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Prevention of BSI and VAP Measuring Change in Outcomes Part II. Ted Speroff, PhD. Using NNIS Rate Measures is a Problem for QI. NNIS Rates are used in surveillance to detect outbreaks – a rise in rates! Also, easier to make site comparisons And easier to pool data into single rate
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Prevention of BSI and VAPMeasuring Change in OutcomesPart II Ted Speroff, PhD
Using NNIS Rate Measures is a Problem for QI • NNIS Rates are used in surveillance to detect outbreaks – a rise in rates! • Also, easier to make site comparisons • And easier to pool data into single rate • However, the goal of QI is to decrease the rate. • The area you have to work with is between the mean rate and 0. • It is very hard to show improvement using rate as your measure.
To show improvement the rate will be in this area. UCL Central Line is Mean =5.0/1000 days LCL = -1.7 X-axis is Time Scale: days, weeks months When the lower (LCL) control limit is below zero, you have to collect data for a much longer period of time to move the LCL above zero. Control Chart for NNIS Rate
Solution: g Chart • Change your Measure • The number of days between events • Date #2 minus Date #1 • Goal: to increase the number of days between events • There is no upper boundary • As the NNIS rate decreases, the number of days between events increases. • G chart is sensitive for detecting a decrease in NNIS rate • Don’t need to know the census (denominator), just the dates of infections. Thus, not dependent on the number of line-days or vent-days of your ICU.
Additional Rules for Control ChartsStatistical Significance • Single point above the UCL • 2 of 3 consecutive points between 2 and 3 sigma • 6 consecutive points in an upward trend • 9 consecutive points above or below the central line (mean)
Continue with Second EntryNote: Days between Events takes at least two entries
End of Part IIQuestions and Commentsso far?Continue Part III