Females constituted the vast majority of the surveyed doctors (316, 84.7%). Most of the respondent doctors were registrars (298, 79.9%), while those with clinical experience ranging from 1 to 5 amounted to (317, 85.0%). Most of the PHC centers (313, 83.9%) were located in urban areas. The majority of the surveyed doctors (301, 80.7%) were stationed in Khartoum state, while the rest were in Gezira state, as displayed by Table (2). Within Khartoum state, most of the surveyed doctors were in Khartoum, Omdurman, Bahri localities, Figure (1).
Table (2): Demographic characteristic of the practicing family medicine doctors, (n = 373).
Variables | Frequency | Percent (%) |
Residence |
Khartoum state | 301 | 80.7 |
Gezira State | 72 | 19.3 |
Gender |
Male | 57 | 15.3 |
Female | 316 | 84.7 |
Job title |
Registrar | 298 | 79.9 |
Consultant/Physician | 75 | 20.1 |
Clinical experience |
1–5 years | 317 | 85.0 |
6–10 years | 51 | 13.7 |
11–15 years | 3 | 0.8 |
More Than 16 years | 2 | 0.5 |
PHC location |
Rural | 60 | 16.1 |
Urban | 313 | 83.9 |
Investigation into CPG implementation revealed that most of the practicing family medicine doctors (367, 98.4%) were following the guidelines in their practice. Of those, (283, 77.1) were regularly following the updated editions of the guidelines. The national (Sudanese) and the international guidelines were followed by (241, 65.7%) of the respondents, Table (3). More than half of the practicing family medicine doctors (256, 68.6%) reported that they have received regular training programs, as displayed in Figure (2).
Table (3): Distribution of the respondents according to their implementation of the clinical practice guidelines.
Variables | Frequency | Percent (%) |
Implementation of the existing clinical guidelines in clinical practice, (n = 373). |
Yes | 367 | 98.4 |
No | 6 | 1.6 |
Type of the Followed guidelines, (n = 367). |
International guidelines | 67 | 18.3 |
Local Sudanese guidelines | 59 | 16. 0 |
Both | 241 | 65.7 |
Following the updated editions of the guidelines, (n = 367). |
Yes | 283 | 77.1 |
No | 84 | 22.9 |
Despite the high adherence and implementation rate of the guidelines, a variety of barriers were expressed by the respondents. Doctors rated guideline inaccessibility (235, 63.0%) as the most frequent barrier. Sudanese guidelines were an example to guideline inaccessibility as stated by the surveyed doctors. Regulatory changes of the guideline’s recommendation (215, 57.6%), large volume of the guideline information (186, 49.9%) and lack of outcome expectancy (150, 40.2%), lack of agreement with specific guidelines (149, 39.9%), lack of Self-Efficacy (120, 32.2%) and lack of agreement with guidelines in general (81, 21.7%) were also barriers to adherence to the guidelines, as displayed in Table (4).
Table (4): Barriers to adherence to the clinical practice guidelines, (n = 373).
Barriers | Frequency | Percent (%) |
Guideline inaccessibility | 235 | 63.0 |
Regulatory changes of the guideline’s recommendation | 215 | 57.6 |
Large volume of the guideline information | 186 | 49.9 |
Lack of outcome expectancy | 150 | 40.2 |
Lack of agreement with specific guidelines | 149 | 39.9 |
Lack of Self-Efficacy | 120 | 32.2 |
Lack of agreement with guidelines in general | 81 | 21.7 |
Regarding barriers to implementation of clinical practice guidelines, services unavailability and inaccessibility, health insurance factors (services not covered by the health insurance) and patient factors were the most frequent barriers to guideline implementation, amounting to (325, 87.1%), (313, 83.9%) and (303, 81.2%) respectively, Table (5). Service cost (298, 79.9%), lack of regular training programs (298, 79.9%), lack of local PHC treatment protocol or guidelines (288, 77.2%), lack of continuity in the comprehensive care process (235, 63.0%) and lack of time (213, 57.1%) were also reported as barriers to guideline implementation, as displayed in Table (5).
Table (5): Barriers to implementation of the clinical practice guidelines, (n = 373).
Barriers | Frequency | Percent (%) |
Services unavailability and inaccessibility | 325 | 87.1 |
Health insurance factors (services not covered by insurance) | 313 | 83.9 |
Patient factors (financial issues or believes) | 303 | 81.2 |
Service cost | 298 | 79.9 |
Lack of regular training programs | 298 | 79.9 |
Lack of local PHC treatment protocol or guidelines | 288 | 77.2 |
Lack of continuity in the comprehensive care process | 235 | 63.0 |
Lack of time | 213 | 57.1 |
Investigation regarding respondents’ perception of clinical practice in Sudan revealed that; most of the respondents (277, 74.3%) noted that practice in Sudan doesn’t allow implementation of the guidelines. Moreover, most of the doctors consider training programs (340, 91.2%) and guidelines adherence (365, 97.9%) improve clinical practice. More than half of the practicing family medicine doctors (208, 55.8%) reported that they prefer to follow the international guidelines rather than the local Sudanese guidelines, Table (6)
Table (6): Distribution of the respondents according to their perception toward the clinical practice guidelines, (n = 373).
Variables | Frequency | Percent (%) |
Practice in Sudan doesn’t allow implementation of the clinical practice guidelines. |
Yes | 277 | 74.3 |
No | 96 | 25.7 |
The post-graduation training programs improve clinical practice. |
Yes | 340 | 91.2 |
No | 33 | 8.8 |
Adherence to the guidelines improves the clinical practice. |
Yes | 365 | 97.9 |
No | 8 | 2.1 |
Preferred guidelines: |
Local (Sudanese) guidelines | 165 | 44.20 |
International guidelines | 208 | 55.80 |
Residence of the respondents, job title, experience and PHC location revealed no statistically significant association when tested in cross tabulation with the CPG implementation, p value = 0.099, 0.257, 0.563 and 0.654, respectively, Table (7).
Guideline implementation revealed significant association when tested in cross tabulation with following the updated editions of the guidelines and the type of the followed guideline, p value = 0. 000 and 0. 000, respectively, Table (7). Training programs revealed no significant association when tested in cross tabulation with the guideline implementation, p value = 0. 280, as displayed in Table (7).
Table (7): Association between demographic characteristics of the participants and implementation of the clinical practice guidelines, (n = 373).
Variables | Guideline implementation | P-value |
Yes | No |
Residence: |
Khartoum state | 295 | 6 | 0.099 |
Gezira state | 72 | 0 |
Job titles: |
Registrar | 292 | 6 | 0.257 |
Consultant/Physician | 75 | 0 |
Clinical experience: |
0–5 Years | 313 | 4 | 0.563 |
6-10Years | 49 | 2 |
11–15 Years | 3 | 0 |
More Than 16 Years | 2 | 0 |
PHC location: |
Rural | 59 | 1 | 0.654 |
Urban | 308 | 5 |
Follow the updated editions of the guidelines: |
Yes | 283 | 0 | 0. 000 |
No | 81 | 3 |
Type of the followed guidelines: |
International guidelines | 67 | 0 | 0. 000 |
Local Sudanese guidelines | 59 | 0 |
Both of them | 240 | 1 |
Training programs: |
Yes | 253 | 3 | 0. 280 |
No | 114 | 3 |
A binary logistic regression analysis was conducted to assess the relationship between guideline implementation and the respondents’ residence, job title and training programs. The reliability of the model was 99.0%. The model perfectly predicted guideline implementation.
Receiving training programs which contributed to the model by 1.130 was statistically significant with a p-value of 0.000. The training programs affect the guideline implementation positively by 3.095 times, (95% CI: 1.877–5.103). Respondents’ opinion regarding the benefit of the training programs in improving the clinical practice which was contributed to the model by 0.222 was not statistically significant with a p-value of 0.349. It is predicted to affect the guideline implementation positively by 1.249 times. Residence and job title were not statically significant with a p-value of respectively 0.436 and 0.075. Residence affects the guideline implementation by 0.963 times, (95% CI: 0.875–1.059) and job title by 0.535 times, (95% CI: 0.269–1.064), as displayed by Table (8).
Table (8): Logistic regression model predicting guideline implementation based on the respondent’s residence, job title and training programs, (n = 373).
Variables in the Equation | B | S.E | Wald | df | p-value | Odds Ratio | 95% C.I. for OR |
| | | | | | | Lower | Upper |
Residence | 0.038 | 0.049 | .606 | 1 | 0.436 | 0.963 | 0.875 | 1.059 |
Job title | 0.625 | 0.351 | 3.175 | 1 | 0.075 | 0.535 | 0.269 | 1.064 |
Training programs | 1.130 | 0.255 | 19.603 | 1 | 0.000 | 3.095 | 1.877 | 5.103 |
Training programs improve clinical practice | 0.222 | 0.237 | 0.876 | 1 | 0.349 | 1.249 | 0.784 | 1.988 |
Constant | 1.380 | 0.225 | 37.682 | 1 | 0.000 | 0.252 | | |
A binary logistic regression analysis was conducted to assess the effect of the barriers on the guideline implementation. The reliability of the model was 76.0%. Patient factors, services unavailability, lack of local PHC treatment protocol and health insurance factors were all not significant with a p-value of 0.348, 0.997, 0.611 and 0.300. Patient factors affect guideline implementation by 2.324 times (95% CI: 0.399–13.531). Lack of local PHC treatment protocol affects guideline implementation by 1.604 times (95% CI: 0.260–9.897). Health insurance factors affect guideline implementation by 2.661times (95% CI: 0.418–16.946), as displayed by Table (9).
Table (9): Logistic regression model predicting guideline implementation based on the barriers, (n = 373).
Variables in the Equation | B | S.E | Wald | df | p-value | Odds Ratio | 95% C.I. for OR |
| | | | | | | Lower | Upper |
Patient factors | 0.843 | 0.899 | 0.881 | 1 | 0.348 | 2.324 | 0.399 | 13.531 |
Services unavailability | -17.718- | 5631.819 | 0.000 | 1 | 0.997 | 0.000 | 0.000 | . |
Lack of local PHC treatment protocol | 0.473 | 0.928 | 0.259 | 1 | 0.611 | 1.604 | 0.260 | 9.897 |
Health insurance factors | 0.979 | 0.945 | 1.074 | 1 | 0.300 | 2.661 | 0.418 | 16.946 |
Constant | -4.510- | 0.601 | 56.295 | 1 | 0.000 | 0.011 | | |