IMPROVING STROKE OUTCOMES THROUGH OPERATIONAL POLICIES
Beste Kucukyazicia, Linda Greenb and Vedat Verterc,1
aMIT-Zaragoza
International Logistics Program, Zaragoza, Spain
Graduate School of Business, Columbia University, New York, US
c
Desautels Faculty of Management, McGill University, Montreal, Canada
b
1. Introduction
The care provided in a hospital setting –including the emergency department (ED) and the stroke
unit(s) – constitutes one of the most critical elements of an integrated stroke system. Many
different services of the hospital are needed to treat patients during the acute-phase of stroke, and
the coordination of these multi-level services is often a formidable challenge. Failure in matching
the hospital’s service capacity (e.g., the number of properly staffed beds) and the patients’
demand for certain levels of care can be problematic. As a result, stroke victims may not receive
care from the appropriate professional at the appropriate time and place.
The optimal care pathway for stroke is particularly time-sensitive i.e., the initial 24 to 48 hours
after stroke onset is critical for optimizing patient outcomes (Castillo, 1999). Recent studies have
shown that such critically ill patients are more effectively treated in specialized inpatient settings
(Chalfin et al., 2007). However, it has been suggested that the benefits of specialized care might
be offset by long wait times in the ED that arise when the supply of these properly staffed acute
care beds is insufficient to meet demand in a timely fashion (Cameron and Campbell, 2003).
In hospitals that have specialized stroke care, stroke patients arriving to the ED are first assessed
by the stroke team aided by an MRI (magnetic resonance imaging) scan of the brain to determine
their exact diagnosis and the severity of the stroke. Strokes are either hemorraghic, i.e. the result
of bleeding in the brain, or ischemic, i.e. the result of a blood clot. Those with hemorraghic
stroke are generally transferred to surgery in an attempt to control the bleeding. However, about
90% of stroke victims are ischemic and these are the patients we focus on in our study. Medical
guidelines suggest that all stroke patients be transferred to a monitored stroke unit until
stabilized. If the patient is determined to have suffered an ischemic stroke within the past three
hours, tPA (tissue plasminogen activator), a clot-dissolving agent, is administered either in the
ED or in the monitored stroke unit – as specified by the hospital’s care pathway. Upon
stabilization, the patient is transferred to a stroke ward where acute care continues while the
patient receives initial rehabilitation services. Ultimately, patients who are well enough are
discharged home. Others, whose recovery are not as complete and require further care and/or
treatment, are discharged to a long-term care facility or rehabilitation center.
In many hospitals, the hospital units in which stroke patients are cared for are small and may be
shared with other types of patients. This results in long delays in the ED waiting for a bed. Since
adding bed capacity is costly and may be physically constrained, it is important for hospitals to
understand the impact of delays on clinical outcomes and evaluate alternative methods of
1
Corresponding author: vedat.verter@mcgill.ca
managing stroke capacity. The research described here was motivated by the concern of hospital
officials at three Montreal hospitals that delays for stroke patients were detrimental to their
patients. The aim of our study was to determine the impact of inadequate capacity on patient
outcomes and to identify appropriate capacity levels as well as patient admission and bed
allocation policies to improve performance. To this end, we first conducted an empirical study to
establish the potential impact of ED delays on inpatient operations and health outcomes. The
findings of our empirical research were then used in the development of a comprehensive
simulation model of the in-hospital stroke care process to investigate and evaluate alternative
policies for improving capacity management.
2. Empirical Analysis
The data for our study was obtained from the ED, the neuro intensive care unit (neuro-ICU) and
the neuro-ward at the Montreal Neurological Institute and Hospital (MNI), a large McGill
University affiliated teaching hospital. In MNI, the neuro-ICU, which has four beds, acts as the
monitored stroke unit and the neuro-ward, with 16 beds, corresponds to the stroke ward. It is
important to note, however, that MNI treats patients with a wide range of neurological conditions
in both of these units. For the purposes of this research we classify the patients into two groups:
stroke patients and non-stroke patients. Currently, 18% of the stroke patients (i.e., the most
severe cases as well as those who receive tPA and require close monitoring) at MNI are accepted
to the neuro-ICU. The care pathway for these stroke cases is implemented quite efficiently. The
ED length of stay (LOS) for these patients is about 30 minutes and does not exhibit much
variability and their LOS at the neuro-ICU is about 48 hours. Therefore, our empirical analysis
focuses on the stroke patients who are transferred to one of the 16 beds in the neuro-ward
directly from the ED and who more likely to experience long delays. These delays are due not
only to the volume of stroke patients originating from the ED, but also patients from the neuroICU who are given priority in admission to the neuro-ward, as well as non-stroke patients
admitted from the ED. The study period was from January 1, 2005 to June 30, 2008. We relied
on three sources of data: the hospital’s ED information system, the stroke registry of McGill
University Health Center (MUHC), and the paper-based patient charts of the stroke patients
admitted to MNI. The aim of our empirical analysis was to determine the potential operational
and clinical impact of ED waiting time for the neuro-ward. We formulated three hypotheses:
Hypothesis 1 Longer LOS in the ED worsens the functionality of the patient at the time of
discharge from hospital.
Since the functionality of stroke patients may continue to worsen prior to stabilization in an
inpatient stroke unit, we hypothesized that this would be manifested in patients' ultimate
condition upon discharge. We used discharge destination as a proxy of the patient’s functionality
at the time of discharge. We estimated the probability that the patient will be sent to a
rehabilitation center or a long term care facility upon discharge by means of a logistics
regression model. We controlled for the underlying heterogeneity in patient characteristics by
including several clinical preoperative risk factors that may have an impact on functionality and
LOS. In particular, age, gender, having family support following discharge, severity of stroke at
the time of admission, history of stroke, history of bleeding, and various specific medical comorbidities. We used the Charlson Index Score to summarize the co-morbid conditions, and the
Canadian Neurological Scale for quantifying the stroke severity of the patient.
Hypothesis 2: Longer LOS in the ED leads to longer in-hospital LOS.
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We hypothesized that the potential deterioration in a patient's condition while waiting for a bed
may translate into more inpatient time needed for stabilization and rehabilitative treatment. As
above, we controlled for clinical pre-admission risk factors
Hypothesis 3: Higher workload in the neuro-ward leads to longer waiting times in the ED.
Workload in the neuro-ward was measured as the ward utilization at the time of patient’s arrival
to the ED i.e., the ratio of the number of occupied beds in the neuro-ward to the total number of
beds. Our analysis differentiated between weekday and weekend arrivals to account for different
staffing levels for these periods.
3. Results
Our results are based on a sample of 403 stroke patients corresponding to all admissions in the
study period. During the period of the study, the average ED LOS for stroke patients was 15
hours with a fairly large variance (i.e. std. dev.14 hours). We found that longer ED LOS is
strongly associated with increased risk of being discharged to either a rehabilitation center or a
long term care facility (p<0.01). In particular, a 10% increase in ED LOS is related to a 7.7%
increase in the probability of not being able to go home upon discharge. We also observed that as
ED LOS increases, the neuro-ward LOS increases as well. Specifically, a 10% increase in the ED
LOS leads to a 12% increase in the neuro-ward LOS (p<0.05). In addition, the ED LOS increases
with the workload in the neuro-ward. In particular, a 10% increase in neuro-ward utilization
leads to a 15% increase in ED LOS (p<0.05).
The empirical analysis supports the hypothesis that a patient's condition tends to deteriorate as
his/her ED stay is prolonged and that this has a long-term adverse effect on health outcomes.
This is evident from the longer time required to discharge the patient from the neuro-ward as
well as the patient’s destination at discharge. We also found out that the access blocking to the
neuro-ward due to high bed utilization indeed constitutes one of the main determinants of
extended ED LOS. This is the first study, to our knowledge, that establishes a link between
inpatient capacity, inpatient LOS and clinical outcomes for stroke victims, and hence is an
important contribution to the medical community involved in stroke care.
Using the results of our empirical analyses, we developed a simulation model of the entire
process for all stroke patients from arrival to discharge. The model was used to evaluate the
current admissions and bed allocation policies of MNI as well as to explore alternatives that
might decrease ED delays and hence improve clinical outcomes. As a result of this work, the
recommendation was made to switch from a static bed allocation in the neuro-ward to a dynamic
policy.
References
Cameron P.A, Campbell D.A. 2003. Access block: problems and progress. Medical Journal of
Australian; 178: 99-100
Castillo J. 1999. Deteriorating stroke: diagnostic criteria, predictors, mechanisms and treatment.
Cerebrovascular Disease; 9: 1-8.
Chalfin D.B., Trzeciak S., Likourezos A., et al. 2007. Impact of delayed transfer of critically ill
patients from the emergency department to the intensive care unit. Critical Care Medicine;
35:1477-83.
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