How Fewer Hospitals Can Employ More People
The U.S. hospital industry’s national time series raises a precise question: how could the number of included hospital establishments fall while employment in them rose? The useful answer is not a slogan about “bigger hospitals.” It is a way of reading three linked measures—establishment count, employee count, and employees per establishment—without mistaking their relationship for a complete explanation. That distinction helps us see what the historical series demonstrates and what it only suggests about consolidation.
The previous discussion established that the evidence concerns establishments with at least 50 employees, not every facility or every healthcare worker. With that boundary in place, the national pattern can be reconstructed as a simple mechanism. One measure counts places, another counts people, and the ratio between them describes how employment is distributed across those places.
Three measures, one changing industry
Start with the denominator: the number of included hospital establishments. An establishment is a business location recorded as an operating unit. If two locations become one operating establishment, or if activity moves from a smaller location into a larger one, the establishment count can fall even when the organization’s total work does not.
Next is the employee count. This is the number of employees working in the included establishments during the period being measured. It is an industry-wide total, not a count of distinct clinical roles, a measure of full-time-equivalent staffing, or a record of where every employee lives. It tells us how much employment is attached to the included hospital establishments, but not how evenly that employment is spread.
The third measure is the average number of employees per establishment:
average establishment size = total employees ÷ included establishments
The ratio is not a fourth kind of hospital. It is a summary of how the numerator and denominator move together. If establishments decline and employees increase, the ratio must rise. That mathematical relationship is the key to the apparent paradox. It does not require every location to grow; it only requires the overall workforce to become larger relative to the number of included sites.
This also explains why the phrase “fewer hospitals” can be misleading if left unqualified. The study’s measure is a population of establishments above a size threshold. A change in that population can reflect the expansion of some sites, the disappearance or reclassification of others, and changes in how activity is organized. The ratio captures the resulting structure but does not identify each transition.
The establishment curve has a peak, a trough, and a partial rebound
The establishment series has a definite shape rather than a smooth, uninterrupted slide. Hospitals meeting the size threshold peaked in 1988 at more than 6,400 establishments. By 2010, the number had fallen by more than 20%, to about 5,040. The count then rose slightly after the Great Recession and continued to the end of the study period in 2019, but that later movement did not erase the much larger decline across the three decades.
The timing matters for two reasons. First, it prevents an overly simple story in which the industry loses establishments at the same rate every year. The national pattern includes a long decline and a modest recovery. Second, it shows why an observed change should not be assigned a cause merely because a policy or economic event occurred nearby in time. The paper notes that provisions in the 2009 American Recovery and Reinvestment Act offered incentives to physicians and hospitals, funded construction and renovation, and continued health insurance coverage for unemployed workers. Those provisions may help explain why the establishment count rose after the Great Recession, but the study does not estimate that relationship as a causal effect.
The safer historical claim is therefore about direction and scale: the number of included establishments was substantially lower at the end of the period than around its late-1980s peak. The exact path matters, but the broader structural movement is not dependent on treating the post-recession uptick as either irrelevant or definitive.
Employment does not follow the facility count
The employee series moves in the opposite direction. In 1987, the included hospitals employed just under 4 million people. By 2019, they employed almost 5.6 million—an increase of more than 40%. The industry therefore ended the period with a larger recorded hospital workforce even though it had fewer included establishments than at its peak.
The authors use the two series to calculate an approximately 75% increase in average hospital size, measured by employees per establishment. The number is an important compression of the story. It does not say that every hospital expanded by 75%, or that every community gained hospital employment. It says that the employee total became much larger relative to the establishment total.
A small example makes the logic visible without pretending to reproduce the data. Suppose an industry moves from 100 establishments employing 100,000 people to 80 establishments employing 110,000 people. The workforce has grown, but the average establishment has risen from 1,000 employees to 1,375. The industry has more work and fewer sites at the same time. The Census analysis describes this kind of relationship at national scale, with the actual historical totals and a much larger population of establishments.
The flow from the first two boxes to the larger average is descriptive arithmetic. The branches that follow are questions of interpretation. Fewer, larger sites may create scale advantages. They may also concentrate services and employment in particular markets. Neither possibility can be inferred from the ratio alone, and both can be true in different places.
Why might larger establishments emerge?
One plausible mechanism is internal economies of scale. Hospitals carry costs that do not rise one-for-one with every additional employee or service: buildings, equipment, administrative systems, specialized staff, and some forms of compliance and coordination. If a larger organization can spread such costs over more activity, its average cost may fall as it expands. Hospital administrators may therefore have reasons to consolidate functions or grow existing sites.
Scale can also affect the organization of care. A larger establishment may support a wider range of specialists, centralized administration, more sophisticated equipment, or staffing arrangements that are difficult for a small facility to sustain. These are plausible operational advantages, not outcomes measured by the national time series. The data show the employment and establishment pattern; they do not show whether costs fell, quality improved, or patients benefited.
It helps to separate three levels of the argument. At the workforce level, the industry has more employees. At the establishment level, those employees are concentrated in larger operating locations. At the access level, the question is whether patients can reach the services they need and whether a nearby institution remains available. Growth at the first two levels may support the third, but it does not guarantee it. A larger hospital might add specialists or emergency capacity, yet a community that loses its local establishment may still face greater travel or dependence on a neighboring market. Conversely, a nearby hospital could remain open while its employment changes little, or while services are reorganized in ways the employee count cannot reveal.
This separation also guards against confusing employment with output. More employees could reflect more services, more administrative work, higher staffing intensity, or other changes. The supplied evidence does not measure patient volume, service quality, costs, or clinical outcomes alongside the employee total. It therefore supports a structural claim about where employment is attached, not a verdict about whether the resulting arrangement delivers more or better care. The value of the national series is to identify the reorganization that those other measures must investigate.
Consolidation is another plausible interpretation. If some establishments close while other hospitals become larger, the industry can contain more employees in fewer operating locations. Mergers and acquisitions could be part of that process, as could organic expansion. The paper notes that it does not directly observe mergers and acquisitions, even though related research has documented health-system growth through acquisition of physician practices. That distinction matters: a pattern consistent with consolidation is not the same as a verified count of consolidation transactions.
The word “consolidation” should therefore be used as a description of changing structure, not as a complete causal diagnosis. It can refer to employment and capacity becoming concentrated in fewer establishments. It does not by itself tell us whether the concentration came from ownership changes, service transfers, closures, growth, or a combination of them.
The same aggregate pattern can have several causes
A national ratio is powerful enough to reveal that the industry changed, but too coarse to tell us how. Several processes could produce more employees per included establishment:
- Existing hospitals may have expanded in response to population growth, higher demand, or added services.
- A health system may have moved functions into a central site while retaining some organizational relationships with other locations.
- Some establishments may have closed, merged, changed classification, or fallen outside the study’s size threshold while surviving sites grew.
- Staffing may have increased within the remaining establishments even if the number of physical care locations did not.
These are not equally likely everywhere, and the evidence supplied here does not rank them. Listing them is useful only to mark the missing decomposition. The historical series establishes a joint movement, not the proportion attributable to each mechanism.
The denominator also requires care. Because the analysis includes establishments with at least 50 employees, average size is conditional on membership in that group. It is not the average size of every facility that might be called a hospital. If the composition of included establishments changes, the average can move for reasons beyond growth at a typical surviving site. This is one reason to avoid turning a national average into a claim about a representative hospital.
The result also says nothing by itself about jobs’ distribution across workers or places. Employment could grow in large metropolitan hospitals while rural establishments contract. A region could gain hospital employees through a few expanding centers even as several counties lose local sites. The national total cannot distinguish those possibilities; that requires geographic evidence.
What the national series can—and cannot—settle
The strongest conclusion is narrow but meaningful. From 1987 to 2019, the included U.S. hospital industry had fewer establishments, more employees, and a substantially larger number of employees per establishment. Those facts are enough to reject the assumption that facility decline and job decline are interchangeable.
The next conclusion is interpretive. The joint pattern is consistent with consolidation and internal scale economies, and the paper presents it as an era of hospital consolidation. But the evidence does not establish that consolidation was the only cause, that it produced net efficiency, or that its consequences were the same for all communities. A larger establishment may be more capable in some respects while being farther away for some patients. A workforce may be more productive or more specialized in one market while less available in another.
A final boundary is temporal. The series ends in 2019. It cannot be silently extended to current employment conditions, and later policy developments cannot be read backward into the historical counts. Nor can the national series answer whether residents of a particular county experienced longer travel, reduced choice, better specialized care, or no practical change.
That last limitation points to the next analytical step. If the industry’s workers are increasingly concentrated in larger establishments, the important question is where those establishments are located and what happens to counties that lose one or more of them. Employment growth explains how the paradox is possible. It does not tell us whether the places left behind have lost competition, proximity, or an economic anchor. To answer that, the national average has to be placed on a map.