Direct Costs for the Management of Road Traffic Accident Casualties in Six Hospitals. Case of Mbandaka City in the Democratic Republic of Congo ()
1. Introduction
Trauma is a major issue, both in developing and developed countries. Globally, road traffic accidents account for 25% of all trauma-related deaths [1]. They are responsible for 12% of the global burden of disease and are the third leading cause of death in the world. Road Traffic Accidents are one of the top neglected issues in public health despite their high contribution to mortality and morbidity globally. Road traffic accidents are considered the 8th cause of mortality worldwide [2] leading to deaths in children and adults ranking above tuberculosis and malaria in 2016 [2]. About 50 million road traffic injuries (RTIs) are reported yearly with over 1.3 million mortalities associated with these RTIs yearly [1] [3]. While Road Traffic Accidents occur globally, developing countries, notably in Southeast Asia and Africa, consistently report high numbers of Road Traffic Accidents. Road traffic injuries -associated mortality in Africa is estimated as 26.6 per 100,000 population and considered the highest globally and is three times that of Europe [2].
In Ghana, road accidents significantly contribute to mortality and morbidity, particularly affecting individuals aged 5 to 29. Road accidents represent a considerable physical and economic burden for individuals, households, and governments, especially in African countries [3].
They contribute significantly to the burden of morbidity as well as mortality in the Democratic Republic of Congo.
2. Methodology
This study was carried out in the city of Mbandaka the Democratic Republic of Congo, using hospital data on motor vehicle crashes registered in six hospitals (public and private) of the provincial health division of Mbandaka. It covers a year and a half period, from January 1, 2023, to June 30, 2024. The study was in form of an analytical cross-sectional study focusing on the Hospital register. Six hospitals were involved in our study, namely: The General Reference Hospital of Wangata, the General Reference Hospital of Mbandaka, Bolenge Hospital, the Military Hospital, the Jourdain Medical Center, and the TABE Medical Center.
The sampling was comprehensive, including all reported road crash cases. Data were collected using a pro-forma data sheet. Data analysis was performed with SPSS version 23 software (SPSS, Armonk, NY). The P-value was determined as the statistical assessment.
3. Results
Table 1. Distribution of victims by age.
Ages (in years) |
Percentage |
Percentage |
1 to 17 |
81 |
26.8 |
18 to 23 |
46 |
15.2 |
Greater than 23 |
175 |
57.9 |
Minimum |
1 |
1 |
Maximum |
|
78 |
Means |
|
29.2 |
Standard déviation |
|
16.9 |
Total |
302 |
100 |
Table 1 indicates that those aged over 23 had more victims of road traffic accidents (175 cases or 57.9%) compared to those aged between 18 and 23 years (15.2%), while victims aged between 1 and 17 years represent a proportion of 15.2%.
Table 2. Distribution of victims by gender.
Sex |
Frequency |
Percentage |
Female |
140 |
46.4 |
Male |
162 |
53.6 |
Total |
302 |
100 |
Male victims are predominantly represented (53.6%) compared to female victims (46.4%). (See Table 2)
Table 3. Distribution of accident victims according to the means used to reach the hospital.
Means used to get to the hospital |
Frequency |
Percentage |
Medicalized |
3 |
1.0 |
Non-medicalized |
299 |
99.0 |
Total |
302 |
100.0 |
Table 3 shows us that most victims arrived at the hospital using non-medicalized means (99%) compared to those who used medicalized transport (1%).
Table 4. Distribution of accident victims according to the mode of admission to the hospital.
Admission mode |
Frequency |
Percentage |
Unreferred patient |
288 |
95.4 |
Referred patient |
14 |
4.6 |
Total |
302 |
100.0 |
Non-reference was the most observed mode of admission compared to reference, with 95.4% and 4.6% respectively. (See Table 4)
According to Table 5, we observe that the Wangata general reference hospital (HGR)received a large proportion of the victims (33.8%), followed respectively by the Jourdain medical center (27.2%), TABE medical center (12.3%), Bolenge general reference hospital (9.9%), Mbandaka general reference hospital (8.9%), and the Military hospital (7.9%). The proportion of road traffic accidents in the six health facilities is 0.71% while the fatality rate is 12.3%.
Table 5. Distribution of accident victims according to frequency and lethality.
Name of the medical facility |
Number of hospitalized patients |
Victims of road traffic accidents |
Deaths related to road traffic accidents |
Lethality related to road accidents |
Proportion of the injured |
JourdainMedical Center |
1227 |
82 |
1 |
|
|
Centre Médicale TABE |
499 |
37 |
20 |
|
|
HGR Bolenge |
4251 |
30 |
3 |
|
|
HGR Mbandaka |
6490 |
27 |
3 |
|
|
HGR Wangata |
7575 |
102 |
7 |
|
|
Military Hospital |
22753 |
24 |
3 |
|
|
Total |
42795 |
302 |
37 |
12.3 |
0.71 |
Table 6. Distribution of accident victims according to emergency arrival.
Emergency |
Frequency |
Percentage |
No |
27 |
8.9 |
Yes |
275 |
91.1 |
Total |
302 |
100.0 |
Table 7. Distribution of accident victims by types of injuries.
Lesions types |
Frequency |
Percentage |
Pain in the right leg |
1 |
0.3 |
Skinning |
19 |
6.3 |
Fractures |
228 |
75.5 |
Left shoulder Dislocation |
1 |
0.3 |
Wound |
44 |
14.6 |
TBI |
9 |
3.0 |
Total |
302 |
100.0 |
In most cases, the patients arrived in an emergency (91.1%). (See Table 6)
Fractures were more commonly observed than other injuries (75.5%). (See Table 7)
Table 8. Distribution of accident victims according to the location of the fracture.
Fractures localization |
Frequency |
Percentage |
Lower Limb |
174 |
76.3 |
Upper limb |
54 |
23.7 |
Total |
228 |
100.0 |
The lower limbs were the most affected by fractures (76.3%) compared to the upper limbs (23.7%). (See Table 8)
Table 9. Distribution of victims according to the payment method for medical care.
Payment method |
Frequency |
Percentage |
Direct payment |
276 |
91.4 |
Indirect payment (mutual insurance) |
26 |
8.6 |
Total |
302 |
100.0 |
Most victims opted for direct payment (91.4%) compared to 8.6% for indirect payment. (See Table 9)
Table 10. Distribution of accident victims according to the cost of care.
Total cost of care |
Frequency |
Percentage |
≥50 |
196 |
64.9 |
<50 |
106 |
35.1 |
Total |
302 |
100.0 |
Patients who spent less than 50 US dollars were predominantly represented (64.9%). (See Table 10)
Table 11. Estimated distribution of direct costs.
Costs |
Total costs ($) |
Means($) |
Standard deviation ($) |
Min($) |
Max($) |
Imaging |
2084 |
6.9 |
15.8 |
0 |
85.7 |
Medications |
5785 |
19.2 |
21.6 |
0 |
267.9 |
Procedures |
4761 |
15.8 |
1.6 |
0 |
137.1 |
Hospitalization |
4139 |
13.7 |
63.7 |
0 |
10.71 |
Cout total |
16769 |
55.5 |
|
|
|
$ = US dollars, Standard deviation of the average, Min = minimum cost, Max = maximum cost. The table above indicates that the cost of medications was high, followed by the cost of procedures, the cost of hospitalization, and the cost of imaging with respective amounts of $5785, $4761, $4139, and $2084. (See Table 11)
Table 12. Distribution of accident victims according to the duration of hospital stay.
Length of Stay (in days) |
Frequency |
Percentage |
<12 |
11 |
3.6 |
≥ 12 |
291 |
96.4 |
Total |
302 |
100.0 |
The victims who stayed in the hospital for more than 12 days represent a large proportion (96.4%) compared to those who stayed for less than 12 days. (See Table 12)
Table 13. Associations between length of stay and other variables.
|
Length of hospital stay (in days) |
|
|
Variables |
>12 |
≤12 |
OR |
P-value |
belonging |
|
|
|
|
Public |
10 (5.5%) |
173 (94.5%) |
6.8 |
0.036 |
Private |
1 (0.8%) |
118 (99.2%) |
|
|
Payment method |
|
|
|
Direct payment |
8 (2.9%) |
268 (97.1%) |
0.22 |
0.024 |
Indirect payment (mutual) |
3 (11.5%) |
23 (88.5%) |
|
|
Brought in urgently |
|
|
|
No |
2 (7.4%) |
25 (92.6%) |
2.4 |
0.274 |
Yes |
9 (3.3%) |
266 (96.7%) |
|
|
Type of lesion |
|
|
|
Fractures |
9 (3.9%) |
219 (96.1%) |
1.5 |
0.2 |
2 (2.7%) |
72 (97.3%) |
|
|
|
Table 13 indicates a significant association between the length of hospital stay and the type of hospital (private and public structures) and the mode of payment (direct and indirect).
4. Discussion
This study examined the crash data of a year and a half in the city of Mbandaka (DRC) using hospital crash data. This study examined hospital crash data from a year and a half in the city of Mbandaka (DRC) using hospital crash data. The lethality is 12.3% with an overall mortality of 0.71% (Table 5). This lethality is theoretically higher than that found by Kourouma. [4] in Guinea (1.2%). In Nepal, the prevalence of road traffic accidents was 9.58% [5]. The incidence rate of mortality for road traffic accident victims was 7.34 per 10,000 person-hours in Ethiopia [6].
We observed that out of 302 patients who were victims of traffic accidents, the majority, 175 patients (57.9%), were in the age group older than 23 years (29.2 ± 16.9 years) with extremes of 1 and 78 years (Table 1). In Brazzaville, the average age was 43.5 ± 2.7 years, and the most represented age group was 25 to 35 years (33.87%) [7]. In N’Djamena, the average age was 28.5 years with extremes of 16 and 75 years [8]. In Lebanon, the majority of RTIs (44.4%) were recorded among those aged between 15 and 29 years old [9].
Table 2 indicates that men represent a large proportion (53.6). Our results, although lower, are similar to those found in N’Djamena, where the male sex represented 77% and the sex ratio was 3.4 [8]. The predominance of the male sex was also found in Ethiopia and Nepal [5] [10].
Most victims of road traffic accidents were not referred (95.4%). The prevalence of road traffic accidents is 0.7%. This prevalence is different from that found in Nepal (9.58) [5].
In most cases, patients arrived in emergency (91.1%). Our observation, though higher, is consistent with that of the northeastern Democratic Republic of Congo in Butembo, where 80.4% of patients arrived at the emergency department [11].
The lesions mainly consisted of fractures, and fractures of the lower limbs were common (Table 7 and Table 8). Our result is similar to that found by Boubacar [12]. Kalli Moussa’s study revealed that the less severe injuries (scrapes, superficial wounds) were the most numerous [8]. In Cameroon, the trauma of limb without bone injury (15.9%) was the most commonly encountered [13]. In Nigeria, soft tissue injury only represented 71.9% [1].
Direct payment for care is the most observed method (91.4%) as indicated in Table 9. Some studies across Africa have found similar results to ours, such as in Morocco and Burkina Faso [14] [15].
In our study series, 96.4% had a length of stay ≥ 12 days (Table 13). There is a statistically significant association between the length of hospital stay and the type of facility as well as the method of payment (p < 0.05) whereas the fact of arriving at the hospital in emergency and the length of stay. Seydou Diandio Traoré observed in his study that most road traffic injury victims did not exceed 1 day [16]. Christian Térance found that the average length of hospitalization was 9.7 days [17].
Patients who spent less than 50 US dollars were predominantly represented (64.9%) (Table 10). The average care costs in different facilities are not statistically different (F: 0.224, p = 0.95). The total cost of care is $16,769 with an average total cost of $56 (Table 11). In Ghana, the total direct cost of road traffic accident care at St. Joseph Hospital was approximately $164,483.44 US [3].
5. Conclusion
We conducted a cross-sectional study on the profiles of road accident victims. Appropriate preventive measures such as wearing helmets for motorcycles, wearing seat belts, and complying with traffic laws should be promoted upstream to reduce the incidence related to this global scourge that plunges many families into despair.
Conflicts of Interest
The authors declare no conflicts of interest.