Peter Pronovost

This week, the U.S. Centers for Disease Control and Prevention issued two reports that are simultaneously scary and encouraging.

First, the scary news: A national survey conducted in 2011 found that one in every 25 U.S. hospital patients experienced a healthcare-associated infection. That’s 648,000 patients with a combined 722,000 infections.

About 75,000 of those patients died during their hospitalizations, although it’s unknown how many of those deaths resulted from the infections, the CDC researchers reported in the New England Journal of Medicine.

On the bright side, those numbers are less than half the number of hospital-acquired infections that a national survey estimated in 2007. And a second report issued this week found significant decreases in several infection types that have seen the most focused prevention efforts on a national scale.

Noteworthy was a 44 percent decrease in central line-associated bloodstream infections (CLABSI) between 2008 and 2012, as well as a 20 percent reduction in infections related to 10 surgical procedures over the same time period.

These infections were once thought to be inevitable, resulting from patients who were too old, too sick or just plain unlucky. We now know that we can put a significant dent in these events, and even achieve zero infections among the most vulnerable patients.

At Johns Hopkins, we created a program that combated CLABSI in intensive care units through a multi-pronged approach—implementing a simple checklist of evidence-based measures while changing culture and caregivers’ attitudes through an approach called the Comprehensive Unit-based Safety Program (CUSP). The success was replicated on a larger scale across 103 Michigan ICUs and then later across most U.S. states, withimpressive results.

These and similar successes have changed caregivers’ beliefs about what is possible, and inspired more efforts to reach zero infections.

What will it take to attain this goal—or at least get much closer?

Continue reading “Hospital Acquired Infections: How Do We Reach Zero?”

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Where health care has fallen short in significantly improving quality, our peers in other high-risk industries have thrived. Perhaps we can adapt and learn from their lessons.

For example, health care can learn much from the nuclear power industry, which has markedly improved its safety track record over the last two decades since peer-review programs were implemented. Created in the wake of two nuclear crises, these programs may provide a powerful model for health care organizations.

Following the famous Three Mile Island accident, a partial nuclear meltdown near Harrisburg, Pennsylvania in spring 1979, the Institute of Nuclear Power Operators (INPO) was formed by the CEOs of the nuclear companies. That organization established a peer-to-peer assessment program to share best practices, safety hazards, problems and actions that improved safety and operational performance. In the U.S., no nuclear accidents have occurred since then.

A more devastating nuclear incident in Chernobyl, Ukraine in 1986 spurred the creation of the World Association of Nuclear Operators (WANO), which serves a similar purpose but on an international scale. Since WANO’s inception, no severe nuclear accidents had occurred until the nuclear accident in Fukushima, Japan, caused by a devastating earthquake and tsunami in March 2011.

These programs have succeeded because their purpose and approach is very different from review processes by regulatory agencies. Instead of a punitive process that monitors compliance with minimum standards, peer-to-peer evaluations are thorough, confidential and—importantly—voluntary. They are viewed as mutually beneficial and help advance industry best practices, which are shared widely. The goal is to learn and improve rather than judge and shame. The reviews are done by experts, using validated tools and are ruthlessly transparent  yet confidential.

Peer-to-peer review has not been widely used in health care. A couple notable exceptions are the Northern New England Cardiovascular Study, which used organizational peer-to-peer review to improve the care of cardiac surgery patients, and the National Health Service in the UK, which used it to improve the care of patients with lung disease. While provider-level reviews are more common in health care organizations, they fail to capture the scale needed to achieve system-wide improvements.

At the Armstrong Institute, we have been pilot testing peer-to-peer review and early results are encouraging. We have evaluated specific outcomes, like blood stream infections; specific areas, like the operating room; and whole quality and safety programs.

Continue reading “A Powerful Idea From the Nuclear Industry”

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If you have ever tried to choose a physician or hospital based on publicly available performance measures, you may have felt overwhelmed and confused by what you found online. The Centers for Medicare and Medicaid Services, the Agency for Healthcare Research and Quality, the Joint Commission, the Leapfrog Group, and the National Committee for Quality Assurance, as well as most states and for-profit companies such as Healthgrades and U.S. News and World Report, all offer various measures, ratings, rankings and report cards. Hospitals are even generating their own measures and posting their performance on their websites, typically without validation of their methodology or data.

The value and validity of these measures varies greatly, though their accuracy is rarely publically reported.  Even when methodologies are transparent, clinicians, insurers, government agencies and others frequently disagree on whether a measure accurately indicates the quality of care. Some companies’ methods are proprietary and, unlike many other publicly available measures, have not been reviewed by the National Quality Forum, a public-private organization that endorses quality measures.

Depending where you look, you often get a different story about the quality of care at a given institution. For example, none of the 17 hospitals listed in U.S. News and World Report’s “Best Hospitals Honor Roll” were identified by the Joint Commission as top performers in its 2010 list of institutions that received a composite score of at least 95 percent on key process measures. In a recent policy paper, Robert Berenson, a fellow at the Urban Institute, Harlan Krumholz, of the Robert Wood Johnson Foundation, and I called for dramatic change in measurement.  (Thanks to The Health Care Blog for highlighting this analysis recently.)

We made several recommendations, including focusing more on measuring outcomes such as mortality and infections rather than processes (e.g. whether patients received the recommended treatment) or structures of care (e.g. whether ICUs are staffed around the clock with critical care specialists). We urged that measures be at the organization level rather than clinician level, to reflect the fact that safety and quality are as much products of care delivery systems as of individual clinicians. We propose investments in the “basic science” of measurement so that we better understand how to design good measures. You can read these and other recommendations in the analysis.

Continue reading “A SEC for Health Care?”

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There is a consensus that measuring performance can be instrumental in improving value in U.S. health care. In particular clinical areas, such as cardiac and intensive care, measurement has been associated with important improvements in providers’ use of evidence-based strategies and patients’ health outcomes over the past two decades. Perhaps most important, measures have altered the culture of health care delivery for the better, with a growing acceptance that clinical practice can and should be objectively assessed.

Nevertheless, as we argue in the full-length version of this paper, substantial shortcomings in the quality of U.S. health care persist. Furthermore, the growth of performance measurement has been accompanied by increasing concerns about the scientific rigor, transparency, and limitations of available measure sets, and how measures should be used to provide proper incentives to improve performance.

The challenge is to recognize current limitations in how measures are used in order to build a much stronger infrastructure to support the goals of increased accountability, more informed patient choice, and quality improvement. In the following paper, we offer seven policy recommendations for achieving the potential of performance measurement.

1. Decisively move from measuring processes to outcomes.

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.

Read more.

2. Use quality measures strategically, adopting other quality improvement approaches where measures fall short.

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 [6]. Read more.

Continue reading “Seven Policy Recommendations for Healthcare’s New Era”

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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 [30].

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.

Continue reading “7. Task a single entity with defining standards for measuring and reporting quality and cost data.”

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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.

Continue reading “6. Invest in the basic science of measurement development and applications.”

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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.

Continue reading “5. Use measurement to promote the concept of the rapid-learning health care system.”

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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].

Continue reading “4. Measure patient experience with care and patient-reported outcomes as ends in themselves.”

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Historically, the physician has been viewed as the leader of medicine, with responsibility for the care and outcomes of patients; in iconic photographs and paintings, the physician is seen as a lone, heroic figure. Such a view has led to natural interest in the measurement of individual physicians’ performance. It is therefore not surprising that some information brokers, including the U.S. News and World Report and many city magazines like the Washingtonian, provide ratings of “top doctors,” often based mostly on reputation, warranted or not.

However, this focus on the individual is flawed for most measures of quality and presents substantial technical challenges. Systems-based care is emerging as a key value within health care and a vital component of high-quality care, while the notion that an individual health professional can be held accountable for the outcomes of patients in isolation from other health professionals and their work environment is becoming an outdated perspective. For example, better intensive care unit staffing sometimes mitigates the evidence that surgeons who perform more procedures achieve better outcomes [21].

The communication and coordination of services across providers is required to ensure that patients, many of whom have multiple conditions, are assisted through various health care settings [22]. For some aspects of care, such as diagnosis errors and patient experience, measuring at the individual physician level might be considered. Nevertheless, focusing measurement on an individual runs counter to our goals in promoting teamwork and “systemness” as core health care delivery attributes.

Continue reading “3. Measure quality at the level of the organization, rather than the clinician.”

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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 [6]. 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 [7]. 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 [8], 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 [9]. 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 [10]. 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 [11].

Continue reading “2. Use quality measures strategically, adopting other quality improvement approaches where measures fall short.”

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FROM THE VAULT

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