The U.S. Bureau of Labor Statistics came out with its June jobs report this week and, consistent with usual trends, healthcare jobs are booming. In June 2013 there were approximately 20,000 new healthcare jobs in the U.S., ¾ of which were in the ambulatory care sector and ¼ of which were in hospitals. Healthcare jobs represented 10% of all new jobs created this month.
The June growth in healthcare jobs matches up to the average 19,000 new healthcare jobs we have seen created in each of the prior months of 2013 and the 12% job growth we have seen over the last five years. In a country where new jobs are viewed as even better than baseball, apple pie and mom herself, these new jobs should elicit a huge round of applause, or at least a stadium style wave, right?
Or should they?
Change the channel and a different set of policy makers, employers and industry experts will tell you that the only way to save our economy from ruin is to cut healthcare costs. Cutting healthcare costs means making the people who work within the system vastly more efficient, eliminating unnecessary medical care (and thus reducing the labor that goes along with it), and helping empower consumers to do things for themselves, including taking a more active role in reducing their own demand for healthcare services and, in some cases, doing at home what they might previously have used the healthcare system to do (e.g., diagnostics, home care, etc).
An old data series got new life, when the Brookings Institution issued a report that compared health care jobs growth versus all other industries.
It’s “a truly astonishing graph,” according to Derek Thompson at The Atlantic. “I knew health care had been the most important driver of national employment over the last few years, but I had never seen the case made so starkly.”
Thompson wasn’t alone in his surprise. (Hopefully, readers of The Health Care Blog would be less astonished.) But lost within the reaction—and even mostly overlooked within the industry—is that not all health care jobs are growing, or at least not growing at the same pace.
Take a look at the following chart. It resembles the Brookings data, with one major change: The hospital employment curve has been separated from all other health care jobs growth.
Notice how hospital employment essentially flatlined across 2009—a hard year for the sector, which was still insulated compared to the rest of the economy. But many organizations pared back on staff and sought to cut non-essential services to survive the Great Recession.
Ignaz Semmelweiss was laughed out of his Viennese hospital when he suggested that physicians should wash their hands in between conducting an autopsy and delivering a baby.
150 years later, we know just how right he was, but hand sanitation compliance rates at hospitals still hover in the 30% to 50% range. This makes it easy for hospital-acquired infections (HAIs) such as MRSA and VRE to run rampant, a (literally) dirty, not-so-little, and not-so-secret reality for American patients.
A Healthbox-backed startup is trying to change that. SwipeSense, founded in 2012 by Northwestern University graduates Mert Iseri and Yuri Malina, is a system designed to improve sanitation practices in hospitals using portable hand sanitizers and wirelessly-collected data on their use.
The organization wants to help stem the tide of avoidable HAIs. Each year, about 100,000 Americans die from infections they contract during their time in the hospital – more than the number of Americans killed by guns, motor vehicles, and leukemiacombined. In addition to the direct human toll, HAIs cause patient length of stays to increase by 8.0 days in ICUs and 7.4 to 9.4days in acute care wards, taking up expensive capacity and preventing others from accessing needed hospital beds. They’re also expensive, causing an estimated $4.5 to $5.7 billion in excess costs.
Iseri and Malina were inspired to create SwipeSense by a project they did for Design for America, a student group created to catalyze social change using human-centered design (also founded by Iseri and Malina). It took them to Northwestern Memorial University Hospital in their college town of Evanston, Illinois, where they identified two salient issues with hand sanitation: convenience and compliance.
“It’s obvious it’s not the fault of the nurse or physician…it’s something wrong with the system,” Malina told me in an interview. Even though alcohol foam and soap dispensers are ubiquitous in American hospitals, they often aren’t at the immediate point of care: “medical staff need to sanitize four or five times per patient encounter,” Malina said, making proper sanitation an arduous, time-consuming, and unrealistic task. “Our philosophy at SwipeSense is that the right thing to do should be the easiest thing to do… We want to make something that people love.”
For all of those out there anticipating the 2014 official role out of Obamacare, also known as the ACA (Affordable Care Act), here is a cautionary tale.
Many years ago, as I was growing my cardiology practice, it became evident that diagnostic services for my specialty, like stress tests, echocardiograms, etc., were done less efficiently and cost more at the local hospital, then in the office. This stimulated many groups in the 1980s and 90s to install their own “ancillary” diagnostic services. Patients loved not having to deal with the long waits and higher copay prices at the hospitals. And yes, the cardiologists did increase their revenues with these tests. However, lower costs to patients, insurance companies, Medicare, and improved patient satisfaction were just as powerful a stimulus to the explosive growth of these diagnostic tests, and later even cardiac catheterization labs, when integrated into the physicians’ offices.
As the growth in testing spiraled upward, the hospital industry saw their slice of the outpatient revenue pie nosedive. Hospital lobbyists and policy-makers cried foul and complained of greed and self-referral, which they said was spiking the rapid rise in healthcare costs.
Studies laying blame on self-referrals being the major culprit for escalating healthcare costs, have been inconclusive. However, after years of lobbying and the passage of ACA, the hospital industry finally had the weight of the Federal government on their side. It did not take long for Medicare to start dialing back the reimbursements for in-office ancillary tests and procedures, and outpatient cardiac catheterization labs were one of their main targets. Hospitals had lost millions of dollars to the burgeoning growth of these labs inside the cardiologist’s office.
Our twelve-man group had a safe and successful lab for about ten years. Then after the ACA was passed, Medicare began to cut the reimbursements for global and technical fees in this area. The cuts were so Draconian that it became impossible financially to continue the service. Never mind that we could provide the same service as the hospital more efficiently, with better patient satisfaction, and at a third of the cost.
The Next Health Care calls for very different strategies and tool sets. Many systems are acting as if they read a manual on how to do it wrong. How many of these critical strategic and tactical mistakes is your system making?
So I was beta testing FutureSearch, this cool new Google add-on app I’m writing with a coder, and I found an article that I wrote in 2025. My first thought was, “Cool! It works!” My second thought was, “I’m still working at the age of 75?” It was only then that I focused on the title of the article: “Fail: The 16 Steps by Which Hospitals Failed in the Post-ACA Risk Environment — An Analysis.”
The article detailed a dispiriting history from 2013 to 2020. More important, it listed the 16 most common mistakes that hospitals and health systems made while trying to navigate the new risk environment of the Next Health Care.
I found this interesting because of course right at this moment much of the health care industry, in many different ways, is trying to move away from the traditional fee-for-service payment system, which has given the whole industry adverse incentives, leading to much higher costs, poorer quality and restricted access. The rubric of the day is “volume to value.” And I see many different institutions and systems across the country making exactly these mistakes already in 2013.
As you read this list, ask yourself in what way you and your institution might be making the wrong decisions, and ask yourself what they will look like looking back from 2025.
Stick with fee-for-service. Though they included various incentives and kickbacks, most accountable care organizations and ACO-like structures built in the 2012–2014 period were based on a payment system that remained stubbornly fee-for-service. Systems continued to make more money if they checked off more items on the list (and more complex items), rather than solving their customers’ problems as well and as efficiently as possible.
A question: What is the opposite of health IT return on investment?
The answer: Unintended financial consequences, or UFCs, for short.
The scenario: A sophisticated medical center health system begins to roll out an expensive proprietary EHR and shortly thereafter sustains an operating loss, leaving no choice but to put the implementation on hold. The operating loss is attributed to “unintended financial consequences” directly related to buying a very expensive EHR system.
This is exactly the situation at MaineHealth, who selected Epic. As recently reported, a little while ago Maine Medical Center President and CEO Richard Peterson sent a memo to all employees saying the hospital …
… has suffered an operating loss of $13.4 million in the first half of its fiscal year. The rollout of MaineHealth’s estimated $160 million electronic health record system, which has resulted in charge capture issues that are being fixed, was among several reasons Maine Med’s CEO cited for the shortfall.
“Through March (six months of our fiscal year), Maine Medical Center experienced a negative financial position that it has not witnessed in recent memory,” Richard Peterson, president and CEO of the medical center, wrote in the memo to employees.
Peterson’s memo outlines the specific UFCs that explain, in part, MaineHealth’s operating loss:
- Declines in patient volume because of efforts to reduce re-admissions and infections
- Problems associated with being unable to accurately charge for services provided due to the EHR roll out
- An increase in free care and bad debt cases
- Continued declining reimbursement from Medicare and MaineCare, the state’s Medicaid program
These challenges are common to just about any medical system in the country, making MaineHealth potentially a harbinger of things to come for those hospitals and health systems that pay multi-millions of dollars for a health IT system.
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.
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.
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.
There has been a lot of controversy in health policy circles recently about hospital market consolidation and its effect on costs. However, less noticed than the quickened pace of industry consolidation is a more puzzling and largely unremarked-upon development: hospitals seem to have hit the wall in technological innovation. One can wonder if the two phenomena are related somehow.
During the last three decades of the twentieth century, health policymakers warned constantly that medical technology was driving up costs inexorably, and that unless we could somehow harness technological change, we’d be forced to ration care. The most prominent statement of this thesis was Henry Aaron and William Schwartz’s Painful Prescription (1984). Advocates of technological change argued that higher prices for care were justified by substantial qualitative improvements in hospitals’ output.
Perhaps policymakers should be careful what they wish for. The care provided in the American hospital of 2013 seems eerily similar to that of the hospital of the year 2000, albeit far more expensive. This is despite some powerful incentives for manufacturers and inventors to innovate (like an aging boomer generation, advances in materials, and a revolution in genetics), and the widespread persistence of fee for service insurance payment that rewards hospitals for offering a more complex product.
Technology junkies should feel free to quarrel with these observations. But the last major new imaging platform in the health system was PET , which was introduced into hospital use in the early 1990’s. Though fusion technologies like PET/CT and PET/MR were introduced later, the last “got to have it” major imaging product was the 64 slice CT Scanner, which was introduced in 1998. Both PET and CT angiography were subjects of fierce controversy over CMS decisions to pay for the services.