Effect of Patient Movement
between Wards on the acquisition
of MRSA
Chris Robertson, Wenwen Huo
Jacqui Reilly, David Greenhalgh
University of Strathclyde and Health Protection
Scotland
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Objective
• Assess the role of patient movement between
wards in hospital on the propensity of patients to
acquire MRSA in hospital.
• Patient movement was assessed in a number of
ways
– through the number of wards a patient was in during
his or her stay in hospital
– through measures designed to evaluate if a patient
was in a ward at the same time as other patients who
had MRSA
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Data
• MRSA Pathfinder Study which was designed as a
multicentre cohort study within hospitals in two NHS
Boards
– Ayr & Arran and Grampian.
– 600 and 900 beds respectively
• Patients were screened for MRSA at multiple body sites on
admission and at discharge.
• February to August, 2010
• Tried to recruit all patients
–
–
–
–
Three cohorts depending upon consent
Admission Only Cohort – 7617 patients
Discharge Only Cohort – 2431 patients
Admission – Discharge Cohort – 2724 patients
A Smith, Pr Christie, T Stari, K Kavanagh, C Robertson, J Reilly, I Gould, F MacKenzie, R Masterton: Health Protection Scotland,
National Services Scotland, NHS Scotland MRSA Screening; The Value of Nasal Swabbing versus Full Body Screening or Clinical Risk
Assessment to Detect MRSA Colonisation at Admission to Hospital, 2011, Health Protection Scotland [Report]
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Previous Analyses
• In the sub-cohort of patients who were screened
both on admission and on discharge and negative
for MRSA on admission, 34 patients acquired
MRSA while in hospital.
• In the initial analysis of the admission discharge
cohort, three risk factors for acquisition of MRSA
were identified:
– age group,
– self-reported renal failure, and
– self-reported presence of open wounds.
E.V.H.V. Velzen, J.S. Reilly, K. Kavanagh, A. Leanord, G.F.S. Edwards, E.K. Girvan, I.M. Gould, F.M. MacKenzie, and R. Masterton. A
retrospective cohort study into acquisition of MRSA and associated risk factors after implementation of universal screening in Scottish
hospitals. Infect Control Hosp Epidemiol, 32(9):889-896, 2011
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Part 1: Descriptive analysis of
effect of number of wards
• Based upon Admission Discharge Cohort
• Includes detailed investigation of the effect of
length of stay and number of wards a patients
was in
• Logistic regression
• Cochran-Mantel-Haenzel Stratified analysis
• MRSA Acquisition – MRSA negative on
admission and positive on discharge
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Distribution of the number
of wards a patient was in
87% of patients in 1 or
2 wards
57% only in 1 ward
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Effect of the number of
wards on MRSA acquisition
Trend test , p = 0.039
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Confounding - Relationship
between Age and number
of wards
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Length of stay and number
of wards
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Adjusted odds ratios
Years
Days
Number of wards is not significantly associated with the risk of acquiring
MRSA given that both older age and longer length of stay are associated with
an increased risk of acquisition
An extra day in hospital has the same effect as an extra year of age
The magnitude of the effect of wounds/ulcers is about the same as 20 years of
age
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Adjusted odds ratios
Final parsimonious model
An extra 1.5 days in hospital has the same effect as an extra year of age
The magnitude of the effect of wounds/ulcers is about the same as 20 years of
age
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Comparison with previous
prediction model
• The prediction model based upon the linear
effect of age, linear effect of length of stay and
the dichotomous effect of wounds/ulcers had an
area under the curve (AUC) of 0.81
• Compared to AUC=0.79 from the original
categorical model based upon age group,
wounds/ulcers and renal failure (yes/no).
• This difference was not statistically significant, p =
0.20, and both models have equal predictive
power
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ROC
Sensitivity 80%, Specificity 55%
Sensitivity 20%, Specificity 95%
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Sensitivity 85%, Specificity 70%
Sensitivity 38%, Specificity 95%
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Summary of effect of number
of wards
• The number of wards a patient stayed in during his/her
hospital stay was positively associated with the risk of
having MRSA on discharge.
• However, adjusting for age and length of hospital stay there
was no significant effect of number of wards.
• The effect of the number of wards was confounded with
the effect of age and with the effect of length of stay.
• Older patients tended to be in more wards than younger
patients and the longer the length of stay the greater the
number of wards.
• Within the admission discharge cohort it was not possible
to disentangle the effect of the number of wards from the
effects of length of stay.
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Part 2: Patient Trajectory
• Data from the admission only cohort, the discharge
only cohort and the admission discharge cohort were
pooled and used to map the trajectory of a patient
through the hospital.
• This could only be carried out in the main hospital in
one NHS board as the availability of data on patient
movement was much better there.
• Even then there was missing data on
– the dates of transfer from one ward to another and on
– the dates of discharge, for the admission only cohort, and
– dates of admission, for the discharge only cohort.
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Ideal data to study patient
movement
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Occupancy and MRSA status
by ward and by day
Number of patients in each ward on each day
Number of MRSA positive patients in each ward on each day
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Exposure Variables
• Exposed to MRSA
– In the same ward at the same time as an MRSA
patient
• Days Exposed to MRSA
– Total number of days in the same ward at the same
time as an MRSA patient
• Patient Days Exposed to MRSA
– Total number of days in the same ward at the same
time as an MRSA patient taking into account the
number of MRSA patients in the ward
– (2 MRSA patients 2 patient days exposure)
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Exposure from Ideal data
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Data Availability
• In one hospital a great deal of missing data on
patient movement
– hospital omitted from patient trajectory analysis
• In other hospital number of wards and
sequence of wards was known but not dates
of transfer
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Available Data – One
hospital only
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Two strategies
• Link data back to SMR01 to get dates of
admission and discharge for the discharge
only and admission only cohorts
– This would not solve all the missing data issues
– Also other problems associated with mismatches
• Statistical modelling – imputation to estimate
the missing data
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Imputation
• Statistical modelling and multiple imputation
techniques were used
• To estimate the number of days a patient was in a
specific ward
• to evaluate if any patient was exposed to MRSA in the
same ward.
• Admission discharge cohort used for
modelling
• Imputation in admission only and discharge
only cohorts
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Comparison of imputed
length of stay with observed
Blue – imputed
Pink – observed
Purple – overlap
Imputation has too many in
for 1 day
Too few in for 2-5 days
Imputation is not perfect
but captures the general
pattern
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MRSA patients in a hospital
per ward per day
Number of MRSA
patients in a ward
Black (1)
Red (2)
Green (3)
Blue (4)
Yellow (5)
Day from first admission in the discharge only cohort
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In the same ward as a patient
with MRSA
All Patients
(Average %)
Patients who
Odds Ratio
acquired MRSA
(Average %)
(95% CI); p
17%
26%
1.72
(0.62, 4.82); 0.3
Not Exposed to 83%
MRSA
74%
1
Totals
19
Exposed to
MRSA
1580
Results from the admission discharge cohort in one hospital who were negative for
MRSA on admission.
Imputation only affected the exposure variable not the response – acquisition of
MRSA.
Imputation carried out 100 times and the results are the averages.
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Bootstrap Adjusted Odds
Ratios
Adjusting for age, length of stay, open wounds/ulcers, renal failure
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Patient Trajectory Summary
• 17% of patients, on average, are exposed to an MRSA patient
concurrently in the same ward during their hospital stay,
• 83%, on average, are not exposed in this way.
• The majority of patients who had possibly been exposed to MRSA
did not acquire MRSA while in hospital.
• On average, only 26% of the patients who acquired MRSA were
concurrently in a ward with an MRSA patient while 74% of patients,
on average, who acquired MRSA were not in a ward with another
MRSA patient.
• The effect of patient movement was not significantly associated
with the risk of MRSA acquisition in hospital, after adjustment for
age and length of stay or age, renal failure or wounds/ulcers.
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Conclusions
• This study indicated that cross-transmission of MRSA
can take place in Scottish hospitals despite the
implementation of Universal MRSA Screening.
• However, concurrent exposure to MRSA in the same
ward is not the only source of this cross transmission.
• Other sources of transmission which include
transmission from outside the ward or via hospital staff
or environment are possibly important in the general
hospital population.
• Therefore, infection prevention, control measures and
additional inventions for controlling MRSA in the
hospital will be required.
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Limitations
• Lack of good quality data on patient movement
between wards.
• It was demonstrated that using imputation is feasible
however the conclusions may not be robust.
• The missing data means that there is the potential to
underestimate the presence of MRSA in the wards.
• More robust conclusions would be obtained using data
from a hospital where
– all patients were screened on admission and discharge and
– dates of patient movement between wards and
– date of discharge was recorded.
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Limitations
• Relatively low numbers of patients acquiring
MRSA while in hospital.
• Acquisition rates are low and so studies with a
greater number of cases are required to assess
the separate effects of number of wards,
length of stay, and patient movement.
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