flu transmission. Anything that puts more people in close contact during flu season does so.One study found that the reduction in air travel after the Sept. 11 terrorist attacks postponed that year’s flu peak by almost two weeks. The holiday closure of schools in France reduces flu cases by about 17 percent, according to another study.
Flu rates were higher at the Salt Lake City Winter Olympics in 2002, large music festivals in Hungary and Belgium, and the Hajj pilgrimage. It’s likely that other large gatherings during the flu season lead to greater transmission and mortality as well; they just haven’t been studied.
But the Super Bowl provided a convenient natural experiment. The economists who worked on the study — Charles Stoecker and Alan Barreca, from Tulane, and Nicholas Sanders, from Cornell — compared deaths of people who lived near Super Bowl-participating teams with those who lived near other N.F.L. teams. Using mortality data from 1974 to 2009, the researchers found that areas that send teams to the Super Bowl experience an 18 percent increase in flu deaths in those years, relative to other years and areas with an N.F.L. team not in the Super Bowl.
Across all ages, 5.6 people per million die from the flu, a rate that increases to about 6.6 in Super Bowl-contending areas. Flu deaths are concentrated among those 65 years and older — 40.7 people per million die from the flu. In Super Bowl-contending areas, that figure jumps to 48.
The flu also leads to doctor visits, hospitalizations and missed work and school. All told, the flu’s annual cost is about $100 billion nationally.
The mortality impact is about seven times larger when the peak of the flu season occurs closer to the Super Bowl than when it is held about three weeks or more before or after the peak. During years of more virulent flu strains, mortality effects are stronger. Some N.F.L. teams’ regions are more prone to the flu and flu mortality than others, because of differences in weather and demographics, which can be statistically controlled.
The researchers also found that flu mortality didn’t increase in Super Bowl-contending areas a year or two before or after their teams went to the game. In other words, their results are not driven by generally higher flu mortality in some regions than others — it’s the Super Bowl that makes the difference.
What can Super Bowl fans do to prevent the spread of the flu? Avoiding close contact with others who might be sick is an obvious way to reduce the chances of getting the flu. But for those who don’t want to miss Super Bowl parties and other gatherings during flu season, you can take other steps to reduce the risk.
The Centers for Disease Control and Prevention recommends that people get the flu vaccine; wash their hands frequently; avoid touching their eyes, nose and mouth; and clean surfaces at home. Those hosting Super Bowl parties — whether in Denver and Charlotte, N.C., or elsewhere — might supplement the beer and snacks with some hand sanitizer, and suggest to guests that a dab with each score could be part of the celebration.
The following is a guest post from Steven H Sheingold, Director, Division of Health Financing Policy, Office of Health Policy, Office of the Assistant Secretary for Planning and Evaluation, Department of Health and Human Services; Rachael Zuckerman, Economist, Office of Health Policy, Office of the Assistant Secretary for Planning and Evaluation, Department of Health and Human Services; and Adele Shartzer, Research Associate, Health Policy Center, The Urban Institute.
On January 27, Garret Johnson and Zoe Lyon, research assistants to Dr. Ashish Jha, provided a guest post titled Readmissions Revisited concerning our recent Health Affairs paper. We thank them for their excellent summary of the article and also want to recognize Professor Jha’s contributions to our understanding of readmission differences among hospitals.
There has been concern since the implementation of Medicare’s Hospital Readmission reduction program (HRRP) that safety net hospitals would be unfairly penalized. Whether or not to account for socioeconomic factors is an important and controversial policy issue for the HRRP and for all other health care payment systems that are based on quality indicators. Therefore we thought it useful to clarify a few issues raised by Johnson and Lyon.
First, they raise the issue that our analyses compared the safety net hospitals (the top 20% of hospitals based on their disproportionate share ratios) to all other hospitals rather than to the bottom 20% of hospitals. While the latter might be an interesting comparison, it is not fully relevant to the purposes of our paper. The HRRP penalties are not based on differences between the best and worst performers. Instead, the measure used to determine the HRRP’s penalties — called excess readmission ratio — compares each hospital to an adjusted national average.
Second, Johnson and Lyon were concerned about clustering of patients within hospitals which would make the model look like it has more data than it truly does, meaning that the standard errors are smaller than they should be. While we did not make this explicit in the paper, all of the models were estimated using generalized linear models (GEE) with exchangeable correlation structures. These models do account for correlation within hospitals.
Johnson and Lyon seem to infer that our objective was to slow and refocus the policy debate on this issue. In contrast, our paper provides some answers to move the discussion forward, albeit not as quickly as Johnson and Lyon would prefer. Our recommendations are in line with the evidence driven approach the Congress took under the IMPACT Act of 2014 by mandating and funding extensive research on the relationships between socioeconomic factors, quality and payment. This research, which is now well underway with the Department of Health and Human Services, will better inform policy development in the near future.
Johnson and Lyon advocate immediate implementation of an adjustment using the socioeconomic factors we already have in administrative data since our research shows these factors explain 25% of the difference in readmission rates between safety net and other hospitals, after accounting for the HRRP’s risk adjustment factors. This position misses some key issues policy makers might consider.
First, it presumes that the active debate over whether to adjust quality indicators for socioeconomic factors in payment systems has been resolved in that direction. We do not believe it has.
Second, they presume that the differences in readmission rates translate directly to penalties. In fact, as we noted in comparing penalties between the safety net and other hospitals, the current method of calculating excess readmissions has already eliminated a substantial share of the differential. Therefore, simply adding readily available socioeconomic factors to the current risk adjustor would not affect existing penalties appreciably — even after accounting for the more vulnerable financial position of safety net hospitals. Thus, additional consideration might be given to the costs of the regulatory and systems changes needed to implement such payment modification relative to the potentially very small impact they would have.
We share Johnson and Lyon’s concern for safety net hospitals. Our paper is clear that the plight of providers that treat the most vulnerable patients must be carefully evaluated as we move forward with a greater number of quality based payment mechanisms. In addition to the results of our statistical models, we simply point out what the data show — safety net and other providers have about the same size penalties despite the wide difference in raw readmission rates. At this point, we have not judged this result as fair or unfair as Johnson and Lyon suggest — policy makers must make that call after they are well informed with research and policy analysis.
Much to Austin’s and my surprise, we’ve learned that recent legislation introduced in the House of Representatives would, if enacted, restore research access to Medicare and Medicaid data on substance use disorders. Indeed, the relevant part of the bill is a slightly tweaked copy of language I floated last July here at TIE to accomplish the same goal.
This is really encouraging. As Austin and I have argued again and again, the CMS data-scrubbing impedes research into substance use disorders and into any conditions associated with such disorders, including HIV/AIDS. Yet such research is especially critical today given the opioid epidemic and a rash of HIV infections in rural areas.
Representative Tim Murphy added the relevant language last November during the subcommittee mark-up of a mental health bill that he’s sponsoring:
(i) CLARIFICATION.—In applying this section and part 2 of title 42 of the Code of Federal Regulations, the Secretary shall be considered a ‘‘program director’’ and not a ‘‘third party payor’’, as such terms are defined under such part, for purposes of disclosing patient identifying information to qualified researchers. In carrying out the previous sentence, the Secretary shall, by not later than January 1, 2016, and subject to privacy restrictions under such part, restore access to qualified researchers of patient identifying information held by the Centers for Medicare & Medicaid Services for the programs under titles XVIII and XIX of the Social Security Act.’’
The Murphy bill wouldn’t solve every problem associated with the data-scrubbing. After proposing the language, we learned that all-payer claims databases also can’t get the data they need. Not only is CMS withholding data from the databases, but private payers are starting to do the same. The Murphy bill doesn’t change the status quo for those private payers.
But the legislation would fix the problem with the Medicare and Medicaid data. It’s not the only fix in the works: SAMHSA intends to propose a rule that might also restore research access to data on substance use disorders. That proposal, though, is languishing in bureaucratic limbo at OMB. If it runs into problems, Congress may be the only show in town.
So this counts as progress. We’re not home yet, to be sure. The Murphy bill has made it out of subcommittee, but it’s controversial and it’s not clear that it’s going anywhere during an election year. Plus, its Senate counterpart and a Democrat-sponsored alternative don’t contain the same fix.
From our perspective, though, it’s easier to argue for cutting-and-pasting from an existing bill than to argue for lifting language from a blog post. If SAMHSA doesn’t fix the problem, maybe Congress will.
This past fall, I participated in a series of discussions hosted by the American Journal of Managed Care about health reform and the changing health insurance and delivery landscape. The video below is one exchange from the series. Around the third minute, discussion focuses on drug pricing.
I was joined by
- Leah Binder, President and CEO of The Leapfrog Group
- Margaret O’Kane, President of the National Committee for Quality Assurance
- Matt Salo, Executive Director of the National Association of Medicaid Directors
- Dennis Scanlon (moderator), Professor of Health Policy and Administration and Director of the Center for Healthcare and Policy Research, College of Health and Human Development, The Pennsylvania State University
I’ll post other videos from the discussion series, but if you can’t wait, you’ll find more here.