Steven P Hudson MBA MA Statistician Health Care Excel Inc Objectives Describe what the Standardized Infection Ratio SIR is and how it is calculated Explain how to generate and interpret a report utilizing the SIR ID: 559915
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Slide1
The Standardized Infection Ratio
Steven P Hudson, MBA, MA
Statistician
Health Care Excel, IncSlide2
Objectives
Describe what the Standardized Infection Ratio (SIR) is and how it is calculated.
Explain how to generate and interpret a report utilizing the SIR.
Slide3
What is a standardized infection ratio?
The standardized infection ratio (SIR) is a summary measure used to track healthcare-associated infections (HAIs) at a national, state, or local level over time. The SIR adjusts for patients of varying risk within each facility.
-
The National Healthcare Safety Network (NHSN) Slide4
The SIR calculation
In HAI data analysis, the SIR compares the actual number of HAIs reported (
observed
) with the baseline U.S. experience (
expected/predicted
), adjusting for several risk factors that have been found to be significantly associated with differences in infection incidence.
number of
observed (O) number of expected (E)NHSN aggregate data are used as the standard population and considered the baseline U.S. experienceNHSN baseline data used in a SIR are used to calculate the expected or predicted number of HAIs adjusting for the identified risk factors.
SIR=Slide5
What does the SIR number mean?
Accounting for differences in the types of patient followed:
A SIR
greater than 1.0
indicates that
more
HAIs were observed than predicted.
A SIR less than 1.0 indicates that fewer HAIs were observed than predicted.A SIR equal to 1.0 indicates the same number of HAIs were observed than predicted.However, the SIR alone does not imply statistical significance.Slide6
Statistical significance of the SIR:
p-value and 95% confidence intervals
The SIR is only a point estimate and needs additional information to indicate if it is statistically significantly different from 1.
A 95% confidence interval (CI) and a p-value are calculated by NHSN for each SIR and determines statistical significance.
A 95% CI assesses the magnitude and stability of a SIR. Therefore, a 95% CI is the range of estimated SIR values that have a 95% probability of including the true SIR for the population.
If the 95% CI does
not contain the value 1
, the SIR is “statistically significant.”If the p-value is less than 0.05, the SIR is “statistically significant.”Slide7
Statistical Significance
If the p-value is less than .05, then your rates are different than the national average
If the confidence level does not overlap 1, then your rates are different than the national average.Slide8
I was just getting used to rates, why the SIR?
More sensitive for low denominators
Ability to combine data
Useful for predicting state and national ratesSlide9
OK , I’m no statistician-what’s all this mumbo jumbo about?
In simple terms- you are compared to the average of a referent population and adjusted for risk
In this case, it is a historical control.
The SIRSlide10
Calculation
Observed (
actual number of Infections
)
Expected (
expected number of infections)SIR= Slide11
Let’s take a closer look
Hospital A :
Type of ICU
Number
of Infections
Line days
My
rateNHSN MeanMed/ Surg1865
1.1
2.1
SICU
0
1000
0
2.8
CCICU
2
948
2.1
1.1
MICU
2
1000
2.0
2.1Slide12
Turned into SIR
Type of ICU
Number
of infections
Number expected
SIR
Observed/
expectedP VALUEMed/ Surg10.951.05SICU02.8
0
CCICU
2
0.93
2.1
MICU
2
2.1
0.95
SIR is less than 1Slide13
Simply
Put
A SIR of
1.0
means the observed number of infections is equal to the number of expected infections.
A SIR
above 1.0
means that the infection rate is higher than that found in the "standard population." For HAI reports, the standard population comes from data reported by the hundreds of U.S. hospitals that use the NHSN system. The difference above 1.0 is the percentage by which the infection rate exceeds that of the standard population.
A SIR
below 1.0
means the infection rate is lower than that of the standard population. The difference below 1.0 is the percentage by which the infection rate is lower than that experienced by the standard population. Slide14
How to generate NHSN SIR outputs
Log into NHSN --> enter the Patient Safety Module
Starting from the blue navigation menu on the left, click “Analysis” --> “Generate Data Set” --> “Generate New” (note: this will take some time to load)
Click “Analysis” --> “Output Options”
On the white screen, click “Device-Associated Module” --> “Central Line-Associated BSI” --> “CDC Defined Output” --> “SIR – In-Plan CLAB Data”
Select “Run” for data aggregated by 6-month intervals and CDC location type or select “Modify” to customize the outputSlide15
Conducting your own analysisSlide16Slide17Slide18Slide19
orgid=10330Slide20Slide21
Surgical SIRSlide22
SSI SIRSlide23
SSI data are summarized like they are for CLABSIs:Slide24
Interpreting the SIR
During 2009, there were 524 procedures performed and 13 SSIs identified.
Based on the NHSN 2006-2008 baseline data 6.687 SSIs were expected.
This results in a SIR of 1.94 (13/6.687), signifying that during this time period our facility identified 94% more SSIs than expected.
The p-value and 95% confidence interval indicate that the number of observed SSIs is significantly higher than the number of expected SSIs.Slide25
The SIR
PROS
CONS
Surgical risk adjustment is a significant
improvement
Risk adjustment still suboptimal – especially with CLABSI data
Consistent
with other types of data such as mortalityNot designed to compare one institution to another- only to compare with national averageAdvantages with rare eventsPotential problems with ranking ,etcOverall rates can cloud the big pictureSlide26
Questions ?Slide27
Contact InfoEmail:
shudson@kyqio.sdps.org
502-454-5112 ext 2252
27
This material was prepared by Health Care Excel, the Medicare Quality Improvement Organization for Indiana, under contract with the Centers for Medicare & Medicaid Services (CMS), an agency of the U.S. Department of Health and Human Services. The contents presented do not necessarily reflect CMS policy. 10SOW-IN-INDPAT-13-012 4/1/13