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Resilience of the Canterbury HospitalSystem to the 2011 ChristchurchEarthquake
Caitlin C. Jacques,a) M.EERI, Jason McIntosh,b) Sonia Giovinazzi,c)
Thomas D. Kirsch,d) M.EERI, Thomas Wilson,b) and
Judith Mitrani-Reiser,a), d) M.EERI
The paper analyzes the performance of a hospital system using a holistic and
multidisciplinary approach. Data on impacts to the hospital system were collected
using a standardized survey tool. A fault-tree analysis method is adopted to assess
the functionality of critical hospital services based on three main contributingfactors: staff, structure, and stuff . Damage to utility networks and to nonstructural
components was found to have the most significant effect on hospital function-
ality. The functional curve is integrated over time to estimate the resilience of the
regional acute-care hospital with and without the redistribution of its major ser-
vices. The ability of the hospital network to offer redundancies in services after
the earthquake increased the resilience of the Christchurch Hospital by 12%. The
resilience method can be used to assess future performance of hospitals, and to
quantify the effectiveness of seismic retrofits, hospital safety legislation, and new
seismic preparedness strategies. [DOI: 10.1193/032013EQS074M]
INTRODUCTION
The MW 6.2 earthquake that struck the city of Christchurch, New Zealand, on
22 February 2011 at 12:51 p.m. (NZ local time) caused significant disruption to the
main health care facilities in the city and surrounding region, placing considerable strain
on the Canterbury healthcare system, specifically Christchurch’s network of private and
public hospitals. This earthquake’s impact on a circumscribed urban area, as well as the rich-
ness of the data collected from several sources (including extensive field work by the
authors), offer a unique opportunity to study the performance of a networked hospital systemand to apply newly developed hospital resilience metrics.
Functioning hospitals and other healthcare facilities are a crucial part of disaster response.
As such, they must be able not only to provide emergency care for the victims of a disaster
event, but also to continue to administer the healthcare services necessary to maintain the
health of their catchment community (WHO 2006, FEMA 2008). Policies have been estab-
lished all over the world to help ensure the continuous operations of healthcare facilities. For
more than a decade, the United Nations World Health Organization (WHO) has made
Earthquake Spectra, Volume 30, No. 1, pages 533 – 554, February 2014; © 2014, Earthquake Engineering Research Institute
a) Department of Civil Engineering, Johns Hopkins University, Baltimore, MD b) Department of Geological Sciences, University of Canterbury, Christchurch, New Zealand c) Department of Civil and Natural Resources Engineering, U. of Canterbury, Christchurch, New Zealand d) Department of Emergency Medicine, Johns Hopkins University, Baltimore, MD
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hospital risk and vulnerability reduction a cornerstone of international disaster preparedness
through its “Safe Hospitals” initiative (WHO 2009). In the United States, California Law
SB1953 (California Senate Bill 1953, 1994, an amendment to Alfred E. Alquist Hospital
Facilities Seismic Safety Act of 1983) establishes seismic safety standards for hospitals,
including retrofit requirements to ensure that hospitals continue functioning following a
major earthquake (CAHSC, 2011). Despite these efforts, healthcare facilities have suffered
great losses globally due to natural and human-caused disasters: the 1994 Northridge earth-
quake affected 11 hospitals (Schultz 2003); the 2003 Bam earthquake reportedly destroyed
almost all of the healthcare facilities in the affected area (UNICEF 2004); the 2005 Kashmir
earthquake caused the closure of 68% of the healthcare facilities in the affected region (IASC
2005); and the 2010 Haiti earthquake destroyed or severely damaged 22% of the hospitals
throughout the country, including all the hospitals in Port au Prince (PDNA 2010). Measures
to quantify and predict loss of function of healthcare systems are necessary to improvefuture outcomes. In this paper, field data and fault-tree analysis are used to assess the
loss of function of hospitals, and new metrics are derived to assess the resilience of healthcare
facilities.
A literature review of hospital functionality and resilience assessment methods is
presented in the second section, highlighting the research gaps that exist in emergency man-
agement practice to holistically analyze the expected performance of hospitals. The charac-
teristics and impact of the Christchurch earthquake and an overview of the Canterbury health
care system are presented in the third section in order to provide context for the analysis of the
performance and resilience of the hospital system. The fourth section introduces a framework
for assessing the loss of function of facilities conditioned on disaster impacts to the structure(e.g., ER completely shuts down to extensive water damage), staff (e.g., the administrative
staff did not report to work), and supplies (e.g., all blood supply is lost due to power outage);
this section also introduces a new resilience metric based on the functionality of these facil-
ities. The resilience of Christchurch healthcare facilities are quantified in the fifth section and
concluding remarks are given in the final section.
LITERATURE REVIEW
The need to improve the provision of healthcare services after a disaster is of global
importance. Emergency plans for hospitals do not typically include detailed hazard vulner-
ability assessments of buildings, and therefore fail to directly account for the impact of
physical damage on loss of hospital functions (Yavari et al. 2010). Without detailed loss-
of-function assessments, it is challenging to portray a realistic picture to hospital adminis-
trators, emergency planners, and staff of what they should expect during an emergency.
Ardagh et al. (2012) describe the difficulties encountered in providing patient care at the
Christchurch Hospital after the earthquake, including interrupted utility systems (e.g.,
power and communication), damaged facilities (e.g., collapsed ambulance bay), fluctuating
staff, and the fear of patients that the building would collapse. The following is a brief over-
view of the literature on hospital performance and resilience assessment.
A great deal of research within the engineering community has focused on frameworks to
characterize seismic hazards and assess structural and nonstructural performance of health-
care facilities. WHO (2006) and Federal Emergency Management Agency (FEMA 2007)
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describe structural vulnerability as dependent on three factors: the level to which the seismic
hazard forces have been addressed in the structural system, the quality of the materials and
construction, and the architectural and structural form of the building. There is also signifi-
cant research that examines the actual performance of structural and nonstructural systems in
hospitals, either for specific physical components, specific seismic events, or specific
regions. For example, Myrtle et al. (2005) identify the nonstructural systems considered
to be most critical for hospital functionality over various phases of an emergency using sur-
veys completed by the hospital disaster coordinators, safety officers, facilities directors, and
the heads of major hospital departments. Masi et al. (2012) perform an analysis of the seismic
risk level for hospitals in the Basilicata region of Italy based on the building stock of the
region’s hospitals and the expected structural and nonstructural performance under different
levels of peak ground acceleration. Miniati and Iasio (2012) describe a rapid seismic assess-
ment of the hospitals in Florence, Italy, which includes structural and nonstructural elements.Uma and Beattie (2010) identify nonstructural elements that are critical to hospital perfor-
mance and make observations both on the performance of these elements in recent events and
on their specifications in the New Zealand code. Davenport (2004) traces the development of
New Zealand ’s building code and its specifications of structural and nonstructural design for
seismic hazards over time. This body of literature mainly focuses on seismic impacts to the
physical structure of healthcare facilities.
The impact of disasters on a hospital’s patients and personnel, excluding the above
physical impacts, is a central theme in hospital preparedness literature. The Institute of
Medicine (IOM 2006) describes how emergency departments function and interact with
other organizations, and how this changes in a disaster. It identifies some of the key vul-nerabilities to individuals, including: a lack of surge capacity; variable levels of emergency
training; and lack of adequate protection for hospitals and their staff from hazards (i.e.,
chemicals and infectious agents that may be a part of the disaster). The office of the Assis-
tant Secretary for Preparedness and Response (ASPR 2013) takes a similar perspective and
identifies crucial capacities that must be considered in the creation of an emergency plan,
including: healthcare system preparedness, healthcare system recovery, emergency opera-
tions coordination, fatality management, information sharing, medical surge, responder
safety and health, and volunteer management. Hossain and Kit (2012) examine the effect
of group interaction on patient treatment by using social network analysis to model coor-
dination between the emergency departments of different hospitals during an emergencysituation. Fawcett and Oliviera (2000) present a model of patient care after a disaster
that includes transportation of patients to healthcare facilities and the response of these
facilities after the patients arrive. These examples, however, neglect the possibility that
the hospital facilities themselves may somehow be damaged, resulting in partial or total
loss of critical functions.
There are a few methods of vulnerability assessment that explicitly link physical and
personnel systems to the resilience of hospitals and the impact on patient care. As an exam-
ple, the Hyogo framework (WHO 2006, UN/ISDR 2005) includes strategies and guidelines
for mitigating the impact of disasters; these guidelines led to the Safe Hospitals initiative,which provides a set of metrics for structural, nonstructural, and administrative vulnerability
of hospitals. The World Health Organization (WHO 2006) assesses these vulnerabilities
using the health facility vulnerability evaluation (HVE), which begins with a rapid qualitative
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assessment of the structural, nonstructural and personnel aspects by field-specific experts. In
its current form, however, the interconnections between the structural and nonstructural per-
formance and the personnel performance are extremely limited, since experts do no consult
across disciplinary lines when performing post-event assessments. Yavari et al. (2010) pro-
pose a metric for assessing post-disaster functionality based on four major interacting sys-
tems of hospitals: structural, nonstructural, lifelines, and personnel. The framework accounts
for all combinations of damage to these four systems to assess overall hospital functionality,
but the authors do not include the personnel system in their case study due to lack of data.
Miniati and Iasio (2012) combine complex systems analysis and empirical data from rapid
seismic vulnerability assessments to identify weaknesses in a hospital system; their analysis
accounts for damage to structural and nonstructural systems, as well as organizational factors
(i.e., staffing levels, emergency plans, redundancies in equipment, etc.). Their model is based
on expert opinion to establish interdependencies in the hospital system, but is not validated using historical events. The “ready, willing, and able” framework described in McCabe et al.
(2010) allows for the consideration of damage via its effects on the ability and willingness of
providers to respond in an emergency, though it does not currently include physical damage
directly.
Physical damage and staff fluctuations will certainly disrupt healthcare services. How-
ever, the extent of these disruptions cannot be predicted unless models explicitly account for
damage in physical building systems and supplies, impact to personnel, and available redun-
dancies. A necessary first step in quantifying the impact of disaster-related disruptions to
regular hospital operations is to formally link the loss of function to resilience metrics,
such as those introduced by Bruneau et al. (2003) and Cimellaro et al. (2010). These authors
quantify hospital seismic resilience as the integral of the system’s functionality, Qðt Þ. Theyestimate Qðt Þ in terms of quality of service (a function of patient waiting time) at the indi-vidual facility level, and in terms of quality of life (a function of healthy populations before
and after the event) at the community level. Functionality is defined as a piecewise function
that captures the reduction in system performance and ranges from 0% (total loss of system
functionality) to 100% (no reduction in system functionality). Resilience, then, is essentially
a measurement of total functionality lost over time. The equation for resilience ( Bruneau and
Reinhorn 2007) is represented mathematically by
EQ-TARGET;t em p:in t r a link -;e1;41;254r ¼ð t OE þT RE
t OE
½100 Qðt Þ dt (1)
where t OE is the time of occurrence of the event and T RE is the recovery time.
There are four key properties outlined by Bruneau et al. (2003) that are needed to define
resilience: robustness, redundancy, resourcefulness, and rapidity. They define robustness as a
system’s ability to withstand stress without a loss of function; redundancy as the substitut-
ability of different elements within the system; resourcefulness as the ability of a system to
adapt in order to prevent or reduce disruption of the system; and rapidity as the ability to
respond to and mitigate disruption in a timely manner (Bruneau et al. 2003). This studydemonstrates how the four elements of resilience can be informed by earthquake reconnais-
sance data collected with survey tools designed by the authors and available as an appendix in
Mitrani-Reiser et al. (2012a). The following section demonstrates a procedure for translating
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empirical data to loss of function and ultimately quantifying resilience of hospitals using
fault-tree analysis.
QUANTIFYING SEISMIC RESILIENCE OF HOSPITALS IN CHRISTCHURCH
Although the works described above show the significant progress on seismic perfor-
mance assessment of hospitals, detailed (multi-disciplinary) analysis has not been performed
on how physical damage, supply loss, and personnel fluctuations are linked to the overall loss
of hospital functions and the direct impact to patient care. The focus of this paper is to assess
the vulnerability of hospitals and provide a resilience metric for hospitals that can be adapted
to quantify the resilience of healthcare systems. This study highlights the need for a multi-
disciplinary approach to measure resilience, which is also stressed by FEMA (2007) as a
necessity in U.S. design guidelines for improving the safety of hospitals.
DESCRIPTION OF THE CASE STUDY
The Mw 6.2 Christchurch earthquake occurred at 12:51 p.m. (NZ Standard Time) on
22 February 2011, with an epicenter located about 7 km east-southeast of Christchurch
city center at a depth of approximately 4 km (longitude 172.71 and latitude 43.60).The earthquake was characterized by a short duration, with the severe shaking only
lasting 15 seconds (GeoNet 2011). Significant liquefaction occurred in areas throughout
Christchurch, causing damage to buildings, infrastructure, and lifelines (Giovinazzi et al.
2011, O’Rourke et al. 2014, Tang et al. 2014, Griffith et al. 2014, Bech et al. 2014),
and impacting the hospitals throughout the region. The Central Business District (CBD)was badly affected, with two major building collapses and various partial collapses of
other buildings. Additionally, tens of thousands of residential properties suffered structural
and nonstructural damage, with over 6,500 properties rendered uninhabitable. Sixty percent
of electricity and water supplies were initially disrupted in the city, and the transportation
network was badly impacted, resulting in high traffic congestion on Christchurch roads. The
earthquake caused 185 fatalities and approximately 8,600 injuries, most of which occurred in
the CBD. The immediate medical response was led by Christchurch Hospital, and continuity
of healthcare continued despite scattered minor to moderate structural damage, widespread
nonstructural damage, extensive outages of all the city’s lifelines systems, and damage to
hospital internal services and back-up generators.
The focus of this study is the impact the Christchurch earthquake had on the Canterbury ’s
hospital network, which is comprised of 22 public, private and elderly care hospitals, as well
as seven rural regional hospitals. A map of Christchurch city is shown in Figure 1, which
includes the locations of the local healthcare facilities as well as local characteristics of the
earthquake (represented by a liquefaction index and peak ground accelerations). The epicen-
ter and shaking intensity of the Christchurch earthquake (USGS 2012) are shown in the inset
regional map of Figure 1.
The Canterbury hospital network is relatively centralized, with the Christchurch Hospital
providing the bulk of care. Christchurch Hospital is the largest hospital in the system; it operates the only Emergency Department (ED), and performs the majority of general and
specialty surgery within Canterbury. The Christchurch Hospital serves a population of
560,000 and admits over 35,600 patients each year, of which approximately two-thirds
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are admitted acutely; a further 13,000 people are day patients. There are 16,000 theatre visits
each year and over 197,000 outpatient attendances, excluding those for radiology and labora-
tory services. Half of the regional hospitals in Christchurch have less than 20 beds, and pri-
marily handle elderly and maternity patients. There is little or no redundancy in the
specialized services provided by the hospitals in the system. Princess Margaret (PM) Hospital
provides predominantly geriatric and psychiatric care; the hospital admits approximately
2,000 patients each year for geriatric care, 70% of whom are referred from Christchurch
Hospital. Burwood Hospital specializes in rehabilitation and elective orthopedic surgery.
Hillmorton Hospital accounts for most of Christchurch’s psychiatric care. The private hos-
pitals in Christchurch city, St. George’s and Southern Cross, provide maternity care and
elective surgery. Despite the lack of redundancy in hospital services, all hospitals in the
region actively liaise with one another in order to provide efficient care and cope with capa-
city shortages.
Figure 1. Map of the Christchurch urban area displaying the local healthcare facilities that accepted patients from the Christchurch Hospital, as well as the respective seismic characteristics(LRI and PGA values) at these locations. The inset map (upper right) of the central South Island
(New Zealand) shows the shaking intensity of the 22 February 2011 Christchurch earthquake.
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DISASTER DATA COLLECTED FROM THE STUDY AREA
A survey tool was used to collect functional impact data from the hospitals in the
Canterbury region after the Christchurch earthquake. The original survey tool is availableas an appendix in Mitrani-Reiser et al. (2012a); this tool was modified in this study to include
unique features of the Canterbury District Health Board ’s (CDHB) systems. The updated
survey is divided in two sections: one focused on physical damage, and one on healthcare
service functional impacts. The survey is completed from interviews with facility managers,
engineers, chief medical officers, nursing directors, and emergency planners. These inter-
views were conducted after the Christchurch earthquake by a multi-institutional (University
of Canterbury and Johns Hopkins University), multidisciplinary team composed of experts in
structural and earthquake engineering, risk assessment, disaster medicine, and disaster man-
agement. The interviews were completed between 8 and 15 August 2011 via phone and in-
person meetings with staff across the CDHB. The interviews targeted the hospitals inChristchurch that provide the majority of secondary and tertiary medical care. Additional
hospital operational data were made available via the Researching the Health Impact of Seis-
mic Events (RHISE) group; these data include the number of transferred patients to/from the
Christchurch Hospital in the first two weeks following the earthquake and the average length
of stay (ALOS) of patients. Additional data on how the Canterbury hospital network redis-
tributed resources to add capacity to their system were collected from media sources.
Data on the seismic hazard exposure of the hospitals were obtained via up-to-date
New Zealand specific ground motion predictive equations (Bradley et al. 2014) and a spatial
correlation model (Goda and Hong 2008), combined with the actual recorded PGA values at
various strong motion stations in the Canterbury region (GeoNet 2011). The transient ground
motions experienced by the hospital buildings (Figure 1) were measured in terms of peak
ground accelerations (Bray et al. 2014; Bradley and Hughes 2012). Liquefaction data were
also collected in terms of the liquefaction resistance index (LRI), developed by Cubrinovski
et al. (2011) to characterize the extent of earthquake-induced liquefaction. The LRI values,
shown in Figure 1 and Table 1, represent the qualitative estimate of observed liquefaction
according to a five-level scale, from 0 (most severe) to 4 (less severe); a sixth level exists to
represent areas where liquefaction was not observed.
ESTIMATING LOSS OF FUNCTION OF HOSPITALS IN STUDY AREA
Fault-tree analysis was used in this study to estimate the loss of function of hospitals by
service area. Fault-tree analysis is used in a wide range of studies (Lee et al. 1985, NRC 1975,
Paté-Cornell and Dillon 2001) to analyze the reliability and safety of complex engineered
systems. More recently, Porter and Ramer (2012) apply fault-tree analysis to characterize the
risk of an individual critical facility (e.g., data canter) losing functionality due to earthquake
damage. Unanwa et al. (2000) consider an individual building as a series of interconnected
systems and apply fault-tree analysis to predict the overall system’s response to a hurricane.
In all of these studies, fault-tree analysis is used to relate the functionality of complex systems
to the state of the sub-systems and components upon which they depend. In this study, a set of fault trees was created around the major components identified in the literature review and
used to assess the management of medical surge: staff , structure, and stuff (Barbisch and
Koenig 2006). The fault-tree branches associated with staff include the availability of
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medical staff, support staff, and backup plans for staffing during an emergency. The branches
associated with structure account for damage to all physical space (i.e., inpatient wards,
means of egress, etc.) and support infrastructure (i.e., power, water, etc.) associated with
critical hospital services. Finally, the branches associated with stuff account for the loss
of supplies (i.e., blood, oxygen, etc.) and damage to equipment (e.g., MRI, sterilization
machines, etc.).
An example of the fault trees created for partial and complete loss of function of hospital
service areas is shown in Figure 2. A key of symbols used in the fault trees is also included.The top event, shown as a rectangle, is associated with the complete loss of life-saving (or
emergency) surgery inside the hospital. Top events are chosen as failure or reduction of cri-
tical service areas within a hospital, including: surgery, emergency department, intensive care
unit, in-patient ward, obstetrics ward, laundry, kitchen, medical records storage, radiology,
and administration. The basic events, shown as circles on the diagram, are the lowest level
events that all match specific data collected using the field study surveys. The basic events
considered in this study include: structural damage, nonstructural damage, geotechnical fail-
ures, damage to municipal water, wastewater, power, and communication systems, as well as
damage to their backup systems, damage to or loss of supplies and equipment, and failure to
report by hospital staff. The intermediate events, shown as rectangles, are system states that contribute to the top-level event. Some of the intermediate events considered in this study
include: failure of utility infrastructure, damage to surgical wards, loss of supplies used in a
service area, and failure to report of staff needed in a service area. Note that the top-level
Table 1. Seismic characteristics and utility loss in four surveyed hospitals. P indicates a partial
loss or localized loss, where Y indicates a total loss, and N indicates no loss. Where information
is available, durations of losses are also shown.
Christchurch
Hospital
PM
Hospital
St. George’s
Hospital
Akaroa
Hospital
Liquefaction resistance and ground motion measurements
LRI zone* 2 N/A 3 N/A
PGA (g)** 0.40 0.45 0.27 –
Utility loss
Electricity Y Y (4 hr) Y (
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S u r g i c a l s p a c e i s
s e v e r e l y d a m a g e d
S u p p o r t i n f r a s t r u c t u r e
i s c o m p r o m i s e d
M e a n s o f e g r e s s
a r e
s e v e r e l y d a m a g
e d
P o w e r i n f r a s t r u c t u r e
f a i l s
W a t e r
i n f r a s t r u c t u r e
f a i l s
W a s t e w a t e r
i n f r a s t r u c t u r e f a i l s
M u n i c i p a l
w a t e r f a i l s
B a
c k u p w a t e r
s y s t e m f a i l s
M u n i c i p a l
w a s t e w a t e r
f a i l s
B a c k u p
w a s t e w a t e r
f a i l s
M u n i c i p a l
p o w e r f a i l s
B a c k u p p o w e r
s y s t e m f a i l s
S t a i r s f a i l
E l e v a t o r s f a i l
C o r r i d o r s
s e v e r e l y
d a m a g e d
V e r t i c a l m e a n s o f
e g r e s s a r e
c o m p r o m i s e d
H o r i z o n t a l m e a n s o f
e g r e s s a r e
c o m p r o m i s e d
O p e r a t i n g t h e a t e r
s e v e r e l y d a m a g e d
S e v e r e
s t r u c t u r a l
d a m a g e
S e v e r e
n o n s t r u c t u r a l
d a m a g e
B a c k u p
s p a c e i s
u n a v a i l a b l e
S u r g i c a l s p a c e
i s c o m p r o m i s e d
S u r g i c a l s t a f f
i s u n a v a i l a b l e
N u r s e s
u n a v a i l a b l e
P h y s i c i a n s
u n a v a i l a b l e
S u r g i c a l
s u p p o r t s t a f f
u n a v a i l a b l e
A l t e r n a t i v e
s t a f f i n g
a r r a n g e m e n t s
n o t m a d e
O x y g e n i s
u n a v a i l a b l e
S u r g i c a l
s u p p l i e s a r e
u n a v a
i l a b l e
R x a r e
u n a v a i l a b l e
S u r g i c a
l s u p p l i e s
a r e u n a v a i l a b l e
L i f e - S a v i n g ( o r E m e r g e n c y ) S u r g e r y i s D i s a b l e d
D r i n k i n g W a t e r
i n f r a s t r u c t u r e f a i l s
D r i n k i n g w a t e r
f a i l s
B a c k u p
d r i n k i n g w a t e r
u n a v a i l a b l e
F i g u r e
2 .
F a u l
t - t r e e s t r u c t u r e f o r t h e l o s s o f
f u n c t i o n o f l i f e - s a v i n g ( o r e m
e r g e n c y ) s u r g e r y .
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event is a failure associated with any failure of staff (e.g., surgical staff), structure
(e.g., surgical space), and stuff (e.g., surgical supplies and equipment); the failure of
these three areas are refined with the extension of their fault-tree branches. Knowledgeof relationships between input and output events are derived from expertise by the authors
in hospital management and from data collected in hospitals affected by the Bío-Bío
(Mitrani-Reiser et al. 2012a) and Mexicali (Jacques et al. 2013) earthquakes. Note that
since field data was used to populate the basic events in this study, all the fault trees are
considered deterministic. The probability of losing functionality of hospital services
could be predicted using the same fault-tree framework by estimating the probability of fail-
ures for the basic events and then propagating these up the tree branches. Note that separate
trees are created for the “reduction in functionality” and “complete loss of functionality” for
each critical hospital service.
QUANTIFYING RESILIENCE OF HOSPITALS IN STUDY AREA
The output of the fault-tree analysis described above is the reduction in function or com-
plete elimination of hospital services. This loss of function can be used to estimate the hos-
pital’s ability to bounce back from a disaster (or its resilience) and manage hospital surge
while maintaining healthcare delivery to its community. Resilience metrics give engineers,
emergency planners, and healthcare providers a tool to objectively make decisions about
mitigation efforts needed to improve hospital performance in future events. A resilience
metric was developed in this study to capture the ability of a hospital to manage critical
event surge and continue providing healthcare after the occurrence of an emergency, includ-
ing the recovery phase. The resilience metric is described by Equation 2, and captures the loss
of hospital function as a weighted sum of the loss of critical hospital services.
The function-based metric, Q f ðt Þ, addresses the quality of care by examining the loss and redistribution of n critical clinical and support services at a hospital. Q f ðt Þ is defined as
EQ -TARGET;t em p:int r a lin k -;e2;41;311Q f ðt Þ ¼
Pnwið1 ð1 Riðt ÞÞ L iðt ÞÞP
nwi(2)
where n is the total number of functions considered, wi is a weighting term representing the
importance of function i, L i is the loss of function (ranging from 0 – 1, or “no loss” to “total
loss”), and Ri is the redistribution of function i (ranging from 0 – 1, or “no redistribution of
hospital functions” to “complete redistribution of hospital functions”). It should be noted
that Ri can never equal one when services are redistributed to other facilities, since this
metric measures resilience for a single facility. As all functions within a facility are
fully restored, this metric also approaches one. The weighting constants, wi, can be defined
based on healthcare outcomes or based on the role that each hospital service plays in pro-
viding patient care. This is most easily accomplished through solicitation of expert opinion
from healthcare professionals. The functions-based metric can be used either to evaluate performance of a facility in a past event where basic event failures or service losses
are known, or combined with downtime models to predict future performance and test
planned redistribution strategies.
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RESULTS
This section discusses the impacts of the earthquake on hospital functionality and resi-
lience. Physical damage and its impact to services are summarized below and described further in Mitrani-Reiser et al. (2012b) and McIntosh et al. (2012). Efforts by the medical
community to redistribute crucial services are examined through direct analysis of functional
loss and through examination of patient transfers. A new metric to quantify hospital resilience
is applied to the Christchurch event.
PHYSICAL AND FUNCTIONAL IMPACT OF THE EARTHQUAKE
Loss and reduction of service in Christchurch hospitals post-earthquake was primarily a
result of damage to utilities and lifelines, rather than severe structural damage. Of the hos-
pitals studied in the region, only Christchurch and St. George’s Hospitals suffered any sig-
nificant structural damage. While no global or even local collapse of structures occurred
inside the Christchurch hospital, structural damage did force the closure of some support
areas, such as the tunnel under Riccarton Avenue (the throughway of lifelines across
major roads), the administrative buildings on St. Asaph Street, and a hospital parking struc-
ture. Geotechnical failures and flooding caused most of the damage to Christchurch Hospital.
Liquefaction caused flooding in the basements of nearly all the buildings in the Christchurch
Hospital campus, including the based-isolated Christchurch Women’s Hospital. The worst of
this flooding occurred in the Parkside and Riverside buildings, resulting in major losses to
services housed there. Examples of the badly damaged areas in Christchurch Hospital are
shown in Figure 3. All clinical buildings on the campus suffered minor structural damage,including shear-wall cracking, roof damage, and damage to separation joints (see Figure 4).
The damage in Christchurch Hospital was not severe enough to cause complete loss of func-
tion of the facility after the event, but it did provide obstacles to daily functionality for weeks
and months following the earthquake, as services were temporarily shut down or relocated
during repair work. The structural damage in St. George’s Hospital was less widespread,
though it was more severe. The entire hospital was closed for four days following the earth-
quake. The hospital’s maternity building suffered partial collapse, and therefore had to be
Figure 3. Observed damage throughout hospital campus: (a) Liquefaction-induced damage tothe main sewer line, (b) shear wall panel damage in Riverside building, and (c) spalled concrete in
ground-floor column of a parking structure (photo credit: Alan Bavis).
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closed. In the relatively new Cancer Centre, liquefaction damage contributed to the building’s
closure. As a private hospital that focuses largely on elective surgical services, St. George’s
was able to close for two weeks following the event to focus on repairing seismic damage.
The nonstructural damage included the failures of many components: windows, non-load
bearing ceilings, partition walls, floor coverings, medical equipment, and building contents.
The failures of suspended ceilings, particularly the plaster tiles constructed with tongue-and-
groove joints, proved to be one of the most disruptive nonstructural failures in ChristchurchHospital. These heavy, thick ceilings act as effective fire barriers; however, when damaged,
these older tiles are dangerous falling hazards. When the plaster tile ceilings were first
installed, they were diagonally braced to the walls. However, at some point after construc-
tion, these diagonal braces were replaced with less effective vertical ties that make the ceil-
ings more susceptible to damage. Fallout and sagging of ceiling tiles (identified by laser level
analysis) throughout the hospital campus necessitated the replacement of these nonstructural
components with lightweight ceiling tiles secured to the ceiling grid with clips and diagonal
bracing. The ceiling repairs required parts of the hospital to be closed down for periods ran-
ging from hours to days; these repairs went on for months after the earthquake. Most of the
inpatient wards were disrupted for two weeks while fire retardant tiles covering suspended ceilings were replaced. Many light fittings became dislodged and had to be replaced along-
side ceiling tiles. The failures of suspended ceilings in particular led to precautionary eva-
cuations immediately after the event. Non-load-bearing wallboard partitions were also
heavily damaged throughout the hospitals. This mostly cosmetic damage did not cause
loss of function immediately after the earthquake, but the areas damaged had to be shut
down for repair work months later. Severe ceiling, glazing, and plaster and concrete wall
damage in the Diabetes Centre at the Christchurch Hospital caused it to close for an entire
month for repairs. Other notable nonstructural effects include damage to rooftop equipment.
The majority of all pumps and chillers in rooftop plant rooms jumped off their mounts due to
strong shaking, even though the snubbers themselves were not damaged. They were on seis-mic mounts according to NZ standards, NZS 4219:2009 (SNZ 2009). NZS 4219:2009 pro-
vides design guidelines for better seismic performance of engineering systems, and requires
that all the proprietary components manufactured in New Zealand or overseas need to be
Figure 4. Observed nonstructural damage in support and clinical buildings: (a) Separation joint
damage in Riverside Building, (b) damage to firewalls in Christchurch Hospital, and (c) ceilingtile damage in Christchurch Hospital (photo credit: Alan Bavis).
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verified for the performance level required (i.e., to be operational under a serviceability level
earthquake for hospital buildings; Clause 2.4, SNZ 2009). Additionally, chillers moved dur-
ing the ground shaking and piping for the condenser collapsed in the base-isolated Women’s
Hospital.
Damage to the hospitals also heavily impacted means of egress. Most staircases in the
clinical buildings were damaged and had to be propped up to remain operational in the emer-
gency phase of the disaster. The stairs were eventually taken out of service one at a time and
repaired during the recovery phase. The reason that so many staircases were damaged is that
they were constructed with rigid connections to adjacent floors, which led to extensive cos-
metic cracking in stairwell walls. Issues with power also caused the emergency lights in some
staircases to fail. Vertical egress was further impaired by damage to elevators. Most elevators
were out of function for a couple of hours because of activated seismic switches that force
them to lock out in the event of an earthquake. The most functionally significant nonstruc-tural damage was to internal and external roof coverings and roof top water tanks, which
caused ingress of water into the top two (fifth and sixth) floors of the Riverside Building
of the Christchurch Hospital and forced the immediate evacuation of five adult medical
wards, which held about 30 patients each. There are no horizontal evacuation routes
from these wards, so vertical egress was required. Since emergency lighting in the stairwells
was not functional, patient evacuation took about 35 minutes to complete with flashlights.
The damage to these critical means of egress complicated regular hospital function imme-
diately following the earthquake; however, hospital personnel continued to provide health-
care services and move patients through whatever means necessary. The damaged wards
have not been restored, and constitute the only permanent loss of capacity at ChristchurchHospital.
As expected in a country whose building stock and design codes are similar to those of
the United States (FEMA 2007), most of the hospital service loss that occurred was not
caused by structural damage. The effects of damage to nonstructural building components
and equipment, loss of public services (lifelines), breakdowns of transportation and re-
supply, and failures of other organizational aspects were far more disruptive to functionality.
Table 1 summarizes the seismic characteristics of the four hospitals with most damage and
their associated infrastructure losses. In this table, Y signifies a total loss, P denotes partial
loss, and N indicates no loss. Where the information is available, durations of losses are also
shown. The seismic characteristics are given by peak ground acceleration (g) and the lique-
faction resistance index (LRI) values from the LRI map developed by Cubrinovski et al.
(2011). The LRI values characterize the level of earthquake-induced liquefaction, and are
determined using observed liquefaction data in Christchurch.
FAULT-TREE ANALYSIS RESULTS
A summary of the clinical and support service losses due to the damage described above
is provided in Table 2. The field data were used as input to inform the basic events of the fault
trees. The fault trees are not able to completely capture the complex interaction of all theimportant systems that make up a functioning hospital, and therefore, have a mixed level
of success in capturing all that occurred after the earthquake. The results of the fault-tree
analysis for all the hospitals are given in Table 2, alongside the true losses experienced
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at each facility. For example, outpatient care was eliminated the first day after the earthquake,
and limited for the next two weeks, which is accurately reflected by the fault tree assessment.
In-patient care was lost in the flooded areas of Riverside, and reduced in the rest of the hos-
pital under the strain of lack of utilities. Also, laundry was indeed relocated to another hos-
pital for a few days because the plant was down and because of short-staffing. The model is
less accurate for other services; the intermittent losses in other clinical areas due to failure of
backup power did not occur, owing largely to the emergent behavior of staff to keep the areasrunning through alternate means until the generators could be brought back online. This
included horizontal evacuations within the hospital and the use of headlamps. The total
loss of the kitchen was predicted by the fault tree but not seen in the field; this discrepancy
may be related to the speed at which backups were restored. This reflects the lack of a
dynamic aspect in the fault tree structure.
RESILIENCE RESULTS
To demonstrate the utility of the proposed resilience metric, the field data collected in
Christchurch were used to quantify the resilience of Christchurch Hospital over the first 30days after the Christchurch earthquake. For this preliminary case, all healthcare functions are
given equal weight, and redistributions are calculated purely empirically. Only those that
occur either within the same facility or offsite but managed by the facility’s personnel
Table 2. Global service loss and reduction in damaged hospitals. Y indicates a loss of
service, where R indicates a reduction in service, and N indicates no loss of service
Christchurch
Hospital PM Hospital
St. George’s
Hospital
Akaroa
Hospital
Service Actual
Hind-
casted Actual
Hind-
casted Actual
Hind-
casted Actual
Hind-
casted
SUPPORT
Laundry Y Y Y Y Y Y N R
Kitchen N Y Y Y Y Y N R
Medical records R R R N Y R N N
MRI and CT scan Y Y N/A Y Y N/AX-ray and ultrasound R R N/A Y R N/A
Blood bank N N N N Y N N N
Administration N N R N Y N N N
CLINICAL
Emergency dept. N R N/A N/A N N
In-patient medical care N R N R N/A N R
Out-patient care R R Y R Y R N N
Surgery R R N/A Y N N/A
Intensive care R R N/A Y Y N/AObstetric/delivery N N N/A Y Y N N
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are considered. Any offsite redistribution is assigned a coefficient of 0.75 times the percent of
the function redistributed, in order to reflect the difficulties of splitting staff and resources between multiple sites. Figure 5 shows the Christchurch Hospital’s functionality over time,
considering redistribution (solid line) and no redistribution (dashed) of hospital services. The
hospital’s resilience is calculated by numerically integrating this function from the time of the
event until the time of recovery. The resilience quantities are given in the legend of the plot
accounting for “redistribution” and “no redistribution.” The ability of the hospital network to
increase capacity and offer redundancies in some healthcare service areas after the earthquake
increased the resilience of the Christchurch Hospital by 12%.
SERVICE REDISTRIBUTION AND CAPACITY BUILDING STRATEGIES
The Christchurch earthquake severely strained the Canterbury region’s hospital system,
and various efforts were made to manage the hospital surge and increase capacity in the
emergency phase. A comprehensive Health System Recovery Plan, consisting of over
200 projects and initiatives designed to restore capacity and improve service delivery across
Canterbury, was developed for the long-term recovery (CDHB 2011). The sections below
briefly report on these steps and initiatives with particular focus on patient transfers to man-
age lost bed capacity in the emergency phase and on strategies to surge capacity and redis-
tribute services in the short and long term.
The majority of the earthquake casualties were treated at Christchurch Hospital,
since the hospital is close to the CBD, which produced most of these casualties. Varioussteps were taken by the Christchurch Hospital to continuously provide healthcare to both
earthquake survivors and existing patients, even with reduced functionality and loss of
some services within the hospital (Table 1). The hospital staffing was increased soon
0 5 10 15 20 25 300.6
0.7
0.8
0.9
1
1.1
Qf for Christchurch Hospital − Actual
Time in days
F u n c t i o n a l R e s i l i e n c e M e t r i c Q
f
With Redistribution, R=1.55
Without Redistribution, R=1.73
Figure 5. Functions-based resilience of Christhchurch Hospital with (solid line) and without
(dashed line) redistribution of hospital services.
RESILIENCEOF THE CANTERBURY HOSPITALSYSTEM TOTHE 2011CHRISTCHURCH EARTHQUAKE 547
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after the earthquake; hospital administrators reported spontaneous arrival of additional clin-
ical and support staff in less than an hour after the event. The second adaptation made by
the hospital was to rapidly discharge and transfer patients to other facilities. Hospital staff
also reported that 5 – 10% of all patients, and 50% of post-partum patients “self-discharged ”
in the first few hours.
Table 3 shows the initial capacity of the six Canterbury hospitals included in this study.
The table also shows the number of patients in the hospitals at the time of the event, the
number of patients discharged within 48 hours to increase capacity, and the number of
patients transferred to other facilities. Christchurch Hospital accounted for 387 of the
455 outgoing patient transfers from Canterbury hospitals during the first two weeks after
the event. Ashburton and Burwood Hospitals accounted for most of the remaining out-
going transfers. Approximately 70% of the transfers from Christchurch Hospital occurred
in the first week following the earthquake.
The data do not, however, include discharges, which were significant immediately
after the earthquake. At the time of the earthquake, there were 637 patients present in
Christchurch Hospital; after 24 hours, there were 320 patients; and after 72 hours, this
was further reduced to 270 patients. After one week, the number of patients rose to
400 as some capacity was restored. The decision to transfer patients from Christchurch Hos-
pital was made internally, and supported by CDHB resources, control, and coordination pro-
cess, as well as in cooperation with staff from the receiving hospitals. The transfer and
discharge of patients immediately after the earthquake was largely cautionary due to the
expected large number of casualties and the permanent 19% (∼106beds) reduction in
bed capacity within Christchurch Hospital due to the evacuated adult wards. Because the
hospitals in Canterbury typically operated at around 98% occupancy, there was little
room within the hospitals’ existing facilities to absorb any lost capacity. Therefore, the
lost capacity had to be absorbed by other hospitals and by reducing elective services. In
the first 24 hours, 32 patients were transferred to Princess Margaret Hospital and 12 intensive
care patients were transferred to other hospitals around the country. Over the first two weeks
patients were transferred to 33 different hospitals throughout Christchurch, the Canterbury
region, and the rest of New Zealand. Severe earthquake casualties were transferred to ICUs as
distant as the North Island along with other non-earthquake patients including geriatric
patients. The main mode of transfer for the less critical patients was via roads, using available
Table 3. Summary of reduced hospital capacity (beds) following the Christchurch earthquake
Initial
capacity
(beds)
Residual
capacity
(beds)
In-patients
at the time
of the EQ
Discharged
patients in
first 48 hours
Transferred
patients in
first week
Christchurch Hospital 650 544 637 342 ðÞ 269
PM Hospital 147 147 109 1 ðþÞ 47
St. George’s Hospital 101 80 52 52 0
Akaroa Hospital 8 8 8 8 ðþÞ 8Kaikoura Hospital 26 26 15 0 ðþÞ 3
Ellesmere Hospital 10 10 8 0 ðþÞ 3
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(and sometimes unconventional) vehicles. For example, some patients were transferred
from Christchurch Hospital to Princess Margaret ’s Hospital on the night of the event
using furniture trucks. Fixed wing flights and helicopters were used for the long-distance
transfers to reduce the transfer time to destinations throughout the South Island and the
North Island.
Following the earthquake, many Canterbury hospitals altered their plans for support ser-
vices, such as laundry. Regional hospitals that normally sent their laundry to Christchurch
were able to perform their own laundry service. Timaru Hospital provided clean linens to
Christchurch Hospital for two days. Princess Margaret ’s Hospital lost its laundry services for
seven days (Table 2), and resorted to using both sides of sheets to extend the lifetime of the
linens. Ashburton Hospital helped source clean linens, but existing stock had to be conserved
to retain capacity.
Several initiatives have been taken to either surge/restore the capacity in the system or to
improve service delivery across Canterbury (CDHB 2011). Three new medical wards
were opened at The Princess Margaret Hospital to replace some of the 109 in-patient beds
that can no longer be used at Christchurch Hospital. A 24-hour ward has been established at
Christchurch Hospital as a short-stay ward to accommodate patients post-surgery in order to
speed up the discharge process and reduce bed demands in surgical wards. Average length
of stay (ALOS) has been shortened across all the wards in Christchurch Hospital, which is
the equivalent of adding beds or hiring more staff at the hospital. The ALOS was 3.2 days before
the earthquake, and was reduced to 2.41 days in the two weeks following the event (from 22
February to 8 March 2011). It was further reduced to 1.6 days this year, which was estimated
using data from 11 to 14 February 2013. Another initiative that was created to surge capacity in
the system is the Vulnerable People’s Team, which was established to relocate residents
of damaged residential aged care facilities in the weeks after the earthquake. Additionally,
Canterbury’s Acute Demand Management Services has been extended to enable general prac-
tice teams to take preventative action with their more vulnerable patients. Utilization of the ser-
vice has increased by more than 20%, from 14,000 urgent episodes per annum to more than
18,000. This equates to more than three wards of inpatient activity (assuming the shorter
post-event ALOS), which significantly increases in-system capacity.
CONCLUSIONS AND NEEDS FOR FUTURE RESEARCH
This paper presents an investigation of the impact of the Christchurch earthquake on
the performance and resilience of the local hospital system. A structured survey tool was
used to collect physical and functional impact data on hospitals in the Canterbury region
of New Zealand. The data collected using this tool, as well as operational data made available
by the RHISE group, resulted in the creation of important descriptions of the loss of func-
tionality of physical systems, the impact to healthcare services and support services, and the
sharing of resources and transfer of patients in a hospital system, all of which are often over-
looked in the existing literature. There was relatively little severe structural damage (i.e., no
complete failures or obvious life safety threats) observed in any of the hospitals in the study
area. Although the structural damage and geotechnical failures are not considered life threa-tening, they did provide obstacles to functionality in the following weeks and months, as
services were temporarily shut down or relocated during repair work. Nonstructural damage
was more common and more widespread at all facilities. Failures of critical infrastructure
RESILIENCEOF THE CANTERBURY HOSPITALSYSTEM TOTHE 2011CHRISTCHURCH EARTHQUAKE 549
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(i.e., communications, power systems, and water systems) had the greatest impact on the
functionality of healthcare facilities. Common types of damage observed within the facilities
include broken piping, collapsed suspended ceilings, and damage to partition walls, cladding,
mechanical equipment, and elevators. Nonstructural damage rendered clinical and non-
clinical areas inoperative, forcing hospitals to subcontract some services, and to sharply
reduce (bed) capacity.
The physical infrastructure of the Canterbury health system in Christchurch was robust
considering that earthquake demands were higher than those mandated by the design stan-
dards. The physical damage affected both hospital capacity and services by eliminating a sig-
nificant number of beds at the main Christchurch Hospital and the private St. George’s
hospital, and by disabling critical utilities needed to perform some clinical and support ser-
vices at Christchurch, Princess Margaret, Akaroa, and St. George’s Hospitals. There is little or
no redundancy in the specialized services provided by the hospitals in the Canterbury District Health Board ’s system. The Christchurch Hospital is the only one in the city with an emer-
gency department and comprehensive services, thus requiring it to become the center of the
healthcare response in the earthquake series despite suffering significant damage and losing
capacity. However, a network-wide redistribution of patients and services created surge capa-
city, and allowed the Canterbury region to fulfill the healthcare needs of its residents.
From this study, the relationships between physical damage and clinical and support ser-
vices are identified using risk analysis tools. A fault-tree analysis is introduced to connect
failure of staff, stuff, and structure with reduction and loss of critical functions. A new resi-
lience metric, compatible with the mathematical definition of resilience from Bruneau et al.(2003), is proposed to measure the variation in hospital functionality over time. The effects of
special initiatives to build capacity in the healthcare system as a whole are fully described and
can be used as lessons by other hospital systems that face natural disasters.
While this study starts to address the coupling between physical damage, human
response, and their effect on loss of function, more research is needed to fully understand
the relationships between these key areas and make these relationships adaptable for predic-
tive purposes in other countries and hazard scenarios. The fault-tree analysis presented in this
paper is deterministic, since failures of basic events are informed by empirical data. However,
this framework can easily be transformed into a probabilistic predictive framework if fragility
functions or other risk analysis methods are used to probabilistically estimate the failure of these basic events given the hazard input, and downtime models are used to model recovery.
Additionally, resilience metrics that focus more directly on patient care should be developed
but will depend on the availability of sensitive human subjects’ data, which is outside the
scope of this study.
ACKNOWLEDGEMENTS
The authors gratefully acknowledge financial support from the New Zealand Natural
Hazard Research Platform and from the State of California (SSC 2011-03). The authors
greatly appreciate the assistance and support by Canterbury DHB managers Murray Dickson,Alan Bavis, and Wayne Lawson. Many thanks to Mark Newsome, CDHB, for providing
contacts and facilitating the interview process. The authors also acknowledge the cooperation
of Prof. Michael Ardagh and the RHISE Group; support from Viki Robinson is especially
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appreciated. This work would not have been possible without the support and contributions
of all the interviewed persons in the CDHB.
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