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Table 13. Number of diagnosis codes by procedure
Table of Number of Diagnoses by Procedures
Number of Diagnoses
Principal Procedure
Total
Frequency
Row Pct
Col Pct
3611
3612
3613
3614
3615
3616
3619
2
0
0.00
0.00
0
0.00
0.00
0
0.00
0.00
0
0.00
0.00
3
100.00
0.80
0
0.00
0.00
0
0.00
0.00
3
4
0
0.00
0.00
0
0.00
0.00
1
33.33
0.25
0
0.00
0.00
2
66.67
0.53
0
0.00
0.00
0
0.00
0.00
3
6
1
7.14
0.93
2
14.29
0.69
3
21.43
0.75
4
28.57
1.52
4
28.57
1.07
0
0.00
0.00
0
0.00
0.00
14
8
3
8.33
2.78
7
19.44
2.43
9
25.00
2.24
7
19.44
2.65
6
16.67
1.60
4
11.11
14.29
0
0.00
0.00
36
10
7
10.29
6.48
18
26.47
6.25
20
29.41
4.98
8
11.76
3.03
13
19.12
3.47
2
2.94
7.14
0
0.00
0.00
68
11
8
7.27
7.41
18
16.36
6.25
38
34.55
9.45
14
12.73
5.30
31
28.18
8.27
1
0.91
3.57
0
0.00
0.00
110
12
10
8.47
9.26
17
14.41
5.90
30
25.42
7.46
20
16.95
7.58
39
33.05
10.40
2
1.69
7.14
0
0.00
0.00
118
13
10
5.59
9.26
34
18.99
11.81
42
23.46
10.45
38
21.23
14.39
51
28.49
13.60
4
2.23
14.29
0
0.00
0.00
179
14
33
7.89
30.56
94
22.49
32.64
121
28.95
30.10
91
21.77
34.47
68
16.27
18.13
10
2.39
35.71
1
0.24
100.00
418
15
36
6.96
33.33
98
18.96
34.03
138
26.69
34.33
82
15.86
31.06
158
30.56
42.13
5
0.97
17.86
0
0.00
0.00
517
Total
108
288
402
264
375
28
1
1466
ranking using the number of codes to the rankings from the predictive models in the previous models.
For the first time, the hospital with zero mortality (hospital #2) does not have the lowest rank. There
are three hospitals with zero difference between the actual and predicted values. Overall, this model
more accurately predicts the mortality by hospital than do any of the previous models.
nosocomIal InfectIon
Because nosocomial infection is such a problem, and because providers are reducing or eliminating pay-
ments to treat such infection, we want to look at specific reporting issues related to it. In particular, we
want to see if hospitals are under-reporting a nosocomial rate by looking to the proportion of procedures
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