Principles for effective data systems

1. Principles for effectivedata systems November 2010 Ian Hughes

2. Background

3. Overview • Background • Use of data • Characteristics of good road crash data systems • Data requirements for road safety management • Key sources of data • Minimum data elements • Need for use of recognised definitions • Examples of additional variables commonly collected • Transport-related data elements • Conclusion

4. Background • The collection, analysis, interpretation and application of good data is essential for effective road safety management • Data collection systems are generally not well developed in low and middle income countries globally

5. Use of data • Use of reliable and detailed data as part of a road safety strategy

6. Use of data • Reliable and accurate data can be used to build political will by: • Documenting the scale of the problem • Demonstrating effectiveness of interventions • Providing information on reductions in socio-economic costs

7. Characteristics of good road crash data systems • Road crash data is collected by police, health workers and insurance companies • As a minimum a road crash data system should: • Capture crashes resulting in death and serious injuries • Provide adequate detail on vehicle, road user, road/environment • Include crash location details • Provide reliable output in timely manner

8. Characteristics of good road crash data systems • Summary road crash data is useful for: • describing the magnitude of the problem • monitoring programmes and policies • More detailed information required for evidence-based intervention and management

9. Data requirements for road safety management

10. Data requirements for road safety management • A comprehensive road safety data system should include: • Final outcomes – deaths and serious injuries to road users and crash characteristics • Exposure measures – e.g. demographic data, number of licensed drivers, traffic volume data, infrastructure factors • Intermediate outcomes – e.g. mean traffic speeds, seatbelt and helmet wearing rates, drink-driving, vehicle and infrastructure ratings • Socio-economic costs • Outputs – including enforcement efforts

11. Key sources of data • Police: • Number of road traffic incidents, fatalities and injuries • Road users involved • Age and sex of casualties • Vehicles involved • Police assessment of causes of crashes • Use of safety equipment (e.g. helmets) • Location and sites of crashes • Prosecutions

12. Key sources of data • Health settings: • Fatal and non-fatal injuries • Age and sex of casualties • Costs of treatment • Alcohol or drug use

13. Key sources of data • Vital registration: • Fatal injuries • Age and sex of casualties • Type of road users involved • Insurance companies: • Fatal and non-fatal injuries • Damage to vehicles • Costs of claims

14. Key sources of data • Other private and public institutions, including transport companies: • Number of fatal and non-fatal injuries occurring among employees • Damage and losses • Insurance claims • Legal issues • Operational data

15. Key sources of data • Government departments and specialized agencies collecting data for national planning and development: • Population estimates • Income and expenditure data • Health indicators • Exposure data • Pollution data • Energy consumption • Literacy levels

16. Key sources of data • Special interest groups: • Number of road traffic incidents, fatal and non-fatal injuries • The type of road users involved • Age and sex of casualties • Vehicles involved • Causes • Location and sites of crashes • Social and psychological impacts • Risk factors • Interventions

17. Minimum data elements

18. Need for use of recognised definitions

19. Examples of additional variables commonly collected

20. Transport-related data elements

21. Conclusion