The first time I met one of my staff physicians on Internal Medicine, he told our team he had just one rule:
“Our team must contact the patient’s family physician during the admission, inform him or her of the situation and plan for appropriate patient follow up after discharge.”
If you talk to any hospital physician or family doctor, they would almost certainly agree that this type of integration between hospital and community is essential for reducing avoidable ER visits, readmissions and improving other key health outcomes. Put more simply, it’s just good care.
And so you would think contacting a patient’s family doctor during a hospital admission would be the standard of care – but it’s not.There’s no rule or expectation; rather, it’s just something nice to do.
I’m not here to criticize health care providers who do or don’t act a certain way. I’m sure there are many best practices which some providers do that others don’t, and vice versa.
That said, I don’t think we can deny the harsh truth: It’s no longer about knowing what needs to be done to provide higher quality of care at a lower cost. We know enough answers to begin implementing.
One thing the health care industry should admire about Wall Street capitalists is their ability to define their target and measure how well they are doing in achieving their aim. Most people would agree the aim of capitalism is profit (saying nothing of whether that is the right aim or not). The measures of that aim are reasonably straightforward using a standardized language of accounting rules. These standardized rules make it easy to compare one business to another using financial ratios (e.g., profit margin, return on capital, return on assets, etc.). When armed with knowledge of the rules and data to compute the financial ratios, deciding what to invest in becomes fairly straightforward—you invest in the opportunities that drive the highest profits over the shortest period of time.
What is the aim of health care? Many of us would say it is health. If that is the case, however, we have been rotten resource allocators. Take diabetes, for example. In 2011 there were over 60 million care events in the US related to diabetes. The cost per episode is plotted on the chart below. It clearly shows (not surprisingly) that the sicker you get, the more expensive your care is. This is not to say that we shouldn’t spend anything on very sick patients. What it does indicate is that though we say we value health, we actually choose to spend our money on sickness.
What would need to change to aim the health care system at health (vs. sickness) and effectively measure our returns on that investment? Here are a few thoughts:
1- Institute a common language for measuring health (and return on health investment)—Countries with developed capital markets almost always have a regulator that imposes a standardized language for financial measurement and reporting. In the United States this regulator is the Securities and Exchange Commission and the standardized language is Generally Accepted Accounting Principles (GAAP). Professor Regina Herzlinger of Harvard Business School has advocated for an ‘SEC’ for healthcare measurement and reporting. We join her chorus in advocating for this as a critical foundational need on which to base improvement going forward.
2- Create business models that make money on health (instead of sickness)— Patients have jobs to be done related to both health and sickness. Unfortunately, in the US providers by and large can only be paid for treating sickness, so the incentive to create businesses truly focused on health has been low. That is changing with the advent of new payment models and technologies such as telehealth, remote monitoring, and predictive analytics. We encourage entrepreneurs to ambitiously pursue business models where providers can make money on health care independent of sick care.
ACO, MSSP, BPCI, HIE, CQM, P4P, PCMH, yadda, yadda, yadda … The litany of acronyms describing changing P&D (excuse me, payment and delivery) models can sometimes numb the senses. But it would be unwise to allow the latest healthcare jargon to lull you into an AIC—an acronym-induced coma, for which I believe there is a new ICD-10 code—because the world might look a lot different when you snap out of it.
Little debate exists that the U.S. healthcare system needs to transition from turnstile medicine to value-based care, from a predominantly fee-for-service payment model to one that emphasizes accountability for population health. This, of course, is not a novel concept, so the biggest challenges relate to how we get there. As many skeptics have argued, the same dynamics have existed before – unsustainable healthcare costs and too little value for our money – so the Talmudic question arises: Why is this era different from all other eras?
EHRs have changed the playing field completely
Reporting of comparative performance is now embedded into the delivery system
We understand the centrality of patient engagement
Today’s incentives reward greater accountability and value
There are some fundamental differences compared to, for example, the environment that existed in the 1990s when some experts believed managed care would change the underlying cost structure of the health care system. A majority of providers now have implemented electronic health records (EHRs) and an increasing number are – or soon will be as a result of Stage 2 “Meaningful Use” – able to exchange clinical data across network and vendor boundaries. The expectation that quality measurement will be used for holding providers accountable has taken root and most health care organizations regularly submit standardized performance data to public and private payers, purchasers and independent accrediting bodies. Providers increasingly recognize that their success in population health management relates to their ability to effectively engage with their patients in collaborative relationships.
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.
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.
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 . Read 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.
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 .