Key figures for 2022

  • 35,628
    Hospitalisations
    8.5% lower than the previous year
  • 5.3
    Bed days per case
    6% higher than the previous year
  • 137.0
    Hospitalisations per 100,000 people
    9.7% decrease from the previous year
  • 17,198
    Hospitalisations of Vulnerable Road Users
    10.9% decrease from the previous year

Annual hospitalisations

2017 to 2022

Over the past 6 years, there has been no significant change in the number of hospitalisations due to traffic injuries. On average, there were 3,189 hospitalisations each month with significant variability from month to month. 

Monthly hospitalisations 2017 to 2022
Monthly hospitalisations 2017 to 2022
YearMonth

Hospitalisations

2017January

3,066 

2017February

3,131 

2017March

3,596 

2017April

3,337 

2017May

3,335 

2017June

3,105 

2017July

3,169 

2017August

3,014 

2017September

3,121 

2017October

3,337 

2017November

3,355 

2017December

3,389 

2018January

3,042 

2018February

3,109 

2018March

3,506 

2018April

3,430 

2018May

3,344 

2018June

3,169 

2018July

3,110 

2018August

3,216 

2018September

3,173 

2018October

3,362 

2018November

3,358 

2018December

3,347 

2019January

3,202 

2019February

3,182 

2019March

3,535 

2019April

3,463 

2019May

3,321 

2019June

3,084 

2019July

3,224 

2019August

3,116 

2019September

3,162 

2019October

3,504 

2019November

3,351 

2019December

3,306 

2020January

2,999 

2020February

3,155 

2020March

3,165 

2020April

2,336 

2020May

2,873 

2020June

2,986 

2020July

3,188 

2020August

2,997 

2020September

3,269 

2020October

3,432 

2020November

3,519 

2020December

3,555 

2021January

3,402 

2021February

3,158 

2021March

3,805 

2021April

3,401 

2021May

3,479 

2021June

3,120 

2021July

2,960 

2021August

2,888 

2021September

2,964 

2021October

3,099 

2021November

3,193 

2021December

3,489 

2022January

2,702 

2022February

2,834 

2022March

3,284 

2022April

3,149 

2022May

3,010 

2022June

2,779 

2022July

2,675 

2022August

2,847 

2022September

2,956 

2022October

3,029 

2022November

3,034 

2022December

3,329 

Age group

People aged between 40 and 64 years of age represented the age group with the highest number of hospitalisations in 2022 (33.2% of cases). This age group also had the highest hospitalisation rate (147.8 cases per 100,000 population).

The number of males hospitalised is higher than the number of females hospitalised across all age groups, particularly for cohorts between 17 years and 64 years of age. This trend could be influenced by differences in driving behaviours and higher rates of work-related hospitalisation in industries dominated by male employment. While people aged 65 and over account for lower numbers of hospitalisations, they represent the highest number of bed days per case. This could reflect age-related complications when treating injuries. 

Number of hospitalisations and bed days per case by age group and gender, 2022
Number of hospitalisations and bed days per case by age group and gender, 2022
Age groupGender

Hospitalisations

Bed days per case

0-7Female

244

2

8-16Female

673

4.1

17-25Female

2,367

3

26-39Female

2,891

3.6

40-64Female

3,936

4.8

65-74Female

1,266

7.4

75+Female

1,136

11.3

0-7Male

352

3.7

8-16Male

1,759

3.1

17-25Male

4,619

4.4

26-39Male

5,573

5

40-64Male

7,895

5.7

65-74Male

1,672

8.9

75+Male

1,245

9.9

Road users 

In crashes involving a hospitalised injury, the person suffering trauma is categorised into a road-user group, such as drivers, passengers or pedestrians. Among broad road-user categories: 

  • Drivers had the highest number of hospitalisations (12,601) but the lowest number of bed days per case (4.9 days per case)
  • Motorcyclists had higher bed days per hospitalisation compared to other identified road-user groups (5.6 days per case)
  • Pedestrians and cyclists account for a significant number of hospitalisations (8,657).

While vehicle occupants represent the highest number of hospitalisations, they also account for the largest number of total road users. Therefore, caution should be used when making comparisons between different road user categories.

Number of hospitalisations and bed days per case by road user, 2022
Number of hospitalisations and bed days per case by road user, 2022
Road User

Hospitalisations

Bed days per case

Driver

12,601 

4.9

Pedestrian or Cyclist

8,657 

5.3

Passenger

4,757 

5

Motorcyclist

8,541 

5.6

Other/Unknown

1,072 

9

Remoteness area

Most people hospitalised in 2022 usually lived in Major City areas (23,708 hospitalisations or 67.0% of total hospitalisations). The rate of total hospitalisations from this remoteness area category aligns with the proportion of Australia’s total population that live in Major Cities (72.2% of total estimated resident population). 

Regional and Remote area residents accounted for fewer hospitalisations in 2022, but these cases had higher average bed days of 5.9 days and 5.3 days respectively. In comparison, Major Cities residents averaged 4.8 bed days per case. 
 

Number of hospitalisations and bed days per case by remoteness area, 2022
Number of hospitalisations and bed days per case by remoteness area, 2022
Remoteness area

Hospitalisations

Bed days per case

Major Cities

23,708 

4.8

Regional

10,166 

5.9

Remote

1,005 

5.3

Unknown

749 

5

Across remoteness areas:

  • Remote areas had the highest hospitalisation rate (201.8 per 100,000 people)
  • Major Cities areas had the lowest hospitalisation rate (126.2 per 100,000 people) 

Regional differences in rates of hospitalisation and bed days per case may be influenced by:

  • Disparities in healthcare access, such as limited medical facilities or long transport times
  • Ambulance response times
  • Road conditions and typical travel speeds
  • Access to driver training and education
  • Vehicle fleet age
Hospitalisation rate per 100,000 people by remoteness area, 2022
Hospitalisation rate per 100,000 people by remoteness area, 2022
Remoteness area

Hospitalisation rate

Major Cities

126.2

Regional

151.2

Remote

201.8

Counterparties

Counterparty describes the other party or object involved in a hospitalised injury crash. This may include other vehicles, persons or infrastructure. In most hospitalised injury crashes, the counterparties were light vehicles, accounting for 15,539 of the 35,628 total hospitalisations (43.6% of cases). More than a third of cases had an unspecified or no counterparty involved (‘Other/Unknown’ counterparty) with 12,983 hospitalisations (36.4% of cases). For example, a single vehicle involved in a runoff road crash would have no counterparty recorded. 

Number of hospitalisations by road user and counterparty, 2022
Number of hospitalisations by road user and counterparty, 2022
Road User
Counterparty
Number of hospitalisations
DriverFixed or stationary object

2,938 

Heavy vehicle

545 

Light vehicle

7,085 

Motorcycle

22 

Other or none

1,936 

Pedestrian or cyclist

75 

Motorcyclist Fixed or stationary object

870 

Heavy vehicle

68 

Light vehicle

2,303 

Motorcycle

177 

Other or none

4,921 

Pedestrian or cyclist

202 

Other/UnknownFixed or stationary object

36 

Heavy vehicle

12 

Light vehicle

146 

Motorcycle

Other or none

869 

Pedestrian or cyclist

PassengerFixed or stationary object

950 

Heavy vehicle

213 

Light vehicle

2,481 

Motorcycle

11 

Other or none

1,075 

Pedestrian or cyclist

27 

Pedestrian or CyclistFixed or stationary object

380 

Heavy vehicle

141 

Light vehicle

3,524 

Motorcycle

78 

Other or none

4,182 

Pedestrian or cyclist

352 

 

Definitions

Hospitalisations

Injuries resulting in confirmed admission to hospital excluding in-hospital death from road traffic crashes. Traffic areas exclude off-road and unknown locations.

Bed days

The total number of patient days where admitted care has been provided.

Vulnerable Road User

Road users not in a car, bus or truck, generally including pedestrians, motorcyclists and pedal cyclists. Can also include children 7 years and under, the elderly and users of mobility devices.

Hospitalisation rate

The hospitalisation rate allows comparisons to be made between groups as it is not influenced by differences in changes in population. It is calculated by dividing the count of road deaths in the last 12 months by the estimated resident population at the midpoint of that period, multiplied by 100,000. Population estimates are sourced from ABS' national, state and territory population statistics. The midpoint population may be interpolated if necessary.

Remoteness Area

Remoteness areas are defined using the Australian Bureau of Statistics (ABS) Australian Statistical Geography Standard (ASGS). In the provided data, remoteness area refers to the location of the usual residence of the patient. The classes of remoteness have been aggregated to: 

· Major cities 

· Regional (including Inner Regional and Outer Regional areas)

· Remote (including Remote and Very Remote areas)

· Other or unknown refers to when a person’s residence was unrecorded or migratory/offshore

About the data

We have sourced and prepared hospitalisations data from the Australian Institute of Health and Welfare (AIHW). 

Further information about the data can be found in the Hospitalised Injury Data Dictionary - September 2023. 
 

Download data

Limitations

The data presented here is sourced from hospital admissions and separations. A 'separation' is a term used in Australian hospitals to refer to an episode of care for an admitted patient, which can be a total hospital stay (from admission to discharge, transfer or death), or a portion of a hospital stay beginning or ending in a change of type of care (for example, from acute to rehabilitation). Occasionally patients are transferred between wards and hospitals, and in these cases, protocols are in use to minimise double counting.

Location data refers to location of hospital, not location of crash. Similarly, 'year' refers to year of separation, not year of crash.

Have a question or feedback?

Contact the Road Safety Data Hub team