Demographic characteristics of healthcare professionals
The total healthcare professionals participated in the study was 269. Their mean age was 31.9+7.5 (range 20-53) and majorities of them (58%) were males. Most of the study participants were nurses (36.4%) followed by physicians (24.9%). The majority of professionals (76.6%) were degree holders. Half of the respondents took different trainings related to antimicrobial resistance that were mainly from NRH (81%) (Table 1).
Table 1. Demographic characteristics of healthcare professionals participated in the study in East Wollega, western Ethiopia, from May to June, 2017
Characteristics
|
NRH
|
WURH
|
Total
|
Age (in years)
|
20 – 30
|
59 (41.3)
|
81 (64.3)
|
140 (52.0)
|
31 – 40
|
65 (45.5)
|
37 (29.4)
|
102 (37.9)
|
>40
|
19 (13.3)
|
8 (6.3)
|
27 (10.0)
|
Mean (range)
|
31.9+7.5 (20-53)
|
Sex
|
Male
|
70 (49.0)
|
86 (68.3)
|
156 (58.0)
|
Female
|
73(51.0)
|
40 (31.7)
|
113 (42.0)
|
Level of education
|
Diploma
|
27 (18.9)
|
5 (4.0)
|
32 (11.9)
|
Degree
|
89 (62.2)
|
117 (92.9)
|
206 (76.6)
|
Masters
|
22 (15.4)
|
3 (2.4)
|
25 (9.3)
|
PhD
|
5 (3.5)
|
1 (0.8)
|
6 (2.3)
|
Field of study
|
Nurse
|
45 (31.5)
|
53 (42.1)
|
98 (36.4)
|
Physician
|
31 (21.7)
|
36 (28.6)
|
67 (24.9)
|
Health Officer
|
33 (23.1)
|
10 (7.9)
|
43 (16.0)
|
Pharmacy
|
17 (11.9)
|
15 (11.9)
|
32 (11.9)
|
Midwifery
|
17 (11.9)
|
12 (9.5)
|
29 (10.8)
|
Attended training on antimicrobial resistance
|
Yes
|
116 (81.1)
|
32(25.4)
|
148 (55.0)
|
No
|
27 (18.9)
|
94 (74.6)
|
129 (45.0)
|
*SD, standard deviation
|
General awareness of healthcare professionals on AMR
Nearly three-fifth (59%) of healthcare professionals participated in the study believed that antibiotics were wrongly used in their clinical practices (Fig 1).
Of the respondents who stated that antibiotics were wrongly used, 68.6% (84.5% in NRH vs 25.6% in WURH) did not mention the respective reasons for their wrong use. The most frequently mentioned reasons for their wrong use were inappropriate prescription (24, 14.5%) followed by knowledge or information gaps (11, 6.9%) (Fig 2).
Nearly half of the respondents (47.2%) noted that resistance was the current challenging problem of antibiotic use while 26.4% noted resistance and other issues including toxicity. However, 26.4% respondents did not mention resistance in their list (Fig 3).
More than half of healthcare professionals (55%) believed that they do have sufficient information on antimicrobial resistance (Fig 4).
Among the main sources of information on antimicrobial resistance, academic education followed by training (Fig 5).
Knowledge of healthcare professionals on factors contributing to AMR
Healthcare workers in the two hospitals had higher awareness towards the factors contributing to bacterial resistance. Failure to finish the antibiotic course (89.2 %) and extensive use of newer antibiotics (74.0%) were the most and the least reported contributory factors for antimicrobial resistance, respectively. Poor infection control (88.8%), inappropriate antibiotic use (87.0%), antibiotic use without prescription (88.5%), medical instrumentation (83.3%), inappropriate antibiotic prescription (82.5%), prescribing antibiotics without culture (82.5%), and patient transfer between units (80.3%) were listed as factors for antimicrobial resistance. Two-way contingency table analysis showed that there was significant association between patient transfer between units, poor infection control, medical instrumentation, extensive use of newer antibiotics and prescribing antibiotics when no culture within the healthcare setting (Table 2).
Table 2: Awareness of healthcare professionals on factors contributing to bacterial resistance in East Wollega, western Ethiopia, from May to June, 2017
Contributing Factors
|
Response
|
NRH
|
WURH
|
Total
|
Chi
|
P
|
Patient transfer between units
|
Agree
|
132 (92.3)
|
84 (66.7)
|
216 (80.3)
|
27.84
|
0.000
|
Disagree
|
11 (7.7)
|
42 (33.3)
|
53 (19.7)
|
Poor infection control
|
Agree
|
137 (95.8)
|
102 (81.0)
|
239 (88.8)
|
14.91
|
0.000
|
Disagree
|
6 (4.2)
|
24 (19.0)
|
30 (11.2)
|
Medical Instrumentation
|
Agree
|
137 (95.8)
|
87 (69.0)
|
224 (83.3)
|
34.42
|
0.000
|
Disagree
|
6 (4.2)
|
39 (31.0)
|
45 (16.7)
|
Inappropriate antibiotic prescription
|
Agree
|
121 (84.6)
|
101 (80.2)
|
222 (82.5)
|
0.92
|
0.337
|
Disagree
|
22 (15.4)
|
25 (19.8)
|
47 (17.5)
|
Inappropriate antibiotic Use
|
Agree
|
121 (84.6)
|
113 (89.7)
|
234 (87.0)
|
1.52
|
0.218
|
Disagree
|
22 (15.4)
|
13 (10.3)
|
35 (13.0)
|
Extensive use of newer antibiotics
|
Agree
|
120 (83.9)
|
79 (62.7)
|
199 (74.0)
|
15.66
|
0.000
|
Disagree
|
23 (16.1)
|
47 (37.3)
|
70 (26.0)
|
Failure to finish antibiotic course
|
Agree
|
128 (89.5)
|
112 (88.9)
|
240 (89.2)
|
0.027
|
0.87
|
Disagree
|
15 (10.5)
|
14 (11.1)
|
29 (10.8)
|
Use of antibiotic without prescription
|
Agree
|
131 (91.6)
|
107 (84.9)
|
238 (88.5)
|
2.94
|
0.087
|
Disagree
|
12 (8.4)
|
19 (15.1)
|
31 (11.5)
|
Prescribing antibiotics when no culture
|
Agree
|
128 (89.5)
|
94 (74.6)
|
222 (82.5)
|
10.32
|
0.001
|
Disagree
|
15 (10.5)
|
32 (25.4)
|
47 (17.5)
|
Knowledge of healthcare professionals on strategies used to control AMR
The current findings regarding medical staff awareness on methods used to control bacterial resistance were higher like the reports on the factors contributing to resistance. Infection control (96.7%), accurate diagnosis (94.4%), laboratory capacity surveillance (92.9%), public education (92.6%), better hygiene (91.8%), adherence to guidelines (91.4%), better antibiotic handling (90.3%), reducing hospital stay (88.1%), and hospital antibiotic restriction (81.0%) were noted (Table 3).
Table 3: Awareness of healthcare professionals on strategies used to control the emergence of bacterial resistance in East Wollega, western Ethiopia, from May to June, 2017
Contributing Factors
|
Response
|
NRH
|
WURH
|
Total
|
Better hygiene
|
Agree
|
142 (99.3)
|
105 (83.3)
|
247 (91.8)
|
Disagree
|
1 (0.7)
|
21 (16.7)
|
22 (8.2)
|
Infection control
|
Agree
|
141 (98.6)
|
119 (94.4)
|
260 (96.7)
|
Disagree
|
2 (1.4)
|
7 (5.6)
|
9 (3.3)
|
Reducing hospital stay
|
Agree
|
137 (95.8)
|
100 (79.4)
|
237 (88.1)
|
Disagree
|
6 (4.2)
|
26 (20.6)
|
32 (11.9)
|
Adherence to guidelines
|
Agree
|
134 (93.7)
|
112 (88.9)
|
246 (91.4)
|
Disagree
|
9 (6.3)
|
14 (11.1)
|
23 (8.6)
|
Hospital antibiotic restriction
|
Agree
|
124 (86.7)
|
94 (74.6)
|
218 (81.0)
|
Disagree
|
19 (13.3)
|
32 (25.4)
|
51 (19.0)
|
Better antibiotic handling
|
Agree
|
129 (90.2)
|
114 (90.5)
|
243 (90.3)
|
Disagree
|
14 (9.8)
|
12 (9.5)
|
26 (9.7)
|
Public education
|
Agree
|
133 (93.0)
|
116 (92.1)
|
249 (92.6)
|
Disagree
|
10 (7.0)
|
10 (7.9)
|
20 (7.4)
|
Accurate Diagnosis
|
Agree
|
134 (93.7)
|
120 (95.2)
|
254 (94.4)
|
Disagree
|
9 (6.3)
|
6 (4.8)
|
15 (5.6)
|
Lab capacity surveillance
|
Agree
|
133 (93.0)
|
117 (92.9)
|
250 (92.9)
|
Disagree
|
10 (7.0)
|
9 (7.1)
|
19 (7.1)
|
Belief of healthcare professionals on definition and impact of AMR
One out of five respondents (20%) inappropriately believed that resistance as a ‘body resistance to drugs’. Majority of respondents believed as ‘most infections are becoming increasingly resistant to treatment by antibiotic drugs’ (84.4%) and such resistant strains can spread from one person to another (82.5%). Nearly 80% of respondents told that infections caused by these resistant strains are difficulties to treat. In addition, 91.6% of healthcare professions believed that resistant infections could make some medical procedures like surgery more complicated. The overall correct understanding of healthcare professionals towards the definition and impact of AMR was ranged from 78.8% to 91.1% (Table 4).
Table 4: Belief of healthcare professionals on definition and impact of antimicrobial resistance in East Wollega, western Ethiopia, from May to June, 2017
Belief Questions
|
Response
|
NRH
|
WURH
|
Total
|
AMR occurs when your body becomes resistant to antibiotics and they no longer work as well
|
Agree
|
12 (8.4)
|
42 (33.3)
|
54 (20.1)
|
Disagree
|
131 (91.6)
|
84 (66.7)
|
215 (79.9)
|
Many infections become increasingly resistant to treatment by antibiotics
|
Agree
|
123 (86.0)
|
104 (82.5)
|
227 (84.4)
|
Disagree
|
20 (14.0)
|
22 (17.5)
|
42 (15.6)
|
If bacteria are resistant to antibiotics, it can be very difficult or impossible to treat the infections they cause
|
Agree
|
125 (87.4)
|
87 (69.0)
|
212 (78.8)
|
Disagree
|
18 (12.6)
|
39 (31.0)
|
57 (21.2)
|
Bacteria which are resistant to antibiotics can be spread from person to person
|
Agree
|
122 (85.3)
|
100 (79.4)
|
222 (82.5)
|
Disagree
|
21 (14.7)
|
26 (20.6)
|
47 (17.5)
|
Antibiotic-resistant infections could make medical procedures like surgery and cancer treatment much more dangerous
|
Agree
|
135 (94.4)
|
111 (88.1)
|
246 (91.4)
|
Disagree
|
8 (5.6)
|
15 (11.9)
|
23 (8.6)
|
Belief of healthcare professionals on antibiotic use
Despite the majorities of healthcare professionals (82.5%) believed that doctors should only prescribe antibiotics when they are needed, only 63.6% of healthcare professionals disagreed on the better use of antibiotics usage without prescription. In addition, 90% of respondents disagreed on antibiotic usage for ear infection; however, 36.4% of them agreed on their use for common cold. More than 60% (range 63.6% to 91.1%) of healthcare professionals on antibiotic use had correct beliefs but with some inconsistent response (Table 5).
Table 5: Belief of healthcare professionals on antibiotic use in East Wollega, western Ethiopia, from May to June, 2017
Belief Questions
|
Response
|
NRH
|
WURH
|
Total
|
Doctors should only prescribe antibiotics when they are needed
|
Agree
|
119 (83.2)
|
103 (81.7)
|
222 (82.5)
|
Disagree
|
24 (16.8)
|
23 (18.3)
|
47 (17.5)
|
Since most antibiotics are widely used, safe and important drugs they had better be given without prescription
|
Agree
|
14 (9.8)
|
84 (66.7)
|
98 (36.4)
|
Disagree
|
129 (90.2)
|
42 (33.3)
|
171 (63.6)
|
Common colds are cured more quickly with antibiotics
|
Agree
|
17 (11.9)
|
81 (64.3)
|
98 (36.4)
|
Disagree
|
126 (88.1)
|
45 (35.7)
|
171 (63.6)
|
Ear infections in children 3–6 years old almost always require antibiotics
|
Agree
|
3 (2.1)
|
21 (16.7)
|
24 (8.9)
|
Disagree
|
140 (97.9)
|
105 (83.3)
|
245 (91.1)
|
Belief of healthcare professionals on global, local, and individual impacts of AMR
Majorities of the healthcare professionals (97%) forwarded an appropriate belief towards the global pandemic nature of resistance. However, they had mixed belief towards who will be affected by AMR. Most healthcare professionals (83.3%) agreed with the statement ‘antibiotic resistance is an issue in other countries but not our local settings’. Similarly, 55.4% agreed with the question ‘antibiotic resistance is only a problem for people who take antibiotics regularly’. However, 66.9% of them responded as ‘antibiotic resistance is an issue that could affect them or their family’. A wider range of mixed responses (16.7% to 97%) was reported towards the global, local, and individual level impacts of AMR (Table 6).
Table 6: Belief of healthcare professionals on global, local, and individual level impacts of AMR in East Wollega, western Ethiopia, from May to June, 2017
Belief Questions
|
Response
|
NRH
|
WURH
|
Total
|
Antibiotic resistance is one of the biggest problems the world faces
|
Agree
|
139 (97.2)
|
122 (96.8)
|
261 (97.0)
|
Disagree
|
4 (2.8)
|
4 (3.2)
|
8 (3.0)
|
Antibiotic resistance is an issue in other countries but not here
|
Agree
|
111 (77.6)
|
113 (89.7)
|
224 (83.3)
|
Disagree
|
32 (22.4)
|
13 (10.3)
|
45 (16.7)
|
Antibiotic resistance is an issue that could affect me or my family
|
Agree
|
74 (51.7)
|
106 (84.1)
|
180 (66.9)
|
Disagree
|
69 (48.3)
|
20 (15.9)
|
89 (33.1)
|
Antibiotic resistance is only a problem for people who take antibiotics regularly
|
Agree
|
59 (41.3)
|
90 (71.4)
|
149 (55.4)
|
Disagree
|
84 (58.7)
|
36 (28.6)
|
120 (44.6)
|
Knowledge and belief scores of healthcare professionals
The mean knowledge score of healthcare professionals on AMR was 36.6+11.61 which was ranged from 23 to 83 and the median score was 35. Forty eight percent of healthcare professionals had knowledge above the median score which was a poor score. Similarly, the mean belief score of healthcare professionals on AMR was 28.7+6.88 which was ranged from 13 to 49 and the median score was 29. Nearly 45% of healthcare professionals had poor belief score. A correlation test between knowledge and belief scores showed that there was a significant negative correlation (r = 0.551, p=0.01) (Table 7).
Table 7: Percentage of healthcare professionals with good knowledge and belief score in East Wollega, western Ethiopia, from May to June, 2017
Variables
|
Number
|
Percent
|
Knowledge
|
Knowledge Score< 35
|
139
|
51.7
|
Knowledge Score > 35
|
130
|
48.3
|
Mean score
|
36.6+11.61
|
Median score (range)
|
35.0 (23.0-83.0)
|
Belief
|
Belief Score < 29
|
149
|
53.2
|
Belief Score > 29
|
120
|
46.8
|
Mean score
|
28.7±6.88
|
Median score (range)
|
29 (13-47)
|
Correlation Test
|
Rho (r)= 0.551, P = 0.01
|
Factors affecting good knowledge score
Hospital setting (adjusted odds ratio (AOR): 4.65; 95% confidence interval (CI): 2.39-9.06; P < 0.001) had significant independent association with good knowledge score while having no training had a poor knowledge score (AOR: 0.43; 95% CI: 0.23-0.83; P < 0.05) (Table 8).
Table 8: Factors associated with good knowledge score on antimicrobial resistance among healthcare professionals in East Wollega, western Ethiopia, from May to June, 2017
Variables
|
Crude OR [95% CI]
|
Adjusted OR [95% CI]
|
Age groups (in years)
|
20-30
|
0.30 [0.12-0.73]**
|
0.54 [0.19-1.51]
|
31-40
|
0.65 [0.26-1.63]
|
0.88 [0.31-2.53]
|
>41
|
1
|
1
|
Hospital setting
|
NRH
|
6.93 [4.06-11.85]***
|
4.65 [2.31-9.06]***
|
WURH
|
1
|
1
|
Field of study
|
Midwife
|
0.79 [0.30-2.15]
|
1.61 [0.48-5.41]
|
Physician
|
0.42 [0.19-0.92]*
|
0.82 [0.31-2.19]
|
Nurse
|
0.48 [0.23-1.02]
|
1.08 [0.43-2.74]
|
Pharmacy
|
0.29 [0.11-0.76]*
|
0.45 [0.15-1.34]
|
Health Officer
|
1
|
1
|
Level of education
|
Diploma
|
0.38 [0.04-3.69]
|
0.32 [0.03-3.86]
|
Degree
|
0.18 [0.02-1.58]
|
0.40 [0.04-4.18]
|
Masters
|
0.30 [0.03-2.97]
|
0.28 [0.02-3.12]
|
PhD
|
1
|
1
|
Training
|
Yes
|
1
|
1
|
No
|
0.21 [0.13-0.36]***
|
0.43 [0.23-0.82]*
|
Where*, P < 0.05; **, P < 0.01; and ***, P < 0.001.
Factors affecting good belief score
Training (AOR: 0.13; 95% CI: 0.06-0.25; P < 0.001) and hospital setting (AOR: 3.62; 95% CI: 1.76-7.44; P < 0.001) had significant independent association with good belief score (Table 9).
Table 9: Factors associated with good belief score on antimicrobial resistance among healthcare professionals in East Wollega, western Ethiopia, from May to June, 2017
Variables
|
Crude OR [95% CI]
|
Adjusted OR [95% CI]
|
Sex
|
Male
|
0.52 [0.32-0.86]*
|
0.77 [0.38-1.55]
|
Female
|
1
|
1
|
Field of study
|
Midwife
|
3.33 [1.21-9.16]*
|
0.99 [0.25-3.85]
|
Physician
|
1.25 [0.45-3.45]
|
0.37 [0.12-1.17]
|
Nurse
|
0.60 [0.26-1.39]
|
0.89 [0.30-2.62]
|
Pharmacy
|
1.08 [0.49-2.41]
|
0.54 [0.15-1.87]
|
Health Officer
|
1
|
1
|
Training
|
Yes
|
1
|
1
|
No
|
0.08 [0.04-0.14]***
|
0.13 [0.06-0.25]***
|
Hospital setting
|
NRH
|
8.03 [4.65-13.88]***
|
3.62 [1.76-7.44]***
|
WURH
|
1
|
1
|
Age groups (in years)
|
20-30
|
0.26 [0.10-0.67]**
|
0.62 [0.19-2.06]
|
31-40
|
0.44 [0.16-1.19]
|
0.71 [0.21-2.44]
|
>41
|
1
|
1
|
Level of education
|
Diploma
|
0.51 [0.05-5.00]
|
0.25 [0.02-3.77]
|
Degree
|
0.21 [0.2-1.85]
|
0.35 [0.03-4.09]
|
Masters
|
0.30 [0.03-2.97]
|
0.18 [0.01-2.32]
|
PhD
|
1
|
1
|
Where *, P < 0.05; **, P < 0.01; and ***, P < 0.001.