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Improving the Affordable Care Act Markets (Part 1)

By JONATHAN HALVORSON, PhD

With each passing year, the Affordable Care Act becomes further entrenched in the American health care system. There are dreams on both the far left and far right to repeal and replace it with something they see as better, but the reality is that the ACA is a remarkable achievement which will likely outlast the political lifetimes of those opposing it. Future improvements are more likely to tweak the ACA than to start over from scratch.

A critical part of making the ACA work is for it to support healthy, competitive and fair health insurance markets, since it relies on them to provide health care benefits and improve access to care. This is particularly true for insurance purchased by individuals and small employers, where the ACA’s mandates on benefits, premiums and market structure have the most impact. One policy affecting this dynamic that deserves closer attention is risk adjustment, which made real improvements in the fairness of these markets, but has come in for accusations that it has undermined competition.

Risk adjustment in the ACA works by compensating plans with sicker than average members using payments from plans with healthier members. The goal is to remove an insurer’s ability to gain an unfair advantage by simply enrolling healthier people (who cost less). Risk adjustment leads insurers to focus on managing their members’ health and appropriate services, rather than on avoiding the unhealthy. The program has succeeded enormously in bringing insurers to embrace enrolling and retaining those with serious health conditions.

This is something to celebrate, and we should not go back to the old days in which individuals or small groups would be turned down for health insurance or charged much higher prices because they had a history of health issues. However, the program has also had an undesired effect in many states: it further tilted the playing field in favor of market dominant incumbents.

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What’s on USMLE Step 1?

By BRYAN CARMODY

Recently, I was on The Accad and Koka Report to share my opinions on USMLE Step 1 scoring policy. (If you’re interested, you can listen to the episode on the show website or iTunes.)

Most of the topics we discussed were ones I’ve already dissected on this site. But there was an interesting moment in the show, right around the 37:30 mark, that raises an important point that is worthy of further analysis.

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ANISH: There’s also the fact that nobody is twisting the arms of program directors to use [USMLE Step 1] scores, correct? Even in an era when you had clinical grades reported, there’s still seems to be value that PDs attach to these scores. . . There’s no regulatory agency that’s forcing PDs to do that. So if PDs want to use, you know, a number on a test to determine who should best make up their class, why are you against that?

BRYAN: I’m not necessarily against that if you make that as a reasoned decision. I would challenge a few things about it, though. I guess the first question is, what do you think is on USMLE Step 1 that is meaningful?

ANISH: Well – um – yeah…

BRYAN: What do you think is on that test that makes it a meaningful metric?

ANISH: I – I don’t- I don’t think that – I don’t know that memorizing… I don’t even remember what was on the USMLE. Was the Krebs Cycle on the USMLE Step 1?

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I highlight this snippet not to pick on Anish – who was a gracious host, and despite our back-and-forth on Twitter, we actually agreed much more than we disagreed. And as a practicing clinician who is 15 years removed from the exam, I’m not surprised in the least that he doesn’t recall exactly what was on the test.

I highlight this exchange because it illuminates one of the central truths in the #USMLEPassFail debate, and that is this:

Physicians who took Step 1 more than 5 years ago honestly don’t have a clue about what is tested on the exam.

That’s not because the content has changed. It’s because the memories of minutiae fade over time, leaving behind the false memory of a test that was more useful than it really was.

I’m speaking from experience here.

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Health in 2 Point 00, Episode 98 | Connected Health, Pear Therapeutics & the Sutter Settlement

Today on Health in 2 Point 00, Jess and I are at Connected Health in Boston. On Episode 98, Jess asks me about Sandoz breaking up with Pear Therapeutics; Papa raising $10 million to send college students to keep seniors company (and I’m bitter); and the massive news of the Sutter settlement after they were sued for price fixing and monopoly behavior. Catch us at HLTH in Vegas in a couple of weeks, too. —Matthew Holt

Improving Medical AI Safety by Addressing Hidden Stratification

Jared Dunnmon
Luke Oakden-Rayner

By LUKE OAKDEN-RAYNER MD, JARED DUNNMON, PhD

Medical AI testing is unsafe, and that isn’t likely to change anytime soon.

No regulator is seriously considering implementing “pharmaceutical style” clinical trials for AI prior to marketing approval, and evidence strongly suggests that pre-clinical testing of medical AI systems is not enough to ensure that they are safe to use.  As discussed in a previous post, factors ranging from the laboratory effect to automation bias can contribute to substantial disconnects between pre-clinical performance of AI systems and downstream medical outcomes.  As a result, we urgently need mechanisms to detect and mitigate the dangers that under-tested medical AI systems may pose in the clinic.  

In a recent preprint co-authored with Jared Dunnmon from Chris Ré’s group at Stanford, we offer a new explanation for the discrepancy between pre-clinical testing and downstream outcomes: hidden stratification. Before explaining what this means, we want to set the scene by saying that this effect appears to be pervasive, underappreciated, and could lead to serious patient harm even in AI systems that have been approved by regulators.

But there is an upside here as well. Looking at the failures of pre-clinical testing through the lens of hidden stratification may offer us a way to make regulation more effective, without overturning the entire system and without dramatically increasing the compliance burden on developers.

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Are Neighbors the New Caregivers? | Matiu Bush, RMIT University & One Good Street

By JESSICA DAMASSA, WTF HEALTH

A few weeks ago, WTF Health took the show on the road to Australia’s digital health conference, HIC 2019. We captured more than 30 interviews (!) from the conference, which is run by the Health Informatics Society of Australia (hence the HISA Studio branding) and I had the opportunity to chat with most of the Australian Digital Health Agency’s leadership, many administrators from the country’s largest health systems, and a number of health informaticians, clinicians, and patients. I’ll be spotlighting a few of my favorites here in a four-part series to give you a flavor of what’s happening in health innovation ‘Down Under.’ For much more, check out all the videos on the playlist here.  

One of my favorite stories coming out of Australia is this one about One Good Street, an ad-hoc organization that is working to bring neighbors together to meet up with seniors to provide low-cost caregiving and combat loneliness. 

With a focus on connection and mitigating future hospitalization through neighborly acts of kindness, One Good Street offers neighbors the opportunity to help aging adults living on their block. 

Founder Matiu Bush explains how he started the platform, how it can save thousands of dollars in healthcare costs including unnecessary trips to the emergency room, and how he addresses concerns from the formal healthcare community who worry about “the risk” involved in neighbor-initiated care. 

Bonus! Matiu teaches us a new buzzword: “cybernetics” and talks about how he’s using that in a project with the Royal Melbourne Institute of Technology (RMIT) to build out models that detect loneliness and isolation in seniors.

Let Patients Lead – Explaining Addiction and Recovery to Families

By HANS DUVEFELT, MD

We knew that the most powerful way to provide substance abuse treatment is in a group setting. Group members can offer support to each other and call out each other’s self deceptions and public excuses, oftentimes more effectively than the clinicians. They share stories and insights, car rides and job leads, and they form a community that stays connected between sessions.

Participants with more experience and life skills may say things in group that we clinicians might hesitate saying, like “Now you’re whining” and “Time to put on your big boy pants”. They can become role models by being further along in their recovery and by at the same time revealing their own fear or respect for the threat of relapse.

What has also happened in our clinic, entirely unplanned, was that after an informational meeting where we explained the group model and had a national expert physician speak about opioid recovery, several parents raised their hand and said there should be a group for families, too.

We listened and within a few months we started such a group and now, a year and a half into it, the group is co-led by a few of our patients, who naturally had become leaders of the patient group earlier.

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How to End Egregious Medical Bills (while minimizing the impact on the provider’s bottom line)

By HAYWARD ZWERLING, MD

I recently saw a patient who received a bill for an outpatient procedure for $333. The Medicare allowable reimbursement for the procedure was $180. I have seen other medical bills where the healthcare provider was charging patients more than 10 times the amount they expected to receive from Medicare or any insurance company.

Another one of my patients had an unexpected medical complication which necessitated a visit to an emergency room. He received a huge bill for the services provided. When I subsequently saw him in my office (for poorly controlled diabetes) he told me he could not attend future office visits because he had so many outstanding medical bills and he could not risk incurring any additional medical expenses. While I offered to see him at no cost, he declined, stating the financial risk was too high.

A patient is required to pay the entire medical bill if they have:

  • no insurance
  • poor quality insurance
  • a bureaucratic “referral problem”
  • an out-of-network provider, which means they have no contractural relationship with the healthcare provider/institution, as might result from an emergency room visit or an unexpected hospitalization.

Hospitals, physicians and other healthcare providers usually do not know what they are going to get paid for any given service as they contract with many insurance companies, each of which has a different contracted payment rate. Healthcare providers and institutions typically set their fee schedule at a multiple of what they expect to get paid from the most lucrative payer so as to ensure they capture all the potential revenue. In the process, they create an economically irrational fee schedule which is neither reflective of a competitive marketplace nor reflective of the actual cost of the services provided.

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My Health Record Update

By JESSICA DaMASSA, WTF HEALTH

A few weeks ago, WTF Health took the show on the road to Australia’s digital health conference, HIC 2019. We captured more than 30 interviews (!) from the conference, which is run by the Health Informatics Society of Australia (hence the HISA Studio branding) and I had the opportunity to chat with most of the Australian Digital Health Agency’s leadership, many administrators from the country’s largest health systems, and a number of health informaticians, clinicians, and patients. I’ll be spotlighting a few of my favorites here in a four-part series to give you a flavor of what’s happening in health innovation ‘Down Under.’ For much more, check out all the videos on the playlist here.  

What trip Down Under would be complete without an update on the Australian government’s My Health Record program? The “opt out” period is over and now 22M Aussies (90% of the population) have electronic records managed by the gov’t. Bottom line: They’ve built it, no one’s really opted out, but no one’s really come yet either…especially on the provider side to populate the record with info.

Here are four different takes on what’s going on and what’s next.

For the ‘general gist’ of what’s happening:

Elizabeth Deveny, Chair of the Australian Digital Health Agency

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How are hospitals supposed to reduce readmissions? Part III

By KIP SULLIVAN, JD

The Medicare Payment Advisory Commission (MedPAC) and other proponents of the Hospital Readmissions Reduction Program (HRRP) justified their support for the HRRP with the claim that research had already demonstrated how hospitals could reduce readmissions for all Medicare fee-for-service patients, not just for groups of carefully selected patients. In this three-part series, I am reviewing the evidence for that claim.

We saw in Part I and Part II that the research MedPAC cited in its 2007 report to Congress (the report Congress relied on in authorizing the HRRP) contained no studies supporting that claim. We saw that the few studies MedPAC relied on that claimed to examine a successful intervention studied interventions administered to carefully selected patient populations. These populations were severely limited by two methods: The patients had to be discharged with one of a handful of diagnoses (heart failure, for example); and the patients had to have characteristics that raised the probability the intervention would work (for example, patients had to agree to a home visit, not be admitted from a nursing home, and be able to consent to the intervention).

In this final installment, I review the research cited by the Yale New Haven Health Services Corporation (hereafter the “Yale group”) in their 2011 report to CMS in which they recommended that CMS apply readmission penalties to all Medicare patients regardless of diagnosis and regardless of the patient’s interest in or ability to respond to the intervention. MedPAC at least limited its recommendation (a) to patients discharged with one of seven conditions/procedures and (b) to patients readmitted with diagnoses “related to” the index admission. The Yale group threw even those modest restrictions out the window.

The Yale group recommended what they called a “hospital-wide (all-condition) readmission measure.” Under this measure, penalties would apply to all patients regardless of the condition for which they were admitted and regardless of whether the readmission was related to the index admission (with the exception of planned admissions). “Any readmission is eligible to be counted as an outcome except those that are considered planned,” they stated. (p. 10) [1] The National Quality Forum (NQF) adopted the Yale group’s recommendation almost verbatim shortly after the Yale group presented their recommendation to CMS.

In their 2007 report, MedPAC offered these examples of related and unrelated readmissions: “Admission for angina following discharge for PTCA [angioplasty]” would be an example of a related readmission, whereas “[a]dmission for appendectomy following discharge for pneumonia” would not. (p. 109) Congress also endorsed the “related” requirement (see Section 3025 of the Affordable Care Act, the section that authorized CMS to establish the HRRP). But the Yale group dispensed with the “related” requirement with an astonishing excuse: They said they just couldn’t find a way to measure “relatedness.” “[T]here is no reliable way to determine whether a readmission is related to the previous hospitalization …,” they declared. (p. 17) Rather than conclude their “hospital-wide” readmission measure was a bad idea, they plowed ahead on the basis of this rationalization: “Our guiding principle for defining the eligible population was that the measure should capture as many unplanned readmissions as possible across a maximum number of acute care hospitals.” (p. 17) Thus, to take one of MedPAC’s examples of an unrelated admission, the Yale group decided hospitals should be punished for an admission for an appendectomy within 30 days after discharge for pneumonia. [2]

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Click and Exercise! Amazon, Netflix, Hulu—Are You Listening?

By DEBORAH A. COHEN

Physical inactivity is a mounting challenge for America. In reviewing the 2013-2015 American time use survey, we found that most Americans report spending their daily leisure time watching screens, and devote only a small fraction of leisure time—24 minutes for men and 14 minutes for women—to physical activity. A recent longitudinal examination of the National Health and Nutrition Examination Survey showed that sitting time increased by an hour a day between 2007 and 2016, with the largest increases among adolescents ages 12-19 and adults, 20 years and older. As mortality rates for heart disease have begun to climb, increases in sedentary behavior bodes poorly for future control of disease and health care costs.

The explosion in streaming apps and content is likely contributing to the increased sitting time. According to the Motion Picture Association of America, TV and movie views have more then doubled between 2014 and 2018. The availability of multiple series and the ability to binge watch can keep people glued to their couches for hours at a time. The immersive quality of the programming makes it increasingly difficult for viewers to pull themselves away from their screens. Yet, the technology could provide options to help viewers watch and still get regular physical activity.

Currently, after each episode, an option is available to allow the viewer to immediately call up the next episode. Why not consider adding a pop-up that can remind viewers that sitting more than 20-30 minutes at a time may not be good for health, and that it’s important to move around to avoid chronic diseases? A narrator could ask viewers to treat themselves to an activity break. Then the viewers could have the option to choose a short video that can guide them through a 10- minute exercise break. Or even a 5-minute break. Something is better than nothing.

There could be many options, from a just a simple stand up and stretch, like the 7th inning break at a baseball game, to vigorous workouts, like the 7-minute workout published by the American College of Sports Medicine or doing a Bhangra dance with a Bollywood film star. 

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