I sometimes explain to medical students that they are entering a profession being transformed, like coal to diamonds, under the pressure of a new mandate. “The world is going to push us, relentlessly and without mercy, to deliver the highest quality, safest, most satisfying care at the lowest cost,” I’ll say gravely, trying to get their attention.
“What exactly were you trying to do before?” some have asked, in that wonderful way that smart students blend naiveté with blinding insight.
It is pretty amazing that healthcare has been insulated from the business pressures that everybody from Yahoo! to my father’s garment business have experienced since the days of Adam Smith. We experienced a bit of this pressure in the mid-1990s, when pundits declared healthcare inflation “unsustainable” (sound familiar?) and we invented managed care to slay it. We know how that story ended – the public and professional backlash against HMOs defanged the managed care tiger to the point that it could barely produce a “meow.” The backlash was followed by a 15-year run during which efforts to slash healthcare costs have been remarkably meager.
That run has ended.
Luckily, while we’ve been let off the hook on cost-reduction, we’ve not been given a free pass on improvement. Beginning with the Institute of Medicine reports on safety (2000) and quality (2001), we have been under growing pressure to improve the numerator of the value equation: patient safety, quality of care, and patient satisfaction. Particularly for those of us who work in hospitals, we now feel this pressure from many angles: from accreditors (more vigorous and unannounced Joint Commission inspections, residency duty hour limits), transparency (Medicare’s Hospital Compare), comparative measurement (HealthGrades, Leapfrog, Consumer Reports and many other hospital rankings), and, most recently, payment policies (no pay for “never events,” penalties for readmissions, value-based purchasing, and “Meaningful Use” standards for IT).
These initiatives have created an increasingly robust business case to improve. Hospitals everywhere have responded with new resources, committees, ways of analyzing data, educational programs, computer systems, and more.
There is a plethora of health care quality data being pushed out to the public, yet no rules to assure the accuracy of what is being presented publicly. The health care industry lacks standards for how valid a quality measure should be before it is used in public reporting or pay-for-performance initiatives, although some standards have been proposed.
The NQF does a good job of reviewing and approving proposed measures presented to it, but lacks the authority to establish definitive quantitative standards that would apply broadly to purveyors of performance measures. However, as discussed earlier, many information brokers publically report provider performance without transparency and without meeting basic validity standards. Indeed, even CMS, which helps support NQF financially, has adopted measures for the Physician Quality Reporting System that have not undergone NQF review and approval. Congress now is considering “SGR repeal,” or sustainable growth rate legislation, that would have CMS work directly with specialty societies to develop measures and measurement standards, presumably without requiring NQF review and approval .
Without industry standards, payers, policy makers, and providers often become embroiled in a tug-of-war; with payers and policy-makers asserting that existing measures are good enough, and providers arguing they are not. Most often, neither side has data on how good the contested measures actually are. Most importantly, the public lacks valid information about quality, especially outcomes, and costs.
Indeed, most quality measurement efforts struggle to find measures that are scientifically sound yet feasible to implement with the limited resources available. Unfortunately, too often feasibility trumps sound science. In the absence of valid measures, bias in estimating the quality of care provided will likely increase in proportion to the risks and rewards associated with performance. The result is that the focus of health care organizations may change from improving care to “looking good” to attract business. Further, conscientious efforts to reduce measurement burden have significantly compromised the validity of many quality measures, making some nearly meaningless, or even misleading. Unfortunately, measurement bias often remains invisible because of limited reporting of data collection methods that produce the published results. In short, the measurement of quality in health care is neither standardized nor consistently accurate and reliable.
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.
Initiatives to promote performance measurement need to be accompanied by support to improve care. Quality measure data should not only be technically correct, but should be organized such that their dissemination is a resource to aid in quality improvement activities. As such, quality measurement should be viewed as just one component of a learning health care system that also includes advancing the science of quality improvement, building providers’ capacity to improve care, transparently reporting performance, and creating formal accountability systems.
There are several strategies to make quality measure data more actionable for quality improvement purposes. For example, for publicly reported outcome measures, CMS provides hospitals with lists of the patients who are included in the calculation. Since the outcomes may occur outside the hospital for mortality and for readmissions that are at other hospitals, this information is often beyond what the hospitals already have available to them. These data give providers the ability to investigate care provided to individual patients, which in turn can support a variety of quality improvement efforts.
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 . 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 .
While working to develop a broad set of outcome measures that can be the basis for attaining the goals of public accountability and information for consumer choice, Medicare should ensure that the use of performance measures supports quality improvement efforts to address important deficiencies in how care is provided, not only to Medicare beneficiaries but to all Americans.
CMS’ current focus on reducing preventable rehospitalizations within 30 days of discharge represents a timely, strategic use of performance measurement to address an evident problem where there are demonstrated approaches to achieve successful improvement . Physicians and hospital clinical staff, if not necessarily hospital financial officers, generally have responded quite positively to the challenge of reducing preventable readmissions.
CMS has complemented the statutory mandate to provide financial incentives to hospitals to reduce readmission rates by developing new service codes in the Medicare physician fee schedule that provide payment to community physicians to support their enhanced role in assuring better patient transitions out of the hospital in order to reduce the likelihood of readmission . CMS recently announced that after hovering between 18.5 percent and 19.5 percent for the past five years, the 30-day all-cause readmission rate for Medicare beneficiaries dropped to 17.8 percent in the final quarter of 2012 , simplying some early success with efforts to use performance measures as part of a broad quality improvement approach to improve a discrete and important quality and cost problem.
However, this Timely Analysis of Immediate Health Policy Issues 3“CMS’ current value-based purchasing efforts, requiring reporting on a raft of measures of varying usefulness and validity, should be replaced with the kind of strategic approach used in the national effort to reduce bloodstream infections.”approach is not without controversy.
Improvements have been modest, and some suggest that readmission rates are often outside the hospital’s control, so CMS’ new policy unfairly penalizes hospitals that treat patients who are the sickest . And while readmission in surgical patients is largely related to preventable complications, readmissions in medical patients can be related to socioeconomic status. Also, some have questioned the accuracy of CMS’ seemingly straightforward readmission rate measure, finding that some hospitals reduce both admissions and readmissions—a desirable result—yet do not impact the readmission rate calculation . And one of this paper’s authors (R. Berenson) has suggested a very different payment model that would reward hospital improvement rather than absolute performance, thereby addressing the reality that hospitals’ abilities to influence readmission rates do vary by factors outstside of their control .
There is growing interest in relying more on outcome measures and less on process measures, since outcome measures better reflect what patients and providers are interested in. Yet establishing valid outcome measures poses substantial challenges—including the need to riskadjust results to account for patients’ baseline health status and risk factors, assure data validity, recognize surveillance bias, and use sufficiently large sample sizes to permit correct inferences about performance. We believe the operational challenges of moving to producing accurate and reliable outcome measures, though daunting, are worth the effort to overcome.
Patients, payers, policy-makers, and providers all care about the end results of care—not the technical approaches that providers may adopt to achieve desired outcomes, and may well vary across different organizations. Public reporting and rewards for outcomes rather than processes of care should cause provider organizations to engage in broader approaches to quality improvement activities, ideally relying on rapid-learning through root cause analysis and teamwork rather than taking on a few conveniently available process measures that are actionable but often explain little of the variation in outcomes that exemplifies U.S. health care.
However, given the inherent limitations of administrative data, which are used primarily for payment purposes, and even clinical information in electronic health records (EHRs), consideration should be given to developing a national, standardized system for outcome reporting . A new outcome reporting system would not be simple or inexpensive, but current data systems may simply be insufficient to support accurate reporting of outcomes. An example is the National Health Care Safety Network system for reporting health care infections .
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.
The Leapfrog Group has just released its latest report grading the safety of hundreds of individual hospitals, but the real news isn’t the“incremental progress.” It’s how a group started by some of the most powerful corporations in America has quietly devolved into just one more organization hoping press releases produce change.
Amid the current enthusiasm for “value-based purchasing” by employers and possible privatization of Medicare, it is worth examining why Leapfrog’s initial notion that corporations would spearhead a crackdown on crummy care failed and what we can learn from that publicly unacknowledged failure.
Leapfrog was launched with the hoopla of a high-powered initiative. A widely publicized 1999 report by the Institute of Medicine declared that up to 98,000 patients die every year in hospitals from preventable errors and more than one million are injured. In November, 2000, the newly formed Leapfrog Group announced three targeted “leaps” in patient safety that promised to save some 58,000 lives, prevent a half million medication errors and (in calculations that came later) save billions of dollars.
“The number of tragic deaths brought about by preventable medical errors is too striking for those of us in the business community to ignore,” declared Lewis Campbell, chairman and CEO of Textron TXT -0.29%, at the group’s launch.
Campbell was head of a health care task force of the Business Roundtable, an elite group of corporate leaders that sponsored Leapfrog. Wielding the power of the checkbook to enforce “aggressive but feasible target dates” was “a straightforward business approach to tackling a complex problem,” Campbell explained.
I always believed that, if we could harness the entrepreneurial spirit of the American physician, we could be capable of great things. Physician decisions drive much of what is good and bad about our health care system. Their pens are the biggest driver of cost and their vigilance is the most significant driver of quality. It is a shame that physician-owned hospitals are accelerating the creation of a two-tier system by cherry-picking healthy, well-insured patients.
There are overwhelming monetary incentives for physician-owned hospitals to market to the healthiest and wealthiest, who seek a narrow list of procedural interventions. But then those physicians are rewarded with value-based payments for high satisfaction scores and low readmission rates as mandated by the Affordable Care Act.
What happens to the rest of the patients—the ones with one if not several chronic conditions and minimal if any insurance?
They find their way to teaching hospitals, which treat a disproportionate number of “dual eligibles” (seniors so poor they need both Medicare and Medicaid support), the disabled, and nonwhite patients. Teaching hospitals can quickly become underfunded and over-stretched, offering opportunities for physician-owned hospitals in the market to deliver better quality, albeit more expensive, health care to those who have the ability to choose. In spite of that, many teaching hospitals deliver excellent service and care.
In a May 14 Wall Street Journal article, Alicia Mundy wrote, “Doctor-owned hospitals are largely privately held, so it’s difficult to know their profit margins, despite the law’s growth restrictions. According to the American Hospital Directory, a private firm that provides data about some 6,000 U.S. hospitals, many physician-owned hospitals have enjoyed 20 to 35 percent profit margins in recent years.”