Using and Sharing Findings from Surveillance:
Rates, Ratios Proportions, Data Display & OUTBREAKS
Russ Olmsted, MPH, [email protected]
Reporting HAI Data; Definitions
Larger size image on document at end of this section see also: Lee TB, et al Recommended practices
Incidence rate (“incidence density”)
Number of new cases –––––––––––––––––––––––––––––––Avg. population at risk × Time interval
Number of new cases = ––––––––––––––––––––
Population-time
Prevalence; another important measure
Number of existing (new + old) cases
Prevalence = –––––––––––––––––––––––––––– Population at risk
Often expressed as a proportion
Population at risk
Existing cases: Prevalence
Outcomes
Incident cases: number of kernels popped as heat is applied
Kernals that go unpopped = not susceptible
Incidence and Prevalence• Incidence and prevalence measure different
aspects of disease occurrence Prevalence Incidence
Numerator:
Denominator
Measures:
Most useful:
All cases, no matter how long diseased
Only NEW cases
All persons in population
Only persons at risk of disease
Presence of disease
Risk of disease
Resource allocation
Risk, etiology
Device Utilization Ratio• Device utilization ratio (DUR) is the
proportion of patient or resident days for which a certain device is used
• DUR is specific to one device;e.g. central line, urinary catheter
• DUR reflects the amount of devices used and can be a reflection of patient severity or over utilization
Standardized Infection Ratio (SIR)– Observed # of HAIs
• SIR = ------------------------------------------------- – Expected (Predicted) # of HAIs
• Observed # of HAI – the number of events identified from surveillance HAIs
Expected or predicted # of HAI – comes from national baseline data, e.g. NHSN
Who’s Using SIR? CMS http://www.medicare.gov/hospitalcompare/se
arch.html
PERFORMANCE MEASURES:
ProcessExamples of process measures:
1) Compliance with educational program: calculate percent of personnel who have proper training on urinary cath. insertion
# persons who insert catheters and are trained
__________________________________ # personnel who insert urinary catheters Multiply by 100 to express as percent
Examples of other Uses of Process Measures
Hand Hygiene (HH) Adherence:
Numerator: # of Instances HH was used___________________________________ X 100
Denominator: # of opportunities for HH
++++++++++++++++++++++++++++++++++++++++++++++++++++
PERFORMANCE MEASURES
3. Compliance with documentation of indication for catheter placement
# number of patients on unit with catheter & proper documentation of indication
____________________________________# of patients on unit with catheter
• Multiply by 100 to express as percent
Outcome Measures
Incidence DensityDevice-associated (DA) rates are calculated as Incidence Density
Rates (IDRs) What is an “Incidence Density Rate”?Numerator = # of new cases during a period of timeDenominator = person-time or device day during -same time X a constant, e.g. 100, 1000, or 10,000
Outcome Measures, cont.Recommended outcome measures:
1. Rates of CAUTI – based on surveillance definitions
# of cases of CAUTI ______________________________total # of urinary-catheter days
• Multiply by 1000 to express as # infections per 1000 catheter days
Sharing & Displaying Data
PA Patient Safety Advisory, 2010
Trend Analysis; CDI rates by reporting Quarter
Cumulative CDI rates [community-onset + hospital onset] MDCH. SHARP Michigan 2012 Quarter 4 HAI Surveillance Report
Trend Analysis; CDI rates by reporting Quarter
Cumulative CDI rates [community-onset + hospital onset] MDCH. SHARP Michigan 2012 Quarter 4 HAI Surveillance Report
Distribution of LabID CDI by type
Cumulative CDI rates [community-onset + hospital onset] MDCH. SHARP Michigan 2012 Quarter 4 HAI Surveillance Report
Display of SIRTN Report on HAIs, June 2012
Larger size image on document at end of this section
Description of Outbreaks, U.S. Hospitals
• 35% of 855 hospitals who completed a survey had investigated possible outbreak.
• Frequency = 1.3 investigations/facility/24 months• Triggers:
– unusual organism (38.1%); – rate above baseline for a specific HAI site or for a specific unit
were also frequent triggers (27%) • Pathogens:
– Norovirus (18.2%)– Staphylococcus aureus (17.5)– Acinetobacter spp (13.7)– Clostridium difficile (10.3)
Rhinehart E, et al. AJIC 2012
Date of download: 10/19/2012Copyright © 2012 American Medical
Association. All rights reserved.
From: Hospitalizations and Mortality Associated With Norovirus Outbreaks in Nursing Homes, 2009-2010
JAMA. 2012;():1-8. doi:10.1001/jama.2012.14023
aFor norovirus outbreaks, outbreaks were counted as occurring during the week the first ill case was noted to be symptomatic.
308 Nursing Homes reported Oubreaks, Jan.2009-Dec. 2010
>67,000 hospitalizations; 26,000deaths
Operational Definition of Outbreak/Cluster
• Occurrence of more cases of disease than expected in a given area among a specific group of people over a particular period of time
• Example: cluster of acute gastroenteritis cases is detected in the healthcare facility
Prevention and Control Measures: Influenza in LTCFs
Control of Influenza Outbreaks in Long-Term Care Facilities
• Definition of Cluster: Three or more cases of acute febrile respiratory illness (AFRI) occurring within 48 to 72 hours, in residents who are in close proximity to each other (e.g., in the same area of the facility).
• Outbreak: A sudden increase of AFRI cases over the normal background rate or when any resident tests positive for influenza. One case of confirmed influenza by any testing method in a long-term care facility resident is an outbreak.
– http://www.cdc.gov/flu/professionals/infectioncontrol/longtermcare.htm
Steps of an outbreak investigation
• Confirm outbreak and diagnosis !• Define case • Identify cases and obtain information• Descriptive data collection and analysis• Develop hypothesis• Analytical studies to test hypotheses• Special studies• Communication, including outbreak report
Imp
lemen
t con
tr ol m
easures
Role of the Infection Preventionist
• Identification of risk factors
• Identification of emergency control/long term interventions
• Documentation
• Best practice identification
0
10
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50
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90
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39
DAY
CASES
Confirmation
Outbreak Detection and Response
Detection/Reporting
First Case(s)
First ResponseLong term controls
Evaluation
Describe the casesDescriptive epidemiology
-Who is sick?-Where are they (unit, city, etc.)-When did they become ill?-What were they exposed to?
Person
Place
Time
Cases
0102030
1 2 3 4 5 6 7 8 9 10
0
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1500
Age Group
Evaluate information
Pathogen? Source? Transmission?
Note: Line listing may also be used for routine surveillance of HAIs.