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Table 2 Characteristics of “good” and “poor” auditors from the bivariate analysis. Variables that predict being a “good” auditor from logistic regression analysis

From: Patients and relatives as auditors of safe practices in oncology and hematology day hospitals

Bivariate analysis of the P&Fs characteristics between “good” and “poor” auditors

* Good auditors (> 75% correct answers)

** Poor auditors (= < 75% correct answers)

Logistic regression analysis of the variables that predict being a “good” auditor

  

Good auditors* n = 63

Poor auditors** n = 73

p value

Beta

p value

Odds Ratio

95% CI

Age: mean (sd)

 

51.4 (12.5)

62.5 (12.7)

0.000

−0.061

0.001

0.940

0.908

0.974

Gender: n (%)

Female

33 (46.5)

39 (53.5)

0.903

     

Male

30 (47.6)

34 (52.4)

      

Education: n (%)

Basic level

20 (31.7)

45 (68.2)

0.000

 

0.006

1 (referent)

  

Medium level

14 (43.8)

18 (56.3)

 

0.652

0.208

1.920

0.696

5.301

High level

28 (77.8)

8 (22.2)

 

1.738

0.001

5.684

1.947

16.591

Adverse events suffered n (%)

No

22 (73.3)

8 (26.7)

0.001

0

 

1 (referent)

  

Yes

41 (38.7)

65 (61.3)

 

1.658

0.002

5.250

1.861

14.806

General perception of hospital safety

Totally safe

19 (31.7)

41 (68.3)

0.002

     

Other categories

43 (57.3)

32 (42.7)

      
 

2.388

0.027

10.894

Constant

 

R2 Nagelkerke = 0.411

X2 Hosmer and Lemeshow =3.530 Sig = 0.897

Type of participants: n (%)

Companions

27 (60.0)

19 (40.0)

0.046

     

Patients

36 (40.4)

54 (59.6)

      

Type of treatment: n (%)

Chemotherapy

52 (52.5)

49 (47.5)

0.05

     

Transfusion

11 (31.4)

24 (68.6)

      

Healthcare professional n (%)

Yes

8 (57.1)

6 (42.9)

0.783

     

No

54 (53.5)

49 (46.5)

      

Number of Day Hospital visits: median (IQR)

 

6 (15–3)

7 (12–3)

0.649

     

Number of hospital stays: median (IQR)

 

1 (2–0)

0 (1–0)

0.108