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Tag: Outcomes

6. Invest in the basic science of measurement development and applications.

The unfortunate reality is that there is no body of expertise with responsibility for addressing the science of performance measurement. The National Quality Forum (NQF) comes closest, and while it addresses some scientific issues when deciding whether to endorse a proposed measure, NQF is not mandated to explore broader issues to advance the science of measure development, nor does it have the financial support or structure to do so.

An infrastructure is needed to gain national consensus on: what to measure, how to define the measures, how to collect the data and survey for events, what is the accuracy of EHRs as a source of performance, the cost-effectiveness of various measures, how to reduce the costs of data collection, how to define thresholds for measures regarding their accuracy, and how to prioritize the measures collected (informed by the relative value of the information collected and the costs of data collection).

Despite this broad research agenda, there is little research funding to advance the basic science of performance measurement. Given the anticipated broad use of measures throughout the health system, funding can be a public/private partnership modeled after the Patient-Centered Outcomes Research Institute or a federally-funded initiative, perhaps centered at AHRQ. Given budgetary constraints, finding the funding to support the science of measurement will be a challenge. Yet, the costs of misapplication of measures and incorrect judgments about performance are substantial.

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4. Measure patient experience with care and patient-reported outcomes as ends in themselves.

Performance measurement has too often been plagued by inordinate focus on technical aspects of clinical care—ordering a particular test or prescribing from a class of medication—such that the patient’s perspective of the care received may be totally ignored. Moreover, many patients, even with successful treatment, too often feel disrespected. Patients care not only about the outcomes of care but also and their personal experience with care.

There is marked heterogeneity in the patient experience, and the quality of attention to patients’ needs and values can influence their course, whether or not short-term clinical outcomes are affected. Some patients have rapid recovery of function and strength, and minimal or no symptoms. Other patients may be markedly impaired, living with decreased function, substantial pain, and other symptoms, and with markedly diminished quality of life. It would be remiss to assume that these two groups of patients have similar outcomes just because they have avoided adverse clinical outcomes such as death or readmission.

In recommending a focus on measuring outcomes rather than care processes, we consider surveys or other approaches to obtaining the perspectives of patients on the care they receive to be an essential component of such outcomes. When designed and administered appropriately, patient experience surveys provide robust measures of quality, and can capture patient evaluation of care-focused communication with nurses and physicians [24]. And while patient-reported measures appear to be correlated with better outcomes, we believe they are worth collecting and working to improve in their own right, whether or not better experiences are associated with improved clinical outcomes [25].

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The Oregon Experiment Revisited

It has been a couple of weeks since the landmark Oregon Experiment paper came out, and the buzz around it has subsided.  So what now?  First, with passage of time, I think it is worth reflecting on what worked in Oregon.  Second, we should take a step back, and recognize that what Oregon really exposed is that health insurance is a small part of a much bigger story about health in general.  This bigger story is one we can’t continue to ignore.

So let’s talk quickly about what worked in Oregon.  Health insurance, when properly framed as insurance (i.e. protection against high, unpredictable costs) works because it protects people from financial catastrophe.  The notion that Americans go bankrupt because they get cancer is awful and inexcusable, and it should not happen. We are a better, more generous country than that.  We should ensure that everyone has access to insurance that protects against financial catastrophe.  Whether we want the government (i.e. Medicaid, Medicare) or private companies to administer that insurance is a debate worth having.  Insurance works for cars and homes, and the Oregon experiment makes it clear that insurance works in healthcare.  No surprise.

The far more interesting lesson from Oregon is that we should not oversell the value of health insurance to improving people’s health.  While health insurance improves access to healthcare services (modestly), its impact on health is surprisingly and disappointingly small.  There are two reasons why this is the case.  The first is that not having insurance doesn’t actually mean not having any access to healthcare.  We care for the uninsured and provide people life-saving treatments when they need it, irrespective of their ability to pay.  Sure – we then stick them with crazy bills and bankrupt them – but we generally do enough to help them stay alive.  Yes, there’s plenty of evidence that the uninsured forego needed healthcare services and the consequences of being uninsured are not just financial.  They have health consequences as well.  But, claims like 50,000 Americans die each year because of a lack of health insurance? The data from Oregon should make us a little more skeptical about claims like that.

So what really matters?  Right now, we are pouring $2.8 trillion into healthcare services while failing to deliver the basics.  To borrow a well-known phrase, our healthcare system is perfectly designed to produce the outcomes we get – and here’s what we get: mediocre care and lousy outcomes at high prices.  Great.

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Misunderstanding Oregon

Much has already been written about the Oregon Medicaid study that just came out in the New England Journal of Medicine. Unfortunately, the vast majority is reflex, rather than reflection.  The study seems to serve as a Rorschach test of sorts, confirming people’s biases about whether Medicaid is “good” or “bad”.

The proponents of Medicaid point to all the ways in which Medicaid seems to help those who were enrolled – and the critics point to all the ways in which it didn’t.  But, if we take a step back to read the study carefully and think about what it teaches us, there is a lot to learn.

Here is a brief, and inadequate, summary (you should really read the study):  In 2008, Oregon used a lottery system to give a set of uninsured people access to Medicaid.  This essentially gave Kate Baicker and her colleagues a natural experiment to study the effects of being on Medicaid.

Those who won the lottery and gained access were compared to a control group who participated in the lottery but weren’t selected.  Opportunities to conduct such an experiment are rare and represent the gold standard for studying the effect of anything (e.g. Medicaid) on anything (like health outcomes).

Two years after enrollment, Baicker and colleagues examined what happened to people who got Medicaid versus those who remained uninsured.  There are six main findings from the study.  Compared to people who did not receive Medicaid coverage:

  1. People with Medicaid used more healthcare services – more doctor visits, more medications and even a few more ER visits and hospitalizations, though these last two were not statistically significant.
  2. People with Medicaid were more likely to get lots of tests – some of them probably good (cholesterol screening, Pap smears, mammograms) and some of them, probably bad (PSA tests).
  3. People with Medicaid, therefore, not surprisingly, spent more money on healthcare overall.
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Evidence That Health Does Not Equal Healthcare? Early Results From the Oregon Experiment Are In

The most important study in American health policy in decades, the Oregon Health Insurance Experiment, published two-year results Wednesday in the New England Journal of Medicine. If you’re reading up on the topic, get ready for bombastic claims and scorching heat as opposed to illuminating light. The quick read leads to an easy Drudge headline – “MEDICAID DOESN’T MAKE PEOPLE HEALTHIER: OBAMACARE WILL FAIL!” – but a fuller reading of the evidence provides a more optimistic, and honest, take.

In 2008, Oregon had 90,000 individuals who wanted to enroll in its Medicaid program, but the funding to enroll only a fraction. So it decided to use the opportunity to create an unparalleled experiment: the first Randomized Controlled Trial (RCT) – the gold standard research methodology that is able to isolate the causal effect of an intervention – in Medicaid history. It endeavored to show nothing less than the actual, causal effect that Medicaid has on its population, a first in the field.

This study, in other words, is a big, big deal.

Two years of data are in, and the results are mixed. First up, the disappointing: Medicaid coverage.

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Why Disease Management Won’t Be Going Away Any Time Soon

We’re all aware of the past criticisms of “disease management.” According to the critics, these for-profit vendors were in collusion with commercial insurers, relying robo-calls to blanket unsuspecting patients with dubious advice. Their claims of “outcomes” were based on flawed research that was never intended to be science; it was really intended to market their wares.

But suppose this correspondent alerted you to:

1. A company that had developed a patient registry to identify at-risk patients who had not received an evidence-based care recommendation? Software created mailings to those patients that not only informed them of the recommendation but offered them a toll-free number to call if there were questions. Patients who remained non-compliant were then called by coordinators, who made three attempts to contact the patient and assist in any scheduling needs. If necessary, a nurse was available to telephonically engage patients and develop alternative care options.

If you think that sounds like typical vendor-driven telephonic disease management, you’d be right.  You’d also be describing an approach to care that was studied by Group Health Cooperative using their electronic record, medical assistants and nurses.  When it was applied to colon cancer screening, a randomized study revealed each additional level of support progressively resulted in statistically significant screening rates.

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Health Care Shibboleth

“We spend far more on health care than other peer countries yet have worse outcomes. Why is U.S. health care so expensive?” I’m sure you’ve encountered similar statements, maybe even expressed it yourself. It occurs often, including by knowledgeable people and health-related institutions. However, it’s a fallacy because it confuses health care with population health.

Health care is a proper subset of population health. For example, longevity is determined by more than just health care. Using a specific recent estimate (Appendix Exhibit A6 – gated), an average 20-year old U.S. white male who did not graduate high school will live 10.5 fewer years than a similar man with a college degree. That’s over ten years of life related to educational attainment. Sure, there are many reasons for the difference, and health care or the lack of it is only one of them.

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Accountable Care Organizations Can Change Everything, But Only If We Get the Definition Right

Writing in the March 20 issue of JAMA, Drs. Douglas Noble and Lawrence Casalino say that supporters of Accountable Care Organizations (ACOs) are all muddled over “population health.”

This correspondent says the article is what is muddled and that the readers of JAMA deserve better.

According to the authors, after the Affordable Care Act launched the Medicare Accountable Care Organizations (ACOs), their stated purpose has morphed from Health-System Ver. 2.0 controlling the chronic care costs of their assigned patients to Health System Ver. 3.0 collaboratively addressing “population health” for an entire geography.

Between the here of “improving chronic care” and the there of “population health,” Drs Noble and Casalino believe ACOs are going to have to confront the additional burdens of preventive care, social services, public health, housing, education, poverty and nutrition. That makes the authors wonder if the term “population health” in the context of ACOs is unclear. If so, that lack of clarity could ultimately lead naive politicians, policymakers, academics and patients to be disappointed when ACOs start reporting outcomes that are limited to chronic conditions.

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Engaged Patients Translate to Better Outcomes and Costs

The expansion of health insurance coverage may be the most visible aspect of health reform, but other elements will ultimately have a significant impact on how we all experience health care. One pivotal change is how health care organizations are paid. New payment approaches will reward providers based on whether services actually improve patients’ health and keep costs down versus simply incentivizing them to provide more care.

One of the more consequential changes will be a greater focus on helping patients to be more involved in their care. There is ample evidence that the behaviors people engage in and the health care choices they make have a very clear effect on both health and costs, positively and negatively. The most innovative health care delivery systems recognize this and see their patients as assets who can help them achieve the goals of better health at lower costs. From this point of view, “investing” in patients and helping them to be more effective partners in care makes good sense.

Our study, reported in the February issue of Health Affairs, highlights this role that patients play in determining health-related outcomes. We found that patients who were more knowledgeable, skilled and confident about managing their day-to-day health and health care (also known as “patient activation,” measured by the Patient Activation Measure) had health care costs that were 8 percent lower in the base year and 21 percent lower in the next year compared to patients who lacked this type of confidence and skill. These savings held true even after adjusting for patient differences, such as demographic factors and the severity of illnesses.

Even among patients with the same chronic illness, those who were more “activated” had lower overall health care costs than patients who were less so. Among asthma patients, the least activated patients had costs that were 21 percent higher than the most activated patients. With high blood pressure, the cost differential was 14 percent.

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Getting Pay-For-Performance Right

Over the past decade, there has been yet another debate about whether pay-for-performance, the notion that the amount you get paid is tied to some measure of how you perform, “works” or not. It’s a silly debate, with proponents pointing to the logic that “you get what you pay for” and critics arguing that the evidence is not very encouraging. Both sides are right.

In really simple terms, pay-for-performance, or P4P, can be thought about in two buckets: the “pay” part (how much money is at stake) and the “performance” part (what are we paying for?). So, in this light, the proponents of P4P are right: you get what you pay for. The U.S. healthcare system has had a grand experiment with P4P: we currently pay based on volume of care and guess what? We get a lot of volume. Or, thinking about those two buckets, the current fee-for-service structure puts essentially 100% of the payments at risk (pay) and the performance part is simple: how much stuff can you do? When you put 100% of payments at risk and the performance measure is “stuff”, we end up with a healthcare system that does a tremendous amount of stuff to patients, whether they need it or not.

Against these incentives, new P4P programs have come in to alter the landscape. They suggest putting as much as 1% (though functionally much less than that) on a series of process measures. So, in this new world, 99%+ of the incentives are to do “stuff” to patients and a little less than 1% of the incentives are focused on adherence to “evidence-based care” (though the measures are often not very evidence-based, but let’s not get caught up in trivial details). There are other efforts that are even weaker. None of them seem to be working and the critics of P4P have seized on their failure, calling the entire approach of tying incentives to performance misguided.

The debate has been heightened by the new national “value-based purchasing” program that Congress authorized as part of the Affordable Care Act. Based on the best of intentions, Congress asked Medicare to run a program where 1% of a hospital’s payments (rising to 2% over several years) is tied to a series of process measures, patient experience measures, and eventually, mortality rates and efficiency measures. We tried a version of this for six years (the Premier Hospital Quality Incentives Demonstration) and it didn’t work. We will try again, with modest tweaks and changes. I really hope it improves patient outcomes, though one can understand why the skeptics aren’t convinced.Continue reading…

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