A total of 773 healthcare providers participated in this study. Responses from 0.8% (6) of the participants were excluded due to an incomplete filled questionnaire, therefore the results of this study were recorded from 767 (99.2%) healthcare providers. Amongst 767, there were 405 (52.8%) Medical doctors, 185 (24.2%) Nurse officers, 106 (13.8%) Pharmacists, 53 (6.9%) Medical laboratory scientists, and 18 (2.3%) Dentists. About 85.3% of the participants had a bachelor's degree, 62.1% were males and 72.6% of the participants were working in hospitals, the remaining percent were from other health facilities (Table 1). The remaining 14.7% of participants had both Bachelor's and Master's degrees qualifications.
Table 1. Demographic and professional characteristics of the study participants
Variables
|
Category
|
Frequency
|
Percentage
|
Age group (years)
|
20 – 29
|
138
|
18.0
|
30 – 39
|
364
|
47.5
|
40 – 49
|
184
|
24.0
|
50 – 59
|
66
|
8.6
|
≥ 60
|
15
|
2.0
|
Sex
|
Males
|
476
|
62.1
|
Females
|
291
|
37.9
|
Professional cadre
|
Pharmacist
|
106
|
13.8
|
Medical Doctor
|
405
|
52.8
|
Dentist
|
18
|
2.3
|
Nurse officer
|
185
|
24.1
|
Medical lab scientist
|
53
|
6.9
|
Education level
|
Bachelor degree
|
654
|
85.3
|
Master degree
|
113
|
14.7
|
Working experience
(in years)
|
≤ 5
|
298
|
38.9
|
6 – 10
|
222
|
28.9
|
11 – 15
|
116
|
15.1
|
16 – 20
|
50
|
6.5
|
21 – 25
|
42
|
5.5
|
≥26
|
39
|
5.1
|
Health facilities
|
Hospitals
|
557
|
72.6
|
Health centers
|
77
|
10.0
|
Community pharmacies
|
37
|
4.8
|
Community laboratories
|
3
|
0.4
|
Dental clinics
|
4
|
0.5
|
Other clinics
|
89
|
11.6
|
Zones
|
Northern zone
|
80
|
10.4
|
Lake zone
|
84
|
11.0
|
Southern highlands zone
|
153
|
19.9
|
Eastern zone
|
297
|
38.7
|
Western zone
|
39
|
5.1
|
Southern zone
|
48
|
6.3
|
Central zone
|
66
|
8.6
|
The healthcare providers who responded to all twelve (12) knowledge questions were 767. The proportions of the responses to the questions are shown in Table 2. The scores were adopted from other studies [21-22] in which respondents who scored 7-12 questions (81.9%) were considered to have good knowledge and those who scored 0 to 6 questions (18.1%) as having poor or bad knowledge (Figure 2).
Table 2. The proportion of responses on the knowledge of health care providers regarding substandard and falsified medical products
Questions
|
Responses
|
Frequency
|
Percentage
|
What are substandard/falsified medicine, medical devices, and diagnostics products?
|
Are products from an unknown source
|
206
|
26.9
|
Are placebo products
|
54
|
7.0
|
Are orphan products
|
21
|
2.7
|
Are fake medical products
|
486
|
63.4
|
In which areas do these substandard/falsified medical products are available?
|
Urban areas
|
112
|
14.6
|
Rural areas
|
58
|
7.6
|
Both urban and rural
|
531
|
69.2
|
Don't know
|
66
|
8.6
|
The following are some of the medical products that may be falsified or produced as substandard, which ones are most common?
|
lifestyle medicines
|
264
|
34.4
|
Antimalarial and antibiotic medicines
|
204
|
26.6
|
Diagnostics like blood glucose test strip
|
100
|
13.0
|
Protective devices like Face Masks
|
199
|
25.9
|
What factor contribute to the product of your choice above being at high risk of being falsified or being out of standard?
|
Unavailable & unaffordable
|
132
|
17.2
|
Highly demanded
|
466
|
60.8
|
Highly promoted on the internet
|
116
|
15.1
|
Don't Know
|
53
|
6.9
|
The following are the health impact of using substandard and falsified medical products, which one is correct?
|
Increase in mortality and morbidity
|
95
|
12.4
|
Promote drug resistance
|
146
|
19.0
|
Prevalence of diseases increases
|
15
|
2.0
|
All of the above
|
511
|
66.6
|
The following are the economic outcome of SF medical products, select the appropriate answer
|
Increase in productivity
|
116
|
15.1
|
Reduced poverty
|
16
|
2.1
|
Limited resources are wasted
|
407
|
53.1
|
All of the above
|
228
|
29.7
|
From which source did you become aware/learned about substandard and falsified medical products
|
During practice
|
532
|
69.4
|
From university
|
101
|
13.2
|
From conferences
|
38
|
5.0
|
Not aware of it
|
96
|
12.5
|
What factors contribute to the circulation of SF medical products
|
Highly-priced medical products
|
Yes
|
588
|
76.7
|
No
|
179
|
23.3
|
Inadequate control of medical products by the regulatory authority
|
Yes
|
655
|
85.4
|
No
|
112
|
14.6
|
Poor reporting culture of identified SF medical products by HCPs
|
Yes
|
702
|
91.5
|
No
|
65
|
8.5
|
Allowing patients to buy medical products anywhere due to stock out.
|
Yes
|
582
|
75.9
|
No
|
185
|
24.1
|
Lack of knowledge of SF medical products
|
Yes
|
682
|
88.9
|
No
|
85
|
11.1
|
The findings show that 92.5% of Pharmacists, 88.9% of Dentists, 84.9% of Medical laboratory scientists, 81.7% of Medical doctors, and 74.6% of Nurse Officers had good knowledge regarding substandard and falsified medical products. The difference in knowledge within the cadres was statistically significant with P = 0.003 (Figure 3).
The Pharmacist's knowledge regarding substandard and falsified medical products was significantly higher (92.5%) than other cadres (80.2%) with P = 0.003. However, the knowledge of Nurse Officers was significantly lower (74.6%) than other cadres (84.2%) with P= 0.004 (Table 3). The age, experience, professional cadres, and facilities show a positive correlation to the respondents' knowledge of substandard and falsified medical products with P< 0.05 (Table 4).
Table 3. The knowledge between health professional cadres on substandard and falsified medical products
Variable
|
Category
|
Knowledge frequency(n)
|
P value
|
Poor knowledge
|
Good knowledge
|
Pharmacists
|
Pharmacists
|
8 (7.5 %)
|
98 (92.5%)
|
0.003
|
Other cadres
|
131 (19.8%)
|
530(80.2%)
|
Medical doctors
|
Medical doctors
|
74 (18.3%)
|
331(81.7%)
|
0.925
|
Other cadres
|
65 (18.0%)
|
297 (82.0%)
|
Dentists
|
Dentists
|
2 (11.1%)
|
16 (88.9%)
|
0.755
|
Other cadres
|
137 (18.3%)
|
612 (81.7%)
|
Nurse officers
|
Nurse officers
|
47 (25.4%)
|
138 (74.6%)
|
0.004
|
Other cadres
|
92 (15.8%)
|
490 (84.2%)
|
Medical laboratory scientists
|
Medical laboratory scientists
|
8 (15.1%)
|
45 (84.9%)
|
0.589
|
Other cadres
|
131 (18.3%)
|
583 (81.7%)
|
Notes: P is significant at <0.05, n is the number of participants
Table 4. Factors associated with the knowledge of the respondents on substandard and falsified medical products
Variables
|
Category
|
Knowledge of SF medical products
|
P-Value
|
Poor n (%)
|
Good n (%)
|
Age groups (years)
|
20-29
|
14 (10.1)
|
124 (89.0)
|
<0.001
|
30-39
|
55 (15.1)
|
309 (84.9)
|
40-49
|
52(28.3)
|
132(71.7)
|
50-59
|
14 (21.2)
|
52 (78.8)
|
≥ 60
|
4(26.7)
|
11(73.3)
|
Sex
|
Males
|
86 (18.1)
|
390 (81.9)
|
1.000
|
Females
|
53 (18.2)
|
238 (81.8)
|
Professionals
|
Pharmacists
|
8 (7.5)
|
98 (92.5)
|
0.003
|
Medical Doctors
|
74 (18.3)
|
331 (81.7)
|
Dentists
|
2 (11.1)
|
16 (88.9)
|
Nurse officers
|
47 (25.4)
|
138 (74.6)
|
Medical laboratory scientists
|
8 (15.1)
|
45 (84.9)
|
Education level
|
Bachelor degree
|
124 (19.0)
|
530 (81.0)
|
0.185
|
Master degree
|
15 (13.3)
|
98 (86.7)
|
Experience (years)
|
≤5
|
32 (10.7)
|
266 (89.3)
|
0.001
|
6-10
|
42 (18.9)
|
180 (81.1)
|
11-15
|
32 (27.6)
|
84 (72.4)
|
16-20
|
13 (26.0)
|
37 (74.0)
|
21-25
|
10 (23.8)
|
32 (76.2)
|
≥ 26
|
10 (25.6)
|
29 (74.4)
|
Zones
|
Northern zone
|
15 (18.8)
|
65 (81.3)
|
0.053
|
Lake zone
|
21 (25.0)
|
63 (75.0)
|
Southern highland zone
|
25 (16.3)
|
128 (83.7)
|
Eastern zone
|
40 (13.5)
|
257 (86.5)
|
Western zone
|
10 (25.6)
|
29 (74.4)
|
Southern zone
|
13 (27.1)
|
35 (72.9)
|
Central zone
|
15 (22.7)
|
51 (77.3)
|
Health facilities
|
Hospitals
|
101 (18.1)
|
456 (81.9)
|
0.029
|
Health centers
|
21 (27.3)
|
56 (72.7)
|
Community pharmacies
|
1 (2.7)
|
36 (97.3)
|
Community laboratories
|
0
|
3 (100)
|
Dental clinics
|
0
|
4(100)
|
Other clinics
|
16(18)
|
73 (82)
|
Notes: P is significant at <0.05
On the other hand, the healthcare providers who responded to all twelve (12) practice questions regarding substandard and falsified medical product identification and reporting were 767. The proportions of the responses to the questions are shown in Table 5. Participants who scored 7-12 questions (71.2%) were considered to have good practice and 0 to 6 (28. 8%) as having bad practice (Figure 4).
Table 5. The proportion of responses on identifying and reporting practice of substandard and falsified medical products
Questions
|
Responses
|
Frequency
|
Percent
|
What is the source of information you heard about the presence of substandard and falsified medicines, medical devices, and diagnostic tools?
|
Media and advertising materials
|
313
|
40.8
|
Patients and Colleagues
|
171
|
22.3
|
Encountered in routine work
|
221
|
28.8
|
Never heard
|
62
|
8.1
|
How do you identify substandard/falsified medicine/medical devices/diagnostics from the original?
|
Through label
|
Yes
|
621
|
81.0
|
No
|
146
|
19.0
|
Through packaging materials
|
Yes
|
578
|
75.4
|
No
|
189
|
24.6
|
Through expire date
|
Yes
|
565
|
73.7
|
No
|
202
|
26.3
|
Through cost/price of medical products
|
Yes
|
462
|
60.2
|
No
|
305
|
39.8
|
Through package insert( leaflet)
|
Yes
|
455
|
59.3
|
No
|
312
|
40.7
|
Through unexpected adverse reactions to a few patients after using the same medical product of the same batch.
|
Yes
|
610
|
79.5
|
No
|
157
|
20.5
|
Wrong diagnosis through laboratory results
|
Yes
|
524
|
68.3
|
No
|
243
|
31.7
|
Through reporting treatment outcomes to regulatory authorities
|
Yes
|
610
|
79.5
|
No
|
157
|
20.5
|
(When/if) you encounter SF medical products (do you/will you) report them?
|
Yes
|
665
|
86.7
|
No
|
102
|
13.3
|
Which form (do you use/will you use) to report them to the regulatory authority?
|
Yellow form
|
273
|
35.6
|
Green form
|
36
|
4.7
|
Blue form
|
45
|
5.9
|
Don't know
|
413
|
53.8
|
In your opinion, what is the current situation regarding the circulation of substandard and falsified medicine, medical devices, and diagnostics in Tanzania?
|
It is a big problem
|
203
|
26.5
|
Substandard and falsified medical products are not existing
|
13
|
1.7
|
The products are existing but not identified and reported
|
344
|
44.8
|
Detection of SF medical products is increasing but reporting is a problem.
|
207
|
27.0
|
In which action do you suggest can help to reduce the penetration of substandard and falsified medical products in our country?
|
Through public sensitization to raise their awareness against SF medical products.
|
146
|
19.0
|
Adherence to ethics and reporting the identified SF medical products
|
72
|
9.4
|
The strictness of entry points(Borders)
|
46
|
6.0
|
All of the above
|
503
|
65.6
|
Moreover, the findings show that 84% of Pharmacists, 75.5% of Medical laboratory scientists, 73% of Nurse Officers, 66.7% of Dentists, and 66.7% of Medical doctors had good practice in substandard and falsified medical product identification and reporting. The difference in practice within the cadres was statistically significant with P = 0.009 (Figure 5).
In between the cadres, the practice of Pharmacists was significantly higher (84%) compared to other cadres (69.1%) with P = 0.002. However, the practice among Medical doctors was significantly lower (66.7%) than for other cadres (76.2%) with P = 0.004 (Table 6). The age, experience, and professional cadres revealed a positive association in identifying and reporting substandard and falsified medical products among the respondents with P < 0.05 (Table 7). The knowledge of the respondents regarding substandard and falsified medical products was found to affect the respondents’ practice of identifying and reporting substandard and falsified medical products with P< 0.001 (Figure 6).
Table 6. Practice in identifying and reporting substandard and falsified medical products between the cadres.
Variable
|
Category
|
Practice frequency (n)
|
P value
|
Bad practice
|
Good practice
|
Pharmacists
|
Pharmacists
|
17 (16.0%)
|
89 (84.0%)
|
0.002
|
Other cadres
|
204 (30.9%)
|
457(69.1%)
|
Medical doctors
|
Medical doctors
|
135 (33.3%)
|
270 (66.7%)
|
0.004
|
Other cadres
|
86 (23.8%)
|
276 (76.2%)
|
Dentists
|
Dentists
|
6 (33.3%)
|
12 (66.7%)
|
0.792
|
Other cadres
|
215 (28.7%)
|
534 (71.3%)
|
Nurse officers
|
Nurse officers
|
50 (27.0%)
|
135 (73.0%)
|
0.577
|
Other cadres
|
171 (29.4%)
|
411 (70.6%)
|
Medical laboratory scientists
|
Medical laboratory scientists
|
13 (24.5%)
|
40 (75.5%)
|
0.533
|
Other cadres
|
208 (29.1%)
|
506 (70.9%)
|
Notes: P is significant at <0.05
Table 7 Factors associated with identifying and reporting practice of substandard and falsified medical products
Variable
|
Category
|
Practice handling SF products
|
P-value
|
Bad n (%)
|
Good n (%)
|
Age (years)
|
20 – 29
|
31 (22.5)
|
107 (77.5)
|
< 0.001
|
30 – 39
|
83 (22.8)
|
281 (77.2)
|
40 – 49
|
70 (38.0)
|
114 (62.0)
|
50 – 59
|
29 (43.9)
|
37 (56.1)
|
≥ 60
|
8 (53.3)
|
7 (46.7)
|
Sex
|
Males
|
126 (26.5)
|
350 (73.5)
|
0.071
|
Females
|
95 (32.6)
|
196 (67.4)
|
Health facilities
|
Hospitals
|
175( 31.4)
|
382 (68.6)
|
0.099
|
Health centres
|
20 (26.0)
|
57 (74.0)
|
Community Pharmacies
|
6 (16.2)
|
31 (83.8)
|
Community laboratories
|
1 (33.3)
|
2 (66.7)
|
Dental clinics
|
0
|
4 (100)
|
Other clinics
|
17 (21.3)
|
70 (78.7)
|
Zone
|
Northern zone
|
31 (38.8)
|
49 (61.3)
|
0.237
|
Lake zone
|
28 (33.3)
|
56 (66.7)
|
Southern Highland zone
|
37 (24.2)
|
116 (75.8)
|
Eastern zone
|
79 (26.6)
|
218 (73.4)
|
Western zone
|
14 (35.9)
|
25 (64.1)
|
Southern zone
|
13 (27.1)
|
35 (72.9)
|
Central zone
|
19 (28.8)
|
47 (71.2)
|
Professional cadre
|
Pharmacists
|
17 (16.0)
|
89(84.0)
|
0.009
|
Medical doctors
|
135 (33.3)
|
270 (66.7)
|
Dentists
|
6 (33.3)
|
12 (66.7)
|
Nurse officers
|
50 (27.0)
|
135(73.0)
|
Medical laboratory scientists
|
13 (24.5)
|
40 (75.5)
|
Experience(years)
|
≤ 5
|
67 (22.5)
|
231(77.5)
|
< 0.001
|
6-10
|
56 (25.2)
|
166 (74.8)
|
11-15
|
46 (39.7)
|
70 (60.3)
|
16-20
|
16 (32.0)
|
34 (68.0)
|
21-25
|
17 (40.5)
|
25 (59.5)
|
≥ 26
|
19 (48.7)
|
20 (51.3)
|
Education level
|
Bachelor degree
|
190 (29.1)
|
464 (70.9)
|
0.738
|
Master degree
|
31 (27.4)
|
82 (72.6)
|
Variable
|
Category
|
Practice on handling SF products
|
P value
|
Bad n (%)
|
Good n (%)
|
Age (years)
|
20 – 29
|
31 (22.5)
|
107 (77.5)
|
< 0.001
|
30 – 39
|
83 (22.8)
|
281 (77.2)
|
40 – 49
|
70 (38.0)
|
114 (62.0)
|
50 – 59
|
29 (43.9)
|
37 (56.1)
|
≥ 60
|
8 (53.3)
|
7 (46.7)
|
Sex
|
Males
|
126 (26.5)
|
350 (73.5)
|
0.071
|
Females
|
95 (32.6)
|
196 (67.4)
|
Health facilities
|
Hospitals
|
175( 31.4)
|
382 (68.6)
|
0.099
|
Health centers
|
20 (26.0)
|
57 (74.0)
|
Community Pharmacies
|
6 (16.2)
|
31 (83.8)
|
Community laboratories
|
1 (33.3)
|
2 (66.7)
|
Dental clinics
|
0
|
4 (100)
|
Other clinics
|
17 (21.3)
|
70 (78.7)
|
Zone
|
Northern zone
|
31 (38.8)
|
49 (61.3)
|
0.237
|
Lake zone
|
28 (33.3)
|
56 (66.7)
|
Southern Highland zone
|
37 (24.2)
|
116 (75.8)
|
Eastern zone
|
79 (26.6)
|
218 (73.4)
|
Western zone
|
14 (35.9)
|
25 (64.1)
|
Southern zone
|
13 (27.1)
|
35 (72.9)
|
Central zone
|
19 (28.8)
|
47 (71.2)
|
Professional cadre
|
Pharmacists
|
17 (16.0)
|
89(84.0)
|
0.009
|
Medical doctors
|
135 (33.3)
|
270 (66.7)
|
Dentists
|
6 (33.3)
|
12 (66.7)
|
Nurse officers
|
50 (27.0)
|
135(73.0)
|
Medical laboratory scientists
|
13 (24.5)
|
40 (75.5)
|
Experience(years)
|
≤ 5
|
67 (22.5)
|
231(77.5)
|
< 0.001
|
6-10
|
56 (25.2)
|
166 (74.8)
|
11-15
|
46 (39.7)
|
70 (60.3)
|
16-20
|
16 (32.0)
|
34 (68.0)
|
21-25
|
17 (40.5)
|
25 (59.5)
|
≥ 26
|
19 (48.7)
|
20 (51.3)
|
Education level
|
Bachelor degree
|
190 (29.1)
|
464 (70.9)
|
0.738
|
Master degree
|
31 (27.4)
|
82 (72.6)
|
Notes: p is significant at <0.05