Epidemiological Profile of the Victims Involved in Road Traffic Accidents (RTA) and ICD-10 Classification Attending an Emergency Department: A Descriptive Study

Abstract

Road traffic injuries are the leading cause of death for children and young adults aged 5-29 years. They cause approximately 1.3 million deaths every year, with 20 to 50 million more people suffering nonfatal injuries and many incurring a disability as a result of their injury. A retrospective record-based descriptive study was performed to analyze the epidemiological profile of the patients attending with road traffic accidents (RTA) to emergency/casualty department in a tertiary care hospital. The purposive sample from the last 7 months with those affected from RTA cases came to casualty and undergone treatment during the study duration and the exclusion criteria were brought dead patients. Out of 397 victims, 309 (77.8%) were male and 88 (22.2%) were female and mean age with SD 37.19 ± 13.9 years. Majority 143 (36.0%) had self-fall, 64 (16.1%) 2-wheeler vs pedestrian, 63 (15.9%) 2-wheelers vs 4-wheeler, 55 (13.9%) under 2-wheelers vs 2-wheeler. Majority were happened on Saturday 60 (15.1%), Sundays 71 (17.9%) and the rest on an average of 50 incidents in a day; out of them, the incident happened at evening 98 (24.7%) night 136 (34.2%) morning 109 (27.5%), and in the afternoon time 54 (13.6%), respectively. Accidents have male predominance, with more victims from adults and middle age 21-40 years. Most common category of the victim was motorcycle rider, followed by pedestrians, and as per ICD-10 classification, the common mechanism of incident happened was motorcycle rider noncollision transport accident (Code: V28).

INTRODUCTION

Road traffic injury (RTI) can be defined as, “An event that occurs on a way or street open to public traffic; resulting in one or more persons being injured or killed, where at least one moving vehicle is involved.”[1] Number of “traffic accidents” in the country have increased from 3,68,828 in 2020 to 4,22,659 in 2021. (The rate of deaths in road accidents per thousand vehicles has also increased from 0.45 in 2020 to 0.53 in 2021.)[2] Road accidents are a significant public health problem, causing 1.5 million deaths and 5 million injuries annually worldwide. In India, road traffic accidents are one of the leading causes of death, disability, and hospitalization.[3] In spite of many control measures adopted, fatalities continue to rise, especially in low- and middle-income countries, which account for 90% of all road traffic casualties. Road traffic injuries are the leading cause of death globally and the principal cause of death in the age group of 15 to 49 years. Every year, the lives of approximately 1.3 million people are cut short globally as a result of a road traffic crash.[4] However, the Indian subcontinent saw a decrease in the number of accidents and fatalities during 2020 compared to the previous year 2019, due to many possible factors such as better traffic management, implementation of the new Motor Vehicle Act and COVID-19-induced lockdown.[5] According to NCRB report on accidents and time of occurrence-wise analysis of traffic accidents reveal that the maximum number of “traffic accidents” have taken place during 18:00 hrs–21:00 hrs and 15:00 hrs–18:00 hrs, accounting for 19.9% (84,221) and 17.6% (74,241) of total traffic accidents (4,22,659), respectively, during the year 2021.[4] RTIs will rank as high as third among causes of disability-adjusted life years lost.[6] This study was planned to see the epidemiological profile of the patients attending road traffic accidents (RTA) to the emergency/casualty department in a tertiary care hospital to address the different variables involved and categorize them according to the ICD-10 classification. This is the first study in India to address the ICD-10 classification of injuries involved in accidents.

MATERIALS AND METHODS

A retrospective record-based descriptive study was performed to analyze the epidemiological profile of the patients attending RTA. The data was collected from June 1 to December 31, 2022, in an emergency/casualty department under ESIC Medical College and Hospital. The study sample was to include all the RTA cases that were involved during the study period. The inclusion criteria adopted for the study were those injured from RTA and undergone treatment at the emergency department. Those injured and brought dead caused by RTA cases were excluded since it is a record-based study information was incomplete. Ethical clearance from the Institutional Ethics Committee with IEC No: ESICMC/SNR/IEC-S0212/03-2023 and administrative approval for access to records from concerned authorities with in study setting were obtained. Confidentiality of study participants was maintained, since only anonymized records were analyzed. Since it is a record-based study the consent form and the participant information sheet were not required.

Data collection and analysis procedure

A Google form was created using Google Worksheet, and the questionnaire consists of 21 questions with demographic details, mode of accident, type of injury, anatomical site involved, ICD-10 classification of diseases followed, day of incident, and others. All the variables are entered in the Google form accordingly. Data was taken from the month of June 1 to December 31, 2022 (7 months), a total of 397 entries were performed. All the data collected from the Google Forms was exported to Microsoft Excel, and analysis was performed using the SPSS 20.0 version. The data was represented in the frequencies/proportions.

RESULTS

A total of 397 injured victims were reported to the emergency/casualty department of the tertiary center during the 7-month study period from April 2022 to October 2022. Table 1 shows demographic and road traffic injuries associated characteristics in 397 victims reported to emergency department of tertiary center. Out of those, 309 (77.8%) victims were male, and 88 (22.2%) victims were female. The mean age and standard deviation of the victims was 37.19 ± 13.9 years. Most of the victims 206 (51.9%) belonged to the 21-40 age group. Majority 371 (93.5%) of the patients were accompanied by the attendees, 14 (3.5%) were brought by the ambulance and 12 (3.0%) were reported by themselves. Almost 158 (39.8%) received primary treatment before the emergency and 239 (60.2%) arrived immediately after the accident. According to the mode of accident in Figure 1, the majority, 143 (36.0%) of them had encountered self-fall (Fall from the vehicle while riding by skidding/unable to control the vehicle and without collision to another vehicle), 64 (16.1%) had encountered 2-wheeler vs pedestrian, 63 (15.9%) had encountered 2-wheelers vs 4-wheeler, 55 (13.9%) had encountered under 2-wheelers vs 2-wheeler and others are involved in different methods mentioned in the tabular form.

Table 1.

Distribution of the participants according to their demographic and accident details

Variable	Number	Percentage
Gender
Male	309	77.8
Female	88	22.2
Age in years
<20	37	9.3
21.30	93	23.4
31.40	113	28.5
41.50	77	19.4
>50	77	19.4
Patient reach hospital after accident
Self	12	3.0
By attenders	371	93.5
Ambulance	14	3.5
Primary treatment received before reaching hospital
Yes	158	39.8
No	239	60.2
Mode of accident
*Self-fall from 2-wheeler   2-wheeler vs pedestrian   3-wheelers vs pedestrians   4 wheelers vs pedestrians   2-wheeler vs animal   2-wheeler vs 2-wheeler   2-wheeler vs 3-wheeler   2-wheelers vs 4-wheeler   3-wheelers vs 3-wheelers   3-wheelers vs 4-wheelers   4-wheelers vs 4 wheelers   Heavy vehicle accident	143 64 13 32 02 55 13 63 03 02 04 03	36.0 16.1 3.3 8.1 0.5 13.9 3.3 15.9 1.0 0.8 0.5 0.8

*Self-fall- fall from the vehicle while riding by skidding/unable to control the vehicle and without collision of another vehicle

Figure 1.

Distribution of accidents according to the month-wise

Figure 1 shows the monthly incidents that happened, among them majority, 71 (17.8%) and 75 (18.8%) of the incidents happened in the month of June and December. A smaller number of incidents were reported in July 50 (12.5%) and August 32 (8.1%). The increasing trend of incidents happened during the months of September 57 (12.9%), October 51 (12.8%), and November 61 (15.3%) respectively.

Figure 2 shows the day of the incident. The majority happened during the weekends, like Saturdays 60 (15.1%), Sundays 71 (17.9%), and the remaining days had an average of 50 incidents in a day. Figure 3 shows the time of the incident in a 24-hour, a majority had evening 98 (24.7%) from 4 PM to 6 PM, night 136 (34.2%) during 6 PM to 6 AM, morning 109 (27.5%) during 6 AM to 12 PM and in the afternoon time 54 (13.6%) during 12 PM to 4 PM, respectively. Table 2 represents the mechanism of accidents in terms of vehicle type along with adapted codes (ICD-10), almost one-third of the accidents, 139 (35.0%), had occurred among motorcycle rider noncollision transport accidents followed by 77 (19.3%) were pedestrian collision with two or three-wheeled motor vehicles 68 (17.1%) motorcycle rider collision with two- or three-wheeled motor vehicle and the remaining were involved in other methods of accidents. Table 3 shows the anatomically affected regions based on ICD-10 codes with many patients had multiple injuries. Out of those lower limbs was most commonly injured site 243 (63.3%) followed by upper limb 182 (47.4%) and 169 (44.0%) were involved was head and neck region and the remining had involved other sites like thorax, abdomen, lower back, lumbar spine and pelvic region. Table 4 shows the type of injuries, out of which the majority had superficial injuries, 286 (45.98%) followed by open injuries, 163 (26.20%) and 128 (20.2) had fractures, and very few had dislocations and traumatic amputation and internal injuries.

Figure 2.

Distribution of incidents/accidents that happened on the day of the week

Figure 3.

Distribution of participants according to time of accidents

Table 2.

Mechanism of accidents in terms of vehicle type along with adapted codes (ICD-10) in 397 victims in tertiary center

ICD-10 code	Type of Accident	Frequency (%)
V02	Pedestrian collision with two or three wheeled motor vehicles	77 (19.3)
V03	Pedestrian collision with car or bus or pickup truck	31 (7.8)
V04	Pedestrian collision with heavy transport vehicle or bus)	2 (0.5)
V18	Pedal cyclist noncollision transport accident)	1 (0.2)
V20	Motorcycle rider collision with pedestrian or animal)	2 (0.5)
V22	Motorcycle rider collision with two or three wheeled motor vehicles	68 (17.1)
V28	Motorcycle rider noncollision transport accident	139 (35.0)
V32	Occupant of three wheeled motor vehicle collision with two or three wheeled motor vehicles	3 (0.7)
V33	Occupant of three wheeled motor vehicle collision with car, pickup truck or van	2 (0.5)
V38	Occupant of three wheeled motor vehicle noncollision transport accident	2 (0.5)
V43	Car occupant collision with car, pickup truck or van	4 (1.0)
V47	Car occupant collision with fixed or stationary vehicle	2 (0.5)
V67	Occupant of heavy transport vehicle collision with fixed or stationary vehicle	1 (0.2)

Table 3.

Anatomical affected regions according to ICD-10

ICD 10	Classification	Frequency*
S00-19	Head and neck	169 (44.0%)
S20-29	Thorax	25 (6.29%)
S30-39	Abdomen, lower back. LS spine and pelvis	22 (5.54%)
S40-69	Upper limb	182 (47.4%)
S70-99	Lower limb	243 (63.3%)

*Multiple injuries are involved

Table 4.

Type of injuries among victims reported to emergency department

ICD 10 classification	Frequency*
Superficial injury	286 (45.9)
Open injury	163 (26.2)
Fracture	128 (20.2)
Dislocation, sprain, or strain	41 (6.5)
Injury to nerves, spinal cord	0
Injury to blood vessels	1 (0.1)
Injury to muscles, tendons	0
Crushing injury	0
Traumatic amputation	2 (0.3)
Injury to internal organs	1 (0.1)
Unspecified injuries	0

*Multiple injuries are involved

DISCUSSION

Road traffic injuries are a growing public health problem worldwide. The causes of RTAs are multipronged, and the prevention requires multimodal efforts. In our study, three-fourths (77.8%) of the victims were males, and one-fourth were females. More than half (51.9%) of them were belonging to the age group of 21-40 years. Similar findings were found in the study conducted by Ganveer and Tiwari,[7] Kotresh,[8] and Celine and Antony.[9] It was found that middle-aged and males predominance of road users are the most common victims of RTAs. This shows that the people of the most active and productive age group are involved in RTAs, which adds a serious economic loss to the community. Most of the RTA victims were males (76%), which is consistent with the findings of earlier studies reported from India and other nations.[10,11,12,13,14] Furthermore, more than half of the victims were in the age group of 20–40 years, reflecting an incredibly young and productive age group. The authors observed similar findings in earlier studies where strong gender bias on RTAs was reported among males.[10,13,14,15,16] Men were found to be more outdoor and were the primary breadwinners for the family, mostly using road transport by own vehicle, walk, or public transport.

The current study revealed that the majority of the incidents happened during the evening after 4 PM and in the night-time 6 PM to 6 AM, especially during the weekends, that is, on Saturday and Sundays, and most of them involved were two-wheelers and light motor vehicles. If we look at all the days in a week on an average more than 50 incidents were happened on any day. Studies in different settings across the country such as New Delhi,[17] Himachal Pradesh,[18] and Andhra Pradesh[19] found results similar with respect to timings and day in a week of fatal road crashes, i.e. between late afternoon and evening until night, and more on weekends, respectively. This is the time when vehicular congestion would be high in the city, as a greater number of people will be out of offices and other organizations. The findings are in line with earlier studies from India that reported that two-wheeler occupants are among the majority affected by RTA.[10,11,13,20,21,22] However, this contrasts with the road user demography of fatal RTA victims in Iran, where HMVs (41.9%) and LMVs (36.8%) comprised the majority, as reported by Ghadipasha et al.[14] Since our study had enlisted the injuries according to the accident type, anatomical site involved, and the most affected region by ICD-10 classification. In the present study, the majority were involved with Motorcycle rider noncollision transport accidents followed by pedestrian collisions with two or three wheeled motor vehicles. The anatomical sites involved by the incident were lower limbs, upper limbs, followed by head and neck. The type of injuries among victims reported to the emergency department were superficial injuries followed by open fractures. We can generalize the study results because the majority of the variables in terms of day, time of the incident, the mode of transport, vehicle, and site of injury were almost similar with other studies conducted in India and other countries.

Strengths and limitations

The strength of the study was that reported accident incidents, injuries, and affected regions were classified in terms of the ICD-10 classification of disease. In the current study, we had taken the data for only a few months, not for the entire year on rotation. Hence, the limitation of the study was that a season-wise analysis of the incidents was not considered. The analysis of the details of the riders in vehicles was not possible due to insufficient information from the hospital record in relation to their seating, wearing of seat belt, helmet and amount of alcohol consumption and the extent of internal injury which was not analyzed up due to referral to higher/respective departments.

CONCLUSION

Fatal vehicular accident has male predominance, with more victims from adults and middle age 21-40 years. The most common category of victim was motorcycle rider, followed by pedestrians, and as per ICD-10 classification, the common mechanism of the incident was Motorcycle rider noncollision transport accident (Code: V28). Majority had an injury at the extremities (Code: S40-69 and S70-99) followed by the head and neck (Code: S00-19).

Conflicts of interest

There are no conflicts of interest.

Funding Statement

Nil.