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Economies of Scale and Scope in Hospitals:
An Empirical Study of Volume Spillovers
Michael FreemanINSEAD, Technology and Operations Management Area, 1 Ayer Rajah Avenue, 138676 Singapore
Nicos SavvaLondon Business School, Regents Park, London NW1 4SA, United Kingdom firstname.lastname@example.org
Stefan ScholtesJudge Business School, University of Cambridge, Cambridge CB2 1AG, United Kingdom email@example.com
General hospitals across the world are becoming larger (i.e. admitting more patients each year) and more
complex (i.e. offering a wider range of services to higher acuity patients with more diverse care needs).
Although prior work has shown that increased volume is positively associated with patient outcomes, it is
less clear how volume affects costs in these complex organizations. This paper investigates this relationship
using panel data for 15 specialties comprising both elective and emergency admissions across 157 hospitals
in England over a period of ten years. Although we find significant economies of scale for both elective and
emergency admissions, we also find evidence of negative spillovers across the two admission categories, with
increased elective volume at a hospital being associated with an increase in the cost of emergency care.
Furthermore, for emergency admissions, we find evidence of positive spillovers across specialties increased
emergency activity in one specialty is associated with lower costs of emergency care in other specialties. By
contrast, we find no evidence of such spillovers across specialties for elective admissions. Our findings have
implications for individual hospital growth strategies and for the regional organization of hospital systems.
Key words : healthcare; productivity; economies of scale; economies of scope; spillovers; econometrics
History : June 8, 2018
Scale is an important determinant of productivity and a recurrent theme in the operations man-
agement and economics literature. Although scale is generally associated with higher productivity
(Panzar and Willig 1977), scholars have pointed out that the productivity gains of increased output
have to be traded off against the potential productivity losses caused by the increased hetero-
geneity of that output (Penrose 1959, Schoar 2002). The tension between benefits of scale and
potential disbenefits of scope is of particular concern in the hospital industry (Argote 1982, Clark
and Huckman 2012). General hospitals provide a large and diverse range of services and use a
wide array of technologies and expertise. From both a strategic and operational perspective, this
diversity is surprising. At the strategic level, it is at odds with the focus principle (Skinner 1974),
2 Freeman, Savva, Scholtes: Economies of Scale and Scope in Hospitals
and at the process level, it impedes improvement techniques that are based on the reduction-of-
variation principle (Hopp and Spearman 2004). Recent studies have discussed the negative impact
of the extensive scope of hospital services on service quality measures (e.g. mortality in the hos-
pital context (Kuntz et al. 2017)); however, perhaps due to the lack of sufficiently granular data,
the research literature on the productivity (i.e. cost) implications of scale and scope has been less
conclusive. This paper uses a novel dataset to provide empirical evidence of the trade-off between
scale and scope in the context of the hospital industry.
We focus on two practically relevant sources of heterogeneity in hospital services: (i) admission-
type heterogeneity (i.e. elective or emergency care) and (ii) specialty heterogeneity. Admission-type
heterogeneity is the result of collocating the treatment of elective and emergency patients within
the same hospital. Elective care is often surgical, ranging from simple day cases (e.g. hernia repairs)
and short stays (e.g. joint replacements) to complex, long-stay operations (e.g. open-heart surgery).
Elective care is typically planned in advance along a well-defined plan of care. Emergency care has
a different dynamic as emergency patients exhibit symptoms that need to be diagnosed and treated
under significant time pressure (RCS/DH 2010, AHRQ 2014); there is no a priori treatment plan,
and the eventual treatment sequence emerges as a consequence of decisions made on the spot
as the service progresses. The second source of heterogeneity is related to the medical specialty
(also known as service line) that a patients needs fall under. These are typically organized around
specific body parts (e.g. eye, heart), systems (e.g. nervous system, respiratory system), or diseases
(e.g. cancer, metabolic diseases) and may share some resources required for patient care (e.g.
diagnostic equipment), while other resources are specialty-specific (e.g. specialist physicians). The
fact that care of emergency and elective patients of multiple medical specialties are offered within
an integrated organization the general hospital is as a consequence of the historical evolution
of hospitals over the past two centuries (Risse 1999).
From a cost perspective, arguments can be put forward both for positive and negative volume
spillover effects (i.e. the effect of a change in volume of one type of activity on another type of
activity) that arise from the co-location of multiple medical specialties that treat both elective and
emergency patients. On the one hand, pooling spreads fixed costs across a broader customer base
(Moore 1959) and can make investing in more productive assets or process structures economical
(Argote 2013). Pooling these services may also confer statistical economies of scale by reducing
relative arrival variability (Dijk and Sluis 2004), allowing firms to hold less capacity. Finally, pooling
provides more opportunities for organizations to learn and accumulate experience (Pisano et al.
2001). On the other hand, it is known that pooling benefits diminish with the degree of dissimilarity
Freeman, Savva, Scholtes: Economies of Scale and Scope in Hospitals 3
between the pooled activities (Joustra et al. 2010, Schilling et al. 2003, Staats and Gino 2012),
and these benefits may also be offset by the increase in organizational complexity that comes with
mixing customers with different service needs (Argote 1982, Christensen et al. 2009, Kuntz et al.
2017). In summary, whether or not the advantages of pooling counteract the disadvantages of
increased organizational complexity in the hospital context is an open question and one that this
paper seeks to answer empirically.
Our empirical study is based on annual average cost data of nearly 145 million hospital admissions
for over 2,000 conditions treated in 157 acute care hospitals in England over a period of ten years.
Since the data is longitudinal and comprised of multiple specialties across multiple hospitals, we
estimate the volume effects of interest with within- and between-random-effects multilevel modeling
that exploits variation in volume over time and between different specialties/hospitals explicitly
(Mundlak 1978, Gelman and Hill 2007). After controlling for changes to asset utilization, we find
strong evidence of economies of scale. The more elective patients a hospital treats within a specialty,
the lower the cost of these patients (a 10% increase in volume reduces cost per patient by 0.48%).
Similarly, if the number of emergency patients in a specialty increases, the cost of these patients
decreases (a 10% increase in volume results in a 1.44% reduction in costs). We then focus on
volume spillover effects between admission categories as well as spillovers between specialties within
admission categories. For electives we find no evidence of spillover effects: An increase in the volume
of emergency patients within a focal specialty, or of patients of any admission category across other
specialties, has no significant effect on the cost of elective patients in the focal specialty. By contrast,
for emergency patients, we find both positive spillover effects an increase in volume coming from
emergency patients in different specialties has a positive impact on emergency productivity (a
10% increase in volume reduces costs by 1.08%) and negative spillover effects the volume of
elective patients (coming from the focal or other specialties) has a negative effect on emergency
productivity (a 10% increase in elective patients within the specialty increases emergency costs
by 0.31%, while a 10% increase in elective patients from all other specialties increases emergency
costs by 1.34%). These results are robust to alternative model specifications and we can rule
out alternative explanations for these findings (e.g. reverse causality, patient selection effects, and
endogenous specialty composition).
These findings have important practical implications at both the hospital and regional level. At
the hospital level, they suggest that elective care growth strategies which are often pursued by
hospitals to improve overall productivity because elective care has greater standardization potential
and, therefore, productivity gains are deemed easier to achieve may actually lead to a drop
4 Freeman, Savva, Scholtes: Economies of Scale and Scope in Hospitals
in productivity overall because of the unintended negative spillover effect on emerge