Transcript Lengths in Neonatal Intensive Care Unit at the UICH

LENGTHS IN THE NEONATAL
INTENSIVE CARE UNIT
(NICU) AT THE UICH
Presented by: Sathia Veeramoothoo
Fan Yang
Introduction
• Measurements of growth are a good indication of overall
well being and outcomes in infants.
• Length is a non-invasive measure of skeletal growth.
• Accurate measures of length are important for monitoring
growth in infants transitioning to home, for high risk and
primary care provider follow up, and infant nutrition
programs.
Kirsten’s Goals
• Increased NP knowledge, confidence, and evidence
based techniques for obtaining lengths.
• Increased documentation of discharge lengths in EPIC
growth chart.
• Increased number of lengths in children at risk for growth
failure.
• Increased reliability, precision and accuracy of lengths
measures.
Main Goal
• Problem: Measurement of infant lengths using paper
tape measures is inaccurate and unreliable.
• Purpose: To increase the accuracy, reliability and
precision of length measurements in infants in newborn
and intensive care units cared for and discharged from
UICH.
Data Collection
• Design: For each infant a length measurement will be performed four
times, twice each by two experienced Nurse Practitioners.
• Procedure:
• 1. NP1- Using tape measure in the envelope, obtain a length using
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standard procedure.
2. NP1- Reposition the child and obtain a second measure of the
child’s length using an unmarked tape.
3. Give the envelope to another nurse practitioner to obtain
repeated length within 24 hours.
4. NP 2- Using tape measure, obtain a length using standard
procedure.
5. NP 2 - Reposition the child and obtain a second measure of the
child’s length using an unmarked tape.
Overview of Original Data
Data Re-format using SAS
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/*Reformat data for SAS model fitting.*/
data babiesNew; set babies;
nurse=NP_1;
y=NP1_L1;
treatment="standard";
output;
nurse=NP_1;
y=NP1_L2;
treatment="unmarked";
output;
nurse=NP_2;
y=NP2_L1;
treatment="standard";
output;
nurse=NP_2;
y=NP2_L2;
treatment="unmarked";
output;
keep ID GA BW DOL AGA y nurse treatment;
run;
Modified Data
Modeling
• Rosenberg et al. (1992) essentially performed separate
reliability analyses for each method being compared (e.g.
paper tape vs. Prematometer).
• Using this same tactic for Kirsten’s data, we can model
the variability in lengths within each method (marked vs.
unmarked) as being caused by one of three sources:
1. baby-to-baby variability
2. nurse-to-nurse variability (inter-rater variability)
3. random noise
• The resulting two reliability measures would then be
compared to see if one method was more reliable than
the other.
Modeling Challenges
• Pure within nurse or intra-rater variability:
• Nurses did not repeatedly measure the same baby under the exact same
conditions (i.e. with the same type of tape).
• Intra-baby variability:
• We do have two measurements from the same nurse on the same baby,
but they were under different conditions (specially, one was done on a
marked tape and one was done on an unmarked tape).
• Confounding: the difference in these two measurements could be due to a
difference in the methods (marked vs. unmarked) or due to intra-rater
variability.
Intra-class Correlation and Reliability
• With the previously-mentioned three sources of reliability,
we can compare the reliability of these two methods of
measuring length by comparing the value of their intraclass correlation (ICC).
• ICC is used as a measure of how reliable the method is
for measuring length is, and it essentially relates the
variability between nurses to the variability between
babies.
• For example, if nurses tend to give the same measurement for a
baby, then the ICC will be close to 1.
SAS Code
data standard;
set babiesNewer;
where treatment = “marked";
run;
data unmarked;
set babiesNewer;
where treatment = "unmarked";
run;
proc mixed data=marked;
class ID nurse;
model y = ;
random nurse ID;
run
proc mixed data=unmarked;
class ID nurse;
model y = ;
random nurse ID;
run;
Covariance Parameter
Estimates
Covariance Parameter
Estimates
Cov Parm
nurse
ID
Residual
Cov Parm
nurse
ID
Residual
Estimate
0.01643
10.9737
0.4204
Estimate
0.8301
10.2593
0.7103
ICC Values and Interpretation
Marked tape ICC
0.9617
Unmarked tape ICC 0.8695
• This suggests the nurses were in better alignment when using the
marked tapes.
• Limitation: We haven't tested to see if the ICC values are actually
statistically significantly different.
• Baby-to-baby variability in these two analysis were essentially identical
(as would be expected because the same babies were used for both),
and it was the difference in the nurse-to-nurse variability across the
methods that was the source of the differing ICC values.
More on Reliability
• Lack of data: Kirsten has not yet collected data on length
boards.
• Recommendations for future data collection:
• For intra- and inter-rater reliability:
• Take two (or more) measurements on each baby with the same nurse
AND the same type of measurement instrument
• Get these same measurements by a second nurse
• For comparing intra-rater reliability for length boards compared to
tapes:
• Take the above four measurements under each method (length board
vs. paper tape)
Kirsten’s Survey and Analysis
Survey – Technique Summary
Technique
position
record
put feet
legs
document
after
measure
remove
check
round
hyper
apply
compress
Sum
16
15
12
9
8
6
5
5
3
2
1
1
1
Survey - continued
Table 1 : Question 1
Experience(Year)
Correct
False
Accuracy
2
3
2
17.65%
11.76%
60.00%
3
0
4
0.00%
23.53%
0.00%
4
3
5
17.65%
29.41%
37.50%
4
4
23.53%
23.53%
50.00%
All
6
11
35.29%
64.71%
Table 2 : Question 3
Experience(Year)
Correct
False
Accuracy
2
0
5
0.00%
29.41%
0.00%
Table 3: PNP v.s. NPN Question 1
PNP
Position
Correct
2
13.33%
False
5
33.33%
Accuracy
28.57%
Table 4: PNP v.s. NPN Question 3
PNP
Position
Correct
3
20.00%
False
4
26.67%
Accuracy
42.86%
Table 5: Day v.s. Night Question 1
Day
Position
Correct
2
13.33%
False
9
60.00%
Accuracy
18.18%
Table 5: Day v.s. Night Question 3
Day
Position
Correct
4
26.67%
False
7
46.67%
Accuracy
18.18%
3
1
3
5.88%
17.65%
25.00%
4
All
3
5
NNP
20.00%
33.33%
37.50%
5
10
1
7
NNP
6.67%
46.67%
12.50%
3
11
3
1
Night
20.00%
6.67%
75.00%
5
10
0
4
Night
0.00%
26.67%
75.00%
4
11
33.53%
66.67%
All
26.67%
73.33%
All
33.33%
66.67%
All
26.67%
73.33%
All
5
12
29.41%
70.59%
Point Data Analysis – Overview of Length
Point Data Analysis – Baby Exposure
Number of Lengths Taken at Different Levels of Baby Exposure
Number of Lengths Taken
3.0
2.5
2.0
1.5
1.0
0.5
0.0
230
240
250
260
270
280
290
After Gestational Age (Days)
300
310
Point Data Analysis - Distribution of RF
Pie Chart: Proportion of Babies With and Without at Least 1 Risk Factor
Category
No Risk Factor Present
At Least 1 Risk Factor Present
36.4%
63.6%
Point Data Analysis – Exposure by CLD
Point Data Analysis – Exposure by >=1RF
Point Data Analysis – Other Statistics
Number of Times Babies Are Measured
0
1
2
3
Bay 4
0%
Bay 5
12.50%
66.67% 16.67% 16.67%
75%
12.50%
0%
Discharge Data Analysis - Overview
Dotplot of Number of lengths at discharge
0
1
2
Number of Lengths
3
Discharge Analysis - Exposure
Graphical Correlation Check
4.5
4.0
Birth weight
3.5
3.0
2.5
2.0
1.5
1.0
0.5
25
30
Gestational Age
35
40
Comparison of Lengths by Chart
Number of lengths
Discharge chart
Growth chart
N=0
1
2.86%
21
60%
N=1
34
97.14%
14
40%
Discharge Length in Discharge chart
Discharge Length in
Growth chart
MEAN
N=0
N=1
N=0
0
21
N=1
1
13
Discharge chart
Growth chart
0.97
0.4
Discharge – Correlation with RF
Summary and Conclusion
• More training recommended
• New data collection
• Better documentation
• Positive correlation: number of measurements
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With: length of time spent at the UICH
With: presence of at least 1 risk factor
Positive correlation: GA and BW
No correlation: number of measurements & presence of CLD
No significant differences between bays 4 and 5.
Next steps: paired t-tests on the marked and blank tapes
Statistically: Experience and position do not impact on the
accuracy of the first three survey questions
Thank you.