the insights series · ballina district hospital profile july 2009 - june 2012 30-day mortality...
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The Insights Series30-day mortality following hospitalisation,
five clinical conditions, NSW, July 2009 – June 2012
Acute myocardial infarction, ischaemic stroke,
haemorrhagic stroke, pneumonia and hip fracture surgery
Performance Profile:
Northern NSW Local Health District
Ballina District Hospital summary dashboard, July 2009 - June 2012
30-day mortality following hospitalisation for five conditions
Balli
na D
istr
ict
Ho
sp
ital
Dashb
oard
Hospital-specific risk-standardised mortality ratios (RSMRs) report the ratio of actual or ‘observed’ number of deaths
to the ‘expected’ number of deaths. A hierarchical logistic regression model draws on the NSW patient population’s
characteristics and outcomes to estimate the expected number of deaths for each hospital, given its case mix.
A ratio less than 1.0 indicates lower-than-expected mortality, and a ratio higher than 1.0 indicates higher-than-expected
mortality. Small deviations from 1.0 are not considered to be meaningful. Funnel plots with 90% and 95% control limits
around the NSW rate are used to identify hospitals with higher and lower mortality.
This measure is not designed to compare hospitals and cannot be used to measure the number of avoidable deaths.
RSMRs do not distinguish deaths that are avoidable from those that are a reflection of the natural course of illness.
They do not provide, by themselves, a diagnostic of quality and safety of care.
Risk-standardised mortality ratios (RSMRs) for five conditions, dashboard
Lower mortality No difference Higher mortality Range within 90% control limits
RSMR July 2009 to June 2012
NSW
RSMRs for three-year periods
How to interpret the dashboard
NSW average for index cases
mortality is lower than expected mortality is higher than expected
The length of the bar for each condition reflects the tolerance
for variation around the NSW average. It is wider for hospitals
admitting a small number of patients.
If a hospital's RSMR lies on the grey bar, its mortality is within the range of
values expected for an average NSW hospital of similar size.
( ) Data for hospitals with an expected mortality of <1 are suppressed.
( ) Between 90% and 95% upper control limits; ( ) Outside 95% upper control limits.
( ) Between 90% and 95% lower control limits; ( ) Outside 95% lower control limits.
Notes: RSMR data are for patients with a hospitalisation noting the relevant condition as principal diagnosis.
Patients include those discharged between July 2009 and June 2012 who were initially admitted to this hospital
(regardless of whether they were subsequently transferred) in their last period of care. Deaths are from any cause,
in or out of hospital within 30 days of the hospitalisation admission date.
Details of analyses and risk adjustment are available in Spotlight on Measurement: risk-standardised mortality ratios
for five conditions.
Data source: SAPHaRI, Centre for Epidemiology and Evidence, NSW Ministry of Health.
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au
Acute myocardial infarction (AMI) 101 patients
Ischaemic stroke < 50 patients
Haemorrhagic stroke < 50 patients
Pneumonia 143 patients
Hip fracture < 50 patients
2000-02 2003-05 2006-08 2009-11
Ballina District Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for Acute Myocardial Infarction (AMI)
Balli
na D
istr
ict
Ho
sp
ital
Acute
Myo
card
ial In
farc
tio
n (A
MI)
Total Acute Myocardial Infarction (AMI) hospitalisations
Acute Myocardial Infarction (AMI) patients
Presenting patients (index cases)1
Patients not transferred to another hospital
Patients transferred out to another hospital
This hospital NSW
Age profile, index cases 2
Ballina District Hospital
NSW
% of index cases
Significant patient factors and comorbidities, index cases3
Ballina District Hospital NSW
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 1 of 4
165
101
16
85
37,794
29,223
18,303
10,920
15-55 56-65 66-74 75-82 83+
16 16 20 21 28
19 21 20 19 21
0 10 20 30 40 50 60 70 80 90 100
32Hypertension
33STEMI
10Dysrhythmia
10Congestive heart failure
7Renal failure
3Hypotension
2Dementia
4Cerebrovascular disease
4Malignancy (cancer)
1Shock
0Alzheimer's disease
58
32
21
17
13
11
3
3
3
2
1
0 10 20 30 40 50 60 70 80 90 100
% of index cases with factor recorded
Ballina District Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for Acute Myocardial Infarction (AMI)
Balli
na D
istr
ict
Ho
sp
ital
Acute
Myo
card
ial In
farc
tio
n (A
MI)
Percentages: index cases who died within 30 days of hospitalisation
Of all deaths:
percentage in this hospital
percentage in another hospital following transfer
percentage after discharge
percentage on day of admission
percentage within 7 days
This hospital
percentage
NSW
percentage
Survival of index cases following hospitalisation for Acute Myocardial Infarction (AMI)5
Adjusted for average age and Charlson comorbidity score
Ballina District Hospital
% S
urv
ival
Days since admission
NSW
% S
urv
ival
Days since admission
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 2 of 4
Mortality (all causes) among 101 Acute Myocardial Infarction (AMI) index cases4
6%
17%
33%
50%
17%
50%
(64%)
(6%)
(31%)
(14%)
(61%)
0
90
95
100
0 10 20 30
0
90
95
100
0 10 20 30
Ballina District Hospital profile July 2009 - June 2012
Hospital-level Acute Myocardial Infarction (AMI) risk-standardised mortality ratio by number
of expected deaths, NSW public hospitals
Balli
na D
istr
ict
Ho
sp
ital
Acute
Myo
card
ial In
farc
tio
n (A
MI)
Ballina District Hospital NSW hospitals 90% limits 95% limits
Hospital-specific RSMRs report the ratio of actual or ‘observed’ number of deaths to the ‘expected’ number
of deaths. A hierarchical logistic regression model draws on the NSW patient population’s characteristics and
outcomes to estimate the expected number of deaths for each hospital, given the characteristics of its patients.
Actual and expected deaths, compared to local peers
This hospital,
actual deaths
Peer group hospitals,
actual deaths
Expected deaths
(based on model)
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 3 of 4
Kempsey Hospital
Maclean District Hospital
Lithgow Health Service
Moruya District Hospital
Milton and Ulladulla Hospital
Blue Mountains District Anzac Memorial Hospital
RSMR = 0.87Ballina District Hospital
Casino and District Memorial Hospital
Bateman's Bay District Hospital
0 5 10 15 20 25
Deaths
0
1
2
3
4
5
Ris
k s
tand
ard
ised
mo
rtalit
y r
atio
(R
SM
R)
0 50 100 150
Expected number of deaths within 30 days
Ballina District Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for Acute Myocardial Infarction (AMI)
Balli
na D
istr
ict
Ho
sp
ital
Acute
Myo
card
ial In
farc
tio
n (A
MI)
Illustrating the effect of standardisation, July 2009 - June 2012
In order to make fair comparisons, a number of risk adjustments are made to mortality data. These take into account
patient level factors that influence the likelihood of dying. The table below illustrates the cumulative effect of the statistical
adjustments. For each ratio, hospitals are compared to the average NSW result, given their case mix.
Lower mortality No difference Higher mortality
Time series risk-standardised mortality ratio, July 2000 - June 20126
Lower mortality No difference Higher mortality
Year (financial years)
Risk-standardised mortality ratio
(1) Index cases refer to patients discharged between July 2009 and June 2012 who were initially admitted to this hospital
(regardless of whether they were subsequently transferred) in their last period of care.
(2) Age at admission date.
(3) Only those conditions that were shown to have a significant impact on mortality (P<0.05) are shown. Many are a result of
end-organ damage resulting from comorbidities, such as diabetes. A broader set of comorbidities was screened for potential
impacts on mortality. Comorbidities as recorded on patient record, with one year look back. STEMI refers to ST-elevation
myocardial infarction.
(4) Deaths are from any cause, in or out of hospital within 30 days of the index hospitalisation admission date.
(5) Kaplan-Meier survival curve for 30-day following admission for haemorrhagic stroke, adjusted for average age and average
Charlson comorbidity score. Survival curves depict the proportion of patients who were alive, day 0 – day 30.
(6) To make RSMRs comparable over time, a reference population is required. Time series RSMRs for each hospital are based
on the reference years (July 2009 - June 2012). Control limits are based on the NSW average within each period.
( ) Data for hospitals with an expected mortality of <1 are suppressed.
( ) Between 90% and 95% upper control limits; ( ) Outside 95% upper control limits.
( ) Between 90% and 95% lower control limits; ( ) Outside 95% lower control limits.
Details of analyses and risk adjustment are available in Spotlight on Measurement: risk-standardised mortality ratios
Data source: SAPHaRI, Centre for Epidemiology and Evidence, NSW Ministry of Health.
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 4 of 4
Unadjusted ratio Age and sex standardised ratio Risk-standardised mortality ratio
0.79 0.71 0.87
2000-02 2003-05 2006-08 2009-11
0.50 0.93 0.98 0.87
Ballina District Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for pneumonia
Balli
na D
istr
ict
Ho
sp
ital
Pneum
onia
Total pneumonia hospitalisations
Pneumonia patients
Presenting patients (index cases)1
Patients not transferred to another hospital
Patients transferred out to another hospital
This hospital NSW
Age profile, index cases 2
Ballina District Hospital
NSW
% of index cases
Significant patient factors and comorbidities, index cases3
Ballina District Hospital NSW
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 1 of 4
160
143
105
38
50,644
44,059
39,655
4,404
18-51 52-67 68-77 78-85 86+
17 14 26 23 20
20 20 19 22 19
0 10 20 30 40 50 60 70 80 90 100
14Dysrhythmia
24Chronic obstructive pulmonary disease
8Renal failure
13Congestive heart failure
5Hypotension
9Malignancy (cancer)
3Dementia
3Cerebrovascular disease
0Liver disease
0Shock
0Alzheimer's disease
1Parkinson's disease
17
16
16
15
12
9
7
3
2
2
1
1
0 10 20 30 40 50 60 70 80 90 100
% of index cases with factor recorded
Ballina District Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for pneumonia
Balli
na D
istr
ict
Ho
sp
ital
Pneum
onia
Percentages: index cases who died within 30 days of hospitalisation
Of all deaths:
percentage in this hospital
percentage in another hospital following transfer
percentage after discharge
percentage on day of admission
percentage within 7 days
This hospital
percentage
NSW
percentage
Survival of index cases following hospitalisation for pneumonia5
Adjusted for average age and Charlson comorbidity score
Ballina District Hospital
% S
urv
ival
Days since admission
NSW
% S
urv
ival
Days since admission
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 2 of 4
Mortality (all causes) among 143 pneumonia index cases4
12%
71%
0%
29%
0%
53%
(66%)
(3%)
(31%)
(6%)
(54%)
0
75
80
85
90
95
100
0 10 20 30
0
75
80
85
90
95
100
0 10 20 30
Ballina District Hospital profile July 2009 - June 2012
Hospital-level pneumonia risk-standardised mortality ratio by number
of expected deaths, NSW public hospitals
Balli
na D
istr
ict
Ho
sp
ital
Pneum
onia
Ballina District Hospital NSW hospitals 90% limits 95% limits
Hospital-specific RSMRs report the ratio of actual or ‘observed’ number of deaths to the ‘expected’ number
of deaths. A hierarchical logistic regression model draws on the NSW patient population’s characteristics and
outcomes to estimate the expected number of deaths for each hospital, given the characteristics of its patients.
Actual and expected deaths, compared to local peers
This hospital,
actual deaths
Peer group hospitals,
actual deaths
Expected deaths
(based on model)
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 3 of 4
Blue Mountains District Anzac Memorial Hospital
Bateman's Bay District Hospital
Kempsey Hospital
Queanbeyan Health Service
Maclean District Hospital
RSMR = 1.24Ballina District Hospital
Moruya District Hospital
Macksville District Hospital
Lithgow Health Service
Casino and District Memorial Hospital
Milton and Ulladulla Hospital
Cooma Health Service
0 10 20 30 40 50
Deaths
0
1
2
3
Ris
k s
tand
ard
ised
mo
rtalit
y r
atio
(R
SM
R)
0 50 100 150 200
Expected number of deaths within 30 days
Ballina District Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for pneumonia
Balli
na D
istr
ict
Ho
sp
ital
Pneum
onia
Illustrating the effect of standardisation, July 2009 - June 2012
In order to make fair comparisons, a number of risk adjustments are made to mortality data. These take into account
patient level factors that influence the likelihood of dying. The table below illustrates the cumulative effect of the statistical
adjustments. For each ratio, hospitals are compared to the average NSW result, given their case mix.
Lower mortality No difference Higher mortality
Time series risk-standardised mortality ratio, July 2000 - June 20126
Lower mortality No difference Higher mortality
Year (financial years)
Risk-standardised mortality ratio
(1) Index cases refer to patients discharged between July 2009 and June 2012 who were initially admitted to this hospital
(regardless of whether they were subsequently transferred) in their last period of care.
(2) Age at admission date.
(3) Only those conditions that were shown to have a significant impact on mortality (P<0.05) are shown. Many are a result of
end-organ damage resulting from comorbidities, such as diabetes. A broader set of comorbidities was screened for potential
impacts on mortality. Comorbidities as recorded on patient record, with one year look back. STEMI refers to ST-elevation
myocardial infarction.
(4) Deaths are from any cause, in or out of hospital within 30 days of the index hospitalisation admission date.
(5) Kaplan-Meier survival curve for 30-day following admission for haemorrhagic stroke, adjusted for average age and average
Charlson comorbidity score. Survival curves depict the proportion of patients who were alive, day 0 – day 30.
(6) To make RSMRs comparable over time, a reference population is required. Time series RSMRs for each hospital are based
on the reference years (July 2009 - June 2012). Control limits are based on the NSW average within each period.
( ) Data for hospitals with an expected mortality of <1 are suppressed.
( ) Between 90% and 95% upper control limits; ( ) Outside 95% upper control limits.
( ) Between 90% and 95% lower control limits; ( ) Outside 95% lower control limits.
Details of analyses and risk adjustment are available in Spotlight on Measurement: risk-standardised mortality ratios
Data source: SAPHaRI, Centre for Epidemiology and Evidence, NSW Ministry of Health.
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 4 of 4
Unadjusted ratio Age and sex standardised ratio Risk-standardised mortality ratio
1.10 1.07 1.24
2000-02 2003-05 2006-08 2009-12
2.21 1.52 1.34 1.24
Casino and District Memorial Hospital summary dashboard, July 2009 - June 2012
30-day mortality following hospitalisation for five conditions
Casin
o a
nd
Dis
tric
t M
em
orial H
osp
ital
Dashb
oard
Hospital-specific risk-standardised mortality ratios (RSMRs) report the ratio of actual or ‘observed’ number of deaths
to the ‘expected’ number of deaths. A hierarchical logistic regression model draws on the NSW patient population’s
characteristics and outcomes to estimate the expected number of deaths for each hospital, given its case mix.
A ratio less than 1.0 indicates lower-than-expected mortality, and a ratio higher than 1.0 indicates higher-than-expected
mortality. Small deviations from 1.0 are not considered to be meaningful. Funnel plots with 90% and 95% control limits
around the NSW rate are used to identify hospitals with higher and lower mortality.
This measure is not designed to compare hospitals and cannot be used to measure the number of avoidable deaths.
RSMRs do not distinguish deaths that are avoidable from those that are a reflection of the natural course of illness.
They do not provide, by themselves, a diagnostic of quality and safety of care.
Risk-standardised mortality ratios (RSMRs) for five conditions, dashboard
Lower mortality No difference Higher mortality Range within 90% control limits
RSMR July 2009 to June 2012
NSW
RSMRs for three-year periods
How to interpret the dashboard
NSW average for index cases
mortality is lower than expected mortality is higher than expected
The length of the bar for each condition reflects the tolerance
for variation around the NSW average. It is wider for hospitals
admitting a small number of patients.
If a hospital's RSMR lies on the grey bar, its mortality is within the range of
values expected for an average NSW hospital of similar size.
( ) Data for hospitals with an expected mortality of <1 are suppressed.
( ) Between 90% and 95% upper control limits; ( ) Outside 95% upper control limits.
( ) Between 90% and 95% lower control limits; ( ) Outside 95% lower control limits.
Notes: RSMR data are for patients with a hospitalisation noting the relevant condition as principal diagnosis.
Patients include those discharged between July 2009 and June 2012 who were initially admitted to this hospital
(regardless of whether they were subsequently transferred) in their last period of care. Deaths are from any cause,
in or out of hospital within 30 days of the hospitalisation admission date.
Details of analyses and risk adjustment are available in Spotlight on Measurement: risk-standardised mortality ratios
for five conditions.
Data source: SAPHaRI, Centre for Epidemiology and Evidence, NSW Ministry of Health.
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au
Acute myocardial infarction (AMI) 58 patients
Ischaemic stroke < 50 patients
Haemorrhagic stroke < 50 patients
Pneumonia 156 patients
Hip fracture < 50 patients
2000-02 2003-05 2006-08 2009-11
Casino and District Memorial Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for Acute Myocardial Infarction (AMI)
Casin
o a
nd
Dis
tric
t M
em
orial H
osp
ital
Acute
Myo
card
ial In
farc
tio
n (A
MI)
Total Acute Myocardial Infarction (AMI) hospitalisations
Acute Myocardial Infarction (AMI) patients
Presenting patients (index cases)1
Patients not transferred to another hospital
Patients transferred out to another hospital
This hospital NSW
Age profile, index cases 2
Casino and District Memorial Hospital
NSW
% of index cases
Significant patient factors and comorbidities, index cases3
Casino and District Memorial Hospital NSW
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 1 of 4
83
58
12
46
37,794
29,223
18,303
10,920
15-55 56-65 66-74 75-82 83+
22 17 10 22 28
19 21 20 19 21
0 10 20 30 40 50 60 70 80 90 100
36Hypertension
50STEMI
21Dysrhythmia
16Congestive heart failure
9Renal failure
9Hypotension
10Dementia
9Cerebrovascular disease
3Malignancy (cancer)
2Shock
0Alzheimer's disease
58
32
21
17
13
11
3
3
3
2
1
0 10 20 30 40 50 60 70 80 90 100
% of index cases with factor recorded
Casino and District Memorial Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for Acute Myocardial Infarction (AMI)
Casin
o a
nd
Dis
tric
t M
em
orial H
osp
ital
Acute
Myo
card
ial In
farc
tio
n (A
MI)
Percentages: index cases who died within 30 days of hospitalisation
Of all deaths:
percentage in this hospital
percentage in another hospital following transfer
percentage after discharge
percentage on day of admission
percentage within 7 days
This hospital
percentage
NSW
percentage
Survival of index cases following hospitalisation for Acute Myocardial Infarction (AMI)5
Adjusted for average age and Charlson comorbidity score
Casino and District Memorial Hospital
% S
urv
ival
Days since admission
NSW
% S
urv
ival
Days since admission
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 2 of 4
Mortality (all causes) among 58 Acute Myocardial Infarction (AMI) index cases4
9%
20%
20%
60%
0%
80%
(64%)
(6%)
(31%)
(14%)
(61%)
0
90
95
100
0 10 20 30
0
90
95
100
0 10 20 30
Casino and District Memorial Hospital profile July 2009 - June 2012
Hospital-level Acute Myocardial Infarction (AMI) risk-standardised mortality ratio by number
of expected deaths, NSW public hospitals
Casin
o a
nd
Dis
tric
t M
em
orial H
osp
ital
Acute
Myo
card
ial In
farc
tio
n (A
MI)
Casino and District Memorial Hospital NSW hospitals 90% limits 95% limits
Hospital-specific RSMRs report the ratio of actual or ‘observed’ number of deaths to the ‘expected’ number
of deaths. A hierarchical logistic regression model draws on the NSW patient population’s characteristics and
outcomes to estimate the expected number of deaths for each hospital, given the characteristics of its patients.
Actual and expected deaths, compared to local peers
This hospital,
actual deaths
Peer group hospitals,
actual deaths
Expected deaths
(based on model)
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 3 of 4
Kempsey Hospital
Maclean District Hospital
Lithgow Health Service
Moruya District Hospital
Milton and Ulladulla Hospital
Blue Mountains District Anzac Memorial Hospital
Ballina District Hospital
RSMR = 0.76Casino and District Memorial Hospital
Bateman's Bay District Hospital
0 5 10 15 20 25
Deaths
0
1
2
3
4
5
Ris
k s
tand
ard
ised
mo
rtalit
y r
atio
(R
SM
R)
0 50 100 150
Expected number of deaths within 30 days
Casino and District Memorial Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for Acute Myocardial Infarction (AMI)
Casin
o a
nd
Dis
tric
t M
em
orial H
osp
ital
Acute
Myo
card
ial In
farc
tio
n (A
MI)
Illustrating the effect of standardisation, July 2009 - June 2012
In order to make fair comparisons, a number of risk adjustments are made to mortality data. These take into account
patient level factors that influence the likelihood of dying. The table below illustrates the cumulative effect of the statistical
adjustments. For each ratio, hospitals are compared to the average NSW result, given their case mix.
Lower mortality No difference Higher mortality
Time series risk-standardised mortality ratio, July 2000 - June 20126
Lower mortality No difference Higher mortality
Year (financial years)
Risk-standardised mortality ratio
(1) Index cases refer to patients discharged between July 2009 and June 2012 who were initially admitted to this hospital
(regardless of whether they were subsequently transferred) in their last period of care.
(2) Age at admission date.
(3) Only those conditions that were shown to have a significant impact on mortality (P<0.05) are shown. Many are a result of
end-organ damage resulting from comorbidities, such as diabetes. A broader set of comorbidities was screened for potential
impacts on mortality. Comorbidities as recorded on patient record, with one year look back. STEMI refers to ST-elevation
myocardial infarction.
(4) Deaths are from any cause, in or out of hospital within 30 days of the index hospitalisation admission date.
(5) Kaplan-Meier survival curve for 30-day following admission for haemorrhagic stroke, adjusted for average age and average
Charlson comorbidity score. Survival curves depict the proportion of patients who were alive, day 0 – day 30.
(6) To make RSMRs comparable over time, a reference population is required. Time series RSMRs for each hospital are based
on the reference years (July 2009 - June 2012). Control limits are based on the NSW average within each period.
( ) Data for hospitals with an expected mortality of <1 are suppressed.
( ) Between 90% and 95% upper control limits; ( ) Outside 95% upper control limits.
( ) Between 90% and 95% lower control limits; ( ) Outside 95% lower control limits.
Details of analyses and risk adjustment are available in Spotlight on Measurement: risk-standardised mortality ratios
Data source: SAPHaRI, Centre for Epidemiology and Evidence, NSW Ministry of Health.
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 4 of 4
Unadjusted ratio Age and sex standardised ratio Risk-standardised mortality ratio
1.14 1.03 0.76
2000-02 2003-05 2006-08 2009-11
0.93 0.00 0.38 0.76
Casino and District Memorial Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for pneumonia
Casin
o a
nd
Dis
tric
t M
em
orial H
osp
ital
Pneum
onia
Total pneumonia hospitalisations
Pneumonia patients
Presenting patients (index cases)1
Patients not transferred to another hospital
Patients transferred out to another hospital
This hospital NSW
Age profile, index cases 2
Casino and District Memorial Hospital
NSW
% of index cases
Significant patient factors and comorbidities, index cases3
Casino and District Memorial Hospital NSW
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 1 of 4
169
156
142
14
50,644
44,059
39,655
4,404
18-51 52-67 68-77 78-85 86+
22 19 22 15 21
20 20 19 22 19
0 10 20 30 40 50 60 70 80 90 100
12Dysrhythmia
24Chronic obstructive pulmonary disease
6Renal failure
10Congestive heart failure
8Hypotension
8Malignancy (cancer)
10Dementia
4Cerebrovascular disease
3Liver disease
1Shock
0Alzheimer's disease
3Parkinson's disease
17
16
16
15
12
9
7
3
2
2
1
1
0 10 20 30 40 50 60 70 80 90 100
% of index cases with factor recorded
Casino and District Memorial Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for pneumonia
Casin
o a
nd
Dis
tric
t M
em
orial H
osp
ital
Pneum
onia
Percentages: index cases who died within 30 days of hospitalisation
Of all deaths:
percentage in this hospital
percentage in another hospital following transfer
percentage after discharge
percentage on day of admission
percentage within 7 days
This hospital
percentage
NSW
percentage
Survival of index cases following hospitalisation for pneumonia5
Adjusted for average age and Charlson comorbidity score
Casino and District Memorial Hospital
% S
urv
ival
Days since admission
NSW
% S
urv
ival
Days since admission
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 2 of 4
Mortality (all causes) among 156 pneumonia index cases4
9%
79%
7%
14%
0%
50%
(66%)
(3%)
(31%)
(6%)
(54%)
0
75
80
85
90
95
100
0 10 20 30
0
75
80
85
90
95
100
0 10 20 30
Casino and District Memorial Hospital profile July 2009 - June 2012
Hospital-level pneumonia risk-standardised mortality ratio by number
of expected deaths, NSW public hospitals
Casin
o a
nd
Dis
tric
t M
em
orial H
osp
ital
Pneum
onia
Casino and District Memorial Hospital NSW hospitals 90% limits 95% limits
Hospital-specific RSMRs report the ratio of actual or ‘observed’ number of deaths to the ‘expected’ number
of deaths. A hierarchical logistic regression model draws on the NSW patient population’s characteristics and
outcomes to estimate the expected number of deaths for each hospital, given the characteristics of its patients.
Actual and expected deaths, compared to local peers
This hospital,
actual deaths
Peer group hospitals,
actual deaths
Expected deaths
(based on model)
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 3 of 4
Blue Mountains District Anzac Memorial Hospital
Bateman's Bay District Hospital
Kempsey Hospital
Queanbeyan Health Service
Maclean District Hospital
Ballina District Hospital
Moruya District Hospital
Macksville District Hospital
Lithgow Health Service
RSMR = 0.87Casino and District Memorial Hospital
Milton and Ulladulla Hospital
Cooma Health Service
0 10 20 30 40 50
Deaths
0
1
2
3
Ris
k s
tand
ard
ised
mo
rtalit
y r
atio
(R
SM
R)
0 50 100 150 200
Expected number of deaths within 30 days
Casino and District Memorial Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for pneumonia
Casin
o a
nd
Dis
tric
t M
em
orial H
osp
ital
Pneum
onia
Illustrating the effect of standardisation, July 2009 - June 2012
In order to make fair comparisons, a number of risk adjustments are made to mortality data. These take into account
patient level factors that influence the likelihood of dying. The table below illustrates the cumulative effect of the statistical
adjustments. For each ratio, hospitals are compared to the average NSW result, given their case mix.
Lower mortality No difference Higher mortality
Time series risk-standardised mortality ratio, July 2000 - June 20126
Lower mortality No difference Higher mortality
Year (financial years)
Risk-standardised mortality ratio
(1) Index cases refer to patients discharged between July 2009 and June 2012 who were initially admitted to this hospital
(regardless of whether they were subsequently transferred) in their last period of care.
(2) Age at admission date.
(3) Only those conditions that were shown to have a significant impact on mortality (P<0.05) are shown. Many are a result of
end-organ damage resulting from comorbidities, such as diabetes. A broader set of comorbidities was screened for potential
impacts on mortality. Comorbidities as recorded on patient record, with one year look back. STEMI refers to ST-elevation
myocardial infarction.
(4) Deaths are from any cause, in or out of hospital within 30 days of the index hospitalisation admission date.
(5) Kaplan-Meier survival curve for 30-day following admission for haemorrhagic stroke, adjusted for average age and average
Charlson comorbidity score. Survival curves depict the proportion of patients who were alive, day 0 – day 30.
(6) To make RSMRs comparable over time, a reference population is required. Time series RSMRs for each hospital are based
on the reference years (July 2009 - June 2012). Control limits are based on the NSW average within each period.
( ) Data for hospitals with an expected mortality of <1 are suppressed.
( ) Between 90% and 95% upper control limits; ( ) Outside 95% upper control limits.
( ) Between 90% and 95% lower control limits; ( ) Outside 95% lower control limits.
Details of analyses and risk adjustment are available in Spotlight on Measurement: risk-standardised mortality ratios
Data source: SAPHaRI, Centre for Epidemiology and Evidence, NSW Ministry of Health.
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 4 of 4
Unadjusted ratio Age and sex standardised ratio Risk-standardised mortality ratio
0.83 0.87 0.87
2000-02 2003-05 2006-08 2009-12
0.78 1.36 0.95 0.87
Grafton Base Hospital summary dashboard, July 2009 - June 2012
30-day mortality following hospitalisation for five conditions
Gra
fto
n B
ase H
osp
ital
Dashb
oard
Hospital-specific risk-standardised mortality ratios (RSMRs) report the ratio of actual or ‘observed’ number of deaths
to the ‘expected’ number of deaths. A hierarchical logistic regression model draws on the NSW patient population’s
characteristics and outcomes to estimate the expected number of deaths for each hospital, given its case mix.
A ratio less than 1.0 indicates lower-than-expected mortality, and a ratio higher than 1.0 indicates higher-than-expected
mortality. Small deviations from 1.0 are not considered to be meaningful. Funnel plots with 90% and 95% control limits
around the NSW rate are used to identify hospitals with higher and lower mortality.
This measure is not designed to compare hospitals and cannot be used to measure the number of avoidable deaths.
RSMRs do not distinguish deaths that are avoidable from those that are a reflection of the natural course of illness.
They do not provide, by themselves, a diagnostic of quality and safety of care.
Risk-standardised mortality ratios (RSMRs) for five conditions, dashboard
Lower mortality No difference Higher mortality Range within 90% control limits
RSMR July 2009 to June 2012
NSW
RSMRs for three-year periods
How to interpret the dashboard
NSW average for index cases
mortality is lower than expected mortality is higher than expected
The length of the bar for each condition reflects the tolerance
for variation around the NSW average. It is wider for hospitals
admitting a small number of patients.
If a hospital's RSMR lies on the grey bar, its mortality is within the range of
values expected for an average NSW hospital of similar size.
( ) Data for hospitals with an expected mortality of <1 are suppressed.
( ) Between 90% and 95% upper control limits; ( ) Outside 95% upper control limits.
( ) Between 90% and 95% lower control limits; ( ) Outside 95% lower control limits.
Notes: RSMR data are for patients with a hospitalisation noting the relevant condition as principal diagnosis.
Patients include those discharged between July 2009 and June 2012 who were initially admitted to this hospital
(regardless of whether they were subsequently transferred) in their last period of care. Deaths are from any cause,
in or out of hospital within 30 days of the hospitalisation admission date.
Details of analyses and risk adjustment are available in Spotlight on Measurement: risk-standardised mortality ratios
for five conditions.
Data source: SAPHaRI, Centre for Epidemiology and Evidence, NSW Ministry of Health.
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au
Acute myocardial infarction (AMI) 215 patients
Ischaemic stroke 54 patients
Haemorrhagic stroke < 50 patients
Pneumonia 291 patients
Hip fracture < 50 patients
2000-02 2003-05 2006-08 2009-11
Grafton Base Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for Acute Myocardial Infarction (AMI)
Gra
fto
n B
ase H
osp
ital
Acute
Myo
card
ial In
farc
tio
n (A
MI)
Total Acute Myocardial Infarction (AMI) hospitalisations
Acute Myocardial Infarction (AMI) patients
Presenting patients (index cases)1
Patients not transferred to another hospital
Patients transferred out to another hospital
This hospital NSW
Age profile, index cases 2
Grafton Base Hospital
NSW
% of index cases
Significant patient factors and comorbidities, index cases3
Grafton Base Hospital NSW
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 1 of 4
268
215
91
124
37,794
29,223
18,303
10,920
15-55 56-65 66-74 75-82 83+
18 20 17 20 26
19 21 20 19 21
0 10 20 30 40 50 60 70 80 90 100
46Hypertension
28STEMI
24Dysrhythmia
19Congestive heart failure
5Renal failure
8Hypotension
6Dementia
5Cerebrovascular disease
3Malignancy (cancer)
1Shock
0Alzheimer's disease
58
32
21
17
13
11
3
3
3
2
1
0 10 20 30 40 50 60 70 80 90 100
% of index cases with factor recorded
Grafton Base Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for Acute Myocardial Infarction (AMI)
Gra
fto
n B
ase H
osp
ital
Acute
Myo
card
ial In
farc
tio
n (A
MI)
Percentages: index cases who died within 30 days of hospitalisation
Of all deaths:
percentage in this hospital
percentage in another hospital following transfer
percentage after discharge
percentage on day of admission
percentage within 7 days
This hospital
percentage
NSW
percentage
Survival of index cases following hospitalisation for Acute Myocardial Infarction (AMI)5
Adjusted for average age and Charlson comorbidity score
Grafton Base Hospital
% S
urv
ival
Days since admission
NSW
% S
urv
ival
Days since admission
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 2 of 4
Mortality (all causes) among 215 Acute Myocardial Infarction (AMI) index cases4
7%
47%
0%
53%
7%
53%
(64%)
(6%)
(31%)
(14%)
(61%)
0
90
95
100
0 10 20 30
0
90
95
100
0 10 20 30
Grafton Base Hospital profile July 2009 - June 2012
Hospital-level Acute Myocardial Infarction (AMI) risk-standardised mortality ratio by number
of expected deaths, NSW public hospitals
Gra
fto
n B
ase H
osp
ital
Acute
Myo
card
ial In
farc
tio
n (A
MI)
Grafton Base Hospital NSW hospitals 90% limits 95% limits
Hospital-specific RSMRs report the ratio of actual or ‘observed’ number of deaths to the ‘expected’ number
of deaths. A hierarchical logistic regression model draws on the NSW patient population’s characteristics and
outcomes to estimate the expected number of deaths for each hospital, given the characteristics of its patients.
Actual and expected deaths, compared to local peers
This hospital,
actual deaths
Peer group hospitals,
actual deaths
Expected deaths
(based on model)
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 3 of 4
Shellharbour Hospital
Mount Druitt Hospital
Belmont Hospital
Ryde Hospital
Bowral and District Hospital
RSMR = 0.85Grafton Base Hospital
Bathurst Base Hospital
Goulburn Base Hospital
Broken Hill Base Hospital
Griffith Base Hospital
Hawkesbury District Health Service
Bega District Hospital
Murwillumbah District Hospital
Armidale and New England Hospital
0 10 20 30 40 50
Deaths
0
1
2
3
4
5
Ris
k s
tand
ard
ised
mo
rtalit
y r
atio
(R
SM
R)
0 50 100 150
Expected number of deaths within 30 days
Grafton Base Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for Acute Myocardial Infarction (AMI)
Gra
fto
n B
ase H
osp
ital
Acute
Myo
card
ial In
farc
tio
n (A
MI)
Illustrating the effect of standardisation, July 2009 - June 2012
In order to make fair comparisons, a number of risk adjustments are made to mortality data. These take into account
patient level factors that influence the likelihood of dying. The table below illustrates the cumulative effect of the statistical
adjustments. For each ratio, hospitals are compared to the average NSW result, given their case mix.
Lower mortality No difference Higher mortality
Time series risk-standardised mortality ratio, July 2000 - June 20126
Lower mortality No difference Higher mortality
Year (financial years)
Risk-standardised mortality ratio
(1) Index cases refer to patients discharged between July 2009 and June 2012 who were initially admitted to this hospital
(regardless of whether they were subsequently transferred) in their last period of care.
(2) Age at admission date.
(3) Only those conditions that were shown to have a significant impact on mortality (P<0.05) are shown. Many are a result of
end-organ damage resulting from comorbidities, such as diabetes. A broader set of comorbidities was screened for potential
impacts on mortality. Comorbidities as recorded on patient record, with one year look back. STEMI refers to ST-elevation
myocardial infarction.
(4) Deaths are from any cause, in or out of hospital within 30 days of the index hospitalisation admission date.
(5) Kaplan-Meier survival curve for 30-day following admission for haemorrhagic stroke, adjusted for average age and average
Charlson comorbidity score. Survival curves depict the proportion of patients who were alive, day 0 – day 30.
(6) To make RSMRs comparable over time, a reference population is required. Time series RSMRs for each hospital are based
on the reference years (July 2009 - June 2012). Control limits are based on the NSW average within each period.
( ) Data for hospitals with an expected mortality of <1 are suppressed.
( ) Between 90% and 95% upper control limits; ( ) Outside 95% upper control limits.
( ) Between 90% and 95% lower control limits; ( ) Outside 95% lower control limits.
Details of analyses and risk adjustment are available in Spotlight on Measurement: risk-standardised mortality ratios
Data source: SAPHaRI, Centre for Epidemiology and Evidence, NSW Ministry of Health.
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 4 of 4
Unadjusted ratio Age and sex standardised ratio Risk-standardised mortality ratio
0.92 0.84 0.86
2000-02 2003-05 2006-08 2009-11
0.42 0.80 0.83 0.86
Grafton Base Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for ischaemic stroke
Gra
fto
n B
ase H
osp
ital
Ischaem
ic s
tro
ke
Total ischaemic stroke hospitalisations
Ischaemic stroke patients
Presenting patients (index cases)1
Patients not transferred to another hospital
Patients transferred out to another hospital
This hospital NSW
Age profile, index cases 2
Grafton Base Hospital
NSW
% of index cases
Significant patient factors and comorbidities, index cases3
Grafton Base Hospital NSW
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 1 of 4
62
54
51
3
15,299
14,205
11,757
2,448
15-63 64-72 73-79 80-85 86+
17 22 15 26 20
20 18 20 21 21
0 10 20 30 40 50 60 70 80 90 100
43Female
6Renal failure
7Congestive heart failure
4Malignancy (cancer)
47
10
7
4
0 10 20 30 40 50 60 70 80 90 100
% of index cases with factor recorded
Grafton Base Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for ischaemic stroke
Gra
fto
n B
ase H
osp
ital
Ischaem
ic s
tro
ke
Percentages: index cases who died within 30 days of hospitalisation
Of all deaths:
percentage in this hospital
percentage in another hospital following transfer
percentage after discharge
percentage on day of admission
percentage within 7 days
This hospital
percentage
NSW
percentage
Survival of index cases following hospitalisation for ischaemic stroke5
Adjusted for average age and Charlson comorbidity score
Grafton Base Hospital
% S
urv
ival
Days since admission
NSW
% S
urv
ival
Days since admission
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 2 of 4
Mortality (all causes) among 54 ischaemic stroke index cases4
9%
40%
0%
60%
0%
20%
(67%)
(2%)
(31%)
(2%)
(51%)
0
80
85
90
95
100
0 10 20 30
0
80
85
90
95
100
0 10 20 30
Grafton Base Hospital profile July 2009 - June 2012
Hospital-level ischaemic stroke risk-standardised mortality ratio by number
of expected deaths, NSW public hospitals
Gra
fto
n B
ase H
osp
ital
Ischaem
ic s
tro
ke
Grafton Base Hospital NSW hospitals 90% limits 95% limits
Hospital-specific RSMRs report the ratio of actual or ‘observed’ number of deaths to the ‘expected’ number
of deaths. A hierarchical logistic regression model draws on the NSW patient population’s characteristics and
outcomes to estimate the expected number of deaths for each hospital, given the characteristics of its patients.
Actual and expected deaths, compared to local peers
This hospital,
actual deaths
Peer group hospitals,
actual deaths
Expected deaths
(based on model)
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 3 of 4
Ryde Hospital
Shellharbour Hospital
Bowral and District Hospital
Belmont Hospital
Griffith Base Hospital
Broken Hill Base Hospital
Moruya District Hospital
Goulburn Base Hospital
Bathurst Base Hospital
Hawkesbury District Health Service
Kempsey Hospital
Armidale and New England Hospital
RSMR = 0.72Grafton Base Hospital
0 10 20 30 40 50
Deaths
0
1
2
3
Ris
k s
tand
ard
ised
mo
rtalit
y r
atio
(R
SM
R)
0 25 50 75 100 125
Expected number of deaths within 30 days
Grafton Base Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for ischaemic stroke
Gra
fto
n B
ase H
osp
ital
Ischaem
ic s
tro
ke
Illustrating the effect of standardisation, July 2009 - June 2012
In order to make fair comparisons, a number of risk adjustments are made to mortality data. These take into account
patient level factors that influence the likelihood of dying. The table below illustrates the cumulative effect of the statistical
adjustments. For each ratio, hospitals are compared to the average NSW result, given their case mix.
Lower mortality No difference Higher mortality
Time series risk-standardised mortality ratio, July 2000 - June 20126
Lower mortality No difference Higher mortality
Year (financial years)
Risk-standardised mortality ratio
(1) Index cases refer to patients discharged between July 2009 and June 2012 who were initially admitted to this hospital
(regardless of whether they were subsequently transferred) in their last period of care.
(2) Age at admission date.
(3) Only those conditions that were shown to have a significant impact on mortality (P<0.05) are shown. Many are a result of
end-organ damage resulting from comorbidities, such as diabetes. A broader set of comorbidities was screened for potential
impacts on mortality. Comorbidities as recorded on patient record, with one year look back. STEMI refers to ST-elevation
myocardial infarction.
(4) Deaths are from any cause, in or out of hospital within 30 days of the index hospitalisation admission date.
(5) Kaplan-Meier survival curve for 30-day following admission for haemorrhagic stroke, adjusted for average age and average
Charlson comorbidity score. Survival curves depict the proportion of patients who were alive, day 0 – day 30.
(6) To make RSMRs comparable over time, a reference population is required. Time series RSMRs for each hospital are based
on the reference years (July 2009 - June 2012). Control limits are based on the NSW average within each period.
( ) Data for hospitals with an expected mortality of <1 are suppressed.
( ) Between 90% and 95% upper control limits; ( ) Outside 95% upper control limits.
( ) Between 90% and 95% lower control limits; ( ) Outside 95% lower control limits.
Details of analyses and risk adjustment are available in Spotlight on Measurement: risk-standardised mortality ratios
Data source: SAPHaRI, Centre for Epidemiology and Evidence, NSW Ministry of Health.
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 4 of 4
Unadjusted ratio Age and sex standardised ratio Risk-standardised mortality ratio
0.69 0.71 0.72
2000-02 2003-05 2006-08 2009-11
1.27 1.62 1.46 0.72
Grafton Base Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for pneumonia
Gra
fto
n B
ase H
osp
ital
Pneum
onia
Total pneumonia hospitalisations
Pneumonia patients
Presenting patients (index cases)1
Patients not transferred to another hospital
Patients transferred out to another hospital
This hospital NSW
Age profile, index cases 2
Grafton Base Hospital
NSW
% of index cases
Significant patient factors and comorbidities, index cases3
Grafton Base Hospital NSW
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 1 of 4
334
291
282
9
50,644
44,059
39,655
4,404
18-51 52-67 68-77 78-85 86+
22 24 18 22 13
20 20 19 22 19
0 10 20 30 40 50 60 70 80 90 100
18Dysrhythmia
28Chronic obstructive pulmonary disease
10Renal failure
13Congestive heart failure
6Hypotension
7Malignancy (cancer)
5Dementia
4Cerebrovascular disease
2Liver disease
1Shock
0Alzheimer's disease
1Parkinson's disease
17
16
16
15
12
9
7
3
2
2
1
1
0 10 20 30 40 50 60 70 80 90 100
% of index cases with factor recorded
Grafton Base Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for pneumonia
Gra
fto
n B
ase H
osp
ital
Pneum
onia
Percentages: index cases who died within 30 days of hospitalisation
Of all deaths:
percentage in this hospital
percentage in another hospital following transfer
percentage after discharge
percentage on day of admission
percentage within 7 days
This hospital
percentage
NSW
percentage
Survival of index cases following hospitalisation for pneumonia5
Adjusted for average age and Charlson comorbidity score
Grafton Base Hospital
% S
urv
ival
Days since admission
NSW
% S
urv
ival
Days since admission
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 2 of 4
Mortality (all causes) among 291 pneumonia index cases4
10%
48%
3%
48%
7%
55%
(66%)
(3%)
(31%)
(6%)
(54%)
0
75
80
85
90
95
100
0 10 20 30
0
75
80
85
90
95
100
0 10 20 30
Grafton Base Hospital profile July 2009 - June 2012
Hospital-level pneumonia risk-standardised mortality ratio by number
of expected deaths, NSW public hospitals
Gra
fto
n B
ase H
osp
ital
Pneum
onia
Grafton Base Hospital NSW hospitals 90% limits 95% limits
Hospital-specific RSMRs report the ratio of actual or ‘observed’ number of deaths to the ‘expected’ number
of deaths. A hierarchical logistic regression model draws on the NSW patient population’s characteristics and
outcomes to estimate the expected number of deaths for each hospital, given the characteristics of its patients.
Actual and expected deaths, compared to local peers
This hospital,
actual deaths
Peer group hospitals,
actual deaths
Expected deaths
(based on model)
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 3 of 4
Ryde Hospital
Hawkesbury District Health Service
Bowral and District Hospital
Belmont Hospital
Goulburn Base Hospital
Mount Druitt Hospital
Shellharbour Hospital
Bathurst Base Hospital
RSMR = 1.09Grafton Base Hospital
Griffith Base Hospital
Murwillumbah District Hospital
Bega District Hospital
Armidale and New England Hospital
Broken Hill Base Hospital
0 20 40 60 80 100
Deaths
0
1
2
3
Ris
k s
tand
ard
ised
mo
rtalit
y r
atio
(R
SM
R)
0 50 100 150 200
Expected number of deaths within 30 days
Grafton Base Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for pneumonia
Gra
fto
n B
ase H
osp
ital
Pneum
onia
Illustrating the effect of standardisation, July 2009 - June 2012
In order to make fair comparisons, a number of risk adjustments are made to mortality data. These take into account
patient level factors that influence the likelihood of dying. The table below illustrates the cumulative effect of the statistical
adjustments. For each ratio, hospitals are compared to the average NSW result, given their case mix.
Lower mortality No difference Higher mortality
Time series risk-standardised mortality ratio, July 2000 - June 20126
Lower mortality No difference Higher mortality
Year (financial years)
Risk-standardised mortality ratio
(1) Index cases refer to patients discharged between July 2009 and June 2012 who were initially admitted to this hospital
(regardless of whether they were subsequently transferred) in their last period of care.
(2) Age at admission date.
(3) Only those conditions that were shown to have a significant impact on mortality (P<0.05) are shown. Many are a result of
end-organ damage resulting from comorbidities, such as diabetes. A broader set of comorbidities was screened for potential
impacts on mortality. Comorbidities as recorded on patient record, with one year look back. STEMI refers to ST-elevation
myocardial infarction.
(4) Deaths are from any cause, in or out of hospital within 30 days of the index hospitalisation admission date.
(5) Kaplan-Meier survival curve for 30-day following admission for haemorrhagic stroke, adjusted for average age and average
Charlson comorbidity score. Survival curves depict the proportion of patients who were alive, day 0 – day 30.
(6) To make RSMRs comparable over time, a reference population is required. Time series RSMRs for each hospital are based
on the reference years (July 2009 - June 2012). Control limits are based on the NSW average within each period.
( ) Data for hospitals with an expected mortality of <1 are suppressed.
( ) Between 90% and 95% upper control limits; ( ) Outside 95% upper control limits.
( ) Between 90% and 95% lower control limits; ( ) Outside 95% lower control limits.
Details of analyses and risk adjustment are available in Spotlight on Measurement: risk-standardised mortality ratios
Data source: SAPHaRI, Centre for Epidemiology and Evidence, NSW Ministry of Health.
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 4 of 4
Unadjusted ratio Age and sex standardised ratio Risk-standardised mortality ratio
0.93 1.10 1.09
2000-02 2003-05 2006-08 2009-12
1.25 1.29 1.02 1.09
Lismore Base Hospital summary dashboard, July 2009 - June 2012
30-day mortality following hospitalisation for five conditions
Lis
mo
re B
ase H
osp
ital
Dashb
oard
Hospital-specific risk-standardised mortality ratios (RSMRs) report the ratio of actual or ‘observed’ number of deaths
to the ‘expected’ number of deaths. A hierarchical logistic regression model draws on the NSW patient population’s
characteristics and outcomes to estimate the expected number of deaths for each hospital, given its case mix.
A ratio less than 1.0 indicates lower-than-expected mortality, and a ratio higher than 1.0 indicates higher-than-expected
mortality. Small deviations from 1.0 are not considered to be meaningful. Funnel plots with 90% and 95% control limits
around the NSW rate are used to identify hospitals with higher and lower mortality.
This measure is not designed to compare hospitals and cannot be used to measure the number of avoidable deaths.
RSMRs do not distinguish deaths that are avoidable from those that are a reflection of the natural course of illness.
They do not provide, by themselves, a diagnostic of quality and safety of care.
Risk-standardised mortality ratios (RSMRs) for five conditions, dashboard
Lower mortality No difference Higher mortality Range within 90% control limits
RSMR July 2009 to June 2012
NSW
RSMRs for three-year periods
How to interpret the dashboard
NSW average for index cases
mortality is lower than expected mortality is higher than expected
The length of the bar for each condition reflects the tolerance
for variation around the NSW average. It is wider for hospitals
admitting a small number of patients.
If a hospital's RSMR lies on the grey bar, its mortality is within the range of
values expected for an average NSW hospital of similar size.
( ) Data for hospitals with an expected mortality of <1 are suppressed.
( ) Between 90% and 95% upper control limits; ( ) Outside 95% upper control limits.
( ) Between 90% and 95% lower control limits; ( ) Outside 95% lower control limits.
Notes: RSMR data are for patients with a hospitalisation noting the relevant condition as principal diagnosis.
Patients include those discharged between July 2009 and June 2012 who were initially admitted to this hospital
(regardless of whether they were subsequently transferred) in their last period of care. Deaths are from any cause,
in or out of hospital within 30 days of the hospitalisation admission date.
Details of analyses and risk adjustment are available in Spotlight on Measurement: risk-standardised mortality ratios
for five conditions.
Data source: SAPHaRI, Centre for Epidemiology and Evidence, NSW Ministry of Health.
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au
Acute myocardial infarction (AMI) 553 patients
Ischaemic stroke 168 patients
Haemorrhagic stroke 97 patients
Pneumonia 382 patients
Hip fracture 376 patients
2000-02 2003-05 2006-08 2009-11
Lismore Base Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for Acute Myocardial Infarction (AMI)
Lis
mo
re B
ase H
osp
ital
Acute
Myo
card
ial In
farc
tio
n (A
MI)
Total Acute Myocardial Infarction (AMI) hospitalisations
Acute Myocardial Infarction (AMI) patients
Presenting patients (index cases)1
Patients not transferred to another hospital
Patients transferred out to another hospital
This hospital NSW
Age profile, index cases 2
Lismore Base Hospital
NSW
% of index cases
Significant patient factors and comorbidities, index cases3
Lismore Base Hospital NSW
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 1 of 4
774
553
207
346
37,794
29,223
18,303
10,920
15-55 56-65 66-74 75-82 83+
17 19 18 23 22
19 21 20 19 21
0 10 20 30 40 50 60 70 80 90 100
51Hypertension
25STEMI
23Dysrhythmia
17Congestive heart failure
15Renal failure
6Hypotension
3Dementia
1Cerebrovascular disease
3Malignancy (cancer)
2Shock
0Alzheimer's disease
58
32
21
17
13
11
3
3
3
2
1
0 10 20 30 40 50 60 70 80 90 100
% of index cases with factor recorded
Lismore Base Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for Acute Myocardial Infarction (AMI)
Lis
mo
re B
ase H
osp
ital
Acute
Myo
card
ial In
farc
tio
n (A
MI)
Percentages: index cases who died within 30 days of hospitalisation
Of all deaths:
percentage in this hospital
percentage in another hospital following transfer
percentage after discharge
percentage on day of admission
percentage within 7 days
This hospital
percentage
NSW
percentage
Survival of index cases following hospitalisation for Acute Myocardial Infarction (AMI)5
Adjusted for average age and Charlson comorbidity score
Lismore Base Hospital
% S
urv
ival
Days since admission
NSW
% S
urv
ival
Days since admission
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 2 of 4
Mortality (all causes) among 553 Acute Myocardial Infarction (AMI) index cases4
8%
55%
7%
39%
16%
55%
(64%)
(6%)
(31%)
(14%)
(61%)
0
90
95
100
0 10 20 30
0
90
95
100
0 10 20 30
Lismore Base Hospital profile July 2009 - June 2012
Hospital-level Acute Myocardial Infarction (AMI) risk-standardised mortality ratio by number
of expected deaths, NSW public hospitals
Lis
mo
re B
ase H
osp
ital
Acute
Myo
card
ial In
farc
tio
n (A
MI)
Lismore Base Hospital NSW hospitals 90% limits 95% limits
Hospital-specific RSMRs report the ratio of actual or ‘observed’ number of deaths to the ‘expected’ number
of deaths. A hierarchical logistic regression model draws on the NSW patient population’s characteristics and
outcomes to estimate the expected number of deaths for each hospital, given the characteristics of its patients.
Actual and expected deaths, compared to local peers
This hospital,
actual deaths
Peer group hospitals,
actual deaths
Expected deaths
(based on model)
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 3 of 4
RSMR = 1.11Lismore Base Hospital
The Tweed Hospital
Shoalhaven and District Memorial Hospital
Tamworth Base Hospital
Maitland Hospital
Port Macquarie Base Hospital
Dubbo Base Hospital
Manning Base Hospital
Coffs Harbour Base Hospital
Wagga Wagga Base Hospital
Orange Base Hospital
0 10 20 30 40 50
Deaths
0
1
2
3
4
5
Ris
k s
tand
ard
ised
mo
rtalit
y r
atio
(R
SM
R)
0 50 100 150
Expected number of deaths within 30 days
Lismore Base Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for Acute Myocardial Infarction (AMI)
Lis
mo
re B
ase H
osp
ital
Acute
Myo
card
ial In
farc
tio
n (A
MI)
Illustrating the effect of standardisation, July 2009 - June 2012
In order to make fair comparisons, a number of risk adjustments are made to mortality data. These take into account
patient level factors that influence the likelihood of dying. The table below illustrates the cumulative effect of the statistical
adjustments. For each ratio, hospitals are compared to the average NSW result, given their case mix.
Lower mortality No difference Higher mortality
Time series risk-standardised mortality ratio, July 2000 - June 20126
Lower mortality No difference Higher mortality
Year (financial years)
Risk-standardised mortality ratio
(1) Index cases refer to patients discharged between July 2009 and June 2012 who were initially admitted to this hospital
(regardless of whether they were subsequently transferred) in their last period of care.
(2) Age at admission date.
(3) Only those conditions that were shown to have a significant impact on mortality (P<0.05) are shown. Many are a result of
end-organ damage resulting from comorbidities, such as diabetes. A broader set of comorbidities was screened for potential
impacts on mortality. Comorbidities as recorded on patient record, with one year look back. STEMI refers to ST-elevation
myocardial infarction.
(4) Deaths are from any cause, in or out of hospital within 30 days of the index hospitalisation admission date.
(5) Kaplan-Meier survival curve for 30-day following admission for haemorrhagic stroke, adjusted for average age and average
Charlson comorbidity score. Survival curves depict the proportion of patients who were alive, day 0 – day 30.
(6) To make RSMRs comparable over time, a reference population is required. Time series RSMRs for each hospital are based
on the reference years (July 2009 - June 2012). Control limits are based on the NSW average within each period.
( ) Data for hospitals with an expected mortality of <1 are suppressed.
( ) Between 90% and 95% upper control limits; ( ) Outside 95% upper control limits.
( ) Between 90% and 95% lower control limits; ( ) Outside 95% lower control limits.
Details of analyses and risk adjustment are available in Spotlight on Measurement: risk-standardised mortality ratios
Data source: SAPHaRI, Centre for Epidemiology and Evidence, NSW Ministry of Health.
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 4 of 4
Unadjusted ratio Age and sex standardised ratio Risk-standardised mortality ratio
1.05 1.01 1.11
2000-02 2003-05 2006-08 2009-11
1.05 1.17 1.01 1.11
Lismore Base Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for ischaemic stroke
Lis
mo
re B
ase H
osp
ital
Ischaem
ic s
tro
ke
Total ischaemic stroke hospitalisations
Ischaemic stroke patients
Presenting patients (index cases)1
Patients not transferred to another hospital
Patients transferred out to another hospital
This hospital NSW
Age profile, index cases 2
Lismore Base Hospital
NSW
% of index cases
Significant patient factors and comorbidities, index cases3
Lismore Base Hospital NSW
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 1 of 4
183
168
118
50
15,299
14,205
11,757
2,448
15-63 64-72 73-79 80-85 86+
24 17 18 26 15
20 18 20 21 21
0 10 20 30 40 50 60 70 80 90 100
43Female
8Renal failure
5Congestive heart failure
4Malignancy (cancer)
47
10
7
4
0 10 20 30 40 50 60 70 80 90 100
% of index cases with factor recorded
Lismore Base Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for ischaemic stroke
Lis
mo
re B
ase H
osp
ital
Ischaem
ic s
tro
ke
Percentages: index cases who died within 30 days of hospitalisation
Of all deaths:
percentage in this hospital
percentage in another hospital following transfer
percentage after discharge
percentage on day of admission
percentage within 7 days
This hospital
percentage
NSW
percentage
Survival of index cases following hospitalisation for ischaemic stroke5
Adjusted for average age and Charlson comorbidity score
Lismore Base Hospital
% S
urv
ival
Days since admission
NSW
% S
urv
ival
Days since admission
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 2 of 4
Mortality (all causes) among 168 ischaemic stroke index cases4
17%
79%
0%
21%
7%
72%
(67%)
(2%)
(31%)
(2%)
(51%)
0
80
85
90
95
100
0 10 20 30
0
80
85
90
95
100
0 10 20 30
Lismore Base Hospital profile July 2009 - June 2012
Hospital-level ischaemic stroke risk-standardised mortality ratio by number
of expected deaths, NSW public hospitals
Lis
mo
re B
ase H
osp
ital
Ischaem
ic s
tro
ke
Lismore Base Hospital NSW hospitals 90% limits 95% limits
Hospital-specific RSMRs report the ratio of actual or ‘observed’ number of deaths to the ‘expected’ number
of deaths. A hierarchical logistic regression model draws on the NSW patient population’s characteristics and
outcomes to estimate the expected number of deaths for each hospital, given the characteristics of its patients.
Actual and expected deaths, compared to local peers
This hospital,
actual deaths
Peer group hospitals,
actual deaths
Expected deaths
(based on model)
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 3 of 4
Dubbo Base Hospital
Coffs Harbour Base Hospital
Shoalhaven and District Memorial Hospital
Port Macquarie Base Hospital
Tamworth Base Hospital
RSMR = 1.47Lismore Base Hospital
Manning Base Hospital
The Tweed Hospital
Wagga Wagga Base Hospital
Orange Base Hospital
Maitland Hospital
0 10 20 30 40 50
Deaths
0
1
2
3
Ris
k s
tand
ard
ised
mo
rtalit
y r
atio
(R
SM
R)
0 25 50 75 100 125
Expected number of deaths within 30 days
Lismore Base Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for ischaemic stroke
Lis
mo
re B
ase H
osp
ital
Ischaem
ic s
tro
ke
Illustrating the effect of standardisation, July 2009 - June 2012
In order to make fair comparisons, a number of risk adjustments are made to mortality data. These take into account
patient level factors that influence the likelihood of dying. The table below illustrates the cumulative effect of the statistical
adjustments. For each ratio, hospitals are compared to the average NSW result, given their case mix.
Lower mortality No difference Higher mortality
Time series risk-standardised mortality ratio, July 2000 - June 20126
Lower mortality No difference Higher mortality
Year (financial years)
Risk-standardised mortality ratio
(1) Index cases refer to patients discharged between July 2009 and June 2012 who were initially admitted to this hospital
(regardless of whether they were subsequently transferred) in their last period of care.
(2) Age at admission date.
(3) Only those conditions that were shown to have a significant impact on mortality (P<0.05) are shown. Many are a result of
end-organ damage resulting from comorbidities, such as diabetes. A broader set of comorbidities was screened for potential
impacts on mortality. Comorbidities as recorded on patient record, with one year look back. STEMI refers to ST-elevation
myocardial infarction.
(4) Deaths are from any cause, in or out of hospital within 30 days of the index hospitalisation admission date.
(5) Kaplan-Meier survival curve for 30-day following admission for haemorrhagic stroke, adjusted for average age and average
Charlson comorbidity score. Survival curves depict the proportion of patients who were alive, day 0 – day 30.
(6) To make RSMRs comparable over time, a reference population is required. Time series RSMRs for each hospital are based
on the reference years (July 2009 - June 2012). Control limits are based on the NSW average within each period.
( ) Data for hospitals with an expected mortality of <1 are suppressed.
( ) Between 90% and 95% upper control limits; ( ) Outside 95% upper control limits.
( ) Between 90% and 95% lower control limits; ( ) Outside 95% lower control limits.
Details of analyses and risk adjustment are available in Spotlight on Measurement: risk-standardised mortality ratios
Data source: SAPHaRI, Centre for Epidemiology and Evidence, NSW Ministry of Health.
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 4 of 4
Unadjusted ratio Age and sex standardised ratio Risk-standardised mortality ratio
1.29 1.42 1.47
2000-02 2003-05 2006-08 2009-11
1.49 1.63 1.16 1.47
Lismore Base Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for haemorrhagic stroke
Lis
mo
re B
ase H
osp
ital
Haem
orr
hag
ic s
tro
ke
Total haemorrhagic stroke hospitalisations
Haemorrhagic stroke patients
Presenting patients (index cases)1
Patients not transferred to another hospital
Patients transferred out to another hospital
This hospital NSW
Age profile, index cases 2
Lismore Base Hospital
NSW
% of index cases
Significant patient factors and comorbidities, index cases3
Lismore Base Hospital NSW
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 1 of 4
108
97
63
34
6,573
5,681
4,148
1,533
15-62 63-73 74-80 81-85 86+
16 23 18 29 14
20 21 21 19 19
0 10 20 30 40 50 60 70 80 90 100
34Female
6History of haemorrhagic stroke
4Malignancy (cancer)
5Congestive heart failure
46
8
6
6
0 10 20 30 40 50 60 70 80 90 100
% of index cases with factor recorded
Lismore Base Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for haemorrhagic stroke
Lis
mo
re B
ase H
osp
ital
Haem
orr
hag
ic s
tro
ke
Percentages: index cases who died within 30 days of hospitalisation
Of all deaths:
percentage in this hospital
percentage in another hospital following transfer
percentage after discharge
percentage on day of admission
percentage within 7 days
This hospital
percentage
NSW
percentage
Survival of index cases following hospitalisation for haemorrhagic stroke5
Adjusted for average age and Charlson comorbidity score
Lismore Base Hospital
% S
urv
ival
Days since admission
NSW
% S
urv
ival
Days since admission
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 2 of 4
Mortality (all causes) among 97 haemorrhagic stroke index cases4
41%
78%
0%
23%
28%
70%
(76%)
(3%)
(21%)
(20%)
(75%)
0
50
55
60
65
70
75
80
85
90
95
100
0 10 20 30
0
50
55
60
65
70
75
80
85
90
95
100
0 10 20 30
Lismore Base Hospital profile July 2009 - June 2012
Hospital-level haemorrhagic stroke risk-standardised mortality ratio by number
of expected deaths, NSW public hospitals
Lis
mo
re B
ase H
osp
ital
Haem
orr
hag
ic s
tro
ke
Lismore Base Hospital NSW hospitals 90% limits 95% limits
Hospital-specific RSMRs report the ratio of actual or ‘observed’ number of deaths to the ‘expected’ number
of deaths. A hierarchical logistic regression model draws on the NSW patient population’s characteristics and
outcomes to estimate the expected number of deaths for each hospital, given the characteristics of its patients.
Actual and expected deaths, compared to local peers
This hospital,
actual deaths
Peer group hospitals,
actual deaths
Expected deaths
(based on model)
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 3 of 4
Port Macquarie Base Hospital
RSMR = 1.26Lismore Base Hospital
Coffs Harbour Base Hospital
Shoalhaven and District Memorial Hospital
The Tweed Hospital
Orange Base Hospital
Manning Base Hospital
Tamworth Base Hospital
Wagga Wagga Base Hospital
Dubbo Base Hospital
0 10 20 30 40 50
Deaths
0.0
0.5
1.0
1.5
2.0
2.5
3.0
Ris
k s
tand
ard
ised
mo
rtalit
y r
atio
(R
SM
R)
0 25 50 75 100 125
Expected number of deaths within 30 days
Lismore Base Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for haemorrhagic stroke
Lis
mo
re B
ase H
osp
ital
Haem
orr
hag
ic s
tro
ke
Illustrating the effect of standardisation, July 2009 - June 2012
In order to make fair comparisons, a number of risk adjustments are made to mortality data. These take into account
patient level factors that influence the likelihood of dying. The table below illustrates the cumulative effect of the statistical
adjustments. For each ratio, hospitals are compared to the average NSW result, given their case mix.
Lower mortality No difference Higher mortality
Time series risk-standardised mortality ratio, July 2000 - June 20126
Lower mortality No difference Higher mortality
Year (financial years)
Risk-standardised mortality ratio
(1) Index cases refer to patients discharged between July 2009 and June 2012 who were initially admitted to this hospital
(regardless of whether they were subsequently transferred) in their last period of care.
(2) Age at admission date.
(3) Only those conditions that were shown to have a significant impact on mortality (P<0.05) are shown. Many are a result of
end-organ damage resulting from comorbidities, such as diabetes. A broader set of comorbidities was screened for potential
impacts on mortality. Comorbidities as recorded on patient record, with one year look back. STEMI refers to ST-elevation
myocardial infarction.
(4) Deaths are from any cause, in or out of hospital within 30 days of the index hospitalisation admission date.
(5) Kaplan-Meier survival curve for 30-day following admission for haemorrhagic stroke, adjusted for average age and average
Charlson comorbidity score. Survival curves depict the proportion of patients who were alive, day 0 – day 30.
(6) To make RSMRs comparable over time, a reference population is required. Time series RSMRs for each hospital are based
on the reference years (July 2009 - June 2012). Control limits are based on the NSW average within each period.
( ) Data for hospitals with an expected mortality of <1 are suppressed.
( ) Between 90% and 95% upper control limits; ( ) Outside 95% upper control limits.
( ) Between 90% and 95% lower control limits; ( ) Outside 95% lower control limits.
Details of analyses and risk adjustment are available in Spotlight on Measurement: risk-standardised mortality ratios
Data source: SAPHaRI, Centre for Epidemiology and Evidence, NSW Ministry of Health.
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 4 of 4
Unadjusted ratio Age and sex standardised ratio Risk-standardised mortality ratio
1.22 1.24 1.26
2000-02 2003-05 2006-08 2009-11
1.26 1.54 1.38 1.26
Lismore Base Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for pneumonia
Lis
mo
re B
ase H
osp
ital
Pneum
onia
Total pneumonia hospitalisations
Pneumonia patients
Presenting patients (index cases)1
Patients not transferred to another hospital
Patients transferred out to another hospital
This hospital NSW
Age profile, index cases 2
Lismore Base Hospital
NSW
% of index cases
Significant patient factors and comorbidities, index cases3
Lismore Base Hospital NSW
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 1 of 4
461
382
328
54
50,644
44,059
39,655
4,404
18-51 52-67 68-77 78-85 86+
23 18 23 23 13
20 20 19 22 19
0 10 20 30 40 50 60 70 80 90 100
23Dysrhythmia
14Chronic obstructive pulmonary disease
21Renal failure
12Congestive heart failure
10Hypotension
12Malignancy (cancer)
5Dementia
3Cerebrovascular disease
2Liver disease
1Shock
1Alzheimer's disease
2Parkinson's disease
17
16
16
15
12
9
7
3
2
2
1
1
0 10 20 30 40 50 60 70 80 90 100
% of index cases with factor recorded
Lismore Base Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for pneumonia
Lis
mo
re B
ase H
osp
ital
Pneum
onia
Percentages: index cases who died within 30 days of hospitalisation
Of all deaths:
percentage in this hospital
percentage in another hospital following transfer
percentage after discharge
percentage on day of admission
percentage within 7 days
This hospital
percentage
NSW
percentage
Survival of index cases following hospitalisation for pneumonia5
Adjusted for average age and Charlson comorbidity score
Lismore Base Hospital
% S
urv
ival
Days since admission
NSW
% S
urv
ival
Days since admission
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 2 of 4
Mortality (all causes) among 382 pneumonia index cases4
11%
72%
7%
21%
12%
56%
(66%)
(3%)
(31%)
(6%)
(54%)
0
75
80
85
90
95
100
0 10 20 30
0
75
80
85
90
95
100
0 10 20 30
Lismore Base Hospital profile July 2009 - June 2012
Hospital-level pneumonia risk-standardised mortality ratio by number
of expected deaths, NSW public hospitals
Lis
mo
re B
ase H
osp
ital
Pneum
onia
Lismore Base Hospital NSW hospitals 90% limits 95% limits
Hospital-specific RSMRs report the ratio of actual or ‘observed’ number of deaths to the ‘expected’ number
of deaths. A hierarchical logistic regression model draws on the NSW patient population’s characteristics and
outcomes to estimate the expected number of deaths for each hospital, given the characteristics of its patients.
Actual and expected deaths, compared to local peers
This hospital,
actual deaths
Peer group hospitals,
actual deaths
Expected deaths
(based on model)
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 3 of 4
Shoalhaven and District Memorial Hospital
Manning Base Hospital
Coffs Harbour Base Hospital
Port Macquarie Base Hospital
Tamworth Base Hospital
Wagga Wagga Base Hospital
The Tweed Hospital
Dubbo Base Hospital
Orange Base Hospital
Maitland Hospital
RSMR = 1.08Lismore Base Hospital
0 20 40 60 80 100
Deaths
0
1
2
3
Ris
k s
tand
ard
ised
mo
rtalit
y r
atio
(R
SM
R)
0 50 100 150 200
Expected number of deaths within 30 days
Lismore Base Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for pneumonia
Lis
mo
re B
ase H
osp
ital
Pneum
onia
Illustrating the effect of standardisation, July 2009 - June 2012
In order to make fair comparisons, a number of risk adjustments are made to mortality data. These take into account
patient level factors that influence the likelihood of dying. The table below illustrates the cumulative effect of the statistical
adjustments. For each ratio, hospitals are compared to the average NSW result, given their case mix.
Lower mortality No difference Higher mortality
Time series risk-standardised mortality ratio, July 2000 - June 20126
Lower mortality No difference Higher mortality
Year (financial years)
Risk-standardised mortality ratio
(1) Index cases refer to patients discharged between July 2009 and June 2012 who were initially admitted to this hospital
(regardless of whether they were subsequently transferred) in their last period of care.
(2) Age at admission date.
(3) Only those conditions that were shown to have a significant impact on mortality (P<0.05) are shown. Many are a result of
end-organ damage resulting from comorbidities, such as diabetes. A broader set of comorbidities was screened for potential
impacts on mortality. Comorbidities as recorded on patient record, with one year look back. STEMI refers to ST-elevation
myocardial infarction.
(4) Deaths are from any cause, in or out of hospital within 30 days of the index hospitalisation admission date.
(5) Kaplan-Meier survival curve for 30-day following admission for haemorrhagic stroke, adjusted for average age and average
Charlson comorbidity score. Survival curves depict the proportion of patients who were alive, day 0 – day 30.
(6) To make RSMRs comparable over time, a reference population is required. Time series RSMRs for each hospital are based
on the reference years (July 2009 - June 2012). Control limits are based on the NSW average within each period.
( ) Data for hospitals with an expected mortality of <1 are suppressed.
( ) Between 90% and 95% upper control limits; ( ) Outside 95% upper control limits.
( ) Between 90% and 95% lower control limits; ( ) Outside 95% lower control limits.
Details of analyses and risk adjustment are available in Spotlight on Measurement: risk-standardised mortality ratios
Data source: SAPHaRI, Centre for Epidemiology and Evidence, NSW Ministry of Health.
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 4 of 4
Unadjusted ratio Age and sex standardised ratio Risk-standardised mortality ratio
1.05 1.18 1.08
2000-02 2003-05 2006-08 2009-12
1.46 1.43 0.94 1.08
Lismore Base Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for hip fracture surgery
Lis
mo
re B
ase H
osp
ital
Hip
fra
ctu
re s
urg
ery
Total hip fracture surgery hospitalisations
Hip fracture surgery patients
Presenting patients (index cases)1
Patients not transferred to another hospital
Patients transferred out to another hospital
This hospital NSW
Age profile, index cases 2
Lismore Base Hospital
NSW
% of index cases
Significant patient factors and comorbidities, index cases3
Lismore Base Hospital NSW
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 1 of 4
387
376
171
205
16,355
15,836
10,739
5,097
50-75 76-82 83-86 87-89 90+
18 23 20 19 20
19 23 20 15 22
0 10 20 30 40 50 60 70 80 90 100
27Male
23Dementia
13Dysrhythmia
7Renal failure
9Acute respiratory tract infection
5Congestive heart failure
9Ischemic heart disease
4Malignancy (cancer)
28
23
18
13
12
10
9
4
0 10 20 30 40 50 60 70 80 90 100
% of index cases with factor recorded
Lismore Base Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for hip fracture surgery
Lis
mo
re B
ase H
osp
ital
Hip
fra
ctu
re s
urg
ery
Percentages: index cases who died within 30 days of hospitalisation
Of all deaths:
percentage in this hospital
percentage in another hospital following transfer
percentage after discharge
percentage on day of admission not applicable for hip fracture surgery
percentage within 7 days
This hospital
percentage
NSW
percentage
Survival of index cases following hospitalisation for hip fracture surgery5
Adjusted for average age and Charlson comorbidity score
Lismore Base Hospital
% S
urv
ival
Days since admission
NSW
% S
urv
ival
Days since admission
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 2 of 4
Mortality (all causes) among 376 hip fracture surgery index cases4
7%
41%
0%
59%
33%
(50%)
(0%)
(50%)
(27%)
0
90
95
100
0 10 20 30
0
90
95
100
0 10 20 30
Lismore Base Hospital profile July 2009 - June 2012
Hospital-level hip fracture surgery risk-standardised mortality ratio by number
of expected deaths, NSW public hospitals
Lis
mo
re B
ase H
osp
ital
Hip
fra
ctu
re s
urg
ery
Lismore Base Hospital NSW hospitals 90% limits 95% limits
Hospital-specific RSMRs report the ratio of actual or ‘observed’ number of deaths to the ‘expected’ number
of deaths. A hierarchical logistic regression model draws on the NSW patient population’s characteristics and
outcomes to estimate the expected number of deaths for each hospital, given the characteristics of its patients.
Actual and expected deaths, compared to local peers
This hospital,
actual deaths
Peer group hospitals,
actual deaths
Expected deaths
(based on model)
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 3 of 4
Orange Base Hospital
Coffs Harbour Base Hospital
Tamworth Base Hospital
RSMR = 1.23Lismore Base Hospital
Port Macquarie Base Hospital
Maitland Hospital
Dubbo Base Hospital
Manning Base Hospital
Wagga Wagga Base Hospital
The Tweed Hospital
Shoalhaven and District Memorial Hospital
0 10 20 30 40 50
Deaths
0.0
0.5
1.0
1.5
2.0
2.5
3.0
Ris
k s
tand
ard
ised
mo
rtalit
y r
atio
(R
SM
R)
0 20 40 60 80 100
Expected number of deaths within 30 days
Lismore Base Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for hip fracture surgery
Lis
mo
re B
ase H
osp
ital
Hip
fra
ctu
re s
urg
ery
Illustrating the effect of standardisation, July 2009 - June 2012
In order to make fair comparisons, a number of risk adjustments are made to mortality data. These take into account
patient level factors that influence the likelihood of dying. The table below illustrates the cumulative effect of the statistical
adjustments. For each ratio, hospitals are compared to the average NSW result, given their case mix.
Lower mortality No difference Higher mortality
Time series risk-standardised mortality ratio, July 2000 - June 20126
Lower mortality No difference Higher mortality
Year (financial years)
Risk-standardised mortality ratio
(1) Index cases refer to patients discharged between July 2009 and June 2012 who were initially admitted to this hospital
(regardless of whether they were subsequently transferred) in their last period of care.
(2) Age at admission date.
(3) Only those conditions that were shown to have a significant impact on mortality (P<0.05) are shown. Many are a result of
end-organ damage resulting from comorbidities, such as diabetes. A broader set of comorbidities was screened for potential
impacts on mortality. Comorbidities as recorded on patient record, with one year look back. STEMI refers to ST-elevation
myocardial infarction.
(4) Deaths are from any cause, in or out of hospital within 30 days of the index hospitalisation admission date.
(5) Kaplan-Meier survival curve for 30-day following admission for haemorrhagic stroke, adjusted for average age and average
Charlson comorbidity score. Survival curves depict the proportion of patients who were alive, day 0 – day 30.
(6) To make RSMRs comparable over time, a reference population is required. Time series RSMRs for each hospital are based
on the reference years (July 2009 - June 2012). Control limits are based on the NSW average within each period.
( ) Data for hospitals with an expected mortality of <1 are suppressed.
( ) Between 90% and 95% upper control limits; ( ) Outside 95% upper control limits.
( ) Between 90% and 95% lower control limits; ( ) Outside 95% lower control limits.
Details of analyses and risk adjustment are available in Spotlight on Measurement: risk-standardised mortality ratios
Data source: SAPHaRI, Centre for Epidemiology and Evidence, NSW Ministry of Health.
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 4 of 4
Unadjusted ratio Age and sex standardised ratio Risk-standardised mortality ratio
1.05 1.04 1.23
2000-02 2003-05 2006-08 2009-11
1.05 1.66 1.00 1.23
Maclean District Hospital summary dashboard, July 2009 - June 2012
30-day mortality following hospitalisation for five conditions
Macle
an D
istr
ict
Ho
sp
ital
Dashb
oard
Hospital-specific risk-standardised mortality ratios (RSMRs) report the ratio of actual or ‘observed’ number of deaths
to the ‘expected’ number of deaths. A hierarchical logistic regression model draws on the NSW patient population’s
characteristics and outcomes to estimate the expected number of deaths for each hospital, given its case mix.
A ratio less than 1.0 indicates lower-than-expected mortality, and a ratio higher than 1.0 indicates higher-than-expected
mortality. Small deviations from 1.0 are not considered to be meaningful. Funnel plots with 90% and 95% control limits
around the NSW rate are used to identify hospitals with higher and lower mortality.
This measure is not designed to compare hospitals and cannot be used to measure the number of avoidable deaths.
RSMRs do not distinguish deaths that are avoidable from those that are a reflection of the natural course of illness.
They do not provide, by themselves, a diagnostic of quality and safety of care.
Risk-standardised mortality ratios (RSMRs) for five conditions, dashboard
Lower mortality No difference Higher mortality Range within 90% control limits
RSMR July 2009 to June 2012
NSW
RSMRs for three-year periods
How to interpret the dashboard
NSW average for index cases
mortality is lower than expected mortality is higher than expected
The length of the bar for each condition reflects the tolerance
for variation around the NSW average. It is wider for hospitals
admitting a small number of patients.
If a hospital's RSMR lies on the grey bar, its mortality is within the range of
values expected for an average NSW hospital of similar size.
( ) Data for hospitals with an expected mortality of <1 are suppressed.
( ) Between 90% and 95% upper control limits; ( ) Outside 95% upper control limits.
( ) Between 90% and 95% lower control limits; ( ) Outside 95% lower control limits.
Notes: RSMR data are for patients with a hospitalisation noting the relevant condition as principal diagnosis.
Patients include those discharged between July 2009 and June 2012 who were initially admitted to this hospital
(regardless of whether they were subsequently transferred) in their last period of care. Deaths are from any cause,
in or out of hospital within 30 days of the hospitalisation admission date.
Details of analyses and risk adjustment are available in Spotlight on Measurement: risk-standardised mortality ratios
for five conditions.
Data source: SAPHaRI, Centre for Epidemiology and Evidence, NSW Ministry of Health.
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au
Acute myocardial infarction (AMI) 100 patients
Ischaemic stroke < 50 patients
Haemorrhagic stroke < 50 patients
Pneumonia 130 patients
Hip fracture < 50 patients
2000-02 2003-05 2006-08 2009-11
Maclean District Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for Acute Myocardial Infarction (AMI)
Macle
an D
istr
ict
Ho
sp
ital
Acute
Myo
card
ial In
farc
tio
n (A
MI)
Total Acute Myocardial Infarction (AMI) hospitalisations
Acute Myocardial Infarction (AMI) patients
Presenting patients (index cases)1
Patients not transferred to another hospital
Patients transferred out to another hospital
This hospital NSW
Age profile, index cases 2
Maclean District Hospital
NSW
% of index cases
Significant patient factors and comorbidities, index cases3
Maclean District Hospital NSW
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 1 of 4
120
100
30
70
37,794
29,223
18,303
10,920
15-55 56-65 66-74 75-82 83+
5 19 26 24 26
19 21 20 19 21
0 10 20 30 40 50 60 70 80 90 100
50Hypertension
26STEMI
28Dysrhythmia
17Congestive heart failure
11Renal failure
12Hypotension
3Dementia
5Cerebrovascular disease
4Malignancy (cancer)
2Shock
0Alzheimer's disease
58
32
21
17
13
11
3
3
3
2
1
0 10 20 30 40 50 60 70 80 90 100
% of index cases with factor recorded
Maclean District Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for Acute Myocardial Infarction (AMI)
Macle
an D
istr
ict
Ho
sp
ital
Acute
Myo
card
ial In
farc
tio
n (A
MI)
Percentages: index cases who died within 30 days of hospitalisation
Of all deaths:
percentage in this hospital
percentage in another hospital following transfer
percentage after discharge
percentage on day of admission
percentage within 7 days
This hospital
percentage
NSW
percentage
Survival of index cases following hospitalisation for Acute Myocardial Infarction (AMI)5
Adjusted for average age and Charlson comorbidity score
Maclean District Hospital
% S
urv
ival
Days since admission
NSW
% S
urv
ival
Days since admission
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 2 of 4
Mortality (all causes) among 100 Acute Myocardial Infarction (AMI) index cases4
10%
50%
0%
50%
10%
80%
(64%)
(6%)
(31%)
(14%)
(61%)
0
90
95
100
0 10 20 30
0
90
95
100
0 10 20 30
Maclean District Hospital profile July 2009 - June 2012
Hospital-level Acute Myocardial Infarction (AMI) risk-standardised mortality ratio by number
of expected deaths, NSW public hospitals
Macle
an D
istr
ict
Ho
sp
ital
Acute
Myo
card
ial In
farc
tio
n (A
MI)
Maclean District Hospital NSW hospitals 90% limits 95% limits
Hospital-specific RSMRs report the ratio of actual or ‘observed’ number of deaths to the ‘expected’ number
of deaths. A hierarchical logistic regression model draws on the NSW patient population’s characteristics and
outcomes to estimate the expected number of deaths for each hospital, given the characteristics of its patients.
Actual and expected deaths, compared to local peers
This hospital,
actual deaths
Peer group hospitals,
actual deaths
Expected deaths
(based on model)
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 3 of 4
Kempsey Hospital
RSMR = 1.21Maclean District Hospital
Lithgow Health Service
Moruya District Hospital
Milton and Ulladulla Hospital
Blue Mountains District Anzac Memorial Hospital
Ballina District Hospital
Casino and District Memorial Hospital
Bateman's Bay District Hospital
0 5 10 15 20 25
Deaths
0
1
2
3
4
5
Ris
k s
tand
ard
ised
mo
rtalit
y r
atio
(R
SM
R)
0 50 100 150
Expected number of deaths within 30 days
Maclean District Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for Acute Myocardial Infarction (AMI)
Macle
an D
istr
ict
Ho
sp
ital
Acute
Myo
card
ial In
farc
tio
n (A
MI)
Illustrating the effect of standardisation, July 2009 - June 2012
In order to make fair comparisons, a number of risk adjustments are made to mortality data. These take into account
patient level factors that influence the likelihood of dying. The table below illustrates the cumulative effect of the statistical
adjustments. For each ratio, hospitals are compared to the average NSW result, given their case mix.
Lower mortality No difference Higher mortality
Time series risk-standardised mortality ratio, July 2000 - June 20126
Lower mortality No difference Higher mortality
Year (financial years)
Risk-standardised mortality ratio
(1) Index cases refer to patients discharged between July 2009 and June 2012 who were initially admitted to this hospital
(regardless of whether they were subsequently transferred) in their last period of care.
(2) Age at admission date.
(3) Only those conditions that were shown to have a significant impact on mortality (P<0.05) are shown. Many are a result of
end-organ damage resulting from comorbidities, such as diabetes. A broader set of comorbidities was screened for potential
impacts on mortality. Comorbidities as recorded on patient record, with one year look back. STEMI refers to ST-elevation
myocardial infarction.
(4) Deaths are from any cause, in or out of hospital within 30 days of the index hospitalisation admission date.
(5) Kaplan-Meier survival curve for 30-day following admission for haemorrhagic stroke, adjusted for average age and average
Charlson comorbidity score. Survival curves depict the proportion of patients who were alive, day 0 – day 30.
(6) To make RSMRs comparable over time, a reference population is required. Time series RSMRs for each hospital are based
on the reference years (July 2009 - June 2012). Control limits are based on the NSW average within each period.
( ) Data for hospitals with an expected mortality of <1 are suppressed.
( ) Between 90% and 95% upper control limits; ( ) Outside 95% upper control limits.
( ) Between 90% and 95% lower control limits; ( ) Outside 95% lower control limits.
Details of analyses and risk adjustment are available in Spotlight on Measurement: risk-standardised mortality ratios
Data source: SAPHaRI, Centre for Epidemiology and Evidence, NSW Ministry of Health.
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 4 of 4
Unadjusted ratio Age and sex standardised ratio Risk-standardised mortality ratio
1.32 1.14 1.21
2000-02 2003-05 2006-08 2009-11
1.14 1.75 0.95 1.21
Maclean District Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for pneumonia
Macle
an D
istr
ict
Ho
sp
ital
Pneum
onia
Total pneumonia hospitalisations
Pneumonia patients
Presenting patients (index cases)1
Patients not transferred to another hospital
Patients transferred out to another hospital
This hospital NSW
Age profile, index cases 2
Maclean District Hospital
NSW
% of index cases
Significant patient factors and comorbidities, index cases3
Maclean District Hospital NSW
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 1 of 4
142
130
101
29
50,644
44,059
39,655
4,404
18-51 52-67 68-77 78-85 86+
13 25 21 28 12
20 20 19 22 19
0 10 20 30 40 50 60 70 80 90 100
15Dysrhythmia
23Chronic obstructive pulmonary disease
12Renal failure
17Congestive heart failure
8Hypotension
11Malignancy (cancer)
8Dementia
4Cerebrovascular disease
2Liver disease
1Shock
0Alzheimer's disease
2Parkinson's disease
17
16
16
15
12
9
7
3
2
2
1
1
0 10 20 30 40 50 60 70 80 90 100
% of index cases with factor recorded
Maclean District Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for pneumonia
Macle
an D
istr
ict
Ho
sp
ital
Pneum
onia
Percentages: index cases who died within 30 days of hospitalisation
Of all deaths:
percentage in this hospital
percentage in another hospital following transfer
percentage after discharge
percentage on day of admission
percentage within 7 days
This hospital
percentage
NSW
percentage
Survival of index cases following hospitalisation for pneumonia5
Adjusted for average age and Charlson comorbidity score
Maclean District Hospital
% S
urv
ival
Days since admission
NSW
% S
urv
ival
Days since admission
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 2 of 4
Mortality (all causes) among 130 pneumonia index cases4
15%
25%
10%
65%
10%
60%
(66%)
(3%)
(31%)
(6%)
(54%)
0
75
80
85
90
95
100
0 10 20 30
0
75
80
85
90
95
100
0 10 20 30
Maclean District Hospital profile July 2009 - June 2012
Hospital-level pneumonia risk-standardised mortality ratio by number
of expected deaths, NSW public hospitals
Macle
an D
istr
ict
Ho
sp
ital
Pneum
onia
Maclean District Hospital NSW hospitals 90% limits 95% limits
Hospital-specific RSMRs report the ratio of actual or ‘observed’ number of deaths to the ‘expected’ number
of deaths. A hierarchical logistic regression model draws on the NSW patient population’s characteristics and
outcomes to estimate the expected number of deaths for each hospital, given the characteristics of its patients.
Actual and expected deaths, compared to local peers
This hospital,
actual deaths
Peer group hospitals,
actual deaths
Expected deaths
(based on model)
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 3 of 4
Blue Mountains District Anzac Memorial Hospital
Bateman's Bay District Hospital
Kempsey Hospital
Queanbeyan Health Service
RSMR = 1.33Maclean District Hospital
Ballina District Hospital
Moruya District Hospital
Macksville District Hospital
Lithgow Health Service
Casino and District Memorial Hospital
Milton and Ulladulla Hospital
Cooma Health Service
0 10 20 30 40 50
Deaths
0
1
2
3
Ris
k s
tand
ard
ised
mo
rtalit
y r
atio
(R
SM
R)
0 50 100 150 200
Expected number of deaths within 30 days
Maclean District Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for pneumonia
Macle
an D
istr
ict
Ho
sp
ital
Pneum
onia
Illustrating the effect of standardisation, July 2009 - June 2012
In order to make fair comparisons, a number of risk adjustments are made to mortality data. These take into account
patient level factors that influence the likelihood of dying. The table below illustrates the cumulative effect of the statistical
adjustments. For each ratio, hospitals are compared to the average NSW result, given their case mix.
Lower mortality No difference Higher mortality
Time series risk-standardised mortality ratio, July 2000 - June 20126
Lower mortality No difference Higher mortality
Year (financial years)
Risk-standardised mortality ratio
(1) Index cases refer to patients discharged between July 2009 and June 2012 who were initially admitted to this hospital
(regardless of whether they were subsequently transferred) in their last period of care.
(2) Age at admission date.
(3) Only those conditions that were shown to have a significant impact on mortality (P<0.05) are shown. Many are a result of
end-organ damage resulting from comorbidities, such as diabetes. A broader set of comorbidities was screened for potential
impacts on mortality. Comorbidities as recorded on patient record, with one year look back. STEMI refers to ST-elevation
myocardial infarction.
(4) Deaths are from any cause, in or out of hospital within 30 days of the index hospitalisation admission date.
(5) Kaplan-Meier survival curve for 30-day following admission for haemorrhagic stroke, adjusted for average age and average
Charlson comorbidity score. Survival curves depict the proportion of patients who were alive, day 0 – day 30.
(6) To make RSMRs comparable over time, a reference population is required. Time series RSMRs for each hospital are based
on the reference years (July 2009 - June 2012). Control limits are based on the NSW average within each period.
( ) Data for hospitals with an expected mortality of <1 are suppressed.
( ) Between 90% and 95% upper control limits; ( ) Outside 95% upper control limits.
( ) Between 90% and 95% lower control limits; ( ) Outside 95% lower control limits.
Details of analyses and risk adjustment are available in Spotlight on Measurement: risk-standardised mortality ratios
Data source: SAPHaRI, Centre for Epidemiology and Evidence, NSW Ministry of Health.
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 4 of 4
Unadjusted ratio Age and sex standardised ratio Risk-standardised mortality ratio
1.43 1.48 1.33
2000-02 2003-05 2006-08 2009-12
1.42 1.35 0.92 1.33
Murwillumbah District Hospital summary dashboard, July 2009 - June 2012
30-day mortality following hospitalisation for five conditions
Murw
illum
bah D
istr
ict
Ho
sp
ital
Dashb
oard
Hospital-specific risk-standardised mortality ratios (RSMRs) report the ratio of actual or ‘observed’ number of deaths
to the ‘expected’ number of deaths. A hierarchical logistic regression model draws on the NSW patient population’s
characteristics and outcomes to estimate the expected number of deaths for each hospital, given its case mix.
A ratio less than 1.0 indicates lower-than-expected mortality, and a ratio higher than 1.0 indicates higher-than-expected
mortality. Small deviations from 1.0 are not considered to be meaningful. Funnel plots with 90% and 95% control limits
around the NSW rate are used to identify hospitals with higher and lower mortality.
This measure is not designed to compare hospitals and cannot be used to measure the number of avoidable deaths.
RSMRs do not distinguish deaths that are avoidable from those that are a reflection of the natural course of illness.
They do not provide, by themselves, a diagnostic of quality and safety of care.
Risk-standardised mortality ratios (RSMRs) for five conditions, dashboard
Lower mortality No difference Higher mortality Range within 90% control limits
RSMR July 2009 to June 2012
NSW
RSMRs for three-year periods
How to interpret the dashboard
NSW average for index cases
mortality is lower than expected mortality is higher than expected
The length of the bar for each condition reflects the tolerance
for variation around the NSW average. It is wider for hospitals
admitting a small number of patients.
If a hospital's RSMR lies on the grey bar, its mortality is within the range of
values expected for an average NSW hospital of similar size.
( ) Data for hospitals with an expected mortality of <1 are suppressed.
( ) Between 90% and 95% upper control limits; ( ) Outside 95% upper control limits.
( ) Between 90% and 95% lower control limits; ( ) Outside 95% lower control limits.
Notes: RSMR data are for patients with a hospitalisation noting the relevant condition as principal diagnosis.
Patients include those discharged between July 2009 and June 2012 who were initially admitted to this hospital
(regardless of whether they were subsequently transferred) in their last period of care. Deaths are from any cause,
in or out of hospital within 30 days of the hospitalisation admission date.
Details of analyses and risk adjustment are available in Spotlight on Measurement: risk-standardised mortality ratios
for five conditions.
Data source: SAPHaRI, Centre for Epidemiology and Evidence, NSW Ministry of Health.
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au
Acute myocardial infarction (AMI) 65 patients
Ischaemic stroke < 50 patients
Haemorrhagic stroke < 50 patients
Pneumonia 217 patients
Hip fracture < 50 patients
2000-02 2003-05 2006-08 2009-11
Murwillumbah District Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for Acute Myocardial Infarction (AMI)
Murw
illum
bah D
istr
ict
Ho
sp
ital
Acute
Myo
card
ial In
farc
tio
n (A
MI)
Total Acute Myocardial Infarction (AMI) hospitalisations
Acute Myocardial Infarction (AMI) patients
Presenting patients (index cases)1
Patients not transferred to another hospital
Patients transferred out to another hospital
This hospital NSW
Age profile, index cases 2
Murwillumbah District Hospital
NSW
% of index cases
Significant patient factors and comorbidities, index cases3
Murwillumbah District Hospital NSW
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 1 of 4
76
65
12
53
37,794
29,223
18,303
10,920
15-55 56-65 66-74 75-82 83+
25 23 15 17 20
19 21 20 19 21
0 10 20 30 40 50 60 70 80 90 100
45Hypertension
48STEMI
15Dysrhythmia
9Congestive heart failure
8Renal failure
12Hypotension
5Dementia
3Cerebrovascular disease
2Malignancy (cancer)
2Shock
0Alzheimer's disease
58
32
21
17
13
11
3
3
3
2
1
0 10 20 30 40 50 60 70 80 90 100
% of index cases with factor recorded
Murwillumbah District Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for Acute Myocardial Infarction (AMI)
Murw
illum
bah D
istr
ict
Ho
sp
ital
Acute
Myo
card
ial In
farc
tio
n (A
MI)
Percentages: index cases who died within 30 days of hospitalisation
Of all deaths:
percentage in this hospital
percentage in another hospital following transfer
percentage after discharge
percentage on day of admission
percentage within 7 days
This hospital
percentage
NSW
percentage
Survival of index cases following hospitalisation for Acute Myocardial Infarction (AMI)5
Adjusted for average age and Charlson comorbidity score
Murwillumbah District Hospital
% S
urv
ival
Days since admission
NSW
% S
urv
ival
Days since admission
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 2 of 4
Mortality (all causes) among 65 Acute Myocardial Infarction (AMI) index cases4
8%
20%
40%
40%
20%
80%
(64%)
(6%)
(31%)
(14%)
(61%)
0
90
95
100
0 10 20 30
0
90
95
100
0 10 20 30
Murwillumbah District Hospital profile July 2009 - June 2012
Hospital-level Acute Myocardial Infarction (AMI) risk-standardised mortality ratio by number
of expected deaths, NSW public hospitals
Murw
illum
bah D
istr
ict
Ho
sp
ital
Acute
Myo
card
ial In
farc
tio
n (A
MI)
Murwillumbah District Hospital NSW hospitals 90% limits 95% limits
Hospital-specific RSMRs report the ratio of actual or ‘observed’ number of deaths to the ‘expected’ number
of deaths. A hierarchical logistic regression model draws on the NSW patient population’s characteristics and
outcomes to estimate the expected number of deaths for each hospital, given the characteristics of its patients.
Actual and expected deaths, compared to local peers
This hospital,
actual deaths
Peer group hospitals,
actual deaths
Expected deaths
(based on model)
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 3 of 4
Shellharbour Hospital
Mount Druitt Hospital
Belmont Hospital
Ryde Hospital
Bowral and District Hospital
Grafton Base Hospital
Bathurst Base Hospital
Goulburn Base Hospital
Broken Hill Base Hospital
Griffith Base Hospital
Hawkesbury District Health Service
Bega District Hospital
RSMR = 1.14Murwillumbah District Hospital
Armidale and New England Hospital
0 10 20 30 40 50
Deaths
0
1
2
3
4
5
Ris
k s
tand
ard
ised
mo
rtalit
y r
atio
(R
SM
R)
0 50 100 150
Expected number of deaths within 30 days
Murwillumbah District Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for Acute Myocardial Infarction (AMI)
Murw
illum
bah D
istr
ict
Ho
sp
ital
Acute
Myo
card
ial In
farc
tio
n (A
MI)
Illustrating the effect of standardisation, July 2009 - June 2012
In order to make fair comparisons, a number of risk adjustments are made to mortality data. These take into account
patient level factors that influence the likelihood of dying. The table below illustrates the cumulative effect of the statistical
adjustments. For each ratio, hospitals are compared to the average NSW result, given their case mix.
Lower mortality No difference Higher mortality
Time series risk-standardised mortality ratio, July 2000 - June 20126
Lower mortality No difference Higher mortality
Year (financial years)
Risk-standardised mortality ratio
(1) Index cases refer to patients discharged between July 2009 and June 2012 who were initially admitted to this hospital
(regardless of whether they were subsequently transferred) in their last period of care.
(2) Age at admission date.
(3) Only those conditions that were shown to have a significant impact on mortality (P<0.05) are shown. Many are a result of
end-organ damage resulting from comorbidities, such as diabetes. A broader set of comorbidities was screened for potential
impacts on mortality. Comorbidities as recorded on patient record, with one year look back. STEMI refers to ST-elevation
myocardial infarction.
(4) Deaths are from any cause, in or out of hospital within 30 days of the index hospitalisation admission date.
(5) Kaplan-Meier survival curve for 30-day following admission for haemorrhagic stroke, adjusted for average age and average
Charlson comorbidity score. Survival curves depict the proportion of patients who were alive, day 0 – day 30.
(6) To make RSMRs comparable over time, a reference population is required. Time series RSMRs for each hospital are based
on the reference years (July 2009 - June 2012). Control limits are based on the NSW average within each period.
( ) Data for hospitals with an expected mortality of <1 are suppressed.
( ) Between 90% and 95% upper control limits; ( ) Outside 95% upper control limits.
( ) Between 90% and 95% lower control limits; ( ) Outside 95% lower control limits.
Details of analyses and risk adjustment are available in Spotlight on Measurement: risk-standardised mortality ratios
Data source: SAPHaRI, Centre for Epidemiology and Evidence, NSW Ministry of Health.
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 4 of 4
Unadjusted ratio Age and sex standardised ratio Risk-standardised mortality ratio
1.02 1.08 1.14
2000-02 2003-05 2006-08 2009-11
0.45 0.78 0.90 1.14
Murwillumbah District Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for pneumonia
Murw
illum
bah D
istr
ict
Ho
sp
ital
Pneum
onia
Total pneumonia hospitalisations
Pneumonia patients
Presenting patients (index cases)1
Patients not transferred to another hospital
Patients transferred out to another hospital
This hospital NSW
Age profile, index cases 2
Murwillumbah District Hospital
NSW
% of index cases
Significant patient factors and comorbidities, index cases3
Murwillumbah District Hospital NSW
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 1 of 4
245
217
193
24
50,644
44,059
39,655
4,404
18-51 52-67 68-77 78-85 86+
24 24 13 20 19
20 20 19 22 19
0 10 20 30 40 50 60 70 80 90 100
15Dysrhythmia
15Chronic obstructive pulmonary disease
5Renal failure
16Congestive heart failure
10Hypotension
4Malignancy (cancer)
7Dementia
2Cerebrovascular disease
0Liver disease
1Shock
2Alzheimer's disease
1Parkinson's disease
17
16
16
15
12
9
7
3
2
2
1
1
0 10 20 30 40 50 60 70 80 90 100
% of index cases with factor recorded
Murwillumbah District Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for pneumonia
Murw
illum
bah D
istr
ict
Ho
sp
ital
Pneum
onia
Percentages: index cases who died within 30 days of hospitalisation
Of all deaths:
percentage in this hospital
percentage in another hospital following transfer
percentage after discharge
percentage on day of admission
percentage within 7 days
This hospital
percentage
NSW
percentage
Survival of index cases following hospitalisation for pneumonia5
Adjusted for average age and Charlson comorbidity score
Murwillumbah District Hospital
% S
urv
ival
Days since admission
NSW
% S
urv
ival
Days since admission
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 2 of 4
Mortality (all causes) among 217 pneumonia index cases4
10%
68%
9%
23%
0%
68%
(66%)
(3%)
(31%)
(6%)
(54%)
0
75
80
85
90
95
100
0 10 20 30
0
75
80
85
90
95
100
0 10 20 30
Murwillumbah District Hospital profile July 2009 - June 2012
Hospital-level pneumonia risk-standardised mortality ratio by number
of expected deaths, NSW public hospitals
Murw
illum
bah D
istr
ict
Ho
sp
ital
Pneum
onia
Murwillumbah District Hospital NSW hospitals 90% limits 95% limits
Hospital-specific RSMRs report the ratio of actual or ‘observed’ number of deaths to the ‘expected’ number
of deaths. A hierarchical logistic regression model draws on the NSW patient population’s characteristics and
outcomes to estimate the expected number of deaths for each hospital, given the characteristics of its patients.
Actual and expected deaths, compared to local peers
This hospital,
actual deaths
Peer group hospitals,
actual deaths
Expected deaths
(based on model)
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 3 of 4
Ryde Hospital
Hawkesbury District Health Service
Bowral and District Hospital
Belmont Hospital
Goulburn Base Hospital
Mount Druitt Hospital
Shellharbour Hospital
Bathurst Base Hospital
Grafton Base Hospital
Griffith Base Hospital
RSMR = 1.13Murwillumbah District Hospital
Bega District Hospital
Armidale and New England Hospital
Broken Hill Base Hospital
0 20 40 60 80 100
Deaths
0
1
2
3
Ris
k s
tand
ard
ised
mo
rtalit
y r
atio
(R
SM
R)
0 50 100 150 200
Expected number of deaths within 30 days
Murwillumbah District Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for pneumonia
Murw
illum
bah D
istr
ict
Ho
sp
ital
Pneum
onia
Illustrating the effect of standardisation, July 2009 - June 2012
In order to make fair comparisons, a number of risk adjustments are made to mortality data. These take into account
patient level factors that influence the likelihood of dying. The table below illustrates the cumulative effect of the statistical
adjustments. For each ratio, hospitals are compared to the average NSW result, given their case mix.
Lower mortality No difference Higher mortality
Time series risk-standardised mortality ratio, July 2000 - June 20126
Lower mortality No difference Higher mortality
Year (financial years)
Risk-standardised mortality ratio
(1) Index cases refer to patients discharged between July 2009 and June 2012 who were initially admitted to this hospital
(regardless of whether they were subsequently transferred) in their last period of care.
(2) Age at admission date.
(3) Only those conditions that were shown to have a significant impact on mortality (P<0.05) are shown. Many are a result of
end-organ damage resulting from comorbidities, such as diabetes. A broader set of comorbidities was screened for potential
impacts on mortality. Comorbidities as recorded on patient record, with one year look back. STEMI refers to ST-elevation
myocardial infarction.
(4) Deaths are from any cause, in or out of hospital within 30 days of the index hospitalisation admission date.
(5) Kaplan-Meier survival curve for 30-day following admission for haemorrhagic stroke, adjusted for average age and average
Charlson comorbidity score. Survival curves depict the proportion of patients who were alive, day 0 – day 30.
(6) To make RSMRs comparable over time, a reference population is required. Time series RSMRs for each hospital are based
on the reference years (July 2009 - June 2012). Control limits are based on the NSW average within each period.
( ) Data for hospitals with an expected mortality of <1 are suppressed.
( ) Between 90% and 95% upper control limits; ( ) Outside 95% upper control limits.
( ) Between 90% and 95% lower control limits; ( ) Outside 95% lower control limits.
Details of analyses and risk adjustment are available in Spotlight on Measurement: risk-standardised mortality ratios
Data source: SAPHaRI, Centre for Epidemiology and Evidence, NSW Ministry of Health.
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 4 of 4
Unadjusted ratio Age and sex standardised ratio Risk-standardised mortality ratio
0.94 1.04 1.13
2000-02 2003-05 2006-08 2009-12
0.84 1.14 0.78 1.13
The Tweed Hospital summary dashboard, July 2009 - June 2012
30-day mortality following hospitalisation for five conditions
The T
weed
Ho
sp
ital
Dashb
oard
Hospital-specific risk-standardised mortality ratios (RSMRs) report the ratio of actual or ‘observed’ number of deaths
to the ‘expected’ number of deaths. A hierarchical logistic regression model draws on the NSW patient population’s
characteristics and outcomes to estimate the expected number of deaths for each hospital, given its case mix.
A ratio less than 1.0 indicates lower-than-expected mortality, and a ratio higher than 1.0 indicates higher-than-expected
mortality. Small deviations from 1.0 are not considered to be meaningful. Funnel plots with 90% and 95% control limits
around the NSW rate are used to identify hospitals with higher and lower mortality.
This measure is not designed to compare hospitals and cannot be used to measure the number of avoidable deaths.
RSMRs do not distinguish deaths that are avoidable from those that are a reflection of the natural course of illness.
They do not provide, by themselves, a diagnostic of quality and safety of care.
Risk-standardised mortality ratios (RSMRs) for five conditions, dashboard
Lower mortality No difference Higher mortality Range within 90% control limits
RSMR July 2009 to June 2012
NSW
RSMRs for three-year periods
How to interpret the dashboard
NSW average for index cases
mortality is lower than expected mortality is higher than expected
The length of the bar for each condition reflects the tolerance
for variation around the NSW average. It is wider for hospitals
admitting a small number of patients.
If a hospital's RSMR lies on the grey bar, its mortality is within the range of
values expected for an average NSW hospital of similar size.
( ) Data for hospitals with an expected mortality of <1 are suppressed.
( ) Between 90% and 95% upper control limits; ( ) Outside 95% upper control limits.
( ) Between 90% and 95% lower control limits; ( ) Outside 95% lower control limits.
Notes: RSMR data are for patients with a hospitalisation noting the relevant condition as principal diagnosis.
Patients include those discharged between July 2009 and June 2012 who were initially admitted to this hospital
(regardless of whether they were subsequently transferred) in their last period of care. Deaths are from any cause,
in or out of hospital within 30 days of the hospitalisation admission date.
Details of analyses and risk adjustment are available in Spotlight on Measurement: risk-standardised mortality ratios
for five conditions.
Data source: SAPHaRI, Centre for Epidemiology and Evidence, NSW Ministry of Health.
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au
Acute myocardial infarction (AMI) 584 patients
Ischaemic stroke 173 patients
Haemorrhagic stroke 91 patients
Pneumonia 714 patients
Hip fracture 353 patients
2000-02 2003-05 2006-08 2009-11
The Tweed Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for Acute Myocardial Infarction (AMI)
The T
weed
Ho
sp
ital
Acute
Myo
card
ial In
farc
tio
n (A
MI)
Total Acute Myocardial Infarction (AMI) hospitalisations
Acute Myocardial Infarction (AMI) patients
Presenting patients (index cases)1
Patients not transferred to another hospital
Patients transferred out to another hospital
This hospital NSW
Age profile, index cases 2
The Tweed Hospital
NSW
% of index cases
Significant patient factors and comorbidities, index cases3
The Tweed Hospital NSW
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 1 of 4
711
584
399
185
37,794
29,223
18,303
10,920
15-55 56-65 66-74 75-82 83+
14 21 19 22 24
19 21 20 19 21
0 10 20 30 40 50 60 70 80 90 100
56Hypertension
30STEMI
21Dysrhythmia
18Congestive heart failure
9Renal failure
8Hypotension
4Dementia
2Cerebrovascular disease
3Malignancy (cancer)
2Shock
0Alzheimer's disease
58
32
21
17
13
11
3
3
3
2
1
0 10 20 30 40 50 60 70 80 90 100
% of index cases with factor recorded
The Tweed Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for Acute Myocardial Infarction (AMI)
The T
weed
Ho
sp
ital
Acute
Myo
card
ial In
farc
tio
n (A
MI)
Percentages: index cases who died within 30 days of hospitalisation
Of all deaths:
percentage in this hospital
percentage in another hospital following transfer
percentage after discharge
percentage on day of admission
percentage within 7 days
This hospital
percentage
NSW
percentage
Survival of index cases following hospitalisation for Acute Myocardial Infarction (AMI)5
Adjusted for average age and Charlson comorbidity score
The Tweed Hospital
% S
urv
ival
Days since admission
NSW
% S
urv
ival
Days since admission
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 2 of 4
Mortality (all causes) among 584 Acute Myocardial Infarction (AMI) index cases4
7%
72%
0%
28%
12%
74%
(64%)
(6%)
(31%)
(14%)
(61%)
0
90
95
100
0 10 20 30
0
90
95
100
0 10 20 30
The Tweed Hospital profile July 2009 - June 2012
Hospital-level Acute Myocardial Infarction (AMI) risk-standardised mortality ratio by number
of expected deaths, NSW public hospitals
The T
weed
Ho
sp
ital
Acute
Myo
card
ial In
farc
tio
n (A
MI)
The Tweed Hospital NSW hospitals 90% limits 95% limits
Hospital-specific RSMRs report the ratio of actual or ‘observed’ number of deaths to the ‘expected’ number
of deaths. A hierarchical logistic regression model draws on the NSW patient population’s characteristics and
outcomes to estimate the expected number of deaths for each hospital, given the characteristics of its patients.
Actual and expected deaths, compared to local peers
This hospital,
actual deaths
Peer group hospitals,
actual deaths
Expected deaths
(based on model)
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 3 of 4
Lismore Base Hospital
RSMR = 1.02The Tweed Hospital
Shoalhaven and District Memorial Hospital
Tamworth Base Hospital
Maitland Hospital
Port Macquarie Base Hospital
Dubbo Base Hospital
Manning Base Hospital
Coffs Harbour Base Hospital
Wagga Wagga Base Hospital
Orange Base Hospital
0 10 20 30 40 50
Deaths
0
1
2
3
4
5
Ris
k s
tand
ard
ised
mo
rtalit
y r
atio
(R
SM
R)
0 50 100 150
Expected number of deaths within 30 days
The Tweed Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for Acute Myocardial Infarction (AMI)
The T
weed
Ho
sp
ital
Acute
Myo
card
ial In
farc
tio
n (A
MI)
Illustrating the effect of standardisation, July 2009 - June 2012
In order to make fair comparisons, a number of risk adjustments are made to mortality data. These take into account
patient level factors that influence the likelihood of dying. The table below illustrates the cumulative effect of the statistical
adjustments. For each ratio, hospitals are compared to the average NSW result, given their case mix.
Lower mortality No difference Higher mortality
Time series risk-standardised mortality ratio, July 2000 - June 20126
Lower mortality No difference Higher mortality
Year (financial years)
Risk-standardised mortality ratio
(1) Index cases refer to patients discharged between July 2009 and June 2012 who were initially admitted to this hospital
(regardless of whether they were subsequently transferred) in their last period of care.
(2) Age at admission date.
(3) Only those conditions that were shown to have a significant impact on mortality (P<0.05) are shown. Many are a result of
end-organ damage resulting from comorbidities, such as diabetes. A broader set of comorbidities was screened for potential
impacts on mortality. Comorbidities as recorded on patient record, with one year look back. STEMI refers to ST-elevation
myocardial infarction.
(4) Deaths are from any cause, in or out of hospital within 30 days of the index hospitalisation admission date.
(5) Kaplan-Meier survival curve for 30-day following admission for haemorrhagic stroke, adjusted for average age and average
Charlson comorbidity score. Survival curves depict the proportion of patients who were alive, day 0 – day 30.
(6) To make RSMRs comparable over time, a reference population is required. Time series RSMRs for each hospital are based
on the reference years (July 2009 - June 2012). Control limits are based on the NSW average within each period.
( ) Data for hospitals with an expected mortality of <1 are suppressed.
( ) Between 90% and 95% upper control limits; ( ) Outside 95% upper control limits.
( ) Between 90% and 95% lower control limits; ( ) Outside 95% lower control limits.
Details of analyses and risk adjustment are available in Spotlight on Measurement: risk-standardised mortality ratios
Data source: SAPHaRI, Centre for Epidemiology and Evidence, NSW Ministry of Health.
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 4 of 4
Unadjusted ratio Age and sex standardised ratio Risk-standardised mortality ratio
0.98 0.93 1.02
2000-02 2003-05 2006-08 2009-11
0.72 0.81 0.74 1.02
The Tweed Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for ischaemic stroke
The T
weed
Ho
sp
ital
Ischaem
ic s
tro
ke
Total ischaemic stroke hospitalisations
Ischaemic stroke patients
Presenting patients (index cases)1
Patients not transferred to another hospital
Patients transferred out to another hospital
This hospital NSW
Age profile, index cases 2
The Tweed Hospital
NSW
% of index cases
Significant patient factors and comorbidities, index cases3
The Tweed Hospital NSW
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 1 of 4
184
173
117
56
15,299
14,205
11,757
2,448
15-63 64-72 73-79 80-85 86+
19 21 24 20 17
20 18 20 21 21
0 10 20 30 40 50 60 70 80 90 100
42Female
3Renal failure
6Congestive heart failure
5Malignancy (cancer)
47
10
7
4
0 10 20 30 40 50 60 70 80 90 100
% of index cases with factor recorded
The Tweed Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for ischaemic stroke
The T
weed
Ho
sp
ital
Ischaem
ic s
tro
ke
Percentages: index cases who died within 30 days of hospitalisation
Of all deaths:
percentage in this hospital
percentage in another hospital following transfer
percentage after discharge
percentage on day of admission
percentage within 7 days
This hospital
percentage
NSW
percentage
Survival of index cases following hospitalisation for ischaemic stroke5
Adjusted for average age and Charlson comorbidity score
The Tweed Hospital
% S
urv
ival
Days since admission
NSW
% S
urv
ival
Days since admission
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 2 of 4
Mortality (all causes) among 173 ischaemic stroke index cases4
16%
67%
0%
33%
7%
56%
(67%)
(2%)
(31%)
(2%)
(51%)
0
80
85
90
95
100
0 10 20 30
0
80
85
90
95
100
0 10 20 30
The Tweed Hospital profile July 2009 - June 2012
Hospital-level ischaemic stroke risk-standardised mortality ratio by number
of expected deaths, NSW public hospitals
The T
weed
Ho
sp
ital
Ischaem
ic s
tro
ke
The Tweed Hospital NSW hospitals 90% limits 95% limits
Hospital-specific RSMRs report the ratio of actual or ‘observed’ number of deaths to the ‘expected’ number
of deaths. A hierarchical logistic regression model draws on the NSW patient population’s characteristics and
outcomes to estimate the expected number of deaths for each hospital, given the characteristics of its patients.
Actual and expected deaths, compared to local peers
This hospital,
actual deaths
Peer group hospitals,
actual deaths
Expected deaths
(based on model)
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 3 of 4
Dubbo Base Hospital
Coffs Harbour Base Hospital
Shoalhaven and District Memorial Hospital
Port Macquarie Base Hospital
Tamworth Base Hospital
Lismore Base Hospital
Manning Base Hospital
RSMR = 1.32The Tweed Hospital
Wagga Wagga Base Hospital
Orange Base Hospital
Maitland Hospital
0 10 20 30 40 50
Deaths
0
1
2
3
Ris
k s
tand
ard
ised
mo
rtalit
y r
atio
(R
SM
R)
0 25 50 75 100 125
Expected number of deaths within 30 days
The Tweed Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for ischaemic stroke
The T
weed
Ho
sp
ital
Ischaem
ic s
tro
ke
Illustrating the effect of standardisation, July 2009 - June 2012
In order to make fair comparisons, a number of risk adjustments are made to mortality data. These take into account
patient level factors that influence the likelihood of dying. The table below illustrates the cumulative effect of the statistical
adjustments. For each ratio, hospitals are compared to the average NSW result, given their case mix.
Lower mortality No difference Higher mortality
Time series risk-standardised mortality ratio, July 2000 - June 20126
Lower mortality No difference Higher mortality
Year (financial years)
Risk-standardised mortality ratio
(1) Index cases refer to patients discharged between July 2009 and June 2012 who were initially admitted to this hospital
(regardless of whether they were subsequently transferred) in their last period of care.
(2) Age at admission date.
(3) Only those conditions that were shown to have a significant impact on mortality (P<0.05) are shown. Many are a result of
end-organ damage resulting from comorbidities, such as diabetes. A broader set of comorbidities was screened for potential
impacts on mortality. Comorbidities as recorded on patient record, with one year look back. STEMI refers to ST-elevation
myocardial infarction.
(4) Deaths are from any cause, in or out of hospital within 30 days of the index hospitalisation admission date.
(5) Kaplan-Meier survival curve for 30-day following admission for haemorrhagic stroke, adjusted for average age and average
Charlson comorbidity score. Survival curves depict the proportion of patients who were alive, day 0 – day 30.
(6) To make RSMRs comparable over time, a reference population is required. Time series RSMRs for each hospital are based
on the reference years (July 2009 - June 2012). Control limits are based on the NSW average within each period.
( ) Data for hospitals with an expected mortality of <1 are suppressed.
( ) Between 90% and 95% upper control limits; ( ) Outside 95% upper control limits.
( ) Between 90% and 95% lower control limits; ( ) Outside 95% lower control limits.
Details of analyses and risk adjustment are available in Spotlight on Measurement: risk-standardised mortality ratios
Data source: SAPHaRI, Centre for Epidemiology and Evidence, NSW Ministry of Health.
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 4 of 4
Unadjusted ratio Age and sex standardised ratio Risk-standardised mortality ratio
1.17 1.26 1.32
2000-02 2003-05 2006-08 2009-11
2.26 1.41 1.23 1.32
The Tweed Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for haemorrhagic stroke
The T
weed
Ho
sp
ital
Haem
orr
hag
ic s
tro
ke
Total haemorrhagic stroke hospitalisations
Haemorrhagic stroke patients
Presenting patients (index cases)1
Patients not transferred to another hospital
Patients transferred out to another hospital
This hospital NSW
Age profile, index cases 2
The Tweed Hospital
NSW
% of index cases
Significant patient factors and comorbidities, index cases3
The Tweed Hospital NSW
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 1 of 4
98
91
49
42
6,573
5,681
4,148
1,533
15-62 63-73 74-80 81-85 86+
16 18 23 25 18
20 21 21 19 19
0 10 20 30 40 50 60 70 80 90 100
42Female
8History of haemorrhagic stroke
3Malignancy (cancer)
2Congestive heart failure
46
8
6
6
0 10 20 30 40 50 60 70 80 90 100
% of index cases with factor recorded
The Tweed Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for haemorrhagic stroke
The T
weed
Ho
sp
ital
Haem
orr
hag
ic s
tro
ke
Percentages: index cases who died within 30 days of hospitalisation
Of all deaths:
percentage in this hospital
percentage in another hospital following transfer
percentage after discharge
percentage on day of admission
percentage within 7 days
This hospital
percentage
NSW
percentage
Survival of index cases following hospitalisation for haemorrhagic stroke5
Adjusted for average age and Charlson comorbidity score
The Tweed Hospital
% S
urv
ival
Days since admission
NSW
% S
urv
ival
Days since admission
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 2 of 4
Mortality (all causes) among 91 haemorrhagic stroke index cases4
33%
80%
0%
20%
20%
77%
(76%)
(3%)
(21%)
(20%)
(75%)
0
50
55
60
65
70
75
80
85
90
95
100
0 10 20 30
0
50
55
60
65
70
75
80
85
90
95
100
0 10 20 30
The Tweed Hospital profile July 2009 - June 2012
Hospital-level haemorrhagic stroke risk-standardised mortality ratio by number
of expected deaths, NSW public hospitals
The T
weed
Ho
sp
ital
Haem
orr
hag
ic s
tro
ke
The Tweed Hospital NSW hospitals 90% limits 95% limits
Hospital-specific RSMRs report the ratio of actual or ‘observed’ number of deaths to the ‘expected’ number
of deaths. A hierarchical logistic regression model draws on the NSW patient population’s characteristics and
outcomes to estimate the expected number of deaths for each hospital, given the characteristics of its patients.
Actual and expected deaths, compared to local peers
This hospital,
actual deaths
Peer group hospitals,
actual deaths
Expected deaths
(based on model)
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 3 of 4
Port Macquarie Base Hospital
Lismore Base Hospital
Coffs Harbour Base Hospital
Shoalhaven and District Memorial Hospital
RSMR = 0.98The Tweed Hospital
Orange Base Hospital
Manning Base Hospital
Tamworth Base Hospital
Wagga Wagga Base Hospital
Dubbo Base Hospital
0 10 20 30 40 50
Deaths
0.0
0.5
1.0
1.5
2.0
2.5
3.0
Ris
k s
tand
ard
ised
mo
rtalit
y r
atio
(R
SM
R)
0 25 50 75 100 125
Expected number of deaths within 30 days
The Tweed Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for haemorrhagic stroke
The T
weed
Ho
sp
ital
Haem
orr
hag
ic s
tro
ke
Illustrating the effect of standardisation, July 2009 - June 2012
In order to make fair comparisons, a number of risk adjustments are made to mortality data. These take into account
patient level factors that influence the likelihood of dying. The table below illustrates the cumulative effect of the statistical
adjustments. For each ratio, hospitals are compared to the average NSW result, given their case mix.
Lower mortality No difference Higher mortality
Time series risk-standardised mortality ratio, July 2000 - June 20126
Lower mortality No difference Higher mortality
Year (financial years)
Risk-standardised mortality ratio
(1) Index cases refer to patients discharged between July 2009 and June 2012 who were initially admitted to this hospital
(regardless of whether they were subsequently transferred) in their last period of care.
(2) Age at admission date.
(3) Only those conditions that were shown to have a significant impact on mortality (P<0.05) are shown. Many are a result of
end-organ damage resulting from comorbidities, such as diabetes. A broader set of comorbidities was screened for potential
impacts on mortality. Comorbidities as recorded on patient record, with one year look back. STEMI refers to ST-elevation
myocardial infarction.
(4) Deaths are from any cause, in or out of hospital within 30 days of the index hospitalisation admission date.
(5) Kaplan-Meier survival curve for 30-day following admission for haemorrhagic stroke, adjusted for average age and average
Charlson comorbidity score. Survival curves depict the proportion of patients who were alive, day 0 – day 30.
(6) To make RSMRs comparable over time, a reference population is required. Time series RSMRs for each hospital are based
on the reference years (July 2009 - June 2012). Control limits are based on the NSW average within each period.
( ) Data for hospitals with an expected mortality of <1 are suppressed.
( ) Between 90% and 95% upper control limits; ( ) Outside 95% upper control limits.
( ) Between 90% and 95% lower control limits; ( ) Outside 95% lower control limits.
Details of analyses and risk adjustment are available in Spotlight on Measurement: risk-standardised mortality ratios
Data source: SAPHaRI, Centre for Epidemiology and Evidence, NSW Ministry of Health.
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 4 of 4
Unadjusted ratio Age and sex standardised ratio Risk-standardised mortality ratio
0.97 0.96 0.99
2000-02 2003-05 2006-08 2009-11
0.96 0.73 1.21 0.99
The Tweed Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for pneumonia
The T
weed
Ho
sp
ital
Pneum
onia
Total pneumonia hospitalisations
Pneumonia patients
Presenting patients (index cases)1
Patients not transferred to another hospital
Patients transferred out to another hospital
This hospital NSW
Age profile, index cases 2
The Tweed Hospital
NSW
% of index cases
Significant patient factors and comorbidities, index cases3
The Tweed Hospital NSW
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 1 of 4
810
714
669
45
50,644
44,059
39,655
4,404
18-51 52-67 68-77 78-85 86+
21 19 22 22 17
20 20 19 22 19
0 10 20 30 40 50 60 70 80 90 100
14Dysrhythmia
9Chronic obstructive pulmonary disease
10Renal failure
10Congestive heart failure
7Hypotension
8Malignancy (cancer)
7Dementia
2Cerebrovascular disease
2Liver disease
2Shock
1Alzheimer's disease
2Parkinson's disease
17
16
16
15
12
9
7
3
2
2
1
1
0 10 20 30 40 50 60 70 80 90 100
% of index cases with factor recorded
The Tweed Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for pneumonia
The T
weed
Ho
sp
ital
Pneum
onia
Percentages: index cases who died within 30 days of hospitalisation
Of all deaths:
percentage in this hospital
percentage in another hospital following transfer
percentage after discharge
percentage on day of admission
percentage within 7 days
This hospital
percentage
NSW
percentage
Survival of index cases following hospitalisation for pneumonia5
Adjusted for average age and Charlson comorbidity score
The Tweed Hospital
% S
urv
ival
Days since admission
NSW
% S
urv
ival
Days since admission
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 2 of 4
Mortality (all causes) among 714 pneumonia index cases4
8%
57%
2%
41%
10%
43%
(66%)
(3%)
(31%)
(6%)
(54%)
0
75
80
85
90
95
100
0 10 20 30
0
75
80
85
90
95
100
0 10 20 30
The Tweed Hospital profile July 2009 - June 2012
Hospital-level pneumonia risk-standardised mortality ratio by number
of expected deaths, NSW public hospitals
The T
weed
Ho
sp
ital
Pneum
onia
The Tweed Hospital NSW hospitals 90% limits 95% limits
Hospital-specific RSMRs report the ratio of actual or ‘observed’ number of deaths to the ‘expected’ number
of deaths. A hierarchical logistic regression model draws on the NSW patient population’s characteristics and
outcomes to estimate the expected number of deaths for each hospital, given the characteristics of its patients.
Actual and expected deaths, compared to local peers
This hospital,
actual deaths
Peer group hospitals,
actual deaths
Expected deaths
(based on model)
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 3 of 4
Shoalhaven and District Memorial Hospital
Manning Base Hospital
Coffs Harbour Base Hospital
Port Macquarie Base Hospital
Tamworth Base Hospital
Wagga Wagga Base Hospital
RSMR = 0.86The Tweed Hospital
Dubbo Base Hospital
Orange Base Hospital
Maitland Hospital
Lismore Base Hospital
0 20 40 60 80 100
Deaths
0
1
2
3
Ris
k s
tand
ard
ised
mo
rtalit
y r
atio
(R
SM
R)
0 50 100 150 200
Expected number of deaths within 30 days
The Tweed Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for pneumonia
The T
weed
Ho
sp
ital
Pneum
onia
Illustrating the effect of standardisation, July 2009 - June 2012
In order to make fair comparisons, a number of risk adjustments are made to mortality data. These take into account
patient level factors that influence the likelihood of dying. The table below illustrates the cumulative effect of the statistical
adjustments. For each ratio, hospitals are compared to the average NSW result, given their case mix.
Lower mortality No difference Higher mortality
Time series risk-standardised mortality ratio, July 2000 - June 20126
Lower mortality No difference Higher mortality
Year (financial years)
Risk-standardised mortality ratio
(1) Index cases refer to patients discharged between July 2009 and June 2012 who were initially admitted to this hospital
(regardless of whether they were subsequently transferred) in their last period of care.
(2) Age at admission date.
(3) Only those conditions that were shown to have a significant impact on mortality (P<0.05) are shown. Many are a result of
end-organ damage resulting from comorbidities, such as diabetes. A broader set of comorbidities was screened for potential
impacts on mortality. Comorbidities as recorded on patient record, with one year look back. STEMI refers to ST-elevation
myocardial infarction.
(4) Deaths are from any cause, in or out of hospital within 30 days of the index hospitalisation admission date.
(5) Kaplan-Meier survival curve for 30-day following admission for haemorrhagic stroke, adjusted for average age and average
Charlson comorbidity score. Survival curves depict the proportion of patients who were alive, day 0 – day 30.
(6) To make RSMRs comparable over time, a reference population is required. Time series RSMRs for each hospital are based
on the reference years (July 2009 - June 2012). Control limits are based on the NSW average within each period.
( ) Data for hospitals with an expected mortality of <1 are suppressed.
( ) Between 90% and 95% upper control limits; ( ) Outside 95% upper control limits.
( ) Between 90% and 95% lower control limits; ( ) Outside 95% lower control limits.
Details of analyses and risk adjustment are available in Spotlight on Measurement: risk-standardised mortality ratios
Data source: SAPHaRI, Centre for Epidemiology and Evidence, NSW Ministry of Health.
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 4 of 4
Unadjusted ratio Age and sex standardised ratio Risk-standardised mortality ratio
0.75 0.80 0.86
2000-02 2003-05 2006-08 2009-12
1.17 1.01 0.84 0.86
The Tweed Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for hip fracture surgery
The T
weed
Ho
sp
ital
Hip
fra
ctu
re s
urg
ery
Total hip fracture surgery hospitalisations
Hip fracture surgery patients
Presenting patients (index cases)1
Patients not transferred to another hospital
Patients transferred out to another hospital
This hospital NSW
Age profile, index cases 2
The Tweed Hospital
NSW
% of index cases
Significant patient factors and comorbidities, index cases3
The Tweed Hospital NSW
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 1 of 4
361
353
202
151
16,355
15,836
10,739
5,097
50-75 76-82 83-86 87-89 90+
24 28 18 11 19
19 23 20 15 22
0 10 20 30 40 50 60 70 80 90 100
29Male
28Dementia
18Dysrhythmia
9Renal failure
9Acute respiratory tract infection
7Congestive heart failure
9Ischemic heart disease
3Malignancy (cancer)
28
23
18
13
12
10
9
4
0 10 20 30 40 50 60 70 80 90 100
% of index cases with factor recorded
The Tweed Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for hip fracture surgery
The T
weed
Ho
sp
ital
Hip
fra
ctu
re s
urg
ery
Percentages: index cases who died within 30 days of hospitalisation
Of all deaths:
percentage in this hospital
percentage in another hospital following transfer
percentage after discharge
percentage on day of admission not applicable for hip fracture surgery
percentage within 7 days
This hospital
percentage
NSW
percentage
Survival of index cases following hospitalisation for hip fracture surgery5
Adjusted for average age and Charlson comorbidity score
The Tweed Hospital
% S
urv
ival
Days since admission
NSW
% S
urv
ival
Days since admission
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 2 of 4
Mortality (all causes) among 353 hip fracture surgery index cases4
6%
57%
0%
43%
38%
(50%)
(0%)
(50%)
(27%)
0
90
95
100
0 10 20 30
0
90
95
100
0 10 20 30
The Tweed Hospital profile July 2009 - June 2012
Hospital-level hip fracture surgery risk-standardised mortality ratio by number
of expected deaths, NSW public hospitals
The T
weed
Ho
sp
ital
Hip
fra
ctu
re s
urg
ery
The Tweed Hospital NSW hospitals 90% limits 95% limits
Hospital-specific RSMRs report the ratio of actual or ‘observed’ number of deaths to the ‘expected’ number
of deaths. A hierarchical logistic regression model draws on the NSW patient population’s characteristics and
outcomes to estimate the expected number of deaths for each hospital, given the characteristics of its patients.
Actual and expected deaths, compared to local peers
This hospital,
actual deaths
Peer group hospitals,
actual deaths
Expected deaths
(based on model)
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 3 of 4
Orange Base Hospital
Coffs Harbour Base Hospital
Tamworth Base Hospital
Lismore Base Hospital
Port Macquarie Base Hospital
Maitland Hospital
Dubbo Base Hospital
Manning Base Hospital
Wagga Wagga Base Hospital
RSMR = 0.95The Tweed Hospital
Shoalhaven and District Memorial Hospital
0 10 20 30 40 50
Deaths
0.0
0.5
1.0
1.5
2.0
2.5
3.0
Ris
k s
tand
ard
ised
mo
rtalit
y r
atio
(R
SM
R)
0 20 40 60 80 100
Expected number of deaths within 30 days
The Tweed Hospital profile July 2009 - June 2012
30-day mortality following hospitalisation for hip fracture surgery
The T
weed
Ho
sp
ital
Hip
fra
ctu
re s
urg
ery
Illustrating the effect of standardisation, July 2009 - June 2012
In order to make fair comparisons, a number of risk adjustments are made to mortality data. These take into account
patient level factors that influence the likelihood of dying. The table below illustrates the cumulative effect of the statistical
adjustments. For each ratio, hospitals are compared to the average NSW result, given their case mix.
Lower mortality No difference Higher mortality
Time series risk-standardised mortality ratio, July 2000 - June 20126
Lower mortality No difference Higher mortality
Year (financial years)
Risk-standardised mortality ratio
(1) Index cases refer to patients discharged between July 2009 and June 2012 who were initially admitted to this hospital
(regardless of whether they were subsequently transferred) in their last period of care.
(2) Age at admission date.
(3) Only those conditions that were shown to have a significant impact on mortality (P<0.05) are shown. Many are a result of
end-organ damage resulting from comorbidities, such as diabetes. A broader set of comorbidities was screened for potential
impacts on mortality. Comorbidities as recorded on patient record, with one year look back. STEMI refers to ST-elevation
myocardial infarction.
(4) Deaths are from any cause, in or out of hospital within 30 days of the index hospitalisation admission date.
(5) Kaplan-Meier survival curve for 30-day following admission for haemorrhagic stroke, adjusted for average age and average
Charlson comorbidity score. Survival curves depict the proportion of patients who were alive, day 0 – day 30.
(6) To make RSMRs comparable over time, a reference population is required. Time series RSMRs for each hospital are based
on the reference years (July 2009 - June 2012). Control limits are based on the NSW average within each period.
( ) Data for hospitals with an expected mortality of <1 are suppressed.
( ) Between 90% and 95% upper control limits; ( ) Outside 95% upper control limits.
( ) Between 90% and 95% lower control limits; ( ) Outside 95% lower control limits.
Details of analyses and risk adjustment are available in Spotlight on Measurement: risk-standardised mortality ratios
Data source: SAPHaRI, Centre for Epidemiology and Evidence, NSW Ministry of Health.
THE INSIGHTS SERIES: Performance Profiles - 30-day mortality December 2013 www.bhi.nsw.gov.au Page 4 of 4
Unadjusted ratio Age and sex standardised ratio Risk-standardised mortality ratio
0.87 0.94 0.95
2000-02 2003-05 2006-08 2009-11
1.34 0.91 0.53 0.95